Made available in DSpace on 2016-06-02T19:50:28Z (GMT). No. of bitstreams: 1 TeseWLL.pdf: 1443344 bytes, checksum: c7a60d454aff1d1a92e0c0f63c0688ac (MD5) Previous issue date: 2005-06-17 / Universidade Federal de Sao Carlos / This thesis proposes a learning and decision making tool in order to compensate deficiencies related to management activities performed by family farmers managers. The main objective of this thesis is to develop a model of integrated management for family based agriculture. The model integrates different management modules in one shared model. The theoretical structure that supported the research was Family Based Agriculture, Production Systems, Rural Management, Management Systemic Approach, Balanced Scorecard and System Dynamics. The research included an empirical research that supported the diagnostic about the level of management adopted by a group of family based farmers. Based on the diagnostic, it was possible to identify the most important variables in the management process of the rural business. The interdependency of the variables was drawn, resulting in the conceptual model for family based agriculture. Then, this model was translated into a mathematical (operational) language by the means of an adequate methodological tool, resulting in a management simulator. Since different approaches and management tools are included in the simulator, it can be useful for the decision making process regarding business process in family based proprieties. It can also be used by technical assistants, farmers' organization leaders and even financial agents in order to plan, guide and diffuse the business integrated management culture among the farmers and its importance for the satisfactory performance of the productive unit. / Buscando suprir deficiências em atividades de gestão por parte de administradores rurais familiares, essa tese propõe uma ferramenta de aprendizagem e auxílio à tomada de decisão. O objetivo foi desenvolver um modelo de gestão integrada para a agricultura familiar, que integra diferentes módulos de gestão em um único modelo compartilhado. Foram abordados os seguintes marcos teóricos e conceituais: Agricultura Familiar, Sistemas de Produção, Administração Rural, Abordagem Sistêmica da Administração, Balanced Scorecard e Dinâmica de Sistemas. Este trabalho contou com uma pesquisa empírica, que subsidiou a elaboração de um diagnóstico sobre o nível de gestão de um grupo de agricultores familiares. A partir deste diagnóstico, foi possível identificar as variáveis mais relevantes do processo de gestão destes empreendimentos. A interdependência destas variáveis foi, então, desenhada, constituindo-se no modelo conceitual de gestão integrada para a agricultura familiar. Em seguida, tal modelo foi traduzido para uma linguagem matemática (operacional) através de uma ferramenta metodológica adequada, transformando-se em um simulador gerencial. A partir das diversas abordagens e ferramentas de gestão, esse simulador poderá auxiliar o usuário a tomar decisões acerca dos processos de negócio da sua propriedade. Também permitirá à assistência técnica (extensionistas), aos dirigentes de organizações de produtores, e mesmo aos agentes financeiros, planejar, orientar e difundir junto aos produtores uma cultura de gestão integrada da propriedade, e a importância da mesma para o bom desempenho da unidade de produção.

As ações conjuntas vêm sendo adotadas por vários segmentos produtivos visando desempenho e competitividade dos empreendimentos para garantir a presença em mercados mundiais. O agronegócio tem importância no processo de desenvolvimento econômico do Brasil como um todo e do Estado do Rio Grande do Sul pela sua capacidade de geração de riquezas, criação de empregos, transferência e circulação de renda, desenvolvimento de novas tecnologias, pesquisas e desenvolvimento da ciência em geral. Estudos também avaliam o potencial das parcerias rurais, enfocando cinco capitais como categorias de ativos que interferem na formação de parcerias, pois é de grande importância a compreensão dos produtores rurais sobre a estreita relação entre a expansão dos bens de capital e a capacitação organizacional. O problema verificado na presente pesquisa refere-se ao processo de formação de estratégias conjuntas no processo de criação de ovinos em escala local, originando a questão-problema que conduziu a pesquisa: Quais os principais fatores de produção (capitais) que contribuem e que limitam o processo de formação de estratégias conjuntas visando à ampliação da capacidade de produção e a competitividade? O estudo teve por objetivo analisar estes fatores. Para isso, foi utilizado o método de investigação de natureza qualitativa e descritiva, a fim de apreender as características do fenômeno e projetar possíveis melhorias no processo proporcionando uma nova visão do problema. A investigação teve início a partir da literatura originária dos diversos autores com estudos relacionados à formação de estratégias conjuntas. Foram definidas categorias de análise baseadas na avaliação de fatores de produção, denominados de capitais humano, financeiro, natural, social e físico. A região selecionada para o desenvolvimento do estudo abrange as cidades de Santa Maria, São Pedro do Sul, Dilermando de Aguiar e São Martinho da Serra, no Estado do Rio Grande do Sul, com uma população-alvo constituída de produtores de pequeno porte na produção de ovinos de lã e de corte. Foram aplicadas entrevistas semi-estruturadas como instrumento de coleta de dados. Os resultados encontrados evidenciaram que os produtores apresentam potencial capacidade de desenvolver estratégias conjuntas, com estrutura suficiente para obter eficiência, sendo os fatores de convivência, os quais estão relacionados ao capital social, considerados como os indutores do processo. O estudo evidenciou ainda falta de entendimento e compreensão dos pesquisados com as questões relativas às preocupações ambientais. / Joint actions are being taken by many productive segments targeting performance and competitiveness of projects to ensure its presence in world markets. Agribusiness has importance economic development process in Brazil\'s as a whole and the State of Rio Grande do Sul for its ability to generate wealth, create jobs, transference and circulation of income, development of new technologies, research and development of science in general. Studies also evaluate the potential of rural partners, focusing on five capitals as asset categories that interfere in the formation of partners, it is very important to understand the rural farmers about the close relationship between the expansion of capital assets and organizational skills. The problem encountered in this study refers to the formation of joint strategies in the process of sheep farming on a local scale causing the problem-question who led the research : What are the main factors of production (capital) which contribute and which limit the process of formation of joint strategies aimed at expanding of production capacity and competitiveness? The study aimed to analyze these factors. For this, we used the method of investigation of qualitative and descriptive in nature, a view to apprehend the characteristics of the phenomenon and projecting possible improvements in the process by providing a new view of the problem. The investigation began from the literature of the different authors with studies associated to the formation of joint strategies . were defined categories of analysis based on the evaluation of factors of production, called human capital, financial, natural, social and physical . The region selected for the development of the study includes the cities of Santa Maria, São Pedro do Sul, Dilermando de Aguiar and São Martinho da Serra in the state of Rio Grande do Sul, with a target population consists of small producers in the production of sheep wool and cutting. Semi-structured interviews were applied as a tool for data collection. The findings results indicated that producers have the potential capacity to develop joint strategies, with structure large enough to achieve efficiency, and the cohabitation factors, which are related to the social capital, considered as inducers of process. The study also revealed a lack of understanding and comprehension of respondents with issues related to environmental concerns.

Although data collection through discrete choice experimentsconducted using surveys are commonly used in research, aimingto improve data quality is still serviceable and necessary. Three distinct experiments were conducted with the objectives of improving data quality by better tailoring experiments to market conditionsas well as decreasing complexity and fatigue. First, consumer willingness-to-pay(WTP) for yogurt attributes was estimatedusing a survey targeted to be nationally representative of the US.A novel approach was used to allow for self-selection into the choice experiment for commonly purchased types of yogurt.On average, respondentswere willing-to-paya positive amount for requiring pasture access and not permitting dehorning/disbudding for both traditional and Greek yogurt. Respondents had positive WTPfor Greek yogurt labeled free of high fructose corn syrup, and were willing-to-pay morefor low-fat yogurt when compared to nonfat for both yogurt types.<div><br></div><div> Second, anew WTP