1st ISATA – International Symposium on Agricultural

1st ISATA – International Symposium on Agricultural Technology Adoption:studies, methods and experiences

ISSN 1983-974XMarch / 2020

DOCUMENTOS279

Brazilian Agricultural Research CorporationEmbrapa Beef Cattle

Ministry of Agriculture, Livestock, and Food Supply

Embrapa Beef CattleCampo Grande, MS

2020

1st ISATA – International Symposium on Agricultural Technology Adoption:studies, methods and experiences

Mariana de Aragão PereiraJoão Augusto Rossi Borges

Carla Heloisa Faria Domingues

Editors

DOCUMENTOS 279

ISSN 1983-974XMarch/2020

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International Symposium on agricultural Technology Adoption (1. : 2019 : Campo Grande, MS).Studies, methods and experiences : abstracts of the 1th International Symposium on agricultu

ral Technology Adoption, Campo Grande, MS, November 6-8, 2019 / Mariana de Aragão Pereira, João Augusto Rossi Borges, Carla Heloisa Faria Domingues, editors. - Campo Grande, MS : Embrapa Gado de Corte, 2020.

PDF (167 p.). - (Documentos /Embrapa Gado de Corte, ISSN 1983-974X ; 279).

1st ISATA Universidade Federal de Grande Dourados, Universidade Federal de Mato Grosso do Sul.

1. Agricultura. 2. Desenvolvimento sustentável. 3. Extensão rural. 4. Inovação tecnológica. 5.Tecnologia agrícola. 6. Transferência de tecnologia. I. Pereira, Mariana de Aragão. II. Borges, João Augusto Rossi. III. Domingues, Carla Heloisa Faria. IV. Título. V. Série.

CDD 338.926 (23. ed.)

Comitê Local de Publicações da Embrapa Gado de Corte

PresidenteGilberto Romeiro de Oliveira Menezes

Secretário-ExecutivoRodrigo Carvalho Alva

MembrosAlexandre Romeiro de Araújo, Davi José Bungenstab, Fabiane Siqueira, Gilberto Romeiro de Oliveira Menezes, Marcelo Castro Pereira, Mariane de Mendonça Vilela, Marta Pereira da Silva, Mateus Figueiredo Santos, Vanessa Felipe de Souza

Supervisão editorialRodrigo Carvalho Alva

Revisão de textoRodrigo Carvalho Alva

Tratamento das ilustraçõesRodrigo Carvalho Alva

Projeto gráfico da coleçãoCarlos Eduardo Felice Barbeiro

Editoração eletrônicaRodrigo Carvalho Alva

Foto da capaLogomarca: Luiz Antônio Dias Leal

1ª ediçãoPublicação digitalizada (2020)

Organizing Committee

Mariana de Aragão PereiraChair, Embrapa Beef Cattle, Brazil

João Augusto Rossi BorgesVice chair, Federal University of Grande Dourados, Brazil

José Carlos de Jesus LopesMember, Federal University of Mato Grosso do Sul, Brazil

Luiza Marilena Toma Revoredo GihaMember, Scotland Rural College, Scotland

Scientific Committee

Carla Heloisa de Faria Domingues

Clandio Favarini Ruviaro

João Augusto Rossi Borges

Mariana de Aragão Pereira

Best Posters Award

First prize: Aluísio Goulart Silva, Maurizio Canavari, Katia Laura Sidali, Alcido Elenor WanderOrganizations: Embrapa Rice and Beans; Università di Bologna; Free University of Bozen/BolzanoTitle: Intention to Adopt Integrated Production by Common Bean Growers: the Application of the Technology Acceptance Model (TAM)

Second prize: Suzi Cristiny da Costa Marques, Juliano Rosa da Silva, Juliana Rosa Carrijo Mauad, João Augusto Rossi Borges, Carla Heloísa de Farias DominguesOrganizations: Federal University of Grande DouradosTitle: Adoption of Fish Farming by Family Producers: an Application of the Planned Behavior Theory

Table of ContentsForeword ........................................................................................................9

ISATA motivations and aims ......................................................................9

ISATA 2019 ..............................................................................................10

ISATA social-environmental commitments ..............................................10

PANEL 1 - A new look over technology transfer and adoption .....................13

Open Innovation as a Strategy for Leveraging Technology Adoption and Impact: Embrapa´s RD&I Management Model ........................................13

The dynamic impacts of farm-level technology adoption on production, prices and profitability on Brazil’s dairy supply chain ..............................15

Farmers’ uptake of animal health and welfare technologies ...................27

Challenges and Opportunities for the Adoption of Integrated Farming Systems: Lessons from Brazil and Beyond .............................................31

PANEL 2 - Methodology and approaches to technology adoption research 43

Determinants of farmers’ uptake of innovative crop technologies. A structural equation modelling approach applied to survey data ..............43

Theory of Planned Behaviour: assumptions, applications, and limitations ..49

The Ethnographic Decision Tree Model (EDTM) for technology adoption studies .....................................................................................................55

PANEL 3 - Experience and knowledge exchange ........................................65

Factors affecting technology adoption in beef cattle production in Rio Grande do Sul state, Brazil .....................................................................65

Factors affecting technological adoption in beef cattle in Corrientes province, Argentina ..................................................................................79

The influence of technology characteristics and farmers’ objectives on technology adoption behavior .................................................................87

Strategies leading to successful wide adoption of mixed grass-legume pastures for sustainable intensification of beef cattle production systems in the Brazilian Amazon ...........................................................................97

SESSION 1 - Technology transfer and analysis ......................................... 115

Fundamentals of a participatory methodology for Embrapa’s technology adoption ................................................................................................ 115

Behavioral Diagnosis of Productive Activity: an evaluation method based on knowledge, motivation, action and impact indicators ....................... 117

Case study: Kit Embrapa of Manual Milking® adoption to improve milk quality .................................................................................................... 119

Work issues on Tomatec - a tomato sustainable production system .....121

Step-by-step video, a powerful tool for technology transfer: terrace plow as a case study .....................................................................................123

Simulation of a wheat production system for exportation in rural enterprises of Rio Grande do Sul State, Brazil ......................................125

Technology Transfer and Innovation (TT&I): a Disruptive Proposal ......127

PMMacro for Food and Nutrition Safety Promotion in Urban and Rural Areas .....................................................................................................129

Specific indicators for monitoring technology adoption .........................131

SESSION 2 - Agricultural Technology Adoption .........................................133

Adoption of Fish Farming by Family Producers: an Application of the Planned Behavior Theory ......................................................................133

Dairy Technology Adoption Perception in Burkina Faso, West Africa: the Importance of Responsibility in Demands Identification ........................135

Intention to Adopt Integrated Production by Common Bean Growers: the Application of the Technology Acceptance Model (TAM) .......................137

Behavioral Diagnosis of the Productive Activity of Passion Fruit in the Federal District, Brazil, Aiming at Prospecting Real Demands for Research, Extension Rural and Public Policies ....................................139

Adoption of Cover Crop Livestock Grazing in Specialized Integrated Crop-Livestock Systems in the Cerrado ................................................141

Adoption and Impact of Integrated Practices to Mitigate Soil Compaction in Southern Brazil ..................................................................................143

Challenges for Technology Adoption Among Cassava Growers in the State of Amazonas ................................................................................145

Adoption Evaluation of Black Pepper Cultivation with Live Gliricidia (Gliricidia sepium) Tutor in the State of Pará .....................................147

Adoption of a Decision Support System for Coexistence of Extensive Livestock to the Pantanal Flood Dynamics: Related Factors ................149

Adoption of Black Pepper Technology with Live Tutor of Gliricidia sepium in the Municipality of Castanhal, State of Pará ........................151

SESSION 3 - Impacts of Technology Adoption ...........................................153

Impact Assessment of Technology Adoption Aiming the Transition Toward Sustainability in a Rural Establishment in Central Amazonia ................153

Are Extracts of Algae an Innovative Technique to Enhance Soybeans Productivity? ..........................................................................................155

Exchanging Experiences and Learning on the Effects of the Hemiparasitic Striga asiatica in Brazilian Upland Rice Varieties Introduced in Mozambique ..........................................................................................157

Case: Evaluation of Rotational Grazing Stocking Adoption ...................159

Adoption of Dual-Purpose Wheat in Integrated Crop-Livestock Systems in Southern Brazil ......................................................................................161

BRS 5601RR: A Success Case of Soybean Cultivar Adoption in Southern Brazil .....................................................................................................163

Economic and Socio-Environmental Impacts of the Alelo Vegetal System 165

Foreword

ISATA motivations and aims

Technological innovation is a precursor for sustainable development of the Brazilian agriculture and the adoption of technologies is a crucial condition for this process. Based on this premise, the first “International Symposium on Agricultural Technology Adoption (ISATA): studies, methods and expe-riences” was conceived. The proposal of this event arose from the need to advance the discussions on the issue of technology adoption, especially from the perspective of farmers and the context in which they operate. Despite the stock of knowledge and technological solutions readily available for farmers, the average technical and economic performance of the Brazilian primary sector still remains far below its potential. Understanding the reasons for this situation requires a multidisciplinary vision and appropriate methods to ad-dress this complex issue.

Therefore, ISATA aimed to foster, debate and consolidate the theme “Adoption of Agricultural Technologies” in Brazil, and especially in Mato Grosso do Sul, the host-state of this event. Specifically, the objectives were to:

• Promote a methodological discussion about agricultural technology adop-tion and innovation, identifying promising methodologies for teaching, re-search and extension;

• Share national and international studies and experiences on the main theme of the Symposium;

• Stimulate the network and collaborative initiatives in research, teaching and extension on the themes of technological adoption, innovation and behavioral economics;

• Align with, and contribute to, the UN Sustainable Development Goals (SDGs).

ISATA 2019

The Symposium took place between November 6th and 8th, 2019, at the Campo Grande Rural Union, Campo Grande, MS/Brazil, under the coordina-tion of Embrapa Beef Cattle (CNPGC) and the Federal Universities of Grande Dourados (UFGD) and Mato Grosso do Sul (UFMS). Over three days, about 80 participants from diverse Brazilian regions attended lectures by 12 natio-nal and international invited keynote speakers, whose themes were divided into three panels: (1) A new look over technology transfer and adoption; (2) Methodologies and approaches to technology adoption research; and, (3) Experience and knowledge exchange. The event also presented a roundtable discussion on the role of technical assistance and rural extension in the adop-tion of technologies, and presentations of 28 posters on the themes: techno-logy transfer and analysis; adoption of agricultural technology; and, impacts of technology adoption. Participants also had the opportunity to attend a short course on Behavioral Diagnosis of the Productive Activity (BDPA) and to enjoy various networking moments, where they could interact with other participants and ISATA speakers.

ISATA social-environmental commitments

ISATA was committed to reduce environmental impacts and promote positive social impacts on the local community, in full alignment with the SDGs. Given this goal, ISATA participants did not receive the traditional Symposium bags, where various printed materials are usually distributed (and often thrown out). Instead, they received a bag-badge with their names on and a personalized pad and pen inside. This badge was made by women from the Noroeste su-burb; a poor community in Campo Grande. These women were trained at Guataverá Institute, a not-for-profit local organization, under the guidance of the EcoLinhas microenterprise, which is a social startup incubated at the Living Lab of SEBRAE-MS. EcoLinhas only works with recycled material in its craft production. In the case of ISATA, onion bags were used for the bad-ges while recycled banners from scientific events were the base to print the Symposium logo. In addition, the speakers were gifted with a notebook of crafted paper made from plants fibre, such as onion and garlic peel, corn,

111st ISATA – International Symposium on Agricultural Technology Adoption: studies, methods and experiences

tereré tree, banana tree among others. This artisanal work was carried out by the Pestalozzi Association of Campo Grande, which dedicates their effort to support people with disabilities and work for their social inclusion. They also received books on Mato Grosso do Sul rich regional culture (music, art, Pantanal Biome, etc.), provided by UFMS.

With these initiatives, ISATA 2019 contributed, directly and indirectly, to SDG 8 (Decent Work and Economic Growth), SDG 10 (Reducing Inequalities) and SDG 12 (Responsible Consumption and Production). Additionally, the pro-motion and dissemination of the key themes of this Symposium will contribu-te further to SDG 2 (Hunger Zero and Sustainable Agriculture) and SDG 17 (Partnerships and Means of Implementation) since it should result in future advances for the sustainable rural development agenda.

Mariana de Aragão Pereira, ChairOn behalf of the ISATA2019 Organizing Committee and

Scientific Committee

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Keynote Speakers

PANEL 1 - A new look over technology transfer and adoption

Open Innovation as a Strategy for Leveraging Technology Adoption and Impact: Embrapa´s RD&I Management Model

Bruno dos Santos Alves Figueiredo Brasil Research and Development Secretary Embrapa, Secretariat for Research and Development -

SPD, Brasília/DF – Brasil

Historically, it is observed that the generation of wealth, employment and inco-me is directly related to the development of innovations. Brazil invests about 1.2% of GDP in science, technology and innovation, ranking 14th in the global ranking for scientific production, but only 66th in the global ranking for inno-vation. A key strategy for changing this structure is to align the objectives of public and private actors to foster innovative entrepreneurship and collabo-ration between scientific institutions and companies. In fact, this strategy has led to remarkable success in some sectors of the Brazilian economy, such as aeronautics, oil and agriculture. Specifically in agribusiness, the creation of the Brazilian Agricultural Research Corporation (Embrapa) and the National Agricultural Research System (SNPA) laid the foundations for building a sus-tainable tropical agriculture model, overcoming barriers that limited the pro-duction of food, fiber and energy in the country. Since then, Brazilian grain production has grown by more than 500%, while planted area has increased by only 60%. The beef and pork supply increased fourfold, while the chicken supply was increased 22-fold. There was a 240% increase in wheat and corn production and over 300% in rice production. The forestry sector has increa-sed its productivity by 140%, while coffee growing has tripled productivity in the last 25 years. Achievements such as these led Brazil as a staple food importer in the 1960s to one of the largest producers and exporters in the world today.

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Today, agricultural innovation ecosystems have evolved into larger and more complex networks, incorporating new players such as multinational compa-nies, startups, venture capital, private technical assistance, and the advent of new and converging technologies such as digital agriculture, nanotechnology and biotechnology. This context no longer aligns with a linear innovation mo-del, but with the insertion of multiple actors and agents in open innovation sys-tems. Aware of this challenging scenario, Embrapa has upgraded its intelligen-ce processes to capture demands from the productive sector that now drive research, development and innovation (RD&I) management towards mission accomplishment (i.e.: mission-oriented innovation). In addition, Embrapa has adopted the technology readiness level (TRL) asset qualification methodology and incorporated types of public-private open innovation projects inspired by the Embrapii model, with a consequent reflection on building strategic part-nerships and greater asset visibility for the market and other shareholders. These new processes and tools have reinforced Embrapa’s RD&I process performance, making it more agile and effective in building open innovation with the productive sector in favor of the sustainable development of Brazilian agriculture. The key processes related to Embrapa’s RD&I management mo-del for leveraging technology adoption and impact will be addressed during the seminar.


The dynamic impacts of farm-level technology adoption on production, prices and profitability on Brazil’s dairy supply chain

Andre Rozemberg Peixoto Simões2, Charles Frederick Nicholsonb3

1 The original paper is published in the International Food and Agribusiness Management Review. Any citation of the content of this manuscript must reference the original paper https://

doi.org/10.22434/IFAMR2019.00332 Professor - Universidade Estadual de Mato Grosso do Sul, Aquidauana-MS. Rodovia

Aquidauana-UEMS km 12, Aquidauana-MS, BR, CEP:79200-000.3 Professor - Charles H. Dyson School of Applied Economics and Management, Cornell

University, 451 Warren Hall, Ithaca-NY, US

Abstract: Agricultural technology adoption that increases individual firm productivity is generally assumed to improve competitiveness and profi-tability. However, technology that is adopted by many firms in an industry can shift the basic supply relationship, increasing total production while lowering farm prices. While generally beneficial to consumers, this result can reduce (or completely offset) benefits for farmers, especially late or non-adopters. Our objective is to assess the market dynamics of alter-native assumptions about exogenous productivity-enhancing technology adoption by Brazilian dairy farms. Of particular interest is the distributional impact on farm incomes and on the proportion of milk production for diffe-rent farm size classes. To achieve this objective, we developed an empi-rical System Dynamics model that evaluates market and farm profitability impacts from 2006 to 2016. We simulated six counterfactual scenarios comprising three rates of adoption (slow, medium and fast) by two farm size categories (small and large). Technology adoption impact differs in the short- and long-term and depending on the assumed rates and farm sizes. Non-adopters of technology can experience lower incomes and a smaller production and income shares when other farms adopt. The underlying causal structure of farm profitability and the herd management decisions suffices to explain the potential market exclusion of non-adopting farms (especially small-scale farms) when others adopt.

Keywords: Dairy, system dynamics, technology adoption, Brazil, Milk supply.

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Introduction

Although studies have examined the effect of technology adoption on econo-mic performance of Brazilian dairy farms (Breitenbach, 2018; Camilo Neto et al., 2012; Novo et al., 2013; Campos et al., 2014) none of them assesses the dynamic impacts of scaled-up technology adoption on aggregated market out-comes and farm-level profitability by farm-size categories. These impacts can include basic and short-term outcomes such as those on prices and sales, but also longer-term and structural change dynamics with substantive implica-tions for farm income distribution. Supply increases from productivity-enhan-cing technology adoption will lower prices ceteris paribus, which would offset at least to some extent the benefits of productivity enhancement. Further, these offsetting effects will likely not be equally distributed among types and sizes of farms. The heterogeneity at the farm level should be also conside-red when assessing the likely of adoption of new technologies by individuals and the impact of diffusion on markets (Howley et al., 2012). Thus, our main objective is to assess the market dynamics and the distributional impacts of alternative assumptions about exogenous technology adoption by Brazilian dairy farms. Of particular interest is the distributional impact on farm incomes and on the proportion of milk production for different farm size classes. To achieve this objective, we developed an empirical System Dynamics (SD) mo-del that evaluates market and farm profitability impacts during 2006 to 2016.

Methods

The System Dynamics simulation model used represents six farm-size catego-ries with different production strategies and response parameters, an aggrega-ted decision-making process for the manufacture of four aggregated dairy pro-duct types, price responsive aggregate demand. In the SD modeling process, a Causal Loop Diagram (CLD) describes what is termed the “dynamic hypothe-sis”, that is, a depiction of the hypothesized system structure that causes an ob-served dynamic behavior. Our CLD indicates two key reinforcing (R1 and R2) and two key balancing loops (B1 and B2), each with important delays (Figure 1).

The rate of technology adoption (Fractional Technology Adoption Rate) is assumed to vary by farm size (and scenario) and determines a key exogenous input, the Number of Farms Adopting Productivity-Enhancing Technologies. The primary effect of adop-tion of technology is increasing Milk Production Per Cow and consequently overall


Milk Production. Many analyses of technology adoption would consider short-run ef-fects only to the point of increased milk production, without consideration of further relevant follow-on feedback eff ects. However, higher Milk Production would increase Farm Profi tability and, with a delay due to both biological and economic factors, result in an increase in Cow Numbers that also increases Milk Production. This component of the system is thus a reinforcing feedback loop R1. Increased Farm Profi tability also reinforces with a delay the initial eff ect of technology adoption on Milk Production Per Cow, through feedback loop R2. Thus, the initial eff ect of technology adoption on milk production is enhanced by two reinforcing feedback loops.

In addition to the reinforcing processes of exogenous technology adoption the-re are balancing eff ects that occur through changes to the relative supply and demand balance for milk and dairy products. Increased milk production will result in increased Production of Dairy Products and increased Dairy Product Inventories. Increased Dairy Product Inventories has a decreasing eff ect on Dairy Product Price and Farm Milk Price with a delay. A lower Farm Milk Price has a negative eff ect on Farm Profi tability that then also aff ects both Cow Numbers and Milk Per Cow. These balancing eff ects have the potential to partially or completely off set the positive eff ects of the technology adoption on production and farm-level profi tability, through loop B1. The eff ect of balancing loop B2 can help to off set the potential negative eff ects. Lower Dairy Product Price will posi-tively aff ect Dairy Product Demand, which will lower Dairy Product Inventories

Figure 1. Causal Loop Diagram of the main stock-fl ow-feedback processes in the Brazil dairy supply chain model.

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and have a positive influence on Dairy Product Price (and therefore, Farm Milk Price and Farm Profitability). Therefore, the net effects on Farm Profitability and the production outcomes overall and for each farm category will depend on which feedback loops dominate, the two reinforcing loops that enhance milk production or the balancing loops that lower farm milk prices. Other exogenous factors like Climate Conditions and Imports and Exports are shown that affect both the supply and demand components in this conceptual model.

Note that without a quantitative simulation model representing these processes empirically, it is not possible to determine the direction or magnitude of changes in the outcomes with technology adoption. The quantitative System Dynamic tool consists of a large number of stock-flow-feedback processes represented as a system of differential equations. The main stocks of the system are the cows on farm and its categories of young animals (calves and heifers) that are controlled by the herd parameters. The herd aging chain represents the main biological delay that affects the farm supply response. The inventories of dairy products are the main stock in the post-farm supply chain. The relative inventory coverage (measured in months) affects the wholesale price of dairy products and conse-quently the farm milk price. The monthly farm milk price is the central stock of the system formed by a proportional fraction of all dairy products and is adjusted with a delay that represent an adaptive expectation that drive farm-level decision ma-king. The model was built using the software Vensim version DSS® and the data used include official sources, specialized literature and expert opinion.

We assessed six scenarios in which farms in either the Small or Large cate-gories (but not both simultaneously) adopted technologies at each of the three assumed rates (Table 1). The technology improvement scenarios comprised a simultaneous change in a set of practices (i.e., a “technology package”) that modify the farms efficiency parameters.

Table 1. Six scenarios description considering the size category and the rate of transi-tion from Non-adopters to Adopters.

Farm sizeAdoption Rate (% per year)

Slow (0.3) Medium (1.65) Fast (3.0)Small (<200 Liters per day) SS SM SFLarge (>200 Liters per day) LS LM LF

NOTE: For example, SS indicates that 0.3% of farms in the Small category (farms with production less than 200L/day) adopted the improved technology each year. LM indicates that 1.65% of farms in the Large cate-gory (farms with production >200L/day) adopted the improved technology each year.


Results

Our analysis covers the period from January of 2005 to December of 2016, and key outcomes include milk production, milk price and cow numbers. The Baseline scenario of the simulation model replicated the patterns of behavior observed for these three variables. We report the results for technology adop-tion scenarios from three perspectives, first focusing on the average values for the whole period of analysis and with farm categories aggregation, then temporally-aggregated results disaggregated by farm size and finally tempo-rally disaggregated results that indicated behavior over time.

Technology adoption results in larger average milk per cow and annual milk production for all scenarios and consequently lower farm milk prices. Scenarios in which small farms adopt technology (SS, SM, SF) the average annual milk production increases due to increases in milk per cow, which more than offset the average decrease in cow numbers. For the scenarios in which larger far-ms improve their technology (LS, LM, LF), the average annual milk production increases due to increases in both milk per cow and cow numbers (Table 2). In all scenarios the average Net Farm Operating Income (NFOI) is lower than the Baseline.

Table 2. Average values of aggregated farm-related outcome variables for the six sce-narios of technology improvement and the percent difference from Baseline, based on average from January 2006 to December 2016.

Baseline (units) SS (%) SM (%) SF (%) LS (%) LM (%) LF (%)

Milk production (bil. L/year) 27.2 5.5 12.3 14.0 5.7 17.8 21.1

Cows (Mil. Heads) 21.8 -1.9 -7.7 -9.4 2.1 7.0 8.4

Milk per cow (L/cow/year) 1,247 7.5 21.7 25.9 3.5 10.1 11.7

Farm milk price (R$/L) 0.85 -3.7 -9.5 -10.9 -3.4 -10.2 -12.8

Average NFOI (R$/farm/month) 1,013 -8.4 -21.7 -25.7 39.2 80.2 74.1

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Technology adoption increases the average NFOI of adopting farms and gene-rally decreases NFOI for all non-adopting farms when compared with the Baseline. Thus, broad adoption of technologies focused on genetic improvements and strate-gic feeding would improve the individual profitability of farms despite the likely effect of lower milk prices but have a negative impact on non-adopters through price re-duction. Therefore, the aggregated benefits of technology adoption would depend not only on the rate of adoption but also on the fraction of adopters in each farm-size category. For example, the aggregated analysis indicates that in all scenarios of small farms adopting (SS, SM, and SF) the overall average NFOI is always lower than the Baseline, however, the disaggregated interpretation indicates that the net benefits are lower for the non-adopters (larger and small farms) and higher for small farms that adopt technology. Similarly, for the scenarios which larger farms adopt technology (LS, LM, and LF), the aggregated analysis indicates that NFOI is always higher for adopting farms, but small farms experience decreased profitability and large farms that do not adopt benefit less than adopting farms. (Table 3).

Table 3. Net Farm Operating Income in Reals per month of each farm-size category, Baseline and the six scenarios, average from January 2006 to December 2016.

Category (R$/farm/month) Baseline SS SM SF LS LM LF

<50 L/dayNon-adopters -2 -24 -13 48 -24 -69 -85

Adopters - 346 257 236 - - -51-200 L/dayNon-adopters 144 48 13 132 56 -113 -171

Adopters - 1,094 734 655 - - -201-500 L/dayNon-adopters 1,634 1,250 745 637 1,306 774 757

Adopters - - - - 6,779 5,094 4,424501-1000 L/dayNon-adopters 5,542 4,460 2,963 2,640 4,595 2,862 2,366

Adopters - - - - 16,948 13,320 11,910>1000 L/dayNon-adopters 19,729 16,364 11,445 10,355 16,768 11,186 9,339

Adopters - - - - 49,884 39,773 35,946


Adoption of new technology influences NFOI in part through changes in milk per cow but also through changes in cows owned per farm. The number of cows per farm at the end of the simulation by farm size category is reduced for non-adopting farms and increased for adopters in all scenarios and sizes. The assessment of cow numbers supports the hypothesis that the disaggregated analysis is important to understand aggregated behaviors. For instance, the observed cow number reduction in the SS, SM and SF scenarios (Table 2) is because the reduction of cows of non-adopting farms more than offsets the increasing cow numbers for adopting farms. For the scenarios LS, LM and LF, the observed increase of cow numbers at the aggregated level is due the higher magnitude of the increase of adopters in relation to the decreasing of non-adopters.

Technology adoption could markedly affect the structure of Brazil’s dairy sector. In the Baseline the proportion of milk production of small farms and large farms at the end of the simulation was 25% and 75%, respectively. Technology adoption by small farms (scenarios SS, SM, SF) increases the proportion of milk produced by small farms to much closer to half of total milk production (e.g., 43%) under the assumption of the fastest rate of adoption. If technology is adopted by large farms, the proportion of milk production by large farms would reach nearly 90% for fastest rate of adoption (Figure 2). Our results also indicate that the structure of milk production (and therefore the income distribution for dairy farmers) is markedly influenced by which farms adopt and their rate of adoption. The proportion of milk produced by adopters and non-adopters at the end of simulation is similar across each size category given the fixed rate of adoption assumed. In scenarios of slow adoption rate the final proportion produced by non-adopters and adopters are 40% and 60% respectively, for medium adoption rate the proportions are 2% and 98%, and for the fastest adoption rate all milk produced is provided by the adopters.

Technology adoption also affects the distribution of NFOI. When small farms adopt technology (SS, SM, and SF), they experience a substantive increase in aggregated NFOI and the large farms (non-adopters) experience a less dramatic NFOI reduction. In scenarios LS, LM and LF, the NFOI increase is much larger and aggregate NFOI for small non-adopter farms is negative (Figure 3).

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Figure 2. Percentage of annual milk production for each farm-size category for the Baseline and the six scenarios in 2016.

Figure 3. Net Farm Operating Income for each farm-size category for the Baseline and the six scenarios in 2016.


Thus, our analysis suggests that public or private eff orts for dairy sector de-velopment through technology adoption will have diff erent impacts depending on which farms are a focal point for eff orts to promote technology adoption. Although useful, this information in and of itself does not suggest the preferred strategy for such dairy sector development eff orts. This is in part because our scenarios indicate that there are no Pareto-superior outcomes in which all farms experience increased NFOI. This implies that some farms would be made better off through technology adoption and others worse off , posing a policy choice.

Milk prices are on average relatively lower (-8.4%) in technology adoption sce-narios due to the increase in milk supply (based on the scenarios shown in Table 2). However, the decrease in prices with technology adoption varies over time. The gap in milk prices between the baseline and scenarios of medium and fast adoption rate is widest in the middle of the simulation period, then closes after 2013 (Figure 4). This gap illustrates dynamic complexity in Brazil’s dairy sector. In the short-run, prices are the most negatively aff ected, but with completion of the adoption process, dynamic adjustments in cow numbers and demand that play out over longer time frames reduce the size of the gap in the long run.

Our scenarios demonstrate further details beyond the temporal complexity. Technology adoption and higher profi tability of large adopting farms could re-sult in lower profi tability for small non-adopters via price eff ects. This is in agreement with what Weersink and Tauer (1990) determined for contrasting diff erent milk production regions in the US.

Figure 4. Average milk price for ag-gregated farm-size categories in the Baseline and the six scenarios, from January 2005 to December 2016. The exchange rate BRL to USD was 3.26 in December 2016.

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Conclusion

Widespread technology adoption would likely result in higher milk production in Brazil and consequently lower prices. However, the specific impacts on dairy far-ms vary considerably when the focus of technological changes varies by farm size and with the speed of adoption. Market changes due to productivity-enhan-cing technologies affect farm profitability and farmers’ decisions about their herd size and production practices over time. From a farm management perspecti-ve, our analyses indicate adopters always prosper relative to non-adopters; it is profitable to adopt these technologies even with the offsetting effects on prices because of lower unit costs of production. Non-adopters of technology can expe-rience lower incomes and a smaller production and income shares when other farms adopt. The underlying causal structure of farm profitability and the herd management decisions suggests the potential market exclusion (i.e., farm exits) of non-adopting farms (especially small farms) when others adopt. Assuming no complicating changes in product quality, the principal beneficiaries of supply-shif-ting technology adoption will be the buyers of milk along the supply chain.

References

Breitenbach, R. 2018. Economic Viability of Semi-Confined and Confined Milk Production Systems in Free-Stall and Compost Barn. Food and Nutrition Sciences, 09(05):609–618, https://doi.org/10.4236/fns.2018.95046.

Camilo Neto, M., Campos, J. M. de S., Oliveira, A. S. de, Gomes, S. T. 2012. Identification and quantification of benchmarks of milk production systems in Minas Gerais. Revista Brasileira de Zootecnia, 41(10):2279–2288,.

Campos, S. A. C., Coelho, A. B., Gomes, A. P., Mattos, L. B. de. 2014. Efficiency and Costs Associated to Environmental Adequacy for Milk Production in Minas Gerais, Brazil. Organizações Rurais & Agroindustriais, 16(3):324–342,.

Howley, P., Donoghue, C. O., Heanue, K. 2012. Factors Affecting Farmers’ Adoption of Agricultural Innovations: A Panel Data Analysis of the Use of Artificial Insemination among Dairy Farmers in Ireland. Journal of Agricultural Science, 4(6):171, https://doi.org/http://dx.doi.org/10.5539/jas.v4n6p171 Abstract.

Novo, A. M., Slingerland, M., Jansen, K., Kanellopoulos, A., Giller, K. E. 2013. Feasibility and competitiveness of intensive smallholder dairy farming


in Brazil in comparison with soya and sugarcane: Case study of the Balde Cheio Programme. Agricultural Systems, 121(0):63–72, https://doi.org/http://dx.doi.org/10.1016/j.agsy.2013.06.007.

Weersink, A., Tauer, L. 1990. Regional and Temporal Impacts of Technical Change in the U.S. Dairy Sector. American Journal of Agricultural Economics, 72(4):923–934, https://doi.org/10.2307/1242624.

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Farmers’ uptake of animal health and welfare technologiesLuiza Toma1, Jiayi Liu2, Andrew P. Barnes1, Alistair W. Stott1

1 Scotland’s Rural College, Edinburgh, UK 2 Biomathematics and Statistics Scotland, Edinburgh, UK

Abstract: The paper analyses the uptake of animal health and welfare tech-nologies by livestock farmers using latent class analysis modelling and cross-section survey data to construct typologies based on uptake of technologies (genomic technologies, animal electronic identification for farm management, cattle surveillance, welfare qualitative behavioral assessment, anaerobic di-gestion, pedometers or activity monitors to detect oestrus and increase fer-tility/conception, and webcams/smart phones/tablets for animal husbandry) and heterogeneous characteristics. Results suggest that, while three fifths of the farmers are ‘non-adopters’, a third is classified as ‘current adopters’ of animal EID for farm management, and a twelfth as ‘future adopters’ of either or more types of animal health and welfare technologies. Age, agricultural income, perceived difficulty to invest in new technologies, agri-environmental scheme membership, and frequency of access to information on animal EID for farm management and cattle surveillance through British Cattle Movement Service, are significant predictors of typology membership.

Introduction

An underexplored area within the literature on farmer typology relates to the uptake of animal health and welfare technologies. This represents a mixtu-re of regulatory compliance (e.g., electronic identification (EID) scheme for sheep), and voluntary standards established by interest groups (e.g., Linking Environment and Farming (LEAF)) or established by processors or retailers to ensure a higher premium for enhanced standards. Hence, the motivation for this study is to explore, using a classification approach and survey data, farmers’ motivations for uptake of technologies which relate to meeting and exceeding standards of animal welfare and health practices, and their classi-fication in typologies based on technology adoption behaviour.

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Data and Methods

The data used in this study are drawn from a representative telephone sur-vey of Scottish agricultural holdings, which took place in 2013. The sampling frame (approximately 10,000 farms) was derived from the June Agricultural Census (JAS) and stratified by region, activity, size and farming enterprise. This study analysed data for 1,746 livestock farms from a total of 2,416 fully completed questionnaires from livestock, crop and mixed farms. After discar-ding missing values, the total number of valid observations was 1,502.

The section of the questionnaire used in this analysis and consistent with the use of Latent Class Analysis included close-ended questions on the following: socio-economic characteristics; perceived effects on business management from changes in technology, succession planning, access to advice/informa-tion, changes in animal welfare regulations and policies; perceived difficulty to invest in new technologies; frequency of access to novel technological infor-mation on EID for farm management and cattle surveillance; perceived effects of the use of new knowledge or technology on the welfare of animals on own farm during the past ten years; technology adoption behaviour during the past ten years and intentions to adopt technologies during the next ten years (new genomic technologies, animal EID for farm management, cattle surveillance, qualitative behavioural assessment (QBA), anaerobic digestion, pedometers or activity monitors to detect oestrus and increase fertility/conception, web-cams/ smartphones/ tablets for animal husbandry).

We use latent class analysis modelling (McCutcheon 1987) and cross-section survey data to construct typologies of farmers based on technological uptake and heterogeneous characteristics. Latent class analysis (LCA) is a statistical technique for the analysis of multivariate categorical data, also known as a type of finite mixture model. Applied in social sciences, LCA is often used to identify behavioural typologies. We use a latent class (LC) classification mo-del, which assigns each observation into a latent class with an estimated pro-bability – the latent class membership - which in turn produces expectations about how that observation will respond on each item; and extend this using an LC regression model which allows the inclusion of class-specific explana-tory variables/covariates to predict latent class membership. The LC models were fitted using the package poLCA in the statistical software R (Linzer and


Lewis 2011; R Development Core Team 2010). poLCA is an R package used to estimate LC classification models for manifest variables with any number of possible outcomes, and LC regression models with class-specific covariates.

Results and Discussion

Results of the LC regression model including class-specific explanatory varia-bles to predict latent class membership suggest that, while three fifths of the farmers are ‘non-adopters’, a third is classified as ‘current adopters’ of animal EID for farm management, and a twelfth as ‘future adopters’ of either or more types of animal health and welfare technologies (Figure 1).

Age, agricultural income, perceived difficulty to invest in new technologies, agri-environmental scheme membership, and frequency of access to infor-mation on animal EID for farm management and cattle surveillance through British Cattle Movement Service, are significant predictors of typology membership.

Figure 1. The characteristics of the LC three-class regression model (with explanatory variables).

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Conclusions

The findings are policy relevant as they give quantitative evidence on the fac-tors influencing technological uptake and, as such, help identify the most likely adopters and optimise the cost of targeting them. As information access was found to be among the factors influencing multiple technology adoption, policy instruments should include the provision of training as regards the implemen-tation of technologies and their combined impact on farm. Farmers’ adoption of interrelated innovations suggests the need to coordinate individual policies aimed at encouraging uptake of different technologies. As shown here, this would concern not only synchronizing animal health and welfare policies, but also their interaction with others such as agri-environmental ones. Moreover, the results show that animal health policies requiring regulatory compliance may lead to voluntary uptake of additional or complementary technologies which relate to not just meeting but exceeding standards of animal welfare and health practices.

Acknowledgements: We thank the Scottish Government who funded this research as part of the Rural Affairs and the Environment Portfolio Strategic Research Programme 2011–2016 Theme 4 WP4.1 ‘Adaptation to change in land-based and other rural industries’ and the Centre of Expertise on Animal Disease Outbreaks 2011-2016. We also thank the respondents to our survey.

References

Linzer, D. A., Lewis, J. (2011). poLCA: An R package for polytomous variable latent class analysis. Journal of Statistical Software, 42(10), 1-29

McCutcheon, A. C. (1987). Latent Class Analysis. Beverly Hills, CA: Sage

R Development Core Team (2010). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.


Challenges and Opportunities for the Adoption of Integrated Farming Systems: Lessons from Brazil and Beyond

Rachael Garrett1, Owen Cortner1, Juliana D.B. Gil2, Julio Cesar dos Reis3, Joice Ferreira4, Judson F. Valentim5

1 ETH Zurich2 Wageningen University

3 Embrapa Agrossilvipastoril4 Embrapa Amazonia Oriental

5 Embrapa Acre

Abstract: Brazil’s rural landscapes are critically important for global climate, economic development, and food security. The integration of crop and animal production within a single farm (ICLS) is a promising agricultural innovation to improve livelihood and environmental outcomes in these landscapes. Here we synthesize recent work examining the drivers of ICLS adoption in Brazil, as well as the economic, environmental and social tradeoffs associated with these sys-tems, with a focus on the Legal Amazon region. Our research finds that ICLS are largely an economic and environmental win-win compared to existing exten-sive cattle management practices and other pasture intensification alternatives. Adopters of ICLS are well aware of the economic benefits of these systems – improved income, greater adaptability, and reduced environmental impact, while non-adopters are less aware of the benefits. High upfront costs, greater managerial intensity, existing lifestyle preferences, as well as limited access to markets, credit, and technical information remain key barriers to diffusion. Given these diverse barriers to adoption, a comprehensive mix of positive and negative financial incentives is needed to both push and pull further intensifica-tion innovations from their current niche to widespread adoption. On the push side, there is a need to vastly increase the number of demonstration farms and training seminars on successful ICLS practices. On the pull side, agricultural po-licies need to be re-oriented to accommodate the longer-term benefits of ICLS, including longer payback periods on loans and positive incentives for intensifi-cation via stringent restrictions on deforestation for additional land clearing and payments for environmental services. Finally, joint efforts by the private sector and government are needed to promote cattle value chain upgrading, including improved infrastructure and machinery access to enable pasture renovation

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and crop production in more remote regions, and better transparency about cattle origin and management practices to signal the sustainability of the sector.

Introduction

Brazil is one of the largest global producers of food commodities, including beef, milk, corn, oranges, soy, and sugarcane. Yet a majority of the country’s agricultural area is degraded, low productivity pasture (IBGE 2017). Amidst rapidly growing global demand for these commodities, intensification and re-cuperation of the country’s existing pastures could hold the key to protecting the country’s remaining tropical forests and savannas (Strassburg et al. 2014), which are among the largest in the world. Given the low levels of economic development in the Amazon and Cerrado, innovations in agriculture that in-crease the farm incomes may also be an essential pathway for sustainable development in the region (Garrett and Rausch 2015; Medina et al. 2015).

The Amazon and Cerrado biomes in particular face the monumental chal-lenge of reconciling conservation with agricultural growth and development via sustainable intensification of existing areas. Despite many technological advances and rapidly advancing supply chain infrastructure, such intensifica-tion remains a challenge. Integrated crop and livestock systems (ICLS), which couple crops and livestock production through in situ animal grazing, hold formidable promise to meet the needs of farmers to produce high levels of food and farm revenue and reduce risks to climate change and market fluctua-tions, while also reducing agriculture’s water and climate footprints (Schiere, Ibrahim, and Van Keulen 2002; Garrett, Niles, Gil, Gaudin, et al. 2017). Yet, adoption of ICLS in the Amazon and Cerrado remains low (Vicente 2016). Here we synthesize recent work examining the drivers of ICLS adoption in Brazil, as well as the economic, environmental and social tradeoffs associated with these systems, with a focus on the Legal Brazilian Amazon.

Integrated systems are largely a win-win option from an economic, climate, and environmental perspective

A bio-economic whole-farm model using data from Mato Grosso, a state that spans the Brazilian Amazon and Cerrado, found that ICLS can produce nearly three times more income and seven times more protein relative to extensive,


continuously grazed beef cattle systems, with fewer greenhouse (Gil et al. 2018) (Figure 1). The integrated system could also produce more income and protein than a rotational grazing system, with fewer greenhouse gas emis-sions. ICLS also performs better than extensive grazing and rotational grazing under pessimistic (i.e., RCP 8.5) and optimistic (i.e., RCP 2.5) scenarios of climate change. ICLS also perform better than extensive grazing in terms of energy and water usage per unit of protein produced. Integrated systems are even more profi table than continuous soy production when ranchers operate at the economically optimal number of cattle per hectare (estimated as 5.8 animal units for the model farm).

Though ICLS has a higher upfront investment than either continuous cropping or traditional grazing systems, an economic viability study based on seven years of experimental data in Mato Grosso showed that ICLS has a shorter payback period (4 years) than continuous soy and corn production (6 years) and continuous pasture (5 years) (Reis et al. 2019). Furthermore, the net pre-sent value and internal rate of return, and return on investment are all higher than continuous cropping and extensive grazing.

Figure 1. Economic and environmental performance of an integrated crop and livesto-ck system relative to extensive or rotation cattle grazing on a model 2000 hectare farm in Mato Grosso. The ICLS farm produced US$ 638/ha and 299 kg human digestible protein (HDP)/ha with a stocking rate of 5.8 animal units/ha. The environmental impact per kg HDP was: 39 kg of carbon dioxide equivalent, 0.38 kg, Nitrogen, and 300 kg of water.

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Many farmers are already aware of the potential benefits of integrated systems, but both existing adopters and non-adopters cite several pressing challenges to adoption

The Brazilian Amazon and Cerrado contain both frontier and developed agri-business contexts, which span low input, sprawling cattle ranching, to smal-l-scale fruit and horticulture farming, to intensive soy and corn production. Interviews with farm operators and local experts in Acre, Rondônia, Pará, and Mato Grosso from 2014-2018 (Cortner et al. 2019), found that there is nearly universal agreement among integrated system adopters that these systems help to:

a) Increase the competitiveness of cattle ranching, particularly in light of decreasing land availability and growth of the crop sector;

b) Increase cattle productivity, especially where pastures are highly degraded;

c) Increase farm income by adding value to both crop and livestock opera-tions and diversifying revenue streams; and

d) Increase farmer adaptability and reduce risk to market and weather variability.

However, farmers cited numerous drawbacks and barriers to adoption (Figure 2). In regions that are farther from existing consolidated soy and corn produc-tion areas, there is an absence of silos to store grains and multinational tra-ders to create competitive market access conditions. Poor road quality increa-ses the costs associated with accessing these resources. Farmers reported that it was difficult to find or train skilled labor to work in integrated systems. Many also cited an inability to access credit to cover the costs and risks of es-tablishing an integrated system. For example, in Mato Grosso, establishing an integrated farm can cost $863/ha vs. $174/ha for conventional ranching (Reis et al. 2019). Low credit access is exacerbated by land title documentation challenges, particularly in Pará.

Finally, ranchers expressed an aversion to taking on debt or taking risks given the uncertainty about returns, as well as little desire to take on greater managerial intensity as other reasons for not adopting. Technical experts and farmers alike


linked these preferences to a high cultural value placed on well-being, rooted in safety, tranquility, and relationships (segurança), which may dampen the percei-ved benefi ts of ICLS despite the promise of higher fi nancial returns. Our resear-ch also indicates that increases in protected areas and enhanced enforcement of compliance with forest regulations are creating the perception of increased land scarcity and rising land prices, motivating farmers to fi nd ways to add value to their existing land. Indeed, the relationship between increasing policy stringency and intensifi cation has been identifi ed throughout the Brazilian Amazon (Koch et al. 2017; Garrett et al. 2018). But farmers still believe that they should be rewar-ded for the climate mitigation benefi ts that their sustainable intensifi cation eff orts are providing by receiving a payment for environmental services.

Figure 2. Perceived barriers to adopting integrated crop and livestock systems (num-ber of respondents = 33).

Higher education and access to technical information and relevant supply chain infrastructure are key enabling factors for diff usion at the regional level

Spatial analysis of adoption patterns at the state level in Mato Grosso has sho-wn that adopters of integrated systems are more educated and have better access to technical assistance and sector information than continuous crop

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farmers or ranchers (Gil, Garrett, and Berger 2016). This analysis also found that farmers located in close proximity Embrapa research and demonstration units had significantly higher adoption of these systems.

Policy implications

A multi-level analysis of the socio-technical and policy landscape and existing agricultural regime in Brazil and other major cattle production countries indi-cates that a comprehensive mix of positive and negative financial incentives will be needed to motivate ranchers to increase integrated system adoption (Garrett, Niles, Gil, Dy, et al. 2017; Garrett et al. In Review)(Table 1, Figure 3).

Table 1. Challenges for the scalability of ICLS and policy needs.

Challenges for scalability Policy needs

High upfront costs and difficulty acces-sing loans

Regularize land tenure and make loans for entire pro-duction system, not just individual crops

Provide insurance for investment lo-ans

Increase payback period and reduce interest rate of loans

Lack of access to technical informa-tion and labor force with required skills

Increase ICLS de-monstration farms

Increase rural trai-ning programs

Involve farmers in design of future ICLS experiments

Supply chain inade-quacies

Increase access to public machinery and silos

Improve supply chain infrastructure to increase access to crop markets

Upgrade value chains to provide ranchers with pre-miums for sustaina-ble production

Lack of positive in-centives to change practices

Provide positive incentives via pay-ments for ecosys-tem services

In order to improve adoption of integrated systems, agricultural research pro-grams should be redesigned using participatory approaches to focus more on whole farm outcomes. The federal and state governments should allocate more resources towards training and capacity building among agricultural te-chnicians and extension personnel. Additional field experiments should be es-


tablished in the regions that are best primed for adoption and most in need – predominantly cattle ranching communities, located near slaughterhouses but close to consolidated crop areas where cropping supply chain infrastructure is also available. Agricultural research organizations should increase gathe-rings, organization and knowledge exchange on successful farms that have already adopted ICLS and work jointly with farmers to develop and dissemi-nate successful forms of ICLS, for example via demonstration plots and fi eld days. Access to information about outcomes from experiments and outcomes on the farms of early adopters could be greatly improved through social me-dia, such as the integrated crop and livestock YouTube channel, to increase exposure to the technology. Agricultural researchers and practitioners should foster knowledge exchange regarding ICLS between farmers and other cross sectoral stakeholders. Cooperatives could play a role as change agents in the organization of local exchanges among farmers and broader diversifi cation of products by identifying new markets.

Figure 3. Multi-level perspective on push and pull factors needed to move ICLS from a niche innovation to mainstream practice. Adapted from Garrett, Ryschawy, in Review.

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The government already offers low interest loans for integrated system invest-ments through the Low Carbon Agriculture Program. Yet uptake of this credit is somewhat limited and did not explain differences in ICLS adoption across regions. In order to promote wider adoption of ICLS, credit systems should be adjusted to take into account a longer-term view of improved whole farm outcomes from system transformation, including a reduction of economic risk and negative social externalities relative to private returns.

Brazilian beef cattle value chains must be upgraded to access markets that provide premiums for socially and environmentally responsible products. Research and marketing organizations should work together to brand beef production produced with integrated systems for these higher value markets. Labeling programs and certifications could help with this effort. Additionally, the government could help incentivize more sustainable management by pro-viding a system of payments for environmental services associated with chan-ges in farming practices.

Conclusion

Given the magnitudes of Brazil’s grain and beef sectors and remaining forest area, sustainable development of the Brazilian countryside will have large repercussions for global climate and food security. ICLS offer the opportunity to reconcile conservation and agricultural growth in the Brazilian Amazon and Cerrado to meet these sustainable development challenges. ICLS are lar-gely an economic and environmental win-win compared to existing extensive cattle management practices and other pasture intensification alternatives. Adopters of ICLS are well aware of the economic benefits of these systems – improved income, greater adaptability, and reduced environmental impact.

However, high upfront costs, greater managerial intensity, existing lifestyle preferences, as well as limited access to markets, credit, and technical infor-mation remain key barriers to ICLS diffusion. The sustainable transformation of Brazilian cattle production is also restricted by deeply embedded habits of specialization, extensive management, and aversion to taking on risk and debt. As farming systems experience ownership transitions, the habits, prio-rities, and knowledge gaps of cattle ranchers may become more favorable to ICLS adoption. The ongoing generational transition of farm operators could


be further stimulated by helping young farmers to obtain the capital and new skills needed to enter the farming sector.

Given the diverse barriers to ICLS adoption, the existing Brazilian agricultural development strategy of providing low interest loans for machinery investment and operational costs is insufficient to promote the rapid intensification of the country’s extensive pastures. A comprehensive mix of positive and negative financial incentives is needed to motivate ranchers to intensify production: i) increases in demonstration farms using successful ICLS practices and wi-despread training seminars, ii) improved access and terms of public loans to better accommodate ICLS features, iii) improved supply chain infrastructure and machinery access for cropping systems, and iv) increases in positive in-centives for intensification via value chain upgrading and payments for en-vironmental services. In this way Brazil may harness its untapped potential for agricultural development and climate mitigation through intensification and recuperation of degraded pastures.

Acknowledgements: This work was funded by the National Science Foundation Grant #1415352, Harvard Sustainability Science Program, and Italian Ministry of Environment, Land and Sea. It was made possible through a technical cooperation partnership between the Brazilian Agricultural Research Corporation (Embrapa) and Boston University.

References

Cortner, O., Garrett, R., Valentim, J., Ferreira, J., Niles, M., Reis, J., Gil, J. 2019. “Perceptions of Integrated Crop-Livestock Systems for Sustainable Intensification in the Brazilian Amazon.” Land Use Policy 82: 841–53.

Garrett, R. D., Koh, I., Lambin, E. F., le Polain de Waroux, Y., Kastens, J. H., Brown, J. C. 2018. “Intensification in Agriculture-Forest Frontiers: Land Use Responses to Development and Conservation Policies in Brazil.” Global Environmental Change 53 (November): 233–43. https://doi.org/10.1016/j.gloenvcha.2018.09.011.

Garrett, R. D., Niles, M. , Gil, J. D. B., Dy, P., Reis, J., Valentim, J. F. 2017. “Policies for Reintegrating Crop and Livestock Systems: A Comparative Analysis.” Sustainability 9 (2): 473. https://doi.org/10.3390/su9030473.

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Garrett, R. D., Niles, M. T., Gil, J. D. B., Gaudin, A., Chaplin-Kramer, R., Assmann, A., Assmann, T. S. et al. 2017. “Social and Ecological Analysis of Commercial Integrated Crop Livestock Systems: Current Knowledge and Remaining Uncertainty.” Agricultural Systems 155: 136–46. https://doi.org/10.1016/j.agsy.2017.05.003.

Garrett, R. D., Rausch, L. 2015. “Green for Gold: Social and Ecological Tradeoffs Influencing the Sustainability of the Brazilian Soy Industry.” The Journal of Peasant Studies 43 (2): 461–493. https://doi.org/10.1080/03066150.2015.1010077.

Garrett, R. D., J. Ryschawy, Bell, L. W., Cortner, O., Ferreira, J. 5, Garik, A. V.1, Gil, J.D.B.6, Klerkx, L.7, Moraine, M.8, Peterson, C. 9, Reis, J. 10, Valentim, J.11. In Review. “Drivers of Decoupling and Recoupling of Crop and Livestock Systems at Farm and Territorial Scales.”

Gil, J. D. B., R. Garrett, A. Rotz, V. Daiogloud, J. Valentim, M. H. Costa, G. F. Pires, J. Reis, and L. Lopes. 2018. “Tradeoffs in the Quest for Climate Smart Agricultural Intensification in Mato Grosso, Brazil.” Environmental Research Letters 13 (6). https://doi.org/10.1088/1748-9326/aac4d1.

Gil, J. D. B., R. D. Garrett, T. Berger. 2016. “Determinants of Crop-Livestock Integration in Brazil: Evidence from the Household and Regional Levels.” Land Use Policy 59: 557–568.

IBGE. 2017. Agriculture and Livestock Census. Instituto Brasileiro de Geografia e Estatística. http://sidra.ibge.gov.br.

Koch, N., Erasmus KHJ zu Ermgassen, J. Wehkamp, F. Oliveira, G. Schwerhoff. 2017. “Agricultural Productivity and Forest Conservation: Evidence from the Brazilian Amazon.” SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3031416.

Medina, G., C. Almeida, E. Novaes, J. Godar, B. Pokorny. 2015. “Development Conditions for Family Farming: Lessons From Brazil.” World Development 74: 386–396.

Reis, J. C. dos, M. Y. T. Kamoi, D. Latorraca, R. F. F. Chen, M. Michetti, F. J. Wruck, R. D. Garrett, J. F. Valentim, R. de A. R. Rodrigues, S. Rodrigues-Filho. 2019. “Assessing the Economic Viability of Integrated Crop−livestock Systems in Mato Grosso, Brazil.” Renewable Agriculture and Food Systems, 1–12. https://doi.org/10.1017/S1742170519000280.


Schiere, Johannes B, M N M Ibrahim, and H Van Keulen. 2002. “The Role of Livestock for Sustainability in Mixed Farming: Criteria and Scenario Studies under Varying Resource Allocation.” Agriculture, Ecosystems & Environment 90 (2): 139–153.

Strassburg, Bernardo B. N., Agnieszka E. Latawiec, Luis G. Barioni, Carlos A. Nobre, Vanderley P. da Silva, Judson F. Valentim, Murilo Vianna, Eduardo D. Assad. 2014. “When Enough Should Be Enough: Improving the Use of Current Agricultural Lands Could Meet Production Demands and Spare Natural Habitats in Brazil.” Global Environmental Change 28 (0): 84–97. http://dx.doi.org/10.1016/j.gloenvcha.2014.06.001.

Vicente, Marcos. 2016. “Adoção de ILPF Chega a 11,5 Milhões de Hectares (Adoption of ILPF Arrives at 11.5 Million Hectares).” Embrapa. https://www.embrapa.br/busca-de-noticias/-/noticia/17755008/adocao-de-ilpf-chega-a-115-milhoes-de-hectares.

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PANEL 2 - Methodology and approaches to technology adoption research

Determinants of farmers’ uptake of innovative crop technologies. A structural equation modelling approach applied to survey data

Luiza Toma1, Andrew P. Barnes1, Lee-Ann Sutherland2, Steven Thomson1, Fiona Burnett1, Keith Mathews2

1Scotland’s Rural College, Edinburgh, UK2James Hutton Institute, Aberdeen, UK

Abstract: The paper analyses the impact of various determinants on the up-take of innovative crop technologies using structural equation modelling and survey data of Scottish crop farmers. Results show profit orientation, agri-cultural income, technological investment behaviour, farm labour, education, access to technological information and perceived usefulness of sources of information transfer to have the strongest effect on both uptake and intentions, and uptake as a strong determinant of intentions to uptake more technologies in the future.

Introduction

Increasingly during the recent decades technology has developed to meet the needs of a sustainable agriculture focused on increasing production at least cost to the environment. From a focus on higher-yielding crops combined with high use of fertilisers and pesticides, crop technologies have evolved to inclu-de precision farming, biological control, nitrogen fixing. While early adoption studies focused primarily on technological innovations that increased farm productivity, more recently the focus has shifted towards studies on the adop-tion of environmentally friendly technologies. There is an ever growing lite-rature analysing technology adoption behaviour in agriculture, part of which focussing on the factors that influence it (Beedell & Rehman 2000; Nuthall 2001; Sharma et al. 2011).

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This study builds on the existing literature and analyses the impact of a priori identified factors on the adoption of innovative crop technologies by Scottish farmers using survey data and structural equation modelling (SEM).

Data and Method

The data used in this study are drawn from a representative telephone sur-vey of Scottish agricultural holdings completed in September 2013. This study analyses data for 450 crop farms from a total of 2,416 fully comple-ted questionnaires from livestock, crop and mixed farms. The variables from the questionnaire used in this analysis included education, agricultu-ral income, profit orientation, number of employees; perceived usefulness of information sources and frequency of access to information of novel technologies; changes in the amount invested in new technologies; crop technology adoption behaviour during the past ten years and intentions to adopt crop technologies during the next ten years (precision farming technologies; new tillage practices; new or novel crops; GM crops; biolo-gical control methods, elicitors; varieties of nitrogen fixing plants and/or legumes).

We used a structural equation model (SEM) with observed and latent varia-bles to test the conceptual model and assess the strength of the research hypotheses, namely the effects the behavioural determinants have on the te-chnology adoption intentions and behaviour and on each other. Model selec-tion is performed through a nested model approach, in which the number of constructs and indicators remains constant, but the number of estimated rela-tionships is changed iteratively. We estimate the model using the Diagonally Weighted Least Squares (DWLS) method and the statistical package Lisrel 8.80 (Jöreskog and Sörbom 2007).

Results and Discussion

The model explains 83 per cent of the variance in current adoption behaviour and 63 per cent of the variance in intentions to adopt new technologies. All variables have a statistically significant effect on uptake of and intentions to uptake innovative technologies.


The model has very good fit according to the measures of absolute, incremen-tal and parsimonious fit (Hair et al. 2006).

The path diagram for the estimated SEM model is presented in Figure 1.

Figure 1. SEM path diagram (direct effects – standardised solution). Source: Toma et al., 2018.

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Table 1 presents the standardised total effects between the latent variables in the model.

Table 1. Standardised total (direct and indirect) effects (t-values in parentheses).

Observed/ latent variables

Total effects on ‘profits’

Total effects on ‘chtech’

Total effects on

‘info’

Total effects on ‘techinfo’

Total effects on ‘uptech’

Total effects on

‘intech’

educs -0.24 (-3.24)

0.03 (2.26)

0.25 (3.98)

0.06 (2.68)

0.20 (3.20)

0.12 (3.11)

profits - - - - -0.81 (-12.33)

-0.49 (-8.74)

employs -0.20 (-2.54) - - - 0.16

(2.49)0.10

(2.42)

income -0.59 (-12.01)

0.20 (4.32)

0.41 (6.78)

0.41 (8.26)

0.54 (11.79)

0.67 (18.72)

chtech - - - - 0.33 (4.23)

0.20 (3.98)

info - 0.11 (2.82) - 0.24

(3.75)0.04

(3.07)0.02

(3.18)

techinfo - 0.48 (6.07) - - 0.16

(5.43)0.10

(5.28)

uptech - - - - - 0.61 (10.70)

R-square 0.54 0.23 0.24 0.22 0.83 0.63Source: Toma et al., 2018.

Results show economic characteristics (profit orientation, agricultural income, technological investment behaviour and farm labour) to have the strongest effect on both uptake and intentions to uptake novel technologies. Education, access to technological information and perceived usefulness of sources of information transfer are also main influences on behaviour and intentions. Technological uptake behaviour is a strong determinant of intentions to uptake more technologies in the future. The results confirm established evidence from the literature that, besides economic factors, access to technological informa-tion and trust in/perceived usefulness of the different information sources will have an impact on technological uptake. The findings are policy relevant as


they give some indication of the factors influencing the process of targeting specific technological information transfer through the appropriate channels to agricultural producers, which builds a potential driver of behavioural change.

Acknowledgements: We thank Scottish Government who funded this re-search as part of the Rural Affairs and the Environment Portfolio Strategic Research Programme 2011-2016 Theme 4 WP4.1 ‘Adaptation to change in land-based and other rural industries’. We also thank the respondents to our survey.

References

Beedell, J., Rehman, T. (2000). Using social-psychology models to understand farmers’ conservation behaviour. Journal of Rural Studies 16(1), 117-127

Hair, J. F., Black, W., Babin, B., Anderson, R.E., and Tatham, R.L. (2006). Multivariate data analysis. 6th edition, Upper Saddle River, NJ: Pearson Prentice Hall

Jöreskog, K. G., and Sörbom, D. (2007). LISREL8.80: structural equation modeling with the SIMPLIS command language. Chicago, USA: IL Scientific Software International

Nuthall, P. L. (2001). Managerial ability - a review of its basis and potential improvement using psychological concepts. Agricultural Economics 24(3), 247-262

Sharma, A., Bailey, A., Fraser, I. (2011). Technology Adoption and Pest Control Strategies Among UK Cereal Farmers: Evidence from Parametric and Nonparametric Count Data Models. Journal of Agricultural Economics 62(1), 73–92

Toma, L., Barnes, A., Sutherland, L-A, Thomson, S., Burnett, F., Mathews, K. 2018. Impact of information transfer on farmers’ uptake of innovative crop technologies. A structural equation model applied to survey data. Journal of Technology Transfer 43:864–881

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Theory of Planned Behaviour: assumptions, applications, and limitations

João Augusto Rossi BorgesFederal University of Grande Dourados - [email protected]

Introduction

Reasoned action theories (i.e. theory of reasoned action (TRA), theory of planned behavior (TPB), and reasoned action approach (RAA)) have been in-creasingly used to study a variety of farmers’ decisions and behaviors. These theories are useful because they provide a structured and theoretically rational model, a replicable methodology and they can help to identify the underlying causes of farmers’ decisions and behaviors. The aim of this document is to the present the assumptions, a short guide of how to apply such theories and three applications, and some limitations.

Assumptions

The reasoned action theories are social cognitive theories to explain and pre-dict behavior in different contexts. Central to these theories is the concept of intention, which reflects the extent to which individuals are motivated to perform a given behavior and is conceptualized as the most proximal ante-cedent of behavior. In the TPB and RAA, intention is a function of attitude, perceived norms (also known as subjective norms), and perceived behavioral control. Attitude refers to individual’s global positive or negative evaluation of the behavior; perceived norms refers to one’s perception about social su-pport to perform the behavior, and perceived behavioral control refers to the extent one think that can actually perform the behavior. The RAA is a more comprehensive version of TPB, because RAA distinguishes between speci-fic dimensions of the three main TPB constructs. Attitude is differentiated in instrumental and experiential, perceived norms are decomposed in injuncti-ve and descriptive norms, and perceived behavioral control is differentiated in capacity and autonomy dimensions. Instrumental attitude refers to people evaluation of the results of a behavior and experiential attitude refers to peo-ple affective feelings towards the behavior. Injunctive norms capture people perceptions about what others expect them to do and descriptive norms refers

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to people perceptions about what important others on their social network are actually doing. Perceived capacity represents people perceptions about their own capability to perform the behavior and perceived autonomy refers to peo-ple perceptions about their own control over the behavior.

The reasoned action theories argue that beliefs are the foundations of beha-vior. Attitude is derived from behavioral beliefs (bi×ei), where bi is the belief about the likelihood of outcome ith of the behavior, and ei is the evaluation of the ith. The perveived norm is derived from normative beliefs (nj×mj), where nj is the belief about the normative expectations of the jth important referent, and mj is the motivation to comply with the opinion of the jth important referent. Perceived behavioral control originates from control beliefs (ck×pk), where ck is the belief about the presence of the kth factor that may facilitate or inhibit the performance of the behavior, and pk is the perceived power of the kth factor to facilitate or inhibit the behavior. Figure 1 represents the TPP model.

Figure 1. The TPB model.


Guidelines and applications

Short tips

- define the behavior under study according to the target-action-context-time principles;

- formulate the statements as exactly compatible with the behavioral criterion;

- the use of direct measures is useful to test the relative impact of attitude, perceived norms and perceived behavioural control on intention; in such case, I recommend the use of structural equation modelling to analyse the data;

- when the aim of the research is to identify the beliefs that are the foundation of behavior, it is recommended to access the possible outcomes for a specific behavior, possible important referents, and possible factors that facilitate or prevent the behavior. For that, qualitative interviewees are necessary;

- use the guidelines available to build the questionnaire;

- add additional constructs to enhance the model;

Application: Identifying the factors impacting on farmers’ intention to adopt animal friendly practices (paper under review)

Abstract

Brazil, one of the leading countries in livestock production, has not yet deve-loped legislation considering animal welfare issues and most of the actions to improve farm animal welfare (FAW) standards are developed by livestock industries and government focusing in meet the demands of exporting coun-tries. Such actions resulted in FAW protocols and manuals for adoption of best management practices. In this context, farmers’ decisions are of particular importance as they may comply with current FAW protocols or even decide to provide better FAW standards than required. A present example of farmers’ decisions to provide better FAW standards than required by FAW protocols is in the adoption of environmental enrichment in pig farming. This practice is widely available to pig farmers, however, anecdotal evidence shows that the adoption rate is low. This study uses the theory of planned behavior (TPB) as a framework to identify the socio-psychological factors that influence pig

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farmers’ intention to adopt environmental enrichment on their farms. The TPB hypothesizes that intention is determined by three psychological constructs: attitude, subjective norms, and perceived behavioral control. These three constructs are derived from behavioral, normative, and control beliefs, res-pectively. Self-identity was added as an additional construct to explain inten-tion. A survey with 185 farmers was conducted. We used Partial-Least-Square Structural Equation Modeling (PLS-SEM) to identify the impact of attitude, subjective norms, perceived behavioral control, and self-identity on farmers’ intention to adopt environmental enrichment on their farms. We used MIMIC models to identify the most important beliefs underlying farmers’ intention to adopt environmental enrichment in their farms. Results show that the intention of farmers to adopt was mainly determined by their positive perceptions about their own capability to adopt environmental enrichment (perceived behavioral control), followed by their perceptions about the social pressure to adopt it (subjective norms), their positive evaluations of adoption (attitude), and sel-f-identity. The most important behavioral beliefs were ‘increase productivity’, and ‘decrease animals stress’. The most important normative beliefs were ‘family’, ‘neighbor farmers’, ‘pig buyers’, and ‘experts’. The most important control belief was ‘receive bonus when selling pigs’. These results revealed important implications to design public and private interventions aimed to sti-mulate the adoption of animal friendly practices.

Application: Identifying socio-psychological constructs and beliefs un-derlying farmers’ intention to adopt on-farm silos (paper under review)

Abstract

Brazil is one of the leading countries in production and exportation of grains. However, most grain production regions in Brazil do not have an adequate storage capacity, which result in losses for the grain supply chain. A possible solution to increase storage capacity is the adoption of on-farm silos. We used the Reasoned Action Approach as a framework to identify the impact of attitu-de, perceived norms, and perceived behavioral control on farmers’ intention to adopt on-farm silos and to identify the most important beliefs underlying their intentions to adopt it. A survey was conducted with 170 farmers in Brazil. Data was analyzed by means of Partial-Least-Square Structural Equation Modeling and MIMIC models. Results showed that attitude was the main determinant of intention, followed by perceived behavioral control and injunctive norms.


Results also showed that ‘Sell grains at higher price’ ‘Have independence in relation to grain storage firms’, and ‘Have control over grain classification’ are the most important beliefs that drive attitude; ‘Banks’ is the most important belief that drive perceived norm; and ‘Have easy access to silos’ ‘Prioritize other investments’, and ‘Need skilled workers’ are the most important beliefs that drive perceived behavioral control. These results revealed important im-plications to design public and private interventions aimed to stimulate the adoption of on-farm silos.

Application: Understanding the intention of smallholder farmers to adopt fish production as diversification strategy (paper under review)

Abstract

Fish production is frequently mentioned as a farm activity that could be used as a diversification strategy by smallholders farmers. In Brazil, government has provided credit and rural extension services to stimulate smallholder far-mers living in rural settlements to adopt fish production. However, despite these efforts, the adoption rate of fish production is beyond governmental ex-pectations. In this paper, we used the reasoned action approach as a main framework to fulfill two objectives: first, to identify the impact of socio-psycho-logical constructs (i.e. attitude, perceived norms, perceived behavioral control and self-identity) on smallholder farmers’ intention to adopt fish production; and second, to identify the beliefs underlying farmers’ intention to adopt fish production. Results suggest that self-identity, attitude, and perceived norms impact on smallholder farmers’ intention to adopt fish production as a diver-sification strategy. Behavioral beliefs that represent possible outcomes of adoption of fish production were: “having an increase in farm income”, “ha-ving an additional source of food for own consumption”, and “having a better quality of life”. Normative beliefs that represent important others for farmers were: “sons/daughters”, “spouse”, “friends”, “neighbors”, “rural cooperatives”, “farmers’ unions”, “farmers’ associations”, and “governmental institutions”. Control beliefs that represent factors that would facilitate farmers to adopt fish production were: “having an easy way to sell fish production”, “having finan-cial incentive from governmental sources”, “Having free technical assistance”, “Having more knowledge about fish production”, and “Having river water flo-wing in the rural lot”. From a policy perspective, our results highlight the impor-tance of interventions targeted to prime an identity of fish farmers. In addition,

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interventions will benefit from strategies to develop more favorable attitude towards adoption of fish production and to increase social support.

Limitations

Decisions are dynamic. The data collection of constructs are snap-shots of farmers’ intention in time. An ideal approach would be to apply another survey later among the same sample of farmers to analyze whether farmers who sho-wed intention to perform a behavior do really do it. A research with time series data would also to show whether attitudes, subjective norm and perceived behavioral control change over time.

Another limitation is that the measurement of the constructs is open to ac-quiescence biases, which is the tendency of respondents to agree with state-ments regardless of their content.

The application of the questionnaire is time consuming, and there is a need of relatively large sample size for most of the statistical techniques used to analyze the data.


The Ethnographic Decision Tree Model (EDTM) for technology adoption studies

Mariana de Aragão Pereira PhD in Agricultural Management, Researcher from Embrapa Beef Cattle

Introduction: Decision-Making in Farming Contexts

The literature on decision making (DM) within the farm context is comprehensi-ve, including the context for decisions, decisions under risk and uncertainty, the types and relevance of decisions, and the steps of decision making. Farmers around the world constantly face farming decisions including “what” to produ-ce, “how much” to produce, at which technological level and cost. These deci-sions involve personal aspirations and experience, socio-cultural backgrounds, biological processes, economic factors, resources availability and constraints. The ability to make “good” decisions, given all these aspects, has been ackno-wledged by several authors as a determinant of the farm success. According to Kadlec (1985, p. 27), “an important attribute of a successful manager is the ability to make decisions that will enable the business to attain its goals”.

It is not without challenges that decisions are made, however. According to Kay et al. (2008, pp. 30-31), agriculture entails a peculiar environment for decision makers as farms and farming have unique characteristics that are not compara-ble to other non-farming businesses. Firstly, farmers cannot accurately predict production due to climate and biological processes. Moreover, in many cases, family and business are intertwined and there is a dynamic interaction between them, with a direct impact on farming goals. In contrast with non-farming bu-sinesses, it is common for farmers to operate in all levels of management, as they are owners and managers of the farms as well as providing labor. They argue that this situation poses pressure on farmers, who often place mana-gement into a secondary role. Also, it is not possible to fully replicate farming systems if a farmer decides to expand the business (i.e., by buying or renting more land), given the uniqueness of every farm, or piece of land. This means that for each farm, farmers may need to make decisions under quite different contexts. Finally, another important characteristic of agriculture is that most far-mers operate in largely perfectly competitive markets, that is, they have little, if any, influence on input or output prices. All of these challenges illustrate the risk and uncertainty involved in decision making within a farm context.

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There are several sources of risk in a farming context, including production, financial, legal, social, technological (Martin, 2005), market and personal risks (Kay et al., 2008). The relative importance attached to different sources of risk varies amongst different people. Understanding individual’s perception of, and attitude, to risk seems, therefore, a necessary condition for the understanding of how farmers make decisions, including adoption decisions. Despite the risk and uncertainty involved in decision making, farmers are constantly making decisions. The relative importance of these decisions depends on the extent to which the decision impacts on the attainment of farming goals. According to Castle et al. (1987), Kay et al. (2008) and others, this results from: the level of decision (strategic versus tactical); frequency, imminence and revocability of decisions as well as the number of alternatives for choice. The latter is of particular interest here, because the multitude of alternatives to choose from makes the decision more difficult for farmers. In this case, they need to, so-mehow, bring the number of alternatives down to a manageable set in order to make a decision (Harsh et al., 1981).

Decision-Making Models

How farmers make (or should make) decisions is the subject matter of diffe-rent schools of thought that investigated this topic. Within the farm manage-ment field, the DM process has been approached, by and large, from a func-tional standpoint with the objective of showing farmers how they should make decisions if an optimum result is to be achieved (i.e., normative approach) (Castle et al., 1987; Harsh et al., 1981; Kay et al., 2008). Traditionally, the DM process has been described as a series of phases (and steps) that farmers should go through. A summary of the phases involved in decision making, with their respective steps, is presented in Figure 1.

Figure 1. Phases of the decision-making process. Sources: adapted from Castle et al. (1987), Harsh et al. (1981), Kadlec (1985) and Kay et al. (2008).


In the normative approach, the decision process starts with an “assessment” phase where problems, opportunities and possible alternatives are mapped out. This initial phase is followed by a “making sense” phase when farmers gather data and use it to make sense of the pros and cons of each alternative. The “decision” itself (i.e., choice of an alternative) follows and is a step within the “action” phase. This phase also includes the step of implementing the decision. In the final phase, namely “analysis”, outcomes are evaluated and responsibility accepted.

This linear model of DM has been criticized, however. Several authors agree (Olson, 2003; Ohlmer, Olson and Brehmer, 1998; Nuthall, 2010;) that farmers do not follow linear steps when making decisions. To support their argument, Ohlmer et al. (ibid) carried out 18 case studies of Swedish farmers, including two longitudinal studies that lasted three years. Results showed that farmers undertook a dynamic process of decision making which involved constant evaluation of the decision as new information arose. This new information influenced not only the current decision but also fed forward to new decisions as it impacted on farmers’ future expectations and goals (i.e., learning pro-cess). This continuous reassessment of decision is in sharp contrast with the linear model, where evaluation occurs only at the end of the decision process (Figure 1). They proposed, therefore, a matrix model to better represent the dynamics of the decision-making process instead of the linear step-by-step model (Ohlmer et al., 1998).

Despite this advancement, both linear and dynamic models essentially focus on the functional processes of decision making, paying little attention to the mental processes involved. These mental processes provide information on “how” and “why” decisions are made. Therefore, these models lack an expla-nation of the farmers’ cognitive processes that lead to particular choices. This explanation is provided by other theories and models, like the Theory of Real-Life Choice and the Ethnographic Decision Tree Model, respectively.

The theory of real-life choice is concerned with how people do make deci-sions in real-world contexts. In contrast with other decision-making theories (e.g., linear-additive or normative models), the theory of real-life choice main-tains that people do not make decisions by holistically assigning utility and probabilities to each alternative and then ranking and selecting the option with the highest expected utility (Kahneman & Tversky, 1972). Instead, the choice

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among multiple alternatives occurs by comparing alternatives on one dimen-sion at a time and eliminating those with least desired characteristics on this dimension (Gladwin, 1989, p. 10). This process occurs in order to make deci-sions cognitively manageable and viable. According to Nuthall (2010), farmers simplify decision making to achieve efficiency by, for example, using intuition, experience and rules, amongst other strategies, to make decisions.

Studies have shown that in real life people prefer a simple approach to deci-sions rather than complex approaches (Gladwin, 1989; Ohlmer et al., 1998; Sjah, 2005), given the cost in time and mental energy (Nuthall, 2010, p. 87). What is more, people frequently use “rules of thumbs” (i.e., heuristics) in trying to manage multiple alternatives and make decisions easier (Nuthall, 2010, p. 88). Given the limited access and cognitive capability for processing infor-mation, the best decision is the one within people’s reach, given their current knowledge and constraints (Murray-Prior, 1998). Thus, it is realistic to assume that people generally make reasonably rational decisions with respect to their particular objectives, e.g., they have “good” reasons to do what they do.

To assume that people make reasonably rational decisions implies that peo-ple themselves are experts on how (and why) they make their decisions. “People as experts” is the main underlying assumption of the real-life theory (Gladwin, 1989, p. 9). Given this central role of decision makers for real-life choice theory, ethnographic1 techniques have been applied to studies on de-cision making using such a theory as a framework. These techniques allow for decision makers to reveal their own decision criteria and for researchers to develop cognitive based models.

One particular model that uses ethnographic techniques and has become po-pular among scholars is the Ethnographic Decision Tree Modelling (EDTM). Gladwin (1989, p. 9) asserts that this model is built from insider perspectives using “emic” criteria (relevant for interviewees) rather than “etic” criteria (im-posed by researchers). EDTM is, thus, a cognitive based model. In this sense,

1 The dictionary definition of Ethnography is “the study and systematic recording of human cultures [and] a descriptive work produced from such research” (Merriam-Webster, 2011). According to Gladwin (1989, p. 9), it is concerned with describing a culture from “insider’s” (e.g., interviewee) rather than “outsider’s” (e.g., interviewer) point of view. Ethnographic techniques rely heavily on fieldwork and participant observation to minimize researchers’ own ethnocentricity, i.e., “the viewing of another culture through the lens of one’s own cultural values and assumptions” (Gladwin, 1989, p. 9).


the model is not designed to test researchers’ interpretation of what the deci-sion criteria should be, but to identify and describe criteria people use in fact to make decisions. A consequence of this specification of the model is that it is highly context-sensitive, as different people in different environments may use different criteria to address similar issues.

EDTM has been used to understand farmers’ decision making for a variety of decisions in various countries. Examples of studies using EDTM include: farmers‘ tree planting behavior (Fairweather, 1992) and conversion of tradi-tional farming systems into organic production in New Zealand (Fairweather & Campbell, 1996); technology adoption among Mexican farmers (Gladwin, 1977 as cited in Gladwin, 1989); adoption and non-adoption of heifer synchro-nization among dairy farmers in New Zealand (Jangu, 1997); and, access and repayment of agricultural credit in Indonesia (Sjah, 2005).

In Brazil, it has been applied by Santos (2005) with the decision tree being used as a framework to simulate the viability of supplementary irrigation for sugarcane producers in the State of Alagoas, Brazil. The model was built in a prescriptive fashion to indicate the conditions in which the viability of supple-mentary irrigation systems is higher and, consequently, when farmers should adopt such a technology. Another example is found in Pereira et al. (2011), who studied innovative farmers’ decisions on cattle supplementation during the dry season, using EDTM. They found that farmers with a strong producti-vity orientation and crop production on the farm would supplement cattle while farmers having to purchase the supplement were less likely to do so, particu-larly under financial constraints.

A Guideline for applying EDTM

Ethnographic Decision Tree Modelling is used to gain understandings about how individuals make real world decisions. The method allows for the deci-sion makers to elicit themselves the decision criteria, which are organized in a decision tree frame, based on “if-then rules” (Gladwin, 1989). Models are developed based on individuals’ own terms and criteria that they actually use to make decisions. There are common principles underlying decisions and, therefore, the construction of EDTM. Firstly, Gladwin’s (1989) model assumes that people (e.g., farmers) compare alternatives when making decisions. An alternative (e.g., artificial insemination) has a set of aspects or characteris-

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tics and each aspect is one dimension of an alternative (e.g., ease of use). All aspects are discrete and assume probabilities of one or zero (i.e., true or false). When the aspect is a continuous variable, such as cost, it is treated as a constraint by the decision maker (e.g., is the cost < X?). Secondly, aspects are ordered in such a way that alternatives of choice are set at the top of the tree, the decision criteria at the nodes and the outcomes at the ends of the tree, providing several decision paths (i.e., different combinations of criteria). This ordering of aspects gives the model a hierarchical frame.

Within this hierarchical frame, the decision-making process occurs in two sta-ges. In the first stage, known as “elimination-by-aspects” (Tversky, 1972, as cited in Gladwin, 1989), alternatives with unwanted aspects are eliminated wi-thout further thought, often subconsciously (e.g., elimination of artificial inse-mination (AI), if the farm has no breeding herd). The second stage is the “hard core” part of decision making, that is, the conscious and thoughtful stage of the decision process (Gladwin, 1989, p. 20), like illustrated in Figure 2. During this stage, individuals rank relevant (“emic”) aspects and compare alternatives based on these aspects (e.g., availability of qualified staff to carry AI, cost of equipment and semen, difficulties found etc.).

Among all alternatives entering the second stage of decision making, the one that passed through all aspects and ranked highest in a major aspect is the chosen alternative. Gladwin (1989, p. 20) argues that this ordering of aspects assembles the economists’ “maximization subject to constraints”. To elicit these aspects, or decision criteria, Gladwin (1989) suggests the eth-nographic interview and participant observation (i.e., triangulation of data to ensure internal validity of the model). Decision criteria are elicited by contras-ting decision behavior over time, space, and decision makers. After elicitation, decision criteria are then organized in a decision tree frame, based on “if-then rules”. Gladwin (ibid) explains that a decision tree can be constructed for in-dividual farmers and then combined into a composite model (direct method). Alternatively, it can also be built indirectly through continuous review and im-provement of the model, as new informants are interviewed (indirect model). A detailed explanation on how to build the composite model is found in Gladwin (1989, pp. 39-45). When used under a quantitative approach, EDTM has been tested against empirical data, predicting between 80 and 95% of decisions (Gladwin, 1989). However, in qualitative testing the model is not a concern.


The model aims at organizing empirical data in such a way that patterns beco-me evident, improving the understanding of the phenomenon under investiga-tion (as opposed to testing hypotheses). The model is then considered useful when it enables a better understanding of the decision-making processes of the interviewees.

Despite the benefits of using ethnographic decision tree modelling, the model has its pitfalls. One pitfall is that the model building is time consuming (Murray-Prior, 1998) and challenging as there are only general guidelines on how to build the model. This lack of formal procedures of model building is illustrated by Gladwin’s (1989, p. 40) comments: “you juggle decision criteria, by the

Figure 2. Motivations for supplementing rearing cattle with protein-salt complex during the dry season (second stage of DM). Source: PEREIRA (2011).

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seat of your pants‟ and see if the tree you get makes sense and predicts well enough”. Although this may suggest models are arbitrary, they are developed based on real world decisions eliciting criteria that are a cue of people’s men-tal process. Moreover, model testing allows for further confirmation of decision criteria and their ordering.

Researchers’ generalization of “emic” criteria is another challenge with this method. Such generalization is often necessary in order to merge several indi-viduals’ “emic” criteria into one general “quasi-etic” criterion that makes sense in the model. During this process, some minor decision criteria may also be disregarded in the final composite model. The challenge, therefore, is to pre-serve the ethnographic validity of individual models, that is, informants have to “go down” the composite model through the same path and end up with the same outcome as they did before. Usually, model testing minimizes resear-cher’s bias (e.g., misspecification of criteria) and ensures internal validity.

A major limitation of EDTM is that the model does not provide a psychological explanation for the choice of decision criteria (Fairweather & Campbell, 1996; Jangu, 1997; Murray-Prior, 1998; Sjah, 2005). In other words, EDTM does not provide explanations as to why informants choose a particular set of cri-teria to guide their decision-making process. This explanation is only possible by further assessment of informants, which can be done using the Personal Construct Theory - PCT (Murray-Prior, 1998), for example, among other theo-ries. PCT is not part of this scope however.

References

Castle, E. N.; Becker, M. H.; Nelson, A. G. Farm business management: the decision-making process (3 ed.). New York: Macmillan, 1987.

Fairweather, J. R. A tree model for Hawkes Bay farmers’ tree planting decisions. Lincoln: AERU, 1992. (215).

Fairweather, J. R.; Campbell, H. The decision making of organic and conventional agricultural producers. Lincoln: AERU, 1996. (233).

Gladwin, C. H. Ethnographic decision tree modelling (Vol. 19). Beverly Hills: Sage Publications, 1989.


Harsh, S. B.; Connor, L. J.; Schwab, G. D. Managing the farm business. Englewood Cliffs: Prentice-Hall, 1981.

Jangu, N. Decision processes of adopters and non-adopters of an innovation. Unpublished Ph. D., Lincoln University, 1997.

Kadlec, J. E. Farm management: decisions, operation, control. Englewood Cliffs, N.J.: Prentice-Hall, 1985.

Kahneman, D.; Tversky, A. Subjective probability: a judgment of representativeness. Cognitive Psychology, 3(3), 430-454, 1972.

Kay, R. D.; Edwards, W. M.; Duffy, P. A. Farm management (6 ed.). New York: McGraw-Hill, 2008.

Martin, S. Risk management. In: N. Shadbolt; S. Martin (Eds.). Farm management in New Zealand (pp. 201-220). Melbourne: Oxford University, 2005.

Murray-Prior, R. Modelling farmer behaviour: a Personal Construct Theory interpretation of hierarchical decision models. Agricultural Systems, 57(4), 541-556, 1998.

Nuthall, P. L. Farm business management: the human factor. Oxfordshire: Cabi, 2010.

Ohlmer, B.; Olson, K.; Brehmer, B. Understanding farmers’ decision making processes and improving managerial assistance. Agricultural Economics, 18(3), 273- 290, 1998.

Olson, K. D. Farm management: principles and strategies. Ames, Iowa: Iowa State Press, 2003.

Pereira, M. de A. Understanding adoption and non-adoption of technology: a case study of innovative beef farmers from Mato Grosso do Sul State, Brazil. Unpublished PhD, Lincoln University, Lincoln, 2011.

Pereira, M. de A.; Woodford, K. B.; Nuthall, P.; Fairweather, J.; Medeiros, S. R. Suplementação de seca sob a ótica do pecuarista: o processo decisório. In: Reunião anual da Sociedade Brasileira de Zootecnia, 2011, Belém. Anais… Belém: SBZ, 2011.

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Santos, M. A. L. d. Irrigação suplementar da cana-de-açúcar (Sccharum ssp): um modelo de decisão para o Estado de Alagoas. Universidade de São Paulo, Piracicaba, 2005.

Sjah, T. Decision making and strategies for agricultural credit implementation in Lombok, Indonesia. Unpublished PhD, University of Queensland, Gatton, 2005.


PANEL 3 - Experience and knowledge exchange

Factors affecting technology adoption in beef cattle production in Rio Grande do Sul state, Brazil

Matheus Dhein Dill1-2, Júlio Otávio Jardim Barcellos3, Paulo Rodrigo Ramos Xavier Pereira4, João Armando Dessimon Machado5, Gabriel Ribas Pereira3, Vitor Francisco

Dalla Corte6, Odilene de Souza Teixeira3

1 Universidade Federal Rural de Pernambuco, Garanhuns, Pernambuco, Brasil2 Universidade Federal do Rio Grande do Sul, Campus Litoral Norte, Departamento

Interdisciplinar, Rio Grande do Sul, Brasil3 Universidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Zootecnia,

Porto Alegre, Rio Grande do Sul, Brasil4 Universidade Federal do Piauí, Bom Jesus, Piauí, Brasil

5 Universidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Agronegócios, Porto Alegre, Rio Grande do Sul, Brasil

6 Faculdade Meridional, Passo Fundo, Rio Grande do Sul, Brasil

Abstract: The objective of this study was to verify the effects of improved native fields (INF), winter pastures (WP) and summer pastures (SP) on the weaning rate in beef cattle production. Subsequently, the socioeconomic and productive characteristics of the farmers that are related to the adop-tion of technologies that increase the weaning rate were verified. A survey was conducted with 73 farmers of the breeds Hereford and Braford in Rio Grande do Sul state, Brazil. A data analysis was performed using the mi-nimum ordinal squares method and the regression analysis (Tobit). The results showed that cattle farmers who adopt winter pastures have higher weaning rates, and the factors that influence this adoption are related to a higher number of employees on the farm and the use of a crop-livestock production system. In addition, farmers who receive a greater number of technical assistance visits per year are more likely to adopt winter pastures and improved native fields. This information can be useful in the formu-lation of technological dissemination programs that aim at a sustainable production of beef cattle.

Keywords: native pasture, production system, technology diffusion.

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Introduction

The global perspective for population growth and the increase in demand for meat have led to discussions on the rural extension actions needed to pro-mote sustainable food production. In Brazil, most beef cattle herds are raised on pasture due to soil and climatic characteristics as well as the availability of land. In Rio Grande do Sul, native pastures are the main source of feed, however, present variations in the quantity and quality of forage during the year. Moreover, forage production has been reduced using inappropriate ma-nagement practices, causing soil degradation, erosion, and the appearance of species of low nutritional value for animals (Medeiros and Focht, 2007).

In this context of shortage pasture, the feeding of cows becomes worrisome, since the adequate response in kilograms of calves weaned depends on the conditions to which the cows were submitted. This influences the rate of weaning, one of the main efficiency reproductive indicators, which should be above 70% in the cow-calf systems (Lampert et al., 2012; Dill et al., 2015b). In Rio Grande do Sul state (RS), this indicator is around 56% demonstrating that the productive performance should be improved (IBGE, 2017). The alternatives to improve reproductive per-formance include feeding management, natural pasture improvement, utilization of cultivated pasture, feed supplementation (i.e., protein, energy and mineral), stocking rate adjustment, and management techniques (Oliveira et al., 2018).

However, the slow adoption rate of many farming practices is often a source of frustration for researchers and expansion agents. Additionally, many studies assume that a given technology improves the productive performance of the farm; however, they do not directly assess the impact technology has on pro-duction, especially in the sample examined (Mogensen et al., 2016; Florindo et al., 2017). In this way, the originality of this study is highlighted because aside from verifying the impact that new technologies have on the reproducti-ve performance of the herd it also identifies the characteristics of farmers who make use of such new technologies.

In this sense, the objective was to verify how types of pastures (improved nati-ve field, winter pasture, and summer pasture cultivated) influence the weaning rate in beef cattle production. Subsequently, it was identified which characte-ristics of livestock farmers affect the adoption of technologies that positively impact the reproductive performance of their cow-calf system.


Material and Methods

A preliminary questionnaire was elaborated and later tested by means of in-terviews with 10 specialists (researchers on veterinary and animal sciences) in this fi eld intending to characterize the profi le of farmers in relation to the productive structure and cattle raising indicators (e.g., area destined for beef cattle raising; total amount of livestock heads; number of mated cows per year; weaning rate; number of bulls; age of heifers at their fi rst mating; age and weight of calves at weaning).

The farmers also responded about the pasture in which the animals were kept, being native fi elds, winter pastures, and summer pastures. Natural pastures present structural diversity with a predominance of grasses and relatively low proportions of legumes (Nabinger et al., 2000). The main summer forage species cultivated: Panicum maximum, B. brizantha, B. decumbens, B. humidicula, Cynodon spp., Pennisetum purpureum, Pennisetum americanum, Sorghum spp., and Brachiaria plantaginea. The main winter forage species cultivated: Lolium multifl orum, Avena strigosa, Avena sativa, Vicia sativa, Vicia villosa, Trifolium vesiculosum, Trifolium subterraneum, Trifolium repens, Trifolium pratense, Lotus corniculatus, and Medicago sativa (Nabinger et al., 2000).

After validation by the experts during the pre-test, the breeders of Hereford and Braford in RS state were interviewed. The sample was calculated using the equation (1) described by Anderson et al. (2003).

(1)

Where: n = sample; z = confi dence level; p = proportion of one characteristic of the population to be sampled; q = (1-p); ε = margin of error. According to IBGE (2006), RS has 441,467 rural establishments, out of which 329,901 are cattle raisers. The confi dence level of 95% and a margin of error of 10% were used. The sample resulted in 73 farmers (n = 72.56); so, the fi nal questionnaire was applied to this sample in RS. Snowball sampling was used to identify farmers; the respondents were then asked to name another similar farmer. This metho-dology has the analogy of a snowball, which rolls down a slope and becomes larger and larger as more snow is collected from the slope (Anin, 1999).

(1)

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The statistical procedure was performed in two stages. In the first step, using the minimum squares ordinal method, the relationship between the weaning rate and the summer pasture, winter pasture, and improved native fields was examined represented by the participation that each variable had in relation to the total area (hectares) used for beef cattle exploitation on the farm.

Once the variables influencing the weaning rate (i.e., winter pasture and im-proved native fields) were defined, the objective in the second stage was to identify the characteristics of farmers that impacted the adoption of these te-chnologies. The improved native field data (hectares) were transformed into a logarithmic scale to soften the outliers and make the waste distribution normal.

Through a literature review, we can see that the variables that affect tech-nological adoption can be represented by: Internet access (number of days accessed per month) (Dill et al., 2015a); institutions involved (number of asso-ciations and rural unions with which the farmer is affiliated) (Llewellyn, 2007); number of employees and number of technical assistance visits performed on the farm per year (Abdulai and Huffman, 2005), the latter being transformed into a natural logarithm. The other independent variables, characterized as crop-livestock integration and production diversification (≤ 3 of farming activi-ties), are binary, 1 (one) being represented by the farmers who have crop-li-vestock and/or diversification of production and 0 (zero) for farmers who do not have the mentioned activities. The age of farmers (in years) (Johnson et al., 2010) was also taken into consideration as well as the number of emplo-yees (Boahene et al., 1999), which was obtained by dividing the number of people working on the farm by the total area. To verify the characteristics of farmers who influence the adoption of improved native fields and winter pas-ture, the Tobit regression model was used.

The analyses proved consistent for the reset test of specificity and for the White test of heteroscedasticity. The residues of the model showed a normal distribu-tion and the collinearity test by variance increase did not show collinearity.

Results

The rural properties that constituted the sample occupied an average of 1,380 hectares of beef cattle and 1,631 heads, among which 529 cows were mated by means of a natural method using 22 bulls and artificial insemination, that is, one bull


for 24 females. The average age of heifers at first mating was 25 months and calves were weaned weighing around 181 kg at 183 days of age with an average weaning rate of 74%. In these cow-calf operations, the adoption of improved native fields and winter pasture increased the weaning rate in beef cattle production (Table 1).

Table 1. Effect of the level of adoption of cultivated pastures and the rate of weaning of beef cows.

Coefficient SEM P-valueWinter pasture 0.099 0.048 0.044**Improved native pasture 0.090 0.042 0.034**Summer pasture 0.019 0.132 0.885SEM: Standard Error Mean; *P<0.10; **P<0.05.

The null hypothesis was rejected at 1% of the level of significance for the im-proved native field (P = 0.003) and for the winter pasture (P = 0.044) (Table 2).

The values of the coefficients of the Tobit model indicate that the adoption of the improved native field (P = 0.025) and the winter pasture (P = 0.084) is influenced by technical assistance orientation. The farmers with the largest number of employees (P = 0.092) and who have a crop-livestock integration system (P = 0.019) are more likely to adopt winter pastures.

Table 2. Factors that affect the adoption of the type of pasture in cow calf production system.

FactorsImproved native pasture Winter pastureCoeff SEM P-value Coeff SEM P-value

Age 0.012 0.016 0.467 0.111 0.301 0.711Internet access 0.054 0.381 0.887 8.984 7.056 0.203Technical assistance 0.513 0.228 0.025** 8.574 4.965 0.084*Diversification −0.142 0.549 0.794 −0.701 10.554 0.947Number of employees 0.293 0.385 0.447 13.143 7.801 0.092*Association membership 0.362 0.589 0.539 −5.991 10.969 0.585Crop-livestock integration −0.619 0.539 0.259 20.728 8.829 0.019**Coeff: Coefficient; SEM: Standard Error Mean; *P<0.10; **P<0.05.

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Discussion

Considering the average weaning rate obtained in the farms studied, it is pos-sible to see that the production systems are of large-scale and have technical indicators above those obtained in RS state. These results are consequences of the adoption of feeding techniques (i.e., native and winter pasture), which op-timize the reproductive results of the herd. Since the outcome of the economic performance of farms is associated to the beef production, it is essential that this production is taken into account from the females’ productivity point of view by means of the optimization of its efficiency of production (Pardo et al., 2018).

However, in an expansive, traditional, South Brazilian pastoral system, mating occurs at 3 years of age (36 months), something that increases the number of animals in the field, negatively affecting the economic performance of the business (Roso et al., 2009). The main feature of the expansive system is the use of large tracts of land, where the animals can continually graze on the natural pasture throughout the year with little or no supplementation (Dick et al., 2015). The cows and heifers are usually allocated to theses pastures of low nutritional value, changing in quantity and quality throughout the year, due to nutrient depletion after the first frosts. This seasonality interferes in the reproductive performance, especially in primiparous cows, because they have not yet completed their growth. In RS, calving usually concentrates at the end of winter, coinciding with the period of lower native pasture availability and higher nutritional requirements of cows (the late third of gestation and lacta-tion). This food restriction often prevents the animals from achieving adequa-te body conditions and consequently keeps them from reaching satisfactory conditions to conception.

According to Rocha et al. (2003), winter pastures allow adequate develop-ment of animals during the period in which the growth of natural pasture slo-ws. Vaz et al. (2014) reported that cows kept in winter pasture composed of oats (Avena sativa), ryegrass (Lollium multiflorum), and vesicular clover (Trifolium vesiculosum) produced 22.6% more calves than cows retained ex-clusively in native fields.

The postpartum use of improved native fields allows higher weight gains until the beginning of the mating season, leading to higher pregnancy rates when compared to animals allocated in native fields (Lobato and Barcellos, 1992).


In addition, the improved native field can increase profits and reduce environ-mental damage as a result of production optimization. However, adoption of these technologies is often low because of the characteristics of rural farmers (Borges et al., 2014) and due to a lack of financial compensation to preserve natural resources (Nabinger et al., 2009).

According to Florindo et al. (2017), improvement of the environmental per-formance of beef cattle should be associated with financial profitability, redu-cing the environmental impact, and increasing economic viability. Figueiredo et al. (2017) also demonstrated that better managed pasture and integration systems present a great potential to collaborate with the reduction of environ-mental impacts.

The characteristics of rural farmers that influence the adoption of technologies make are possible to observe that the exchange of knowledge between far-mers and technical assistants plays an important role in the decision-making process to adopt new technologies, which in turn, has further implications in the development of new approaches for a rural extension. According to Dill et al. (2015a), with the advancement of technological dissemination, the infor-mation on the benefits of innovations becomes more relevant, thus, favoring adoption by farmers. Gillespie et al. (2007) observed that farmers who do not adopt the best management practices in beef cattle production in the United States lack a better understanding of new techniques. They either believe there is a high cost to implement them or else they think certain technologies have no applicability on their farms. In this sense, it is necessary to develop training programs and implement technical assistance practices in the form of creating effective mechanisms to encourage sustainable food production (Jara-Rojas et al., 2012).

However, access to technical assistance and rural extension in Brazil are still among the main problems related to diffusion and technological adoption in rural areas. According to the Agricultural Census, most rural producers do not receive technical assistance. Only 20% of the farmers use some type of tech-nical guidance to carry out their productive activities, and access to technical assistance is more common in medium and large farms (IBGE, 2006).

Rogers (2003) emphasizes that technological adoption is a process of accep-tance of new ideas, represented by five stages: i) The stage of knowledge is

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the first contact with technology and may be related to a need established in the past or generated at the time of the first contact with innovation. ii) In the stage of persuasion, the rural producer is interested in the attributes of inno-vation and looks for information to minimize the uncertainties and to base an opinion on the new idea. This process is supported by a set of institutional structures that promote knowledge, which are interrelated with factors exoge-nous to organizations (e.g., suppliers, associations, unions, public and private institutions), as well as by endogenous institutional factors (i.e., habits, cus-toms, beliefs, intentions, and attitudes). iii) The decision stage is characterized as the moment at which the individual adopts or rejects the technology. Most individuals adopt only after a period, to verify the usefulness of the technology through the judgment of the first adopters. iv) The deployment phase occurs when people put the technology into use. v) The final stage of the technologi-cal adoption process is characterized as the confirmation phase, when people try to reinforce the decision they have already made.

In a study carried out in RS, Borges et al. (2014) identified that farmers’ inten-tion to use improved natural pastures in beef cattle production is influenced by the availability of qualified technical assistance and social pressure in the way farmers evaluate the use of this type of pasture. Factors such as increasing weight gain, increasing the number of animals per hectare, increasing pasture retention, reducing feed costs, and preventing erosion also have a positive influence on the intention to adopt improved pasture technology.

As observed, the process of technological adoption can often be delayed due to the various personal, social, economic, and institutional factors involved, even for those technologies that already offer recognized productive benefits in rural areas. This is a fact that deserves special attention in the beef cattle production of RS because the diffusion and technological adoption are consi-dered the main obstacles for the sustainable development of the activity. This has implications for the development of rural extension approaches.

The increase in the number of employees per area was positively associated with the increase in adoption of winter pasture. According to Barcellos and Suñe (2011), human resources are one of the most important points for the correct diagnosis of beef cattle ranching. Therefore, the employees’ literacy rate, the level of motivation (awarding programs), and the culture inherent to the activity (tacit knowledge) must all be considered. The development of


certain personal skills through training programs can sensibly influence the performance of the individual as well as benefit the enterprise through the specialization of its workforce. Given this context, it is also possible to infer that the intensification of production triggered by human resources tends to benefit the performance of the farm, since the rural enterprises have a variety of alternatives to be explored.

Farmers with crop-livestock integration systems have proved to be more likely to increase the adoption of winter pasture. The combination of livestock and crop or forest production in the same area tends to increase the amount of or-ganic matter in the soil, favoring the production of biomass and increasing the stocking rate in pasture. Thus, integrated livestock farming can be considered a promising strategy for a sustainable increase in agriculture (Moraes et al., 2014; Gil et al., 2015). In a study with U.S. calves, Pruitt et al. (2012) also identified a possible interaction between productive aspects and the comple-mentarity among technologies as promoters of more technological use.

In such a context, it is possible to see that the process of technological use includes productive factors and an intricate web of social relations in which the agents involved confront different ideas and develop different activities in their struggle to achieve success as rural businesses. Therefore, technologi-cal use should be analyzed considering the socioeconomic context as well as the existing productive aspects (Caceres et al., 1997) because these factors interact with one another, either promoting or inhibiting dissemination and te-chnological use in the rural environment (Souza Filho et al., 2011).

Conclusions

Through this investigation, the elements that guide cattle farmers to use different feeding strategies in their cow-calf systems are understood. Thus, adopting winter pastures in greater proportions optimizes productivity through better weaning rates, as well as, integrated livestock and agricultural practice and the use of a larger number of employees. The presence of various tech-nology diffusing agents and rural extension on the farm stimulates farmers to introduce an improvement of native fields and cultivated pastures. Therefore, technical assistance and rural extension actions, it seems, deserve special attention in the development of public policies aimed at rural development.

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Acknowledgments: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. The financial support of National Council for Scientific and Technological Development (CNPq) (process number: 150309/2014-7) is gra-tefully acknowledged.

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Factors affecting technological adoption in beef cattle in Corrientes province, Argentina

Silvana Inés GiancolaAgricultural Engineer M. Sc. Center for Research in Economics and Prospective Studies

(CIEP), National Agricultural Technology Institute INTA / Argentina

Introduction

The province of Corrientes covers an area of 88,199 km2. Livestock occupies 5,644,736 hectares in this province, which represents 64% of the provincial area (Sampedro and Calvi, 2016) Beef cattle in Corrientes is estimated in 4.5 million heads (SENASA, 2018).

As total Argentinian stock is 54.8 million heads, Corrientes takes the fourth place with 8.5% share (SENASA, 2018) and contributes with 10.4% of the country’s cows (Calvi, 2017). Sampedro and Calvi op. cit. calculate a produc-tive orientation index (IOP2) for Corrientes province of 0.3; which shows that the main activity is breeding - wintering. Although there is a significant deve-lopment of available technologies in Corrientes to improve production rates, there are significant gaps in production between farmers who adopt technolo-gy and provincial or regional average production and weaning rates are low, between 48% and 62%, according to provincial livestock region. Identification of basis and nature of the determining factors regarding technology adoption becomes an issue of particular interest in order to design specific intervention strategies. In this sense, since 2010 researchers at INTA have been studying the phenomena in different productions and regions of the country. In the beef cattle case in Corrientes, the following objectives were raised.

Main objective: Identify the determining factors in technology adoption for bo-vine livestock production for meat corresponding to the 500-3000 head stra-tum (per livestock establishment) in the province of Corrientes.

Specific objectives:

• Establish the critical technologies on which to deepen research of adoption factors.

2 Index of productive orientation (steers + young bulls) / cows, where less than 0.20 predominates breeding, between 0.21 and 0.40 is breeding - wintering, between 0.41 and 0.60 is wintering - breeding and greater than 0.60 is wintering

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• Identify, analyze and link the causes that affect adoption of critical techno-logies through a qualitative approach.

• Quantify technology adoption factors through producer survey.

• Make contributions to institutional and inter-institutional intervention.

Methodology

Definition of the population and study area: Population is defined as livestock producers that have between 500 and 3000 heads of cattle and are mainly de-dicated to raising cattle with an IOP <0.40 in two Homogeneous Agroecological Zones (ZAH): El Malezal, Departments of Santo Tomé, Gral. Alvear and Gral. San Martín; and Afloramiento Rocosos (Rock Outcrops) and Monte de Ñandubay, Departments of Mercedes and Curuzú Cuatiá, province of Corrientes.

Technological profile and identification of critical technologies: The me-thodology of technological profile, developed by INTA, relies on participatory workshops with livestock sector professionals. The technological-productive situation is characterized by homogeneous agroecological zone (ZAH), being classified into three technological levels (NT): low (NTB), medium (NTM) and high (NTA), based on yields associated with technological packages imple-mented at farms. Additionally, (also by NT), the degree of technology adoption for each of the technologies indicated is estimated (Adoption rates) (Cap et al., 2010). This diagnosis phase allows detecting productivity gaps: percenta-ge variance between productivity of the low technological level and the high technological level, not explained by agro ecological issues. As a final product of these workshops, critical technologies are identified, defined as those that, when adopted, generate significant impact on productivity, quality, social and environmental aspects (Giancola et al., 2012).

Qualitative stage: Focus or discussion groups’ techniques were used at fiel-dwork with producers, as they are valuable research tools aimed to obtain knowledge about a social event or a focused issue previously defined by the researcher. It is useful for exploring knowledge, practices and opinions, in not only the sense of examining, what the group consulted thinks but also how and why they think what they think (Kitzinger, 1995).


At this stage with Corrientes farmers, we brought back the critical technolo-gies form (used in previous stage) as main input. 9 focus groups (91 farmers) were carried out in fi ve locations in the province of Corrientes during 2011.

Quantitative stage: Qualitative results were deepened by applying quantita-tive method. It is important to combine both types of studies when inquiring about the determinants of the adoption of certain technologies, since it may reveal valuable and complementary information. Dowbley (2012) states: “If for the design of the form only the vision of the technicians had been considered, biases and errors in the interpretation of the survey results would have been generated. Likewise, the qualitative study also allowed us to fi nd a suitable language to ask farmers questions”. Agricultural establishments (EAPs) of the ZAH Malezal (departments General Alvear, Santo Tomé, San Martín and part of Mercedes) and the ZAH Afl oramientos Rocosos (part of the Mercedes de-partment) of the province of Corrientes were selected.

Figure 1. Selected departments. Province of Corrientes.

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Survey design: The measuring instrument chosen is a semi-structured form organized by chapters that seeks to reveal basic data about the farm, the far-mer, the decision maker and the critical technologies involved in each stage of the production process. Results obtained in focus groups carried out during the qualitative stage were taken into account to design the form. Single and multiple spontaneous questions were included (no answer options were given in advance). Sampling frame: SENASA (National Agrifood Health and Quality Service Argentina) registration. Statistical unit. Livestock farmers who have between 500 and 3000 heads and are mainly dedicated to raising cattle (IOP <0.40). For the sample design, the systematic method of Madow was applied with proportional probability to size.

Fieldwork was carried out between September 2012 and May 2013 (reference period for livestock production set from July 1, 2011 to June 30, 2012. Total surveys carried out 104 (over a total population target of 226 farms.).

Findings

Technological Profile and identification of critical technologies: Productivity gaps were obtained. Findings shows that within the same agro-e-cological zone (ZAH) there are livestock establishments with yield differences (in kg / ha / year) up to 100% and 125% (Giancola et al., 2013). 18 critical technologies were selected: set aside in natural grassland, carrying capacity adjustement, service parking in three months, age of entorement, prevention of venereal diseases, pre-immunization against Bovine Sadness, rational use of antiparasitic, among others.

Qualitative stage: Giancola et al., 2012 and 2013, present qualitative re-sults. Limiting causes evidenced, among others, context factor such as ab-sence of long-term agricultural policies and lack of skilled labor force. Data also showed that farmers express satisfaction “Being a cattleman” appears as a shared identity that is passed from generation to generation, pride of “being a maker and supplier of food” and livestock activity as the main source of income for farmers.

They were able to point out flaws in their knowledge in management and use of the natural field. Lack of adequate crushing appeared as a restriction for the determination of animal load. In addition, they pondered a somewhat complex


subject, the allocation of the animal load of a pasture in relation to the availa-bility of fodder and the nutritional requirements of the animals.

On sanitary issues, there was an important gap between technical recommen-dations given by INTAs professionals and their adoption, with clear expres-sions of resistance to use the sanitary calendar and prevention of venereal di-seases, deworming the entire rodeo (recommendation is up to 18-20 months of age) as well as lack of knowledge in using of HPG3 diagnosis. In addition, very few laboratories in many areas.

Quantitative Stage: Giancola et al. (2018), present survey results. Educational level among farmers is high, 67% initiated or currently hold university or post high school degree. Most farmers receive technical advice through the priva-te sector (69%) or through INTA (16%). However, 49% make management decisions individually. Financing needs are clear: almost 80% of farmers said they were not able to afford adequate paddocks due to capital restrictions. In this sense, Calvo et al. (2016) in a comparative study in five cattle provinces, assert, “The issue of capital and the need for financing property infrastructure, suitable to livestock production horizon and its scale, arises strongly”.

Farmer’s demands towards INTA focus in the need for more training, general in situ research, research in pastures, small producer oriented training and the need of continuous presence of technicians in the field.

The degree of reproductive technologies adoption is adequate; most farmers park the service and implement pregnancy diagnosis. Lack of service planning is a common among smaller establishments. In general, they practice a spring and an autumn service aimed to get a more balance income throughout the year. This matches with Ondo Misi et al. (2015) findings in Chaco Province, which highlights that “this situation places a great challenge for INTA regarding research and extension; it is to create and transfer a set of technologies to increase the productivity and sustainability of small-scale livestock systems.”

Survey outcomes support findings in the qualitative stage regarding lack of knowledge and cultural issues, which may explain important health problems. In this sense, interpretation error regarding control of internal parasites ha-

3 HPG: estimation of the degree of parasitization in each animal (eggs per 100 grams of fecal matter).

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ppens in more than 55% of farms, since farmers deworm throughout the herd, far from the technical recommendation (deworming animals between 18 to 20 months old). This undoubtedly leads to unnecessary expenses.

In line with findings from the qualitative stage, most farmers show low use of HPG3: 25% of total farms. The main reason seems to be lack of laboratories nearby.

Findings regarding to venereal diseases, are inconsistent. 67% of farmers said they vaccine herd to prevent diseases and sampling in bulls (prepucial), but the majority perform a single swab, which indicates lack of technical kno-wledge. In this sense, possible communication problems are noticed, particu-larly in internal parasites control.

Another relevant health aspect is sadness disease. The majority of respon-dents are in a “dirty area”, which implies immunized fields against sadness transmitted by ticks. However, probability of catching sadness transmitted by horseflies or by non-disinfected needles is high, since only 44% disinfect the needles during a routine vaccination.

Regarding the closure of the natural grassland, findings in the qualitative sta-ge were corroborated and quantified, given that only 25% (of total farms) do so in autumn (optimal season). This technology was pointed out as critical at the time by the technicians, since there is an important potential for use and adoption path to follow in management of natural grassland.

A key practice in livestock systems is carrying capacity adjustment, 64% of farmers take into account the amount of fodder supply to decide the amount of animals to be put in pasture, but only 20% of responses were obtained when considering “nutritional requirements of the different categories”. The later also corroborates and quantifies what raised in the qualitative stage and, what is expressed in Calvo et al. op. cit., which conclude the need to generate knowledge about requirements and their relationship with fodder supply.

Conclusion

Farmers are generally well informed. However, both results (focus groups and survey’s respondents) show misunderstanding and lack of knowledge on


health issues and infrastructure investment needs. Therefore, there is a need to strengthen knowledge in other technologies among farmers, such as car-rying capacity adjustement and closure of the natural grassland. INTA should coordinate actions with veterinary schools, laboratories in each area and far-mers organizations, among others; rethink and reinforce specific interventions with an interactive and collective approach and raise specific financing needs to policy makers (Giancola et al., 2013 and 2018).

References

Calvi, M. (2017). Análisis sobre la existencia bovina en la provincia de Corrientes. Hoja Informativa Nº 89. Mercedes, Corrientes, Argentina. INTA Estación Experimental Agropecuaria Mercedes.

Calvi, M. (2011). Actualización de la productividad ganadera en la provincia de Corrientes. Hoja Informativa 43. Mercedes, Corrientes, Argentina. INTA Estación Experimental Agropecuaria Mercedes.

Calvo, S., Giancola, S., Salvador, M. L. (2016). Pequeña y mediana producción ganadera. Configuraciones causales que afectan la dinámica de innovación en cinco provincias argentinas. Mar del Plata, Argentina. XLVII REUNION ANUAL AAEA Facultad de Ciencias Económicas y Sociales, Universidad Nacional de Mar del Plata.

Cap, E. J., Giancola, S. I., Malach, V. (2010). Las limitaciones de las estadísticas ganaderas en los estudios de productividad en Argentina: las encuestas a informantes calificados como fuente complementaria de datos. El caso de la Provincia de San Luis. Trabajo presentado en la XLI Reunión Anual de la Asociación de Economía Agraria, Potrero de los Funes, San Luis, 6 al 8 de octubre de 2010.

Dowbley, V. (2012). Estudios sobre adopción de tecnología: avances en la generación de información cuantitativa a nivel de productor. Corrientes, Argentina. Comunicación. XLIII Reunión Anual de la Asociación de Economía Agraria AAEA.

Giancola, S.; Calvo, S.; Sampedro, D.; Marastoni, A.; Ponce, V.; Di Giano, S.; Storti, M. (2012). Corrientes. Ganadería bovina para carne. Factores que afectan la adopción de tecnología: enfoque cualitativo. Corrientes, Argentina. XLIII Reunión Anual de la Asociación de Economía Agraria. Premio IPCVA 2012.

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Giancola, S., Calvo, S., Sampedro, D., Marastoni, A., Ponce, V., Di Giano, S., Storti, M. (2013). Causas que afectan a adopción de tecnología en la ganadería bovina para carne de la provincia de Corrientes. Enfoque cualitativo. Buenos Aires, Argentina. Serie Estudios socioeconómicos de la adopción de tecnología N°2. Ediciones INTA. 60 p.

Giancola, S., Rabaglio, M., Sampedro, D. Dowbley, M. 2018. Factores que afectan la adopción de tecnología en la ganadería bovina para carne de la provincia de Corrientes. Enfoque cuantitativo. Trabajo presentado en: XLIX Reunión Anual de la Asociación Argentina de Economía Agraria (AAEA), Facultad de Ciencias Económicas, UNL, Provincia de Santa Fe, 17-19 de octubre de 2018.

Giancola, S.I., Sampedro, D. H., Rabaglio, M.D., Dowbley, M.V., Kraemer J., Uguet Vaquer Piloni, J.P., Storti, M. G., Marastoni, A. (2018). Factores que afectan la adopción de tecnología en la ganadería bovina para carne de la provincia de Corrientes. Artículo de divulgación EEA INTA Mercedes.

Kitzinger, J. (1995). Introducing Focus Groups, in N. Mays and C. Pope (eds). Qualitative Research in Health Care. BMJ Publications, London.

Ondo Misi, S., Giancola, S., Pellerano, L., Calvo, S., Balbuena, O., D´Angelo, M.L., Buschiazzo, M., Di Giano, S., Gatti, N., Ferber, O. (2015). Problemáticas de la innovación en la ganadería bovina de la provincia de Chaco: enfoque cualitativo. Resistencia, Chaco. Serie Nº 11. Ediciones INTA - Coedición UNC.

Sampedro, D. y Calvi, M. (2016). Situación actual y perspectivas de la ganadería vacuna de cría en Corrientes. Mercedes, Corrientes, Argentina. Noticias y Comentarios Nº 540. Ediciones INTA

Sampedro, D. (2013). Ajuste de la carga animal en el rodeo de cría. Noticias y Comentarios Nº 497. Mercedes, Corrientes, Argentina. Ediciones INTA.

Servicio Nacional de Sanidad y Calidad Agroalimentaria - SENASA - Ministerio de Agricultura, Ganadería y Pesca de Argentina. Distribución de existencias bovinas por provincia. Consultado octubre 2019.


The influence of technology characteristics and farmers’ objectives on technology adoption behavior

Mariana de Aragão PereiraPhD in Agricultural Management, Researcher A, Embrapa Beef Cattle

Introduction

In an ever-changing world, a farmer constantly considers the adoption of new technology. These adoption decisions have been of particular interest given their spill-over effects beyond the farm gate (Feder et al., 1985; Feder & Umali, 1993), and their impacts on agricultural development (Edwards-Jones, 2006). As a result, a considerable number of studies have been carried out with particular emphasis on the factors that influence, or more specifically constrain, technology adoption decisions. In this paper, the technology cha-racteristics and the farmers’ objectives and values are explored in the context of technology adoption.

The influence of technology characteristics on adoption

Farmers’ perceptions on technology characteristics lead to positive or negati-ve attitudes towards the innovation and these attitudes affect farmers’ willing-ness to adopt technologies (Adesina & Zinnah, 1993). According to Rogers (2003, p. 222), there are five general characteristics associated with techno-logies that explain about 50 percent of the variance in technology adoption rates. These characteristics are: (1) relative advantage; (2) compatibility; (3) complexity; (4) trialability; and (5) observability. The remaining variance is ex-plained by other factors. The technology characteristic “relative advantage” is the degree to which a new technology is perceived as superior to the current technology (Rogers, 2003, p. 229). According to Batz, Peters and Janssen (1999), farmers will adopt an innovation if they perceive the new technology exceeds the utility4 of the traditional technology. As they claim, utility is deter-mined by the nature of the technology, farmers’ personal characteristics (e.g.,

4 In Economics, utility means the capacity of a commodity to satisfy human wants. Given the abstract character of the “utility” of an object, asset or service, it has often been measured in terms of money (i.e. the price one is willing to pay to get the utility derived from the desired article). The utility is not always the same as usefulness in this context, as some articles can provide some types of utility and not be useful (ex. Cigarette).

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goals), the farming system and the farming environment. Thus, the specific aspects of the relative advantage (e.g., profit, risk, social status, environment impact etc.) depend on the utility curve. In general, the greater the perceptions of relative advantage the higher the chances of adoption (Rogers, 2003). Flett et al. (2004), comparing adopters and non-adopters of four technologies for dairy farms, found that the perceived usefulness of technologies was higher for adopters than non-adopters. Perceived usefulness, in this case, may be seen as a proxy for relative advantage because this variable was made up of five dimensions, four of which were associated with technology relative advantage, that is, the technology: (1) is better than the one being replaced; (2) provides an increase in financial profit (i.e., compared to previous techno-logy); (3) provides increased production; and (4) enables time saving. Flett et al. (ibid) found significant positive effect between the farmers’ perceived usefulness of the technology and its adoption.

However, this relative advantage is not always clear to potential adopters, par-ticularly in cases where the technology benefits are delayed, or the outcome of adoption is the avoidance of an undesired future event (Rogers, 2003, p. 234). In the former case, the time gap between adoption and the outcomes brings uncertainty to farmers, with some of them delaying (until they become less uncertain), or discarding adoption. For example, Fairweather (1992) no-ted that one reason mentioned by farmers for not planting trees was the gap between decision (and investment), and returns. When technology adoption results are the prevention of an unwanted event (preventive technology), per-ception of relative advantage is difficult as the “outcome” is the absence of a possible effect. For instance, deworming may avoid a weight loss in cattle which is difficult for farmers to measure or estimate.

The innovation compatibility is another relevant characteristic. Perceptions on technology compatibility are construed on the basis of the technology’s consistency to the individual’s value system, past experience and current needs (Rogers, 2003, p. 240). Technology that is perceived as incompatib-le is unlikely to be adopted. For instance, Pereira et al. (2011) noted envi-ronmental technologies perceived as more compatible with beef production systems had higher levels of adoption compared to other environmental tech-nologies, amongst Brazilian commercial-scale progressive farmers. Gillespie et al. (2007) found the non-adoption of Best Management Practices among


American beef producers was due to the belief that some of these practices did not apply to their farms, even though researchers believed the practices did apply. The more compatible a new technology is to the old technology, the easier it is to be adopted (Wake et al., 1988) due to familiarity. This may introduce, however, the misuse of a technology as farmers may repeat old and sometimes unsuitable practices (Rogers, 2003, p. 244), resulting in less-than-expected performance, and, possibly, discontinuation of adoption.

Finally, an innovation’s compatibility to farmers’ needs is crucial to achieve efficacy. There is little point in developing the right technology to the wrong problem. To a lesser extent, the complexity of an innovation is also important for the adoption behavior because the difficulty in understanding and mana-ging a new technology may affect farmers’ willingness to adopt it (Rogers, 2003, p. 257; Batz et al., 1999). As Flett et al. (2004) demonstrated, farmers not using a technology consistently find it more difficult to understand and use than adopters. However, they noted this may be caused by a systematic bias since those who are using the technology may have re-appraised their initial perceptions (i.e., before adoption) on the “ease of use”. According to Batz et al. (1999, p. 125), the more complex the technology is in relation to the tradi-tional technology, the lower are the adoption rate and the ceiling of adoption. Wake et al. (1988, p. 187) argue technology complexity impacts on farmers’ perception of the cost of learning, and also on the belief of their learn abilities, which may explain the propositions of Batz et al. (ibid). In general, the com-plexity is more of an issue for innovators and early adopters of an innovation than it is for other farmers, who benefit from the experiences and knowledge of the pioneers at lower costs (Wake et al., 1988, pp. 188-189).

The trialing of a technology is another important characteristic as it allows far-mers to develop skills (Ghadim & Pannell, 1999) and, at the same time, assess the performance of an innovation, reducing uncertainties around its adoption. Specifically, Ghadim and Pannell (ibid) claim that farmers review their expecta-tions on profitability (i.e., in a Bayesian fashion) as they “learn-by-doing” during the trial period. The possibility of trialing a technology in a small scale increases the rate of adoption, particularly among innovators and early adopters (Rogers, 2003). However, for non-divisible technology this possibility does not apply. In this case, on-farm observation of the non-divisible technology (i.e., at research centers or other farms) may be more important for farmers.

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Finally, observability is the degree to which an innovation and its results are visible (Rogers, 2003, p. 258). The general rule is that the more visible the results, the more rapid the rate of adoption. Nonetheless, technology is of-ten composed of hardware and software, with the latter not often observable (Rogers, 2003, p. 259). Thus, technology with prevailing software components is usually adopted at slower rates as it possesses less observability.

Pereira et al. (2011) proposed an extension of Rogers’ Diffusion Theory (2003) by considering a hierarchy among the five attributes. Their case study provi-ded some evidence that compatibility and relative advantage are the most important technology attributes while observability and trialability facilitate, but do not by themselves either determine or preclude adoption. Accordingly, “technology complexity does not preclude adoption, but is given considera-tion relative to the technology advantages. If the benefits of a technology are sufficient, then innovative farmers will adopt despite negative issues related to complexity” (Pereira et al., 2011; p. 322).

Farmer’s objectives and technology adoption

Most adoption studies mention farm and farmers’ characteristics impacting on technology adoption (comprehensive reviews include Edwards-Jones, 2006; Feder et al., 1985; Feder & Umali, 1993), but not many focused on the far-mers’ objectives and goals as an important variable in this equation. Farmers’ characteristics usually include age, gender, education and off-farm work. The stage in the family cycle and the level of on-farm pluriactivity are considered too, as pointed out by Edwards-Jones (2006).

Farmers’ values, objectives and goals play a relevant role in adoption decision making as they set the limits for “rational” behavior (i.e., behavior that is fai-thful to one’s own value system). According to Nuthall (2010, p. 164), values form the basis for establishing the boundaries for people’s behavior, as they set limits of what is relevant (and often socially acceptable) in life. Additionally, Gasson (1973, pp. 524-525) argues that values are culturally constructed and less likely to change with time or circumstance than goals, imposing some regularity on behavior. Some examples of values are honesty, humanity, inte-grity, freedom and independence. Objectives, in turn, are established within people’s value sets and become operational by the setting of specific goals,


as Nuthall (2010) describes. For example, a farmer whose objective is to ex-pand his farm business may set himself the goal of buying an additional 500 ha in the next five years. Despite the distinction between objectives and goals, these terms have been used interchangeably as, in many studies, “goals” are referred to as general statements (like objectives).

The neoclassical economic theory assumes a farmer’s objective is to maximize utility, but given its ‘ethereal’ character, utility is often measured in terms of profits, albeit imperfectly (Edwards-Jones, 2006). Therefore, in many agricultural studies a profit maximizing farmer has been assumed. Featherstone et al. (1995), howe-ver, provided some evidence of farmers’ violation of this maximization assumption.

Despite the dominance of the profit maximization paradigm within normative eco-nomics, there has also been an ongoing stream of economically-focused em-pirical literature over many years that has explicitly acknowledged and focused on the importance of both multiple and conflicting goals, and how this impacts on exhibited behavior (Gasson, 1973; Gladwin, 1989; Featherstone et al., 1995; Pereira et al., 2011; Howley, 2013; Wilson et al., 2013). For example, Gasson (ibid) listed, from a series of empirical studies, several values and goals that far-mers held. Among the non-economic objectives relevant to farmers were: lifestyle, social, spiritual and family-related objectives. Gasson (ibid) found that the feeling of satisfaction was more often associated with the achievement of non-economic than economic goals. Another example of the importance of non-economic goals was evident in a case study conducted by Ohlmer et al. (1998) with 18 Swedish farmers. They found that farmers’ highest valued goals were to remain on the farm and hand over an improved farm for the next generation. Goals related to private consumption, leisure time and risk taking were also highly valued.

Under the assumption of multiple objectives, Gasson (1973) points out farmers seek to attain several goals simultaneously and often have to prioritize and trade-off goals (e.g., labor intensive technology may decrease time spent with family). The prioritization of goals is unique to individual farmers and is determi-ned by the interactions between personal and environmental factors that chan-ge over time. In other words, the changing circumstances of an individual impact on the “utility” one gets from particular events (Edwards-Jones, 2006, p. 783), for example the adoption of a new technology. This, in turn, influences how this individual prioritizes the events associated with his/her goals, with direct impact on the balance between economic and non-economic ones. Moreover, in achie-

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ving such a balance, individuals are likely to “satisfice” rather than maximize so-lutions, given their limited cognitive capacity to gather and process information and the unreliable nature of human memory (Simon, 1957).

Historically, the study of farmers’ goals and values started with the premise of better understanding farmers’ motivations for farming and providing resear-chers with insights on major farming orientations. A reference paper is that of Gasson (1973, p. 527), whose literature review pointed to a non-exhaustive list of four farming orientations: (1) instrumental, in which farming is a means of income and security; (2) social, for whom the farm gives opportunity to thrive on interpersonal relationship and community values; (3) expressive, in which farming is seen as a means of self-expression and personal fulfilment; and (4) intrinsic, that is, farming activities and environment are enjoyed for their own sake. Other studies, building on Gasson’s (1973) pioneer work, also contribu-ted to this body of literature. For instance, Fairweather and Keating (1994) and Brodt, Klonsky and Tourte (2006) identified various management styles defined according to the prevailing sets of goals held by New Zealander and American farmers respectively. A common assumption underlying such studies is that gaining insights on farmers’ goals and values enables the understanding, and sometimes the prediction, of their behavior (e.g., technology or policy adoption). In a different fashion, Darnhofer, Schneerberger and Freyer (2005) modelled Austrian farmers’ decisions on whether to convert to an organic farming sys-tem. Based upon their decisions, the researchers drew conclusions on these farmers’ farming orientations and, indirectly, on their prevailing sets of goals.

In Brazil, Pereira et al. (2016) studied a sub-group of 26 innovative beef far-mers and found the common goal of running the farm as a business with close attention to the cash flow. In general, they also wanted to improve pas-ture and animal productivity and be in the forefront of technology adoption. Nonetheless, their distinguishing objectives resulted in four main sets of ob-jectives, named as the Professional Farmer, Committed Environmentalist, Profit Maximizer and Aspirant Top Farmer. Each of the four synthetic farmer types resemble similarities with other farmers’ typologies across various stu-dies, highlighting some major farming orientations, which, according to Pereira et al. (ibid), can provide a framework for farmers’ decision making, including adoption decisions. It may also influence the type and quality of their interac-tions with various social actors within the agricultural innovation system.


A gap remains in the literature, however, as to whether these sets of predomi-nant goals in fact determine behavior and, if so, how this process occurs and to which extent. Unlike the study by Darnhofer et al. (2005), in which farmers’ actual behavior was modelled, most studies on farmers’ goals are limited to the identification of goals. Nevertheless, overlooking the gap between what farmers claim (i.e., intentions) and what they actually do may result in mislea-ding conclusions since constraints may prevent their actions.

Given the multiple sources of influence on adoption, it needs to be investiga-ted under different contexts or regions, amongst different groups of farmers and for different types of technologies. These sources of influence involve not only the technology attributes and the farmers’ goals and values, as discussed here, but also their characteristics, the farm biophysical aspects, the institu-tional environment, the markets and consumers’ demands and so on. Despite the last topics not being within the scope of this paper, all of these factors together determine the suitability and usefulness of a new technology, and, thus, the likelihood of adoption.

Concluding Remarks

The diversity of farmer types, with various sets of values and goals, holds relevance for the agricultural innovation system, in general, and technology adoption in particular. Values and goals are major mediating variables through which farmers filter their perceptions on farming strategies and technology suitability. Thus, a paradigm shift is necessary from an emphasis on the tech-nology itself to an emphasis on farmers (potential users) and their preferred behaviors, when it comes to adoption research.

References

Adesina, A. A., Zinnah, M. M. (1993). Technology characteristics, farmers’ perceptions and adoption decisions: A Tobit model application in Sierra Leone. Agricultural Economics, 9(4), 297-311.

Batz, F. J., Peters, K. J., Janssen, W. (1999). The influence of technology characteristics on the rate and speed of adoption. Agricultural Economics, 21(2), 121-130.

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Brodt, S., Klonsky, K., Tourte, L. (2006). Farmer goals and management styles: Implications for advancing biologically based agriculture. Agricultural Systems, 89(1), 90-105.

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press. Darnhofer, I., Schneerberger, W., Freyer, B. (2005). Converting or not converting to organic farming in Austria: Farmers types and their rationale. Agriculture and Human Values, 22(1), 39-52.

Edwards-Jones, G. (2006). Modelling farmer decision-making: concepts, progress and challenges. Animal Science, 82, 783-790.

Fairweather, J. R. A tree model for Hawkes Bay farmers’ tree planting decisions. Lincoln: AERU, 1992. (215).

Featherstone, A. M., Moghnieh, G. A., Goodwin, B. K. (1995). Farm-level nonparametric analysis of cost-minimization and profit-maximization behavior. Agricultural Economics, 13(2), 109-117.

Feder, G., Just, R. E., Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: a survey. Economic Development and Cultural Change, 33(2), 255-298.

Feder, G., Umali, D. L. (1993). The adoption of agricultural innovations: A review. Technological Forecasting and Social Change, 43(3-4), 215-239.

Flett, R., Alpass, F., Humphries, S., Massey, C., Morriss, S., Long, N. (2004). The technology acceptance model and use of technology in New Zealand dairy farming. Agricultural Systems, 80(2), 199-211.

Gasson, R. (1973). Goals and values of farmers. Agricultural Economics, 24(3), 521-542.

Ghadim, A. A., Pannell, D. J. (1999). A conceptual framework of adoption of an agricultural innovation. Agricultural Economics, 21(2), 145-154.

Gillespie, J., Kim, S., Paudel, K. (2007). Why don’t producers adopt best management practices? An analysis of the beef cattle industry. Agricultural Economics, 36(1), 89-102.

Gladwin, C. H. Ethnographic decision tree modelling (Vol. 19). Beverly Hills: Sage Publications, 1989.


Howley, P., 2013. Examining farm forest owners’ forest management in Ireland: the role of economic, lifestyle and multifunctional ownership objectives. J. Environ. Manag. 123, 105–112. http://dx.doi.org/10.1016/j.jenvman.2013.03.013.

Nuthall, P. L. Farm business management: the human factor. Oxfordshire: Cabi, 2010.

Ohlmer, B., Olson, K., Brehmer, B. Understanding farmers’ decision-making processes and improving managerial assistance. Agricultural Economics, 18(3), 273- 290, 1998.

Pereira, M. de A. Understanding adoption and non-adoption of technology: a case study of innovative beef farmers from Mato Grosso do Sul State, Brazil. Unpublished PhD, Lincoln University, Lincoln, 2011.

Pereira, M. de A., Woodford, K. B., Nuthall, P., Fairweather, J., Medeiros, S. R. Suplementação de seca sob a ótica do pecuarista: o processo decisório. In: Reunião anual da Sociedade Brasileira de Zootecnia, 2011, Belém. Anais… Belém: SBZ, 2011.

Pereira, M. A., Woodford, K. B., 2011. Technological profile of Brazilian Innovative beef farmers: which technologies these farmers adopt, which they don’t and reasons for the difference. 18, International Farm Management Association Congress, Methven, New Zealand (available as online proceedings at: http://www.ifmaonline.org/pdf/congress/11_ Pereira&Woodford_P316-323.pdf).

Simon, H. A. (1957). Models of man: social and rational. New York: John Wiley & Sons.

Wake, J. L., Kiker, C. F., Hildebrand, P. E. (1988). Systematic learning of agri-cultural technologies. Agricultural Systems, 27, 179-193.

Wilson, P., Harper, N., Darling, R., 2013. Explaining variation in farm and farm business performance in respect to farmer behavioural segmentation analy-sis: implications for land use policies. Land Use Policies 30, 147–156. http://dx.doi.org/10.1016/j.landusepol.2012.03.006.

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Strategies leading to successful wide adoption of mixed grass-legume pastures for sustainable intensification of beef cattle production systems in the Brazilian Amazon

Judson Ferreira Valentim1

Carlos Mauricio Soares de Andrade2

1Agronomist, Embrapa Acre.2Agronomist, Embrapa Acre.

Introduction

In the Brazilian Amazon, pasture-based cattle ranching is a source of environ-mental harm and hope for income and well-being improvement for more than 450 thousand rural households (IBGE, 2019). It is both the main deforestation driver (NEPSTAD, et al., 2014) and a key stable capital asset in the path of farmers towards improving their family’s food security, income and well-being (GARRETT et al., 2017; VALENTIM; GARRETT, 2015).

Expansion of agriculture and cattle ranching until 2018 has occurred at the cost of deforestation of 14% (59 million hectares) of the Brazilian Amazon biome, with pastures occupying 90% of these areas (MAPBIOMAS, 2019). In 2017, the cattle herd in the region was 46 million animal units (1 AU = 450 kg of live weight), grazing in 45 million hectares of pastures, resulting in an average stocking rate of 1 AU/ha (LAPIG, 2019). In the Legal Amazon, 50% of the cultivated pastures are either degraded or in degradation process (DIAS-FILHO, 2011). Therefore, intensification of pasture-based cattle production systems is a key variable in solving the sustainable development equation in the Brazilian Amazon. However, current animal productivity of cultivated pastures in Brazil are only 32-34% of the potential. Increasing productivity to 49–52% of the potential would be enough to meet demands for meat, crops, wood products and biofuels until 2040, without additional deforestation and avoid emissions of up to 14.3 Gt CO2 Eq (STRASSBURG et al., 2014).

Intensification and long-term productivity of pasture-based cattle produc-tion systems depends on replenishment of soil nutrient reserves removed or lost by leaching, erosion and volatilization. There is a wide knowledge stock relevant towards the goal of sustainable intensification of cattle production systems in the Brazilian Amazon (BUNGENSTAB et al., 2019; DIAS-FILHO; ANDRADE, 2019; EMBRAPA, 2019). Of particular interest are those aspects

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related to nitrogen (N) supply, since this is the main nutrient required for plant and animal growth and production. Inputs of N into agricultural systems may be from fertilizers or derived from the atmosphere through biological N2 fixa-tion (BNF). However, opportunities for intensification of livestock production systems in the Brazilian Amazon are limited because the majority of farmers can`t afford the high cost external inputs (VALENTIM; ANDRADE, 2004).

Forage legume technologies with effective BNF capacity are among the most promising options to supply N needed for sustainable intensification of lives-tock production systems in Brazil. Mixed with grasses, legumes provide a low cost supply of highly deficient nitrogen (N) to soil-plant-animal ecosystems in the tropics though BNF by soil bacteria of the genus Rhizobium. This contri-butes to increase the quantity and quality of forage produced and additionally, improves biodiversity and resilience of pasture ecosystems. With adoption of adequate management practices, grass-legume pastures can support higher stocking rates and increase productivity per animal and per area over longer periods (GRAHAM; VANCE, 2014; STRASSBURG et al., 2014; LATAWIEC et al., 2014; ANDRADE, 2012; SHELTON et al., 2005; VALENTIM; ANDRADE, 2004). These technologies are particularly relevant to improve food security and income of smallholders in the tropics who can`t afford buying expensive fertilizers to supply essential N for their livestock production systems (FAO, 2009; REARDON et al., 1999; VALENTIM; ANDRADE, 2004).

However, with a few exceptions, forage legumes have failed in delivering in their promise to improve productivity of livestock production systems in the tropics. Unsuccessful experiences in establishing and maintaining productive and per-sistent grass-legumes mixtures resulted in lack of credibility of this alternative among farmers and researchers. Unavailability of commercial cultivars adapted to the different environmental conditions and the high cost of commercial seeds in the market also contributed to restrict wide adoption of grass-legume pastures in the tropics. In many instances where these technologies were promoted, in-sufficient knowledge among farmers regarding adequate management practices, associated with low persistence of legumes in mixed pastures with grasses resul-ted in high rates of failure. Low use of fertilizers in pasture establishment and ma-nagement, still predominant in pasture-based cattle production systems, is also an important factor limiting successful adoption of mixed grass legume pastures in the tropics. Other important factors restricting wide adoption of mixed grass


legume in the tropics are the lack of farmers participation in research and deve-lopment, promotion of technologies that do not meet farmers expectations of so-cioeconomic benefits, and unfavorable policies (ANDRADE, 2012; BARCELLOS et al., 2008; SHELTON et al., 2005; VALENTIM; ANDRADE, 2004).

Although adoption in the tropics has been lower than expected, there are some successful histories of wide use of forage legumes in livestock pro-duction systems in the tropics (SHELTON et al., 2005). In Brazil, less than 2% of the cultivated pastures are mixed with legumes (EMBRAPA, 2019). Meanwhile, in the state of Acre, forage legumes were present in 29% of the 1.94 million hectares of cultivated pastures in 2014, mainly tropical kudzu (Pueraria phaseoloides) and forage peanut (Arachis pintoi) (Embrapa, 2019; AMARAL et al., 2018; VALENTIM; ANDRADE, 2005a; 2005b).

Here we describe and analyze an innovation framework implemented by Embrapa over the last 40 years to promote wide adoption of forage legume technologies for intensification of cattle production systems in the western Brazilian Amazon. We focus on assessing the importance of key adoption factors for the successful use of tropical kudzu and forage peanut in mixed grass-legume pastures in the state of Acre.

Description of the Innovation System for Mixed Grass-Legume Pastures

In 1973, the Brazilian Corporation for Agricultural Research (Embrapa) was established to provide knowledge support services to improve agriculture and livestock productivity and production in Brazil (CABRAL, 2005). One of the main knowledge gaps identified by farmers and the government was the need of adequate technologies for pasture reclamation and improvement to support the policies aiming at increasing pasture-based livestock production in the different Brazilian regions. This led to the establishment of the Project for Pasture Reclamation, Improvement and Management (Propasto) in the Legal Brazilian Amazon in 1976. The project had the main goals of developing improved cultivars of grasses and legumes with higher productivity of better quality forage and adapted to the different environmental conditions of the region; and, developing best management practices to establish and maintain productive and persistent pastures, thus contributing to increase productivity per animal and per area (EMBRAPA, 1980).

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Propasto established a research network in 14 experimental fields, mostly on private cattle farms, in the main production areas of the states of Acre, Amazonas, Pará, Rondônia, Roraima and in a county of Goiás, currently part of the state of Tocantins. These farms were selected after consulting with far-mers based on their strategic location and representativeness of the predo-minant cattle production systems in each state. The innovation framework im-plemented by Embrapa contemplated integration of governmental research, extension, regional development and financing organizations, the private sec-tor, nongovernmental organizations and farmers. From 1976 through 1990, the Superintendence for Amazon Development provided financial support for Embrapa research activities. At the same time, the governmental Bank of Amazon provided credit to finance infrastructure improvements, and farm inputs for farmers collaborating with the Propasto Project (EMBRAPA, 1980).

On-farm research assessed nutritional needs, pest and disease resistance, and forage production and quality characteristics of large collections of intro-duced accessions of grasses and legumes. Pasture and animal productivity of the most promising accessions were assessed under grazing on large on-farm experiments pasture and animal productivity. Researchers and farmers continuously interacted and exchanged knowledge and information during the process of establishment of the experiments, data collection and analysis. The research network promoted annual meetings for assessment of results and planning of future activities. The technologies that were successfully va-lidated were made available to the different stakeholders groups though te-chnical publications, distribution of seeds or vegetative material of the most promising forage species for leading innovative farmers to establish their own seed producing areas and nurseries in order to promote wider adoption. On-farm field days allowed researchers and the collaborating farmers to share their knowledge with extensions agents, other farmers groups, policy makers and other relevant stakeholders for the private sector and nongovernmental organizations (EMBRAPA, 1980b).

In the state of Acre, on farm research activities established by the Propasto project started in 1976 and were conducted until 1982 (VALENTIM; COSTA, 1982; EMBRAPA, 1980). The relevance and saliency of Embrapa research outcomes in meeting farmers’ knowledge needs, during its seven years of ac-tivities, contributed consolidate its credibility and assure commitment of local


stakeholders with the continuity of this innovation framework. Over the last 40 years, the Research Group on Sustainable Cattle production Systems for the western Brazilian Amazon established by Embrapa in Acre in 1979 (CNPq, 2010) has been developing on-farm research and providing knowledge su-pport services for sustainable intensification of beef and dairy cattle produc-tion systems in this region.

Case Description

The initial focus of Embrapa research contemplated the introduction, selection and recommendation of forages adapted to the different socioeconomic and environmental conditions of the Legal Brazilian Amazon (EMBRAPA, 1980). However, most of the Propasto research network concentrated their focus on grasses, since this was the knowledge gap clearly identified by farmers which had no previous tradition of using forage legumes in their production system. Researchers recognized that N was an essential nutrient limiting productivity and sustainability of pasture-based cattle production systems in the Amazon (SERRÃO; FALESI, 1977). However, the costs and logistics of accessing ni-trogen fertilizers made this option economically unviable to most farmers in the Amazon. This led to special focus by Embrapa in the state of Acre to a long-term commitment to promote use of forage legumes aiming as supplying low cost biologically fixed N to the soil-plant-animal ecosystem (VALENTIM; ANDRADE, 2004; VALENTIM; COSTA, 1982).

Key Technologies Promoted

a. Tropical Kudzu (Pueraria phaseoloides)

Tropical kudzu is a vigorous twining and climbing, deeply rooting legume, which can also root at the nodes. It is native from Southeast Asia (Malaysia and Indonesia) and currently widely cultivated throughout the tropics where it is considered a naturalized species (COOK et al. 2005; BOGDAN 1977). In Brazil, this legume was introduced for use as a ground cover in rubber tree plantations in the Amazon in the 1940`s, and with higher intensity in the 1970` and 1980`s (VALENTIM; 2010).

From the large collection of legumes introduced and evaluated by Embrapa in small plots at experimental stations and in farms between 1976 and 1982

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only tropical kudzu showed good productivity of high quality forage, good seed production and excellent persistence in mixed grass-legumes pastures in the state of Acre (VALENTIM; COSTA, 1982). Embrapa Acre successfully promoted tropical kudzu since the early 1980s for use in mixed pastures with cultivars of Panicum maximum, Brachiaria brizantha, B. humidicola and B. decumbens. By 2005, this technology was adopted in over 5,400 farms reaching an area of 480,000 ha, with estimated economic benefits of US$ 33 million/year (SHELTON et al., 2005; VALENTIM; ANDRADE, 2004; 2005a).

b. Forage Peanut (Arachis pintoi) Cultivar Belomonte

Legumes of the genus Arachis are native from South America, where they are distributed in Peru, Bolivia, Brazil, Uruguay, Paraguay and Argentina. Forage peanut cultivars are being successfully adopted in the Nepal, Australia, Brazil, Colombia and the southern United States (SHELTON et al., 2005; COOK et al., 2005; VALENTIM; ANDRADE, 2004; KERRIDGE; HARDY, 1994). Research on experimental station with forage peanut started in Acre in 1990, with intro-duction and evaluation of accessions of Arachis pintoi, Arachis glabrata and Arachis repens (VALENTIM, 1996).

Since 1998, there was increasing degradation of pastures due to the occurren-ce of syndrome of death of Marandugrass (Brachiaria brizantha cv. Marandu) in poorly drained soils of the Amazon. This led farmers to search for forage alternatives to reclaim degraded pastures to maintain the productivity and pro-fitability of cattle production systems. Tropical kudzu, the major forage legume used in mixed pastures in Acre, showed poor compatibility with some of the new grass species being established by farmers, such as African stargrass (Cynodon nlemfuensis), and also failed to persist when managed under rotational stocking at stocking rates above 1.5 AU per hectare (VALENTIM; ANDRADE, 2005b).

In the beginning of 2000, farmers that traditionally collaborated with Embrapa Acre for on-farm validation of technologies demanded new legumes adapted for use in more intensive cattle production systems, which included pasture management under rotational stocking. At that time, forage peanut cultivar Belomonte was in pre-recommendation phase for the environmental condi-tions of Acre. In the year 2000, around 20 of these farmers established cultivar Belomonte in association with stoloniferous grasses such as African stargrass, tangolagrass (B. arrecta x B. mutica) and B. humidicola in the process of re-


claiming degrading Marandugrass pastures. Both the legume and the grass were planted manually, using vegetative material (stolon pieces) supplied for farmers at no cost from a two-hectare nursery at Embrapa Acre. The initial success of this experience spreads rapidly by word of mouth among other far-mers facing similar problems. In 2001, Embrapa Acre officially recommended forage peanut cultivar Belomonte for diversification of pasture ecosystems in Acre. The news of the success of this legume in the reclamation of degraded pastures, and in the improvement of other still productive grass pastures, ra-pidly spread among farmers. By March 2004, close to 1000 small, medium and large farmers of Acre had already peanut into their pastures (VALENTIM; ANDRADE, 2004; 2005b).

Mixed grass-forage peanut pastures results in higher pasture productivity of high quality forage thus increasing carrying capacity and animal performance. In the environmental conditions of Acre, mixed pastures of forage peanut and stargrass have the potential to support an average of 2.5 AU/ha/year and produce over 850 kg of animal live weight/ha/year (ANDRADE et al., 2015). Currently, cultivar Belomonte is adopted in over 79.6 thousand hectares of pastures, providing US$ 19.7 million of economic benefits for farmers in Acre (EMBRAPA, 2019).

However, vegetative propagation of cultivar Belomonte still limits wider adop-tion of this technology due to high labor demand for vegetative propagation. To overcome this challenge, Embrapa Acre developed a new forage peanut cultivar (BRS Mandobi) propagated by seeds (ASSIS et al., 2014). Mixed pas-tures of B. humidicola and forage peanut BRS Mandobi increase animal gains by 66%, compared with pure grass pastures, thus reducing steer slaughter aged from 33 to 25 months (SALES et al., 2019). This new cultivar has the potential to be adopted in the 45 million hectares of cultivated pastures in the Amazon biome (VALENTIM et al., 2017) and 36 million hectares in the Mata Atlântica biome (MABIOMAS, 2019).

Key Factors for Successful Wide Adoption of Mixed Grass-Legume Pastures

Adoption factors were assessed and ranked (Figure 1) according their con-tribution for successful wide adoption of mixed grass-legume pastures in the Brazilian Amazon. These factors are discussed as follows.

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Appropriate Technology Available

Adoption of the grass-legume technology was relatively simple, although mana-gement of mixed pastures was somewhat more complex. However, in the early 1980`s, farmers in the Western Brazilian Amazon had no previous knowledge of the use of legumes as forages in animal production systems. Pastures consisted exclusively of cultivated grass species. Farmers perceived broad leaf plant species as undesirable species in their cultivated pastures and managed to control those using mechanical cutting methods, by burning the pastures or using agrochemi-cals. Convincing farmers to include a legume in association with grasses was very difficult in the beginning, particularly because of the aggressive growing behavior of tropical kudzu and the increased risk of accidental fires during the dry season.

Farmers had access to practical information and materials to support techno-logy adoption. Embrapa made available an accompanying technology packa-ge encompassing specific technology requirements though videos, radio pro-grams, technical bulletins, folders, and demonstration units in large, medium and small farms. Additionally, mixed grass-legume technologies were formally included in recommended beef and dairy cattle productions systems, collabo-

Figure 1. Ranking of key factors for successful wide adoption of mixed grass-legume pastures in the Brazilian Amazon state of Acre.


ratively designed by researchers, farmers, extensions and financial agents of governmental and private organizations.

Embrapa also supported the establishment of local production and supply of affordable good quality tropical kudzu seeds. Small farmers use tropical kudzu as a fallow to reclaim degraded areas for a period of 2-3 years, after which they are converted to cultivation of annual (rice, corn, cassava) and perennial crops (coffee, orange, limes). This trailing legume grows over the regenera-ting native shrub and woody species and produce abundant seeds, which are harvested during the dry season and sold to local retailers (VALENTIM; ANDRADE, 2005a). In the case of forage peanut, Embrapa established two hectares of nursery to supply farmers with no cost plant material for vegetative propagation (VALENTIM; ANDRADE, 2005b).

Long-term Commitment by Key Players

Researchers of Embrapa Acre have a long commitment (around 40 years) in using participatory approaches of research and development and technology transfer activities regarding the use grass-legume technologies with farmers in cattle pro-duction systems in the State of Acre. In addition, Embrapa researchers and colla-borating farmers became champions in advocating the advantages of using mixed grass-legume pastures as a lower cost, higher profitability strategy towards sustai-nable intensification of cattle production systems in the Brazilian Amazon.

Embrapa framework was successful in promoting grass-legume technologies among large farmers that account for 4% of the farms and 40% of the cattle herd in Acre. Although in smaller proportions, small and medium farmers also adop-ted tropical kudzu in their cattle production systems, not only in grass-legume pastures, but also in the process of reclamation of degraded land for agricultural production. This allowed farmers to become seed producers with tropical kudzu becoming a cash crop generating income for many small farmers that represent 96% of the properties and account for 60% of the cattle in the State of Acre.

Socioeconomic Situation of Farmers and Farming System Were Conducive to Adoption

One of the key drivers for wide adoption of mixed grass-legume pastures in the state of Acre was the socioeconomic situation of farmers and their farming systems. Since the late 1980`s farmers have been under pressure to stop

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deforestation for pasture establishment in the Brazilian Amazon. Additionally, incidence of pests and diseases, lack of maintenance fertilization and poor management led to increased pasture degradation, thus increasing costs and reducing profitability of cattle production systems. This established a socioe-conomic environment conducive for farmers to become more receptive to te-chnological changes in their production systems, favoring adoption of grass-legume pasture technologies (VALENTIM; ANDRADE, 2004).

Farmers Centered Innovation System

Farmers and other stakeholders were active participants in most of the pha-ses of the innovation framework. In addition, a flexible approach was used to ensure that farmer innovations were absorbed and integrated into the te-chnology package. Methods for seeding tropical kudzu and adjustments on seeding rate and planting density for pasture establishment or introduction of the legumes in existing pastures were developed with valuable insights from farmer’s trial and error experiences.

Mixed grass-legume pasture technologies were developed and tested on lar-ge, medium and small beef and dairy cattle production farms. Farmers that participated in the development or were early adopters were active agents in the process promoting these technologies. These farmers acted as practical instructors in technology transfer activities for farmers, extension agents, stu-dents and researchers and their farms were used as demonstration units of successful use of mixed grass-legume pastures.

Market Access Available and Financial Benefits of Technology Strong

Global and national demand for livestock products has been increasing stron-gly, because of both population growth and increasing income, particularly in Asia, Latina America, and Africa (DELGADO, 2005). In addition, growing local and regional markets and improvements of infrastructure and logistics that occurred along the last four decades has made meat produced in the Western Brazilian Amazon increasingly competitive in Brazil and in the global mar-ket. This, associated with strong returns from mixed grass legume pastures were enough to support adoption costs of the technology in the state of Acre (VALENTIM; ANDRADE, 2005a; 2005b).


Farms are diverse, therefore, farmers are looking for technologies with multiple benefits, which makes mixed grass-legume pastures very attractive. These te-chnologies contribute to reduce costs associated buying and applying nitrogen fertilizers and agrochemicals for weed suppression (VALENTIM; ANDRADE, 2004). In addition, these technologies increase pasture carrying capacity and animal gains, which results in higher production per animal and per hecta-re, thus increasing profitability of cattle production systems in the Brazilian Amazon (ANDRADE et al., 2015).

Local Institutions Have Capacity to Support Program

Throughout the last four decades, promotion of sustainable intensification of cattle production systems using mixed grass-legumes pastures has been one of the main R&D focus of Embrapa Acre. In addition, researchers have been committed and available to solve problems as they occurred and adopted an interactive on-farm research framework involving farmers in the technology development process.

Strategic Partnerships Between Stakeholders in Place

Strategic partnerships between Embrapa, farmers and private enterprises were in place. However, there has been a lack of continuity (change of sta-ff, lack of financial resources) of activities of extension agencies. This has prevented them from developing personnel with expertise in establishment and management of grass-legume pastures in the region. If more investments were made in capacity building of extension and development agencies, wider adoption would have been possible.

Government Policy Settings Conducive and Support Services Favourable

Research services were available to solve problems as they occurred and to progress technology with farmers, such as management strategies, new grass and legume varieties. Additionally, financial credit was available for reclamation of degraded pastures and for intensification of cattle production systems.

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Challenges and opportunities for wider adoption of mixed grass-legumes pastures

Increasing Availability of Low Cost Forage Peanut Seeds in the Market

The myths that apparently limited successful adoption of mixed grass-legume pasture technologies in the Brazilian Amazon have been overcome by long-term successful on-farm experiences. Research has identified forage peanut as the most persistent and compatible tropical legume, highly adapted for use in more intensive pasture-based cattle production systems. However, current use of this legume in mixed grass pastures is far from fulfilling their potential area of adoption of 45 million hectares of cultivated pastures in the Amazon biome and in the 36 million hectares of pastures in the Mata Atlântica biome.

Restriction for wider adoption of this legume in mixed grass pastures due to dependence of vegetative propagation of cultivar Belomonte was partially solved by development of the seed producing cultivar BRS Mandobi (ASSIS et al., 2013). This cultivar will be released to the market in 2019, with seeds at a price of US$ 25.00/kg. Brazilian seed producing companies are still depen-dent of the development of a more efficient forage peanut seed harvester to make a decision to invest in large-scale seed production.

Expanding the Network of Mixed Grass-Legume Demonstration Farms

Expanding a network of demonstration farms and champion farmers with succes-sful use of mixed grass-legume pastures is an essential step to increase aware-ness of farmers, researchers, extension agents, and public and private decisions makers to promote wider adoption of mixed grass-legume pastures as a strategy to intensify cattle production systems in the Amazon and Mata Atlântica biomes.

Improvement in the Rural Credit System

Another important step is to assure that Brazilian agriculture policies consi-der establishment of mixed grass-legume pastures and the introduction of legumes into existing pastures that are productive or in degradation as an investment in soil quality improvement and pasture productivity and resiliency. As such, this practice would be eligible as part of rural credit framework, parti-cularly the Brazilian Low Carbon Plan (Plano ABC), and the National Program for Strengthening Family Farming (PRONAF).


Regulation of the Forest Code

The Brazilian Forest Code (BRASIL, 2012) is in the process of regulation in the National Congress. Article 41 establishes a Program to Support and Encourage Environmental Preservation and Recovery. The federal govern-ment is authorized to institute a program of support and incentive for envi-ronmental conservation, as well as for the adoption of technologies and good practices that reconcile agricultural and forestry productivity, with reduction of environmental impacts. The program establishes payments or incentives for ecosystem conservation and improvement activities that generate environ-mental services, such as: 1) soil conservation and improvement; 2) seques-tration, conservation, maintenance and increase of stock and reduction of car-bon flow; 3) conservation of water and water services; and, 4) conservation of biodiversity.

Considering that legumes provide several of these environmental services when mixed in grass pastures, as discussed previously, there is a great oppor-tunity to include this practice among those that enable farmers to get pay-ments for environmental services.

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VALENTIM, J. F. Outras leguminosas forrageiras de importância econômica para a pecuária brasileira. In: FONSECA, D. M. da, MARTUSCELLO, J. A. (Ed.). Plantas forrageiras. Viçosa, MG: Ed. UFV, 2010. 537 p. il.

VALENTIM, J. F., ANDRADE, C. M. S. de. Perspectives of grass-legume


pastures for sustainable animal production in the tropics. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 41., 2004, Campo Grande. A produção animal e segurança alimentar: anais. Campo Grande: Sociedade Brasileira de Zootecnia, Embrapa Gado de Corte, 2004. 1 CD ROM

VALENTIM, J. F., ANDRADE, C. M. S. de. Tropical kudzu (Pueraria phaseoloides): successful adoption in sustainable cattle production systems in the western Brazilian Amazon. Tropical Grasslands, 39:221. 2005a.

VALENTIM, J. F., ANDRADE, C. M. S. de. Forage peanut (Arachis pintoi): a high yielding and high quality tropical legume for sustainable cattle production systems in the western Brazilian Amazon. Tropical Grasslands, 39: 222. 2005b.

VALENTIM, J. F., COSTA, A. L. da. Consorciação de gramíneas e leguminosas forrageiras no Acre. Rio Branco, AC: EMBRAPA-UEPAE Rio Branco, 1982. 26 p. (EMBRAPA-UEPAE Rio Branco. Boletim de pesquisa, 2).

VALENTIM, J. F., GARRETT, R. D. Promoção do bem-estar dos produtores familiares com uso de sistemas de produção agropecuários e florestais de baixo carbono no bioma Amazônia In: AZEVEDO, A. A., CAMPANILI, M., PEREIRA, C. (Org.). Caminhos para uma agricultura familiar sob bases ecológicas: produzindo com baixa emissão de carbono. Brasília, DF: Ipam, 2015. 225 p. p. 75-99.

VALENTIM, J. F., ANDRADE, C. M. S. de, ASSIS, G. M. L. de, SÁ, C. P. de, COSTA, F. de S., SALES, M. F. L., FERREIRA, A. S., MESQUISTA, A. Q. de, COSTA, C. R. da. Semeadura de amendoim forrageiro BRS Mandobi em pastagens estabelecidas. Rio Branco, AC: Embrapa Acre, 2017. 16 p. (Embrapa Acre. Circular técnica, 73).

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Abstracts – Poster presentations

SESSION 1 - Technology transfer and analysis

Fundamentals of a participatory methodology for Embrapa’s technology adoption

Joanne Régis da Costa1,2, Maria Elizabeth de Assis Elias2

1 Corresponding author: [email protected] Embrapa Amazônia Ocidental

When developing projects with farmers, it is essential to use tools that can su-pport the construction of a sound decision-making knowledge base, as to im-prove socioeconomic conditions and promote environmental services. In this sense, the objective of this study is to present the foundations of a participatory methodology directed to the adequate management of rural establishments, basis of the projects “Environmental management for small farms”, financed by Embrapa; and “Inovaflora”, funded by the Amazon Fund. By applying the methodology presented here, the objective is to organize ‘Reference Units of Agro-Environmental Adequacy’, where the knowledge and technologies ge-nerated by Embrapa are validated and adopted. The proposed methodolo-gical process is being applied at ‘Tarumã Açu/Tarumã Mirim’ Environmental Protection Area, which overlaps the Tarumã-Mirim Rural Settlement, in the rural area of Manaus (AM, Brazil). The main objective is to build an appro-priate decision-making process with the families, taking into consideration: (i) diagnostics; (ii) strategic, tactical and operational planning; (iii) implementa-tion and (iv) evaluation. Diagnostics are carried out on the community and on the farmstead scales, seeking to understand the local reality and to provide information to devise proposals for food diversification, income generation and reclamation of degraded areas. The family chooses a productive activity to be the flagship of the farm, in which efforts are dedicated in order to reach greater impacts on income generation. Social aspects include family health, food safety and security, formation or strengthening of associations and coo-peratives, in order to reinforce solidarity, claim infrastructure improvements, develop cooperative work, collectively produce and trade, and achieve grea-

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ter efficiency in the use of resources. Non-formal education contributes to the development of skills and technical competence, by providing elements for farmers’ autonomous decisions on their establishments. In this sense, cour-ses, lectures, technical visits, conversation circles, etc. are held, when various topics are addressed, with different forms of interaction. In what concerns the environmental management, measures are adopted to comply with related legislation, considering special areas such as Mandatory Protection Areas (APP) and Legal Reserve, as well as Areas of Restricted Use. Models applied toward environmental reclamation vary depending on family preferences and degree of observed degradation. Water management actions include protec-tion of springs and stream banks using green infrastructure such as ‘Nature-Based Solutions’ (NbS). In each activity, periodic evaluations are carried out and, throughout the process, adjustments are promoted in accordance with current requirements. To appraise the adoption of technologies, the ‘System for Environmental Impact Assessment of Agricultural Technology Innovations’ (Ambitec-Agro) is applied, which consists of integrated modules of multicrite-ria environmental and socioeconomic indicators. Participatory methodologies are essential to the success of research and technology transfer activities with family farmers. Their implementation necessitates due consideration of the multidimensional nature of sustainability and the recognition of the multiple expressions of social vulnerability, which increases the complexity and trans-cends the ‘economicist’ spheres of development.


Behavioral Diagnosis of Productive Activity: an evaluation method based on knowledge, motivation, action and impact indicators

Francisco Eduardo de Castro Rocha1, Maíra Gabriela Santos de Souza2, Fábio Gelape Faleiro3, Paulo Roberto Galerani4

1,3 Embrapa Cerrados. Corresponding author2,4 Embrapa. Embrapa Cerrados, Rodovia BR-020, km 18, Zip Code 73.310-970, Planaltina, DF - Brazil. Embrapa, Parque Estação Biológica, PqEB s/no. Zip Code 70.770-901, Brasília,

DF – Brazil

In the context of the agricultural productive sector, the evaluation of inno-vation processes must involve aspects related to both the technology user and technological assets or objects. The importance of the use of an appro-priate scientific method is emphasized so that the gathering of information with the rural producer reflects aspects that will be relevant for an adequate intervention, as well as for the feedback of the technological innovation pro-cess. From this perspective, it is essential to understand the behavioral issues that lead rural producers to adopt a new productive practice; remain in the practice they were already developing, or even withdraw from their produc-tion chain. Studies of this nature, therefore, should consider human variables that are widely studied internationally so that they can serve as a basis for technical intervention actions. This work aims to present, in general terms, the method entitled Behavioral Diagnosis of Productive Activity - DCAP, deve-loped to evaluate results related to the adoption and impact of technologies. DCAP was elaborated based on two theoretical contributions: the Fishbein and Ajzen Predicting and Changing Behavior: the reasoned action approa-ch and the Taylor-Powell and Henert Developing a Logical Model: teaching and a training guide, which are used in conjunction with variables related to short-term (knowledge and motivation), medium-term (action) and long term outcomes (impact). The method was designed to be operationalized through five sequential steps: 1) Design - definition of the target audience, sample size and sample plan. 2) Instrument - elaboration of the questionnaire based on the logical model, containing four blocks of results with open and closed questions (knowledge, motivation, action and impact). This requires appro-ximately three workshops with subject matter experts (e.g. passion fruit) to survey outcome indicators, plus three workshops for the operational definition of such indicators and questionnaire items. Motivational items are prepared based on Predicting and Changing Behavior: the reasoned action approach.

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3) Procedures for data collection from the target audience (e. g. farmers). 4) Data analysis - Descriptive statistics such as frequencies, percentages, column and bar graphs are indicated in DCAP to verify learning gaps (know-ledge); the interest in staying or not in the production chain (motivation); the assets adopted and how they were adopted (action data) and the degree of consequence in terms of losses and gains (impact data). 5) The Study re-cord - information processed and made available in the form of reports and / or books. DCAP is a method that is suitable for any environment, activity or production chain, as its focus is on human behavior. DCAP is considered innovative for areas of agricultural research, rural extension and public policy, as it allows the joint evaluation of short-term, medium-term and long term out-comes, directing intervention actions to improve the productive activity under analysis.


Case study: Kit Embrapa of Manual Milking® adoption to improve milk qualityJuliana França Monteiro de Mendonca1, Sérgio Rustichelli Teixeira2, Fredson Ferreira

Chaves3

1 Doctoral Student, Federal Fluminense Universidade, Niterói/RJ2 Researcher, Embrapa Dairy Cattle, Juiz de Fora/MG

3 Analyst, Embrapa Corn and Sorghum, Sete Lagoas/MG

Problem statement – The production of safe and quality food is one of the major public health issues worldwide. However, there is a concern to improve the profitability of family farmers. The “Brasil Sem Miséria” (Brazil Without Misery Plan - BWM) was created with the objective of improving the income and quality of life of farmers in extreme poverty. BWM, in the north of Minas Gerais, demanded actions to improve milk quality. It was proposed to use the Embrapa Manual Milking Kit® to improve the milk quality associated with en-couragement of pay for milk quality to farmers.

Objective – To evaluate the improvement of milk quality using Embrapa Manual Milking Kit® social technology among participating of BWM farmers and their acceptance.

Method – 110 Embrapa Manual Milking Kits® were distributed among farmers participating in the BWM Plan, who were oriented on the use of the techno-logy. Three milk samples from each farm were collected by trained extension workers from November 2014 to March 2015 (times 1, 2 and 3). The samples were submitted to Total Bacterial Count (TBT) and Somatic Cell Count (SSC) analyzes at Embrapa Dairy Cattle Milk Quality Laboratory, Juiz de Fora, MG. A questionnaire was also applied to the 30 farmers who had all quality analyzes to obtain information regarding satisfaction with the use of the Kit. The farms were then divided into the “com kit” groups (adoption of at least 70% of the kit items). ) and “sem Kit” (adoption of less than 70% of kit items). The results of the questionnaire were compared to the quality analyzes performed and also to the reports of the technicians of Emater-MG in the Milk Research and Innovation Network (RepiLeite).

Results – An improvement in milk quality after the use of the Kit was empi-rically observed by 66.7% of the farms evaluated by the questionnaire. The average results of the SSC and TBC analyzes confirm these observations (Graph 1). Statistical difference (t-Test) was found in the mean TBC value

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between time 1 (before the use of the kit) and the others for the farms that used the kit correctly (p <0.05). However, in relation to SSC, no significant difference was observed between the three analyzes performed (Graph 1). This was probably due to the short time period analyzed. Farmers who used the Kit reported that “milk is cleaner”, that there was “higher yield in cheese making”, that cheese produced “no longer swells” and is “less puffy”. These testimonials confirm the expectation when using the Kit.

Implications – The use of the Embrapa Manual Milking Kit® was effective in improving milk quality. The adoption of the technology was temporary due to cultural barriers, and disagreements regarding the payment for milk quality to the farmer and because farmers considered the technology laborious.

Acknowledgments - To the participating farmers, to Emater-MG, to Embrapa Corn and Sorghum and Dairy Cattle for the support of the work and to the Brazil Without Misery Program for the financing of the work.


Work issues on Tomatec - a tomato sustainable production system

Igor Rosa Dias de Jesus1, Paula Cristina Silva Bastos1, Michele Belas Coutinho Pereira1, Melissa Silva Leme Dalarme1, José Ronaldo de Macedo1, Petula Ponciano

Nascimento1 Embrapa

Tomatec is a tomato sustainable production system. It encompasses a set of good practices on the crop. The main practices are: irrigation through water-dropping, fertilization within irrigation (ferti-irrigation), integrated pest control (which heavily reduces the use of pesticides), good soil handling with no-tilla-ge cropping and use of contours for planting, use of tiny wires for supporting tomato trees (instead of bamboo logs) and the enveloping of the fruits with paper bags. Enveloping remains as one of the most important practices due to two factors: first, it is visible. Tomatec crops are easily recognized by people because of the white paper bags that involves all bunches, turning all plan-tation into white. The other reason is because enveloping is a very laborious process, and the key for having fruits free of pesticide residues. In order to as-sess the impacts of Tomatec, using the Ambitec method, we have conducted four interviews with Tomatec producers in the State of Rio de Janeiro, Brazil. These interviews happened on 2019 September and took place in four mu-nicipalities: Tanguá, Nova Friburgo, Teresópolis and São Sebastião do Alto. Producers mention that farmworkers use individual protection equipment du-ring their works. On field, we have seen hats and jackets. They mentioned that farmworkers also use masks for pesticides aspersion. Concerning to labour time, we have observed two main ways of contracting. Smaller pro-ducers usually work themselves in the fields. On harvest time, they contract many farmworkers, which are payed by numbers of day working. Bigger ones contract farmworkers by month and sign their workcard, paying the wages as well as the labour benefits, as disposed by Brazilian law. Another interesting finding about work on Tomatec is the genre division. All producers mentioned that pesticide sprinkle is exclusive to men, and enveloping is exclusive to wo-men. It is not defined by rural producers: the farmworkers actually ask for that. Producers reported that farmworkers realize that sprinkling is a more painful and dangerous activity, with potential harms to fertility. Although Tomatec is recognised by strongly reducing the total amount of chemical products on the crop, men still want to save women from that kind of activity. On the other

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hand, enveloping is considered by farmworkers and producers a more delica-te activity. It demands agility and precision to put on the paper bags on tomato flowers and to clip them, making the tomato fruits growing up inside the bags without receiving any drop of pesticide. Men are considered slower and less efficient than women to carry on this activity. So, analysing work issues on Tomatec we can see that the adoption of this production system have establi-shed many different strategies to deal with safety, law and genre issues.


Step-by-step video, a powerful tool for technology transfer: terrace plow as a case study

Lauro Rodrigues Nogueira Junior1, Ivan Ricardo Marinovic Brscan2

1 Embrapa Territorial, Av. Soldado Passarinho, 303, Campinas/SP2 Embrapa Tabuleiros Costeiros, Av, Beira Mar, 3250, Aracaju/SE

Abstract – Social media play an increasingly relevant role in communication. In media such as Youtube and Facebook, step-by-step or how-to videos fea-ture among the most viewed and therefore could be used as tools for tech-nology transfer. Aiming at disclosing the use of contour plowing in a corn pro-duction region undergoing soil degradation in the Brazilian northeastern state of Sergipe, Embrapa Tabuleiros Costeiros launched a step-by-step video with graphic animation ‘Terraceamento com Arado’ (terrace plow, in English) on April 16, 2016 — Brazilian National Soil Conservation Day. The video was coordinated by the authors of this abstract, produced by a media company from Aracaju city, Sergipe state, at the cost of R$ 10,000.00, and made avai-lable on Embrapa’s homepage, Facebook page and YouTube channel. In five steps, the six-minute-long video instructs how to determine the soil’s texture, to calculate the terrain’s slope, to determine the distance between contour plo-wing, to picket the contour curves, and how to make the contour plowing using a plow and tractor. Although it was produced for a specific region, the video has been viewed all over the country, and even in some Portuguese, Spanish and English-speaking countries. It is one of the ten most viewed among all 2,343 videos listed in Embrapa’s channel on YouTube. On September 24, 2019 it reached 245,572 views, with an average 195 daily views. When con-sidering Facebook pages of other agricultural companies and governmental or non-governmental institutions, it surpasses 1,000,000 views. The video was highligh in ‘Rural Pecuária’ Facebook page, where is has been viewed 759,000 times. Videos made available on the Internet show strong advanta-ge in comparison with the method of technology transfer known as ‘Dia de Campo’ when time, space, economic and cognitive aspects are taken into consideration. Videos made available on the Internet are visible anytime and anywhere, as long as there is an Internet connection, and farmers may watch them, and even search for details, whenever they intend to apply the techni-que. Knowledge transferred via videos may be better understood, especially by people that experience reading difficulties, have low education levels or low knowledge retention capacity. This occurs because a person interested in

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adopting a given technology may watch a video as many times as necessary until the knowledgeis completely absorbed, and may consecutively or concur-rently apply it. Digital Marketing specialists estimate that 3% to 5% of video and page content views convert to sales. Specifically for Embrapa, the adop-tion of a technology by farmers may be considered sales. Based on this pre-mise, on YouTube alone this video may have yielded between 7,215 to 12,024 adoptions of terrace plow, which is an excellent cost-benefit ratio. Although we did not estimate the number of technology adoptions, comments from vie-wers indicate that farmers are interested in adopting the contour plowing, and teachers and rural-extension technicians are interested in using the video for broadcasting it.


Simulation of a wheat production system for exportation in rural enterprises of Rio Grande do Sul State, Brazil

Adão da Silva Acosta1, João Leonardo Pires2

1 Analyst, Embrapa Wheat, 2 Researcher, Embrapa Wheat

Brazil produces half of the wheat it consumes. Logistical and competitive as-pects force part of Rio Grande do Sul State ́s production to be destined to external markets and not for the domestic industry. In lights of this scenario, Embrapa Trigo has been developing a wheat production system for expor-tation. The system focused on grain yield, through the best use of cultivars, management practices and other inputs at compatible costs. To promote the adoption of this system, validation units were conducted in cooperatives of Rio Grande do Sul State, obtaining yields equivalent to those obtained in tra-ditional wheat fields, with a reduction in production costs of up to 24% and an increase in net revenues up to 73%. The use of this system was simulated with these results, from the economic and financial point of view, in farmer fields chosen in the municipalities where the validation units were conducted: Passo Fundo, Panambi, São Luiz Gonzaga, Santa Rosa and Campo Novo. These rural enterprises obtained data from the balance sheets, the share of activities in net incomes and cash-flows. All but one of the rural enterprises had fixed assets above 98%, accounting for the most part or exceeding the net equity. Soybean production was responsible for most of the revenues, along with wheat, corn, oats, canola, beef and dairy cattle. The simulations corresponded to the inclusion of wheat in up to one third of the sum of the soybean and corn area of the properties. Considering the productivity, the costs obtained in the validation units and the prices practiced in the coope-ratives, the contribution of wheat production system for exportation observed in the simulation was positive in the property of Passo Fundo, by the diversi-fication of activities, and in the property of São Luiz Gonzaga, by the scale. It was indifferent in Panambi and negative in the Santa Rosa and Campo Novo, because the combined effect of the yields obtained in the validation units was lower than those obtained by the producers and the input costs were higher than those practiced in the farmer fields. Considering postharvest elements, a seasonal variation of up to 25% in the price of wheat in these municipalities was identified and can be just as important as reducing costs. The wheat pro-duction system for exportation is in use because of its lower production costs and increase in profits. However, when incorporating specific economical and

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financial aspects of rural enterprises, such as local production systems and price seasonality, barriers can be found for the adoption of this wheat produc-tion system for exportation.


Technology Transfer and Innovation (TT&I): a Disruptive Proposal

José Luiz Bellini Leite1

1 Ph.D. Economia Aplicada – Analista da Embrapa Gado de Leite - Juiz de Fora (MG)

The communication activities and traditional methods that have supported the technology transfer process (TT), in the recent past, do not seem to maintain an adequate level of efficiency and effectiveness. The rapid changes in pro-duction chains, the intensifying competition worldwide, and the availability of more complex and sophisticated technologies, are requiring changes in the technology transfer modus operandi of extension and research & develop-ment institutions. There is a huge gap between elite producers (high produc-tivity and efficiency) and medium productivity producers, indicating the exis-tence of viable technologies and a huge field of work for technical assistance.

The paper presents concepts and tools that can help institutions rearrange the structure and re-engineer the processes of technology transfer that facilitate, increase reach and speed up the process of technological innovation in diffe-rent production chains. Based on cloud computing technology, continuous te-chnical assistance, long term production planning and knowhow capacitation, the creation of an Innovation Network (INet) by clusters and production chains is suggested. The producer or producer group must hire, or receive from the cooperative / industry, professional private technical assistance to participate in the network. This network should be coordinated and technically supported by public extension institutions and research & development institutions inte-rested in sustainable development of agribusiness, at any production scale.

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The network connects producers and their technical assistance with trained researchers and public technicians to support planning and implementation of production, by means of provision of information, knowledge, technology, on-line capacitation in knowhow and problem solving. Beyond this, the INET organize and provides a big data to support orientation and prioritization of applied research, public and private policy formulation and evaluation.


PMMacro for Food and Nutrition Safety Promotion in Urban and Rural Areas

1 Valéria Sucena Hammes, 2 Cristina Arzabe1 Embrapa Sede, 2 Embrapa Sede, Parque Estação Biológica - PqEB s/no. Brasília, DF

Rural extension aims to stimulate changes in population behavior through the adoption of technological solutions, contributing to sustainable rural develop-ment. Agricultural technical assistance helps to structure food production for both, self-consumption and surplus generation for commercialization, impro-ved income generation and quality of life. Both, availability and quality food are key factors in ensuring the population’s food and nutritional security.

The urbanization trend, with the concentration of population in impermeable areas and sometimes distant from fresh food producing areas, is commonly associated with increased obesity and malnutrition in adults and children. Therefore, it is essential equip the agricultural technical assistance also to stimulate urban agriculture and the production of food for self-consumption by the most vulnerable populations, including those with difficult to access healthy food.

The PMMacro method (PGMacro in Portuguese) stands for Planning and Management (PM) and Macro-Education (Macro), named for prioritizing planning with all stakeholders in the adoption of new technologies, defining shared management. It is a method originally developed to the agro-environ-mental education practiced by agricultural technical assistance in promoting collective behavioral changes through the adoption of good sustainable agri-cultural practices, applicable to rural, urban, agricultural or non-agricultural communities.

The continuous planning and the establishment of co-governance and co-ma-nagement contribute to the method being agile (3 months per step), mobili-zer (involving all stakeholders) and transformative (accomplishing the chan-ge planned by the behavior change of the participants) (Hammes & Arzabe; 2015). The method has four-step cycles of three months, in a gradual and continuous process of learning and broadening of systemic vision, strongly supported by visual and integrative techniques. The method is based on: 1) building a stakeholder team and visualizing the common goal; 2) prioritiza-tion and consensus on the solutions; 3) execution of individual and collective

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agenda; and 4) evaluation, validation of referrals, monitoring of indicators, and celebration. The indicators measure efficiency (mobilization and commitment of the actors involved, with fulfillment of the agendas), readiness (quick res-ponse, accounted for on achievement time) and effectiveness (improvement of economic, social and environmental aspects in the community). The main impact is the formation of sustainable community expressed by the adoption of sustainable technologies.


Specific indicators for monitoring technology adoption

1 Susana Lena Lins de Góis, 1 Caroline Machado Vasconcelos Turazi

1 Researchers at Embrapa. Parque Estação Biológica - PqEB s/nº. Brasília, DF

Farming Process and Cultivar are in the main list of technology engendered of Public Institution of Science and Technology that is analyzed in this research. Public research institutions, mostly, have difficulties to perceive, with accu-racy, of all the determinant factors of adoption of these types of technology and measure them over time in order to establish aims and directions for their researches. The difficulty is in the fact that the adoption of these technologies by productive sector requires specifics indicators, which need to be measured outside the institution, in an unmanageable environment. Internally, the te-chnology’s attributes – usually related to productivity or low production costs – are easier to be assessed even if by estimates, formal partners or official data. Outside the institution, the effects of marketing strategies and technolo-gy diffusion may not achieve results that reach market and the adopter.

Sociocultural, economic and access to natural resources characteristics im-pact especially the decision making process of technology adoption. Beyond the internal and external institutions dynamics, the sum of all them bring about much more complex aspects that would allow to understand all determinant factors to enable the adoption of those technologies. The research aimed at, therefore, identifying differential elements in the process of adopting Cultivar and Farming Process. The sort of technology generated imply different pers-pectives of the adopter regarding the decision-making process and, therefore, requires specific indicators to measure its adoption. A closed questionnaire focused in monitoring indicators of adoption and measurement sources was carried out and answered by 37 research centers of the Institution of Science and Technology. All analysis made indicated the need of specific indicators to Cultivar and Farming Process. The main difference between them is based on the technology characteristic. Farming Process are intensive in knowled-ge by the adopter and demand a transfer of a large amount of information, which is made possible by means of technical assistance and rural extension networks. Their indicators also pass through marketing activities and overta-ke technical dimension. The context in which the Farming Process is imple-

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mented and its relationship with social, economics, politics and environmental aspects – all difficult to predict and measure – should be considered. Cultivar technologies have, instead, knowledge into the technology itself. Market indi-cators – royalties or relationships with licensed – are more difficult to assess or estimate accurately and quickly, directly or via commercial partners. The analysis allowed to bring to the concrete dimension the difficulty in define indi-cators that reflect, in numbers, qualitative information that assurance identify the technology adoption.

Even if some indicators might be much more difficult to be measured and to establish comparative bases, Research Institutions need to brace their net-works to evaluate, periodically, its technology portfolios, its research projects, its strategies to transfer technology and, above all, generating social, econo-mic and environmental impacts for the society.


SESSION 2 - Agricultural Technology Adoption

Adoption of Fish Farming by Family Producers: an Application of the Planned Behavior Theory

Suzi Cristiny da Costa Marques1, Juliano Rosa da Silva1, Juliana Rosa Carrijo Mauad1, João Augusto Rossi Borges1, Carla Heloísa de Farias Domingues1

1 Programa de Pós-Graduação em Agronegócios (UFGD)

More than two thirds of the world’s low-income populations that suffer food insecurity are small farmers. One of the ways to alleviate or even solve this problem is to diversify agricultural production for income generation. One of the alternatives to diversify the production is fish farming, which compared to other agricultural activities, has a lower production cost and is an alternative for household income and protein source of consumption. The aim of this stu-dy was to identify the socio-psychological factors that influence the intention of small farmers to adopt fish farming. The theory of planned behavior (TPB) was used, which puts presupposes that the actual behavior of a person is directly driven by their behavioral intentions. In TPB, a person’s behavioral intention is influenced by three social-psychological constructs: attitudes, sub-jective norms, and perceived behavioral control. These three constructs are formed by beliefs that individuals have about the behavior in question. In this study, we also added the construct self identity. The survey was conducted in the Itamarati settlement, Ponta Porã-MS, which has an area of 50 thousand hectares. For data collection, questionnaires were used through interviews with 184 small farmers. We used the Spearman correlation to identify the correlation between the constructs with the intention. Four behavioral beliefs that represent possible outcomes of adopting fish farming have been identi-fied as attitude-shaping: “increased farm income”, “additional source of food for own consumption” and “better quality of life”. Eight Normative beliefs re-presenting other important people to producers and formed the Social Norms construct: “sons / daughters”, “spouse”, “friends”, “neighbors”, “agricultural cooperatives”, “farmers’ syndicates”, “farmers’ association” and “governmen-tal institutions.” And five control beliefs that represent factors that would make it easier for producers to adopt fish production that were: “to have an easy way to sell fish production”, “to have the financial incentive from governamental sources”, “to have free technical assistance”, “having more knowledge about

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fish production” and “having river water flowing into the rural lot” and formed the perceived behavioral control construct. The results suggest that perceived identity, attitude and perceived norms, impact on small farmers’ intention to adopt fish farming. We also highlight the importance of directed interventions to improve the identity of fish farmers, developing more favorable atitudes regarding the adoption of fish farming and increase social support.


Dairy Technology Adoption Perception in Burkina Faso, West Africa: the Importance of Responsibility in Demands IdentificationSergio Rustichelli Teixeira1, Sergio Guilherme Azevedo2, Antônio C. C. Leite Ribeiro3,

Adriana Mesquita Corrêa Bueno4

1 Pesquisador, Embrapa Gado de Leite, Juiz de Fora/MG2 Analista, Embrapa Semiárido, Petrolina/PE

3 Analista, Embrapa Gado de Leite, Juiz de Fora/MG4 Analista, Secretaria de Inteligência e Relações Estratégicas da Embrapa, Brasília/DF

Problem statement - Embrapa has been requested by the Brazilian Federal Government to contribute to the development of the agricultural sector in se-veral developing countries. This is called South-South Cooperation (SSC). To the Government of Burkina Faso the project “Strengthening Burkina Faso Dairy Farming” was conceived in 2009 and implemented between 2012 and 2017. The project was coordinated by the Brazilian Cooperation Agency (ABC) and co-executed by the National Center for Multiplication of Animals (CMAP) from Burkina Faso. The central problem of the cooperation was the extensive traditional system, practically nomadism, involving more than 70% of the herd with a 700 kg of milk per lactation of approximately 210 days.

Objective - Sustainably forage production to improve its effect on feeding, reproduction and health of dairy cattle.

Method - In the project two Demonstration Units (DUs) were stablished. One at the Loumbilà Experimental Station and one at Samandeni. In these regions, the rainfall is of 500 and 1000 mm of annual rain respectively. As one of the feeding bases nurseries of Mexican elephant ear palm (Opuntia tuna) were made. In addition, the areas for rotational grazing were demarcated. Data exchange between teams from both countries was also organized and sim-ple equipment was brought from Brazil. In 2013, eight burkinabe technicians were trained in Brazil. Within the concept of the Brazilian SSC, the physical implementation of the project and payment of the technicians salary would be the responsibility of each country. As well as the development and adaptation of appropriate solutions to that reality. It was stressed that the Brazilian so-lutions should not be simply copied. A production manual was developed for a production system to be adapted by burkinabe technicians. The Embrapa

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and ABC teams strived to present solutions and jointly discuss actions without imposition.

Results – The forage palm showed good adaptation to that reality. Field Days were implemented and seedlings, spread on private properties (photo). The project did not reach the goal of feeding the entire selected herd to the point of increasing production and improving reproduction. In two years of imple-mentation and data collection, it had only results for four of the 20 cows in Loumbila. Discussion of project specifications and demands was inefficient during the project. It occurred more intensely only in the last mission (2017) when it was reported by CMAP that the number of 20 cows was too large for the reality of most producers. Health data was lacking for broader action.

Implications – With palm and capacity building, CMAP is better able to cope with the challenge of improving dairy production in the country.. The project was successful in palm deployment and awareness of discussion and drafting prior to start. The responsibilities of authorities and project implementation staff need to be very clear to achieve the planned objective.


Intention to Adopt Integrated Production by Common Bean Growers: the Application of the Technology Acceptance Model (TAM)Aluísio Goulart Silva1, Maurizio Canavari2, Katia Laura Sidali3, Alcido Elenor Wander1

1 Embrapa Arroz e Feijão. Rod. GO-462, km 12, Faz. Capivara, Zona Rural. C.P.: 179.75375-000. Santo Antônio de Goiás (GO) - Brazil

2 Alma Mater Studiorum Università di Bologna. Department of Agricultural Sciences. Viale Fanin, 44. 40124. Bologna (BO) – Italy

3 Faculty of Economics, Free University of Bozen/Bolzano, Universitatsplatz 1, 39031 Bruneck, Italy

The Brazilian Government has been promoting Integrated Production (IP), since 2010, as a public policy to ensure sustainable and safe food production. Aiming to reduce the negative environmental impacts of intensive production in irrigated areas of the Brazilian savanna, more recently, the common beans’ growers were encouraged to adopt IP. Notwithstanding the Government ef-forts to enable IP throughout the main regions of bean production and among the specialized growers, few groups accepted to implement IP at the ideal level or for the expected length of time. This undesirable scenario might be explained by certain regional particularities such as different biomes, inequa-lity among agricultural segments (small versus large scale agriculture), and crop interests due to which some of them are targets to export and others to the domestic market (Souza Filho et al., 2011). Therefore, studying the process of technology adoption is important to identify possible problems that could affect adoption of IP. The primary objective of the present study was to determine if the Technology Acceptance Model (TAM) developed by Davis (1989) could provide an adequate explanation of adoption and use of IP by common bean producers from one of the most important producing regions in Brazil. Additionally, to determine the extent to which some economic, so-cial, technical, environmental and market factors influence the decision-ma-king, technology acceptance and usage by bean growers. For the purpose of the present study, IP was considered as a bundle of technologies (Good Agricultural Practices – GAP). Data collection comprehended two phases. The first, qualitative phase, was developed between Oct. 2013 and Feb. 2014 when we used a structured questionnaire with open-ended questions divided into four sections with technical aspects, economic advantages, institutional factors and market aspects, all of them related to IP adoption and an additio-nal section to collect personal and professional data about the respondents

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(N=10). This phase aimed to elicit the salient beliefs for each latent variable using a content analysis. Then, the results were used to construct a structured questionnaire of the quantitative second phase (a pilot survey was adminis-tered, N=38), with three sections involving questions about the respondent’s knowledge on IP, TAM’s constructs and demographic data. The questionnaire was designed considering its validation and reliability (Hair et al., 2006). The internal consistency of dataset was measured for each separate item, inclu-ding the item-to-total correlation (0.50) and the inter-item correlation (0.30). The consistency of the entire scale was verified using Cronbach’s Alpha (≥ 0.7). The final questionnaire was applied during Dec. 2014 and Feb. 2015 when ninety-three interviews were done to different actors along common beans production chain. A Structural Equation Model (SEM) following a con-firmatory factor analysis (CFA) was used to identify the relationship between factors. The findings suggest that respondents have positive perceptions to-ward adopting IP. Perceived usefulness has a positive impact on attitude, and attitudes affect behavioral intention. However, the proposed model only par-tially explains IP adoption intentions. Apparently, models such as TAM do not work very well on non-divisible technologies such as IP.

* Based on Silva, A. G., Canavari, M., & Sidali, K. L. (2018). A Technology Acceptance Model of

common bean growers’ intention to adopt Integrated Production in the Brazilian Central Region.

Die Bodenkultur: Journal of Land Management, Food and Environment, 68(3), 131-143.


Behavioral Diagnosis of the Productive Activity of Passion Fruit in the Federal District, Brazil, Aiming at Prospecting Real Demands for Research, Extension Rural and Public Policies

Fábio Gelape Faleiro1, Francisco Eduardo de Castro Rocha1, Antonio Carlos dos Santos Mendes2, Geraldo Magela Gontijo2, Nilton Tadeu Vilela Junqueira1

1 Embrapa Cerrados. Corresponding author – [email protected] Emater/DF. Embrapa Cerrados, Rodovia BR-020, km 18, Planaltina, DF - Brazil. Emater/DF,

Parque Estação Biológica, Ed. Sede EMATER-DF, Brasília, DF - Brazil

Prospecting demands for research, rural extension, and public policy based on technology adoption and impacts should be based on thorough analysis using scientifically validated methods. In this work, the Behavioral Diagnosis of Productive Activity - DCAP method was used to analyze passion fruit produ-cer at Federal District, Brazil. It was make a diagnosis of the producers profile and the level of adoption and impact of technologies in the production system to prospect real demands for research actions, rural extension and public po-licies. The methodology involved the definition of the design study instrument, data collection, analysis procedures and study registration. Five information blocks were defined to analyze the producer profile, property characterization, knowledge level and motivation of the producers, action-adoption technolo-gy and their impacts. DCAP results show that passion fruit producers in the Federal District are usually small with orchards under 1.5 ha. Most properties have less than 20 ha. Regarding the data analysis of the producers know-ledge, there were learning gaps in the “Integrated management of pests and diseases”, “Ideal passion fruit seedling”, “Greenhouse and open planting” and “Value added to passion fruit “. Regarding the motivation to produce passion fruit in the Federal District, it was observed the predominance of positive fac-tors (advantages - 64.3%, facilities - 77.8%) over negative ones (disadvan-tages - 31.2%, difficulties - 57.4 %). This means that most producers do not intend to leave the passion fruit production chain. Regarding the producers actions, it was found, for example, that many producers adopt genetically su-perior cultivars, carry out manual pollination and other important cultural prac-tices to obtain high yields of passion fruit orchard. Regarding the technology impact, it was observed an average yield of 18.8 t/ha/year of open planting sour passion fruit in the Federal District (maximum 60 t/ha/year) and 98.1 t/ha/year in greenhouse planting (maximum yield 114t/ha/year). These differences between average and maximum productivity are due to the fact that many

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producers do not use proper technology in the production system. High levels of productivity show successful experiences of various passion fruit producers and production systems in Federal District, Brazil. The results of the work allowed the identification of the general and specific problems of the passion fruit production chain in Federal District, which are guiding the intervention process and a program of research, rural extension and public policy actions focused and appropriate to the real needs of passion fruit producers.


Adoption of Cover Crop Livestock Grazing in Specialized Integrated Crop-Livestock Systems in the Cerrado

Paulo Campos Christo Fernandes1, Tito Carlos Rocha de Sousa2, Antônio Carlos Reis de Freitas3

1,2 Embrapa Cerrados3 Embrapa Cocais

In recent years, the expansion of crops in the Cerrado biome has intensi-fied through the incorporation of technologies that enabled a second sum-mer crop in areas previously intended exclusively for the cultivation of cover crops in the no-tillage system. The cover crop grazing system took place in the dry season with specialized integrated crop-livestock systems in areas intercropped with forage plants or in succession with grain crops. The gra-zing period of low availability of forage plants in pastures has a short duration of approximately one hundred days. The no-tillage system is part of the ABC Plan’s technology portfolio to meet the goals of mitigating greenhouse gas emissions agreed on by the Government of Brazil with the United Nations within the scope of tackling global climate change. Thus, there is a need for the establishment of methodologies that enable measuring, verifying and re-porting on the adoption of the technology within the Cerrado. The modeling of an indicator system to estimate the area occupied by cover crops used as a forage plant for livestock grazing simulate the economic impact of low carbon technologies that can be the basis for agricultural credit planning and production forecasting. The objective of this study was to develop a method for periodic evaluation of specialized integrated crop-livestock systems in the Cerrado biome. The model considered the volume of forage seeds com-mercialized and used for dry season grazing in the second-summer season. The forage seed production in Brazil of Brachiaria ruziziensis, Brachiaria brizantha cv. Marandu and Brachiaria brizantha cv. Piatã and animal pro-duction are parameters used in the model. The Association for Promotion of Forage Breeding Research (UNIPASTO) collaborated to estimate the final use of forage seeds in Cerrado. Cover crop livestock grazing in specialized integrated crop-livestock systems in the Cerrado occupied 2,303,263 hec-tares during the crop year 2017/2018. The annual turnover was R$ 5.7 bil-lion with monthly yield of 3.5% per hectare for 2017/2018. The sparing-land effect was 7.1 million hectares in the Cerrado due to the resting period of

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perennial pastures in the dry season and the lower grazing period, which was induced by the reduction of the slaughter age.


Adoption and Impact of Integrated Practices to Mitigate Soil Compaction in Southern Brazil

Jorge Lemaisnki1, José Eloir Denardin2, Adão da Silva Acosta1

1 Analyst, Embrapa Wheat2 Researcher, Embrapa Wheat

In part of Brazil’s annual grain-producing fields, the no-tillage system is not adopted according to the technical indications that made it viable. This has caused soil compaction and consequently soil erosion after heavy rainfall events and plant water deficits even in short periods droughts. These re-sults cause negative environmental and economic impacts. Particularly, in Southern Brazil, soil compaction is responsible for losses in three out of ten soybean cropping seasons. Hence the importance of expanding the adoption of practices to mitigate soil compaction as a feasible and economical way to retain water in the soil. Practices to mitigate soil compaction are: crop diversi-fication through the use of cash crops and cover crops; soil mechanical inter-vention, when required, by the chiseling; contour cultivation; and terraces. In addition to research data, the integration of these practices was validated at two Farmer ́s Technological Reference Units. With the information collected at these Units, since 2015, Embrapa Wheat has been conducting technology transfer activities for extension agents from Cooperatives, with support from the Organization of Brazilian Cooperatives (OCB). To evaluate the adoption and impacts of practices to mitigate soil compaction, the primary data were obtained in two meetings, with the participation of 53 extension agents from 20 large Cooperatives of Southern Brazil. The four practices were evaluated separately, and altogether. To evaluate the impacts, 58 farms were divided in 29 farms with less than 100 hectares (type I typology), and 29 farms with area of over 100 hectares (type II typology). Coefficients for previously cho-sen indicators corresponding to the impact dimensions were obtained. The area of inference for the adoption of the technologies was estimated at 1.2 million hectares, corresponding to the representative area of the cooperati-ves. Cover crops and contour cultivation were adopted in 57% and 41% of the farms, respectively. Cover crop is an established practice, and contour cultivation is easy to promote adoption by extension agents. Terraces were present in around 19% of the farms, while subsoiling is practiced in just over 8%. Subsoiling seems to be the practice that limits the most the integration, requiring greater attention of technology transfer initiatives in the future. The

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adoption of integrated practices is present in only 7,1% of the sampled farms, indicated an adoption area of just over 85,000 ha in 2018. Practices to mitiga-te soil compaction can provide positive impacts on both large and small farms. Positive impacts were observed on soil quality, mainly through lower erosion, less organic matter loss, less nutrient loss and less compaction. There was also a positive impact on income factors due to production stabilization, es-pecially in years of water deficit. In larger farms, the technology produced better social and environmental impacts. Emphasis is given to the impact of the broad training agenda and field days held jointly between Embrapa Wheat and Cooperatives. There were negative effects on both types of farms due to the surface application of fertilizers and limestone, the use of fossil fuels, and the lack of personal protective equipment, and exposure to chemical agents and machine noise.


Challenges for Technology Adoption Among Cassava Growers in the State of Amazonas

Lindomar de Jesus de Sousa Silva1, Gilmar Antônio Meneghetti2, José Olenilson Costa Pinheiro3, Rosângela dos Reis Guimarães4

1 Sociologist, D.Sc. in Sustainable Development of the Humid Tropics, researcher at Embrapa Western Amazon, Manaus, AM

2 Agronomist, M.Sc. in Development, Agriculture and Society, researcher at Embrapa Temperate Climate, Pelotas, PR / Mixed Research and Technology Transfer Unit - UTFPR campus –

Francisco Beltrão-PR 3 Economist, M.Sc. in Family Farming and Sustainable Development, researcher at Embrapa

Western Amazon, Manaus, AM

4 Agronomist, M.Sc. in Agroecosystems, researcher at Embrapa Western Amazon, Manaus, AM

Cassava cultivation in the Amazon exceeds 80,894 ha, spread over 65,000,000 rural establishments, reaching a production of 940,975 t/year, with an average of 11.63 t/ha/year (IBGE, 2015). This production is below the productivity of the Northern region, which is 16.36 t / ha, and the national one, which is 15.43 t/ha (IBGE, 2016). Cassava is the main source of energy in the Amazonian diet, hence its social importance. The low productivity and the socioeconomic importance of the crop led Embrapa western Amazon to develop a set of ac-tions aimed at enhancing production, providing technologies for innovation in the cassava production process. The implementation of a regional germplasm bank from 1994, with more than 2,000 accessions of cassava materials, is an important step in initiating a technology generation process. The germplasm bank aims to prevent genetic erosion of the species by collecting, preserving, characterizing, evaluating, documenting and providing access for research and use. The research process has provided farmers with important produc-tive varieties for human consumption. In addition to technical recommenda-tions for crops, more recently technology transfer has been prioritizing mana-gement known as the yield trio, which includes management techniques in the selection of seedlings, adequate spacing and control of competing plants in the first five months after the harvest. planting. This paper examines the issue of technological adoption based on research and analysis based on testimonials from researchers, technicians and farmers. It assesses the level of adoption of the technologies developed and made available by Embrapa and the innovation achieved through them.

As a result it was observed that there is a cassava production process that uses little technology made available by research institutions. Because cas-

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sava is one of the main household consumption and income generation pro-ducts for the rural environment, socioeconomic research has identified, as a result of the low adoption of technology and low productivity, the impoverish-ment of rural areas, the lack of materials. production and the predominance of rudimentary production techniques. Still, it was found that, being small family farmers producing cassava scattered in large territory, there is a difficulty for the visits of rural technicians and extensionists, public and private assistance. The low level of access to agricultural finance and the difficulty in accessing technologies lead to a lower level of innovation in the establishments. Thus, the work concluded that the availability of technology needs to be made based on a broad rural development policy that strengthens the social, economic and organizational aspects of rural communities. This policy is essential for the availability and adoption of technologies by family farmers.


Adoption Evaluation of Black Pepper Cultivation with Live Gliricidia (Gliricidia sepium) Tutor in the State of Pará

Aldecy José Garcia de Moraes1, Enilson Solano Albuquerque Silva1, Everaldo Almeida do Nascimento2

1 Analysts - Embrapa Amazônia Oriental2 Researcher - Embrapa Amazônia Oriental

In the state of Pará, commercially valuable timber species were used intensi-vely s a wood tutor (dead tutor) for the cultivation of black pepper. The scarcity of these timber species resulting from disorderly logging and the requirements of environmental legislation has made it difficult to legally obtain high-durabi-lity native wood stick as a tutor for the cultivation of black pepper. Limiting the supply of dead tutor, in addition to raising its price, is leading to the reuse of used stations from distant locations and limiting the expansion of tutor-depen-dent species (MENEZES et al., 2013). As an alternative, Embrapa Amazônia Oriental has developed the technology of cultivating the black pepper with live gliricidia tutor, mainly used in small and medium producers properties. Thus, the objective of this paper is to evaluate the adoption of this technolo-gy in the state of Pará, from the estimation of its area, barriers, advantages and opportunities for adoption. For this purpose, data were collected from municipalities that had technology transfer actions by Embrapa and partner institutions, as well as on-site visits to the cultivation areas of black pepper with a live gliricidia tutor. The target audience interviewed were key informants from the staff of public and private institutions such as Emater-PA, municipal producers’ unions, municipal secretariats of agriculture, and other actors lin-ked to the black pepper production chain, in addition to farmers who adopt the technology. The estimated technology adoption area in 2018 was 114 hecta-res, representing a very small share, around 1%, of the technology’s share in the area harvested in the state of Pará, which totaled 15,683 hectares (IBGE, 2019). The following aspects can be listed as the main obstacles to the adop-tion of technology: little domain of the use of technology by the producer, especially about the management (implementation and conduction); difficulty in obtaining the live gliricidia tutor; socioeconomic and cultural characteristics of the producer, due to his experience or custom being essentially with the cultivation of black pepper in wood tutor, thus presenting some resistance to the use of living gliricidia tutor; difficulty in accessing technical assistance; and low technology diffusion. Advantages and opportunities for adoption include:

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reduction of the implantation cost (25% to 28%) of the black pepper hectare with live gliricidia tutor compared to the use of the dead wood tutor; environ-mental benefits related to improved soil quality and product quality as a result of reduced use of chemical inputs; and possibility of opening credit lines to stimulate adoption. Overcoming barriers and institutional efforts to intensify integrated technical assistance and technology transfer actions are necessary to enhance adoption and the resulting benefits.


Adoption of a Decision Support System for Coexistence of Extensive Livestock to the Pantanal Flood Dynamics: Related Factors

Carlos Roberto Padovani1, Alex Fernando de Araújo2, Renato Porfirio Ishii3, Guilherme Carvalho3, Hernandes Almeida3, Edson Takashi Matsubara3, Júlio Cesar

Dalla Mora Esquerdo4, Rogério Alves dos Santos Antoniassi21 Embrapa Pantanal, [email protected], Rua 21 de Setembro, 1880, Corumbá, MS2 Instituto Federal de Educação, R. Angelo Melão, 790 - Jardim das Paineiras, Três Lagoas - MS

3 Faculdade de Computação – Universidade Federal de Mato Grosso do Sul, Av. Costa e Silva, s/no, Bairro Universitário, Campo Grande - MS

4 Embrapa Informática Agropecuária, UNICAMP Universidade Estadual de Campinas -

Embrapa, Av. Dr. André Tosello, 209 - Cidade Universitária, Campinas - SP

Seasonality of Pantanal flooding, depending on the intensity and duration, can drastically reduce the food supply and even the death of livestock by starvation or drowning. In this context, the question that is asked each year is: what will be the magnitude of the rising of rivers and floods and when will this occur, so that cattle removal is necessary? There is a cost involved in the removal of livestock, so this decision should be supported by data that could best estimate the risk of extreme flood events. The Geohidro-Pantanal flood decision-making system is being refined to host three main components: 1 - Mapping and modeling of Pantanal flood dynamics by satellite imagery, 2 - Flood risk forecast modeling for Alerts and floods 3 - Communication of flood and flooded alerts from Internet communication tools, as well as media such as television and radio interviews. As a result of our experience with the system since 2013, we have listed some factors that negatively influence the adoption of digital technologies that make up the Pantanal decision-making alert system: 1 - Values based on beliefs, intuitions and empirical personal ex-perience. Little importance is given to scientific data and studies; 2 - Simplified production system based on practical income passed on from generation to generation; 3 - Because extraordinary events of rainfall and flooding occur less frequently and with a high degree of uncertainty, there is a tendency to focus on more and more desired ordinary and productive patterns and a “temporary forgetting” of extraordinary events. destructive and unwanted; 4 - The reading and interpretation of long technical texts and sophisticated gra-phics are not well understood and therefore are ignored. Maps that are more intuitive in understanding the information you want to share are more widely accepted; 5 - Many farmers know their own farm but ignore the geographical

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context in which their farm is located. Therefore, they do not include proces-ses that occur in the river basin and the Pantanal as a whole and influence their ownership. 6 - Technology transfer is not reaching all producers, or it is in an inadequate format. Considering that the global trend is for the increasing adoption of digital data technology and environmental systems for decision-making in optimizing agricultural and livestock production, we understand that we are on the right track on technology, but we still have a lot to do, to im-prove the factors linked to the adoption of these technologies in the Pantanal.


Adoption of Black Pepper Technology with Live Tutor of Gliricidia sepium in the Municipality of Castanhal, State of ParáEveraldo Nascimento de Almeida1, Aldecy José Garcia de Moraes2, Enilson Solano

Albuquerque Silva2, Oriel Filgueira de Lemos1

1 Researchers Embrapa Amazônia Oriental2 Analysts Embrapa Amazônia Oriental

The technology of the black pepper in association with live tutor of Gliricidia sepium was obtained in order to be an alternative that would increase gains in the pepper production system. In addition, the integration of the leguminous plant as a live tutor comes at an appropriate time, as legislation prohibits the use of dead tutor or big stakes, from lawful woods. The Gliricidia is a legumi-nous species, fixes nitrogen in the soil and thus reducing the input of chemical fertilizers in the system. Based on this premise, the research aimed to analyze the factors that affect the adoption of this productive consortium in areas of family farmers in the municipality of Castanhal, state of Pará.

To evaluate the tecnology adoption process was utilized the “Ambitec-adoption” tool. This method that evaluates the technology adoption process in the farmer’s perception is composed of 05 criteria and 38 indicators that are evaluated between numbers 0 to 1 which means: 0 = there was no con-formity and 1 = there was conformity. The information was collected from the Martins Family farm, it is 17 km from the center of the municipality. The te-chnology became known through the media, however, it was the information from other farmers that allowed the innovation to enter the rural property. The procedures of preservation, preparation of stakes and planting were obtained through Embrapa technical publications. In order to adjust technology to the production system, the following factors were decisive for adoption, namely: i. Tradition in agriculture; ii. Access to school; iii. Return of the results; iv. Land condition; v. Environmental legislation; vi. Manpower; vii. Availability of natural resources and; viii. Rural property location. The decision to continue the ex-periment was strongly linked to economic factors. However, the kilo of black pepper, which was already at the level of R$ 30.00 in 2015, followed decrea-ses. In 2017, it was sold in the region for R$ 7.50; and with a strong trend of low prices in the following years.

On the factors that limited the total adoption of innovation, were identified: i.

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Deficiency of rural technical assistance; ii. Seedlings unproductive and unheal-thy and; iii. Ant frequency in the productive system. The Martins family initiati-ve demonstrtes that it is possible to adopt innovations in production systems. However, the multiplication of these systems depends on a transfer strategy in which the actors assume their roles, not in a sectoral way, but in a context of institution / farmer interaction and continuity of the adoption process. In this continuity, the market component emerges as one of the most important, as well as him, other opportunities must be created to further enhance innovation in rural establishments in the peri-urban area of municipality of Castanhal and region.


SESSION 3 - Impacts of Technology Adoption

Impact Assessment of Technology Adoption Aiming the Transition Toward Sustainability in a Rural Establishment in Central Amazonia

Joanne Régis da Costa1, Geraldo Stachetti Rodrigues2

1 Embrapa Amazônia Ocidental2 Embrapa Meio Ambiente

The current agricultural production scenario emphasizes the sustainable use of natural resources, through the recognition, selection and adoption of envi-ronmental management practices. Management should aim at improving pro-ductive performance, adopting preventive and corrective measures to increa-se productivity, as well as conserving natural resources and preserving natural environments and biodiversity. These objectives should focus on the adoption of technologies according to the socio-environmental context and economic characteristics of rural communities and establishments, in their most diverse conditions and locations. In this sense, the present work refers to the analysis of social and environmental performance indicators of the practices and tech-nologies adopted at ‘Sítio Jardim do Eden’, a Reference Demonstration Unit of a technology transfer project dedicated to rural development actions at the APA Tarumã Açu / Tarumã Mirim (Embrapa Western Amazon, Manaus-AM). The study systematized the analysis of social and environmental impacts, according to the productive context observed since 2008, when a transition occurred from charcoal-making without environmental licensing, to the current production of foodstuffs, especially organic produce for trade, as well as do-mestic animals and vegetables for family consumption. The analysis applied the “System for Environmental Impact Assessment of Agricultural Technology Innovations” (Ambitec-Agro), a set of 148 indicators, organized into 27 crite-ria and seven aspects descriptive of social and environmental performance: (i) Technological efficiency, (ii) Environmental quality, (iii) Customer respect, (iv) Employment, (v) Income, (vi) Health and (vii) Management. The case study showed significant and positive changes in socio-environmental and economic performance at ‘Sítio Jardim do Éden’ (index = 6.91, on a ±15 mul-ticriteria scale), with productivity gains and production diversification resul-ting in important improvements in the family’s food security. Compared to the

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coal-making that occurred 10 years ago, the present productive context has brought advances in issues of environmental and collective interest, in terms of favorable direct and indirect land use changes, reduction of greenhouse gas emissions to the atmosphere, as well as expansion in community par-ticipation and enhancement in social capital. Improvements have been ob-served mainly in terms of private interests, such as income generation and property value, quality of working conditions, and occupational safety and health. Gender and generation equity is emphasized, given emancipation and reward for the engagement of wife and children; besides adequate conditions of commercialization, as well as recycling and reuse of organic residues in favor of production. Improvement s were also observed in the ‘Management’ aspect, with emphasis on the dedication and profile of those responsible for the establishment, dedicated to improving the planning mechanisms for pro-ductive activities and financial management in the short, medium and long term. The results of this analysis of sustainability indicators provided the basis for decision making, in order to improve current management practices and technology adoption, appropriate to the local productive context.


Are Extracts of Algae an Innovative Technique to Enhance Soybeans Productivity?

Cesar Heraclides Behling Miranda1, Simone Palma Favaro1

1 EMBRAPA Agroenergia. PqEB s/n, 70770-901, Brasília, Brazil

There is a growing demand for innovative products that may enhance plant productivity. Producers can find in the market a plentiful of novel products to fulfill these expectations, such as foliar fertilizers packed with a variety of compounds other than common macro and micronutrients (amino acids, hu-mic and fulvic acids, phosphine, and algae extracts, for example). The use of algae extracts, for this purpose in particular, is in full bloom. It is reported here the results of a field evaluation made in a farm that set up an empirical experi-ment to check out the possible benefits of foliar fertilizers containing algae ex-tracts. Farmer asked for technical assistance to collect information in his field that would allow him to make decision whether this is indeed an innovative practice. The farm is located in São Gabriel de Goiás, Planaltina, Goiás. The locally recommended soybean variety Desafio was cropped using recommen-ded agronomic practices regarding soil preparation, basal fertilization, seed inoculation and adequate plant population. Sowing was done in December 27, 2018, in a 10 ha area, with plant emergency completed by January 4, 2019. In February 10, 2019, during the flowering stage, a mixture of commer-cial products containing algae extracts (Dimiagro FIT, 30mL.ha-1; Dimiagro Complexo, 500 mL.ha-1, and DimiPremium Gold, 1.5 L.ha-1) was sprayed into 27 m wide strips, perpendicularly to the planting rows. A 27 m wide non-spra-yed strip separated every sprayed strip, with replications covering the whole field. During harvesting (March 29, 2019), 12 plots (replications) were organi-zed within randomly selected sprayed and non-sprayed strips, encompassing three meters long of five planting lines (2.25 m wide). All plants in the plot were counted, harvested and weighed. The number of pods per plant, number of grains per pod and the weight of 1000 grains were registered from a subsam-ple of 60 plants taken randomly within every plot. Spraying foliar fertilizer con-taining algae extracts improved significantly (p<0,001) the productivity (4539 kg.ha-1, while the non-sprayed areas produced 3941 kg.ha-1), although there was no significant differences (p>0,05) in the other measured parameters (37 and 34 pods per plant for sprayed and non-sprayed areas; 2,5 grains per pod, respectively; and 213 and 203 g per 1000 grains, respectively). This gain represents almost a 10 bags benefit for the farmer. Since the overall costs of

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using the technology is four bags, gains are six bags per hectare. The farmer is quite happy with these results and keen to go along with the technology, as well as to spread the word among his peers. However, the results do not allow concluding that the extracts of algae are the sole cause of such benefits, since they were mixed with macro and micronutrients and provided as foliar fertilizer. The true answer demands a more scientific approach, comparing their single and mixed effects, either in the field or under controlled conditions.


Exchanging Experiences and Learning on the Effects of the Hemiparasitic Striga asiatica in Brazilian Upland Rice Varieties Introduced in Mozambique

Cesar Heraclides Behling Miranda1, Simone Palma Favaro1

1 EMBRAPA Agroenergia. PqEB s/n, 70770-901, Brasília, Brazil

International cooperation programs in agriculture are a good chance for in-terchange of information and exchange of experiences regarding agricultu-ral problems that could be unknown to any partner. During the introduction of five upland rice varieties originated from Brazil (Primavera, Sertaneja, Pepita, Serra Dourada and Esmeralda) in Nampula Province, northeast of Mozambique, it was observed that some plants in the field were infested with Striga asiatica (Striga) locally known as “pequeno-feiticeiro” (small-witch). This is a hemiparasitic plant that infects cereals such as maize, sorghum and rice, as well as grasses such as Brachiaria, causing losses varying from 20% to 100% of their economic value. In 2014, a controlled experiment was devi-sed to better understand how much such parasitism could be deleterious to these varieties. All rice materials, plus three landraces from Cabo Delgado Province, were sown in pots with 10 Kg of a local quartz-sandy soil collected from an area where maize and the rice variety Sertaneja were infested with Striga the previous year. Striga is very proliferous, producing up to 100,000 seeds per plant. Ten rice plants were left per pot after germination, with 16 replications for every treatment. Experiment was run under controlled condi-tions, disposed in a completely randomized block design. Eight replications of every treatment were cleared of any growing Striga pods since its appearance above-ground (Striga controlled treatment), while in another eight replications Striga emergence and growth were free (Striga non-controled treatment). Emergent Striga pods were counted at 20, 40 and 85 days after rice ger-mination, when both rice plants and Striga were harvested, separated, and dried. Rice above-ground and root biomass were recorded. All varieties and local landraces were infected by Striga, although local landraces were faster infected. There was negative Pearson correlations between Striga dry mass and rice total (-0.69 p<0.001), roots (-0.57 p<0.05), and above-ground (-0.68 p<0.001) dry mass, indicating that the parasite effectively drives large part of the plant energy for its own growth. Variety Primavera showed a slower infection and produced significantly (p<0.05) higher biomass than all other va-rieties, despite being also strongly affected by Striga. Rearing Striga pods was

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not suffice to avoid its deleterious effect, confirming that most of the damage is made before the parasite pods emerge to produce flowers and seeds. This exchange of experience allowed Mozambicans to learn that it is possible to crop upland rice in the Nampula area, while Brazilian researchers learned that their varieties are susceptible to this dangerous weed. Variety resistance is the more suitable way to go along with Striga. It could be highly damaging if it is wrongly introduced in Brazil, where ecological conditions are quite similar to those where it is commonly found, in Africa and Asia. Striga is actually present in North America (Florida, North and South Carolina) and Guyana.


Case: Evaluation of Rotational Grazing Stocking AdoptionSergio Rustichelli Teixeira1, Carlos Augusto de Miranda Gomide1, Domingos Sávio

Campos Paciullo1, Mirton José de Frota Morenz1

1 Researchers, Embrapa Dairy Cattle, Juiz de Fora/MG

Problem statement – Rotational grazing enables better forage utilization and increased stocking rate. However, such benefits will only be achieved with proper grazing management. Embrapa Dairy Cattle has been studying pasture management using rotational grazing stocking since 1980 and has Technology Transfer (TT) activities, such as the Zootechnical Residency Program (ZR). At the ZR students from agricultural schools receive training based on the concept of “Learning by Doing ” for 12 months. But what is the perception of these technicians regarding the adoption of this technology and its approach?

Objective – To evaluate the adoption of rotational grazing stocking and how the technology is treated in the field.

Method – It was predominantly qualitative interviewing technicians. In the first step telephone interviews were conducted to select RZ graduates from the Southeast and South Brazilian regions. Data were used to select technicians for the second step, which were semi-structured face-to-face interviews with selected technicians, farmers that were assisted by technicians and super-visors of the technicians. In the final step, a Focus Group Meeting (FGM) was held, including some interviewed technicians, researchers from Embrapa Dairy Cattle and representatives of technical schools in agriculture. In the interview steps, the demands, difficulties and solutions to encourage the use of rotational grazing stocking were asked, in order to evaluate the adoption of the technology.

Results – Twenty one main demands were identified, usually related to the re-duction of production cost. Farmers seek to increase pasture productivity and intensify production. Seventeen difficulties were cited, such as the lack of soil analysis for pasture cultivation. However, when they plant corn and soybeans, the farmer does the soil analysis. Difficulties include lack of understanding of paddock sizing, wrong number of animals in relation to the amount of fodder it produces, lack of fertilization and dry season forage planning, difficulty in dividing and rotating adequate paddocks and adjusting the height of cattle

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entrance and out. In addition, there is a lack of well-trained technicians inclu-ding the proper machinery for the region topography. One Southeast a farmer mentioned that the difficulty is related to the implementation cost. The thirteen solutions presented focused on the implementation of Demonstration Units (DU) on rotational grazing associated with Field Days, the egress persistence to deploy the technology, working the farmer’s emotional showing studies and successful situations.

Implications – The biggest difficulties in technology adoption are prior to ma-naging rotational grazing stocking technology, for example, lack of soil analy-sis. There is a need for both awareness of the usefulness and return of tech-nology and training of technicians to help the farmers.

Acknowledgments – To Embrapa Dairy Cattle for the support during the pro-ject, to the project team for their cooperation in the FGM, to the graduates of the Zootechnical Residency, to farmers, technicians supervisors and teachers of the technical school for their participaion in interviews and meetings.


Adoption of Dual-Purpose Wheat in Integrated Crop-Livestock Systems in Southern Brazil

Renato Serena Fontaneli1, Giovani Stefani Faé2, Adão da Silva Acosta2

1 Researcher, Embrapa Wheat2 Analyst, Embrapa Wheat

The most important winter cereal in Southern Brazil is wheat, followed by oats and barley. However, in this region, the winter cereals uses only about 20% of the area cultivated with soybean and corn in the summer. Thus, there is close to 80% of the cultivated area in the summer still available to increase grain production in the winter, or in the crop-livestock systems.

Aiming to optimize the use of the available areas during winter season, Embrapa Wheat maintains a dual-purpose wheat breeding program that re-leases annually new cultivars that allow grazing in late autumn/winter, and a successive grain production ranging from 1,500 to 4,500 kg/ha. Several technological reference units followed by field days were carried out in mul-tiple regions of Southern Brazil.

The initiative was made possible by the partnership of Embrapa, Emater, Sementes Cometa, SENAR, Milk Cooperatives, seed producers and local leaderships that allowed the adoption of the technology to grow by numerous voices. Since the beginning of the program, six dual-purpose wheat cultivars were released. Today, the cultivars BRS Tarumã and BRS Pastoreio are wi-dely adopted with an estimated cultivated area of 15-20% of the total area cultivated with wheat. The regions with greater adoption of the technology are the north of Rio Grande do Sul state, west of Santa Catarina state and south-west of Paraná state.

The adoption of the dual-purpose wheat cultivars took place for several reasons. First, there is a great lack of high quality fodder for milking ows at a lower cost than corn silage and hay. Second, the forage and grain production potential of the cultivar BRS Tarumã were easily perceived by the farmers that tested the technology. Third, the organization of technical trainings with researchers, extension agents, seed producers and farmers allowed the expansion of its adoption. Currently, more than 300,000 ha are used with dual-purpose wheat varieties in Brazil. Even though most

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farmers plant their own harvested seed every year, there is great potential to increase the adoption of this technology in the region.


BRS 5601RR: A Success Case of Soybean Cultivar Adoption in Southern Brazil

Vladirene Macedo Vieira1, Adão da Silva Acosta1, Lisandra Lunardi1, Paulo Bertagnolli2

1 Analyst, Embrapa Wheat2 Researcher, Embrapa Wheat

Rio Grande do Sul State, Brazil, cultivated 5.8 million hectares of soybean in 2018/2019. It is estimated that 90% of total seed marketed is dominated by six soybean breeding companies, and the proportion of RR cultivars and Bt cultivars is approximately 40 and 60%, respectively. The seed usage rate is around 40% in Rio Grande do Sul State. The number of available cultivars is 134, and the participation of Embrapa cultivars, which was null in recent years, represents 6% of formal market today. The BRS 5601RR was respon-sible for this change by combining three decisive aspects: agronomic cha-racteristics, appropriate validation strategy, and favorable conditions of use. The cultivar has high yield potential, early cycle, upright and compact plant architecture, and root diseases resistance. In 2015, 87 tons of genetic seed were released to 19 seed producers, representing 61% of the validation sites. This final stage of the technological development process brought Embrapa Wheat closer to seed producers, and allowed them to be familiar with the cultivar before its release date. Thus, its agronomic characteristics, techno-logy transfer strategies and the volume of seed offered to seed producers promoted a wide acceptance by farmers and favored the broad seed licensing process, encouraging the cultivar adoption. The number of licensed seed pro-ducers of the cultivar continues to grow. There were 21 in 2015/2016, 25 in 2016/2017, 27 in 2017/2018 and 36 in 2018/2019, reaching 70% of soybean seed producers in Rio Grande do Sul in the last cropping season. In addition, the cultivar records a high number of declarations of saved seed production for own use. The estimated cultivated area with BRS 5601RR was 12,000, 104,000 and 256,000 hectares in the 2016/2017, 2017/2018 and 2018/2019, respectively, considering the estimate of commercialization from registered areas for seed production, sowing density of 60 kg/ha and seed usage rate of 41%. In 2019/2020 it is estimated that seed availability is sufficient to sow 400 thousand hectares. Another favorable feature for its adoption is related to the lower seed cost of RR cultivars in relation to other technologies, since there is no more collection of royalties, resulting in greater economic return to far-

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mers. In addition, few soybean breeding companies have maintained their RR programs, which makes room for companies with competitive cultivars that still maintain this technology, such as Embrapa. Another potential use of RR cultivars is the refuge area, indicated to compose 20% of Bt soybean areas. The BRS 5601RR performance repositioned Embrapa as a soybean genetic supplier in Rio Grande do Sul state, and this cultivar is being considered one of the best RR options on the market for its relative maturity group.


Economic and Socio-Environmental Impacts of the Alelo Vegetal System

Maria Clara da Cruz de Melo1, Silvia Satiko Onoyama Mori1, Gilberto Hiragi1, Ivo Roberto Sias Costa1

1 Embrapa Recursos Genéticos e Biotecnologia

This work aims at presenting the economic and socio-environmental impacts of the Alelo Vegetal System that functions as a digital portal for information on plant genetic resources which were previously stored mainly in Excel spread-sheets and logbooks. The impact assessment used the AMBITEC methodo-logy developed by Brazilian Agriculture Research Corporation - Embrapa. Information was obtained through interviews with 13 germplasm bank curators and additional data were sent by the team responsible for the development of the Alelo Vegetal. The main economic impacts can be considered to be re-lated to the reduction in the cost of working hours in providing information on germplasm banks and in accessing this information. The main socio-environ-mental impacts are: increasing of energy consumption to store computational information, biodiversity conservation and environmental recovery through better availability and quality of information on vegetal genetic resources and improved dedication to managing data on plant genetic resources.

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1st ISATA – International Symposium on Agricultural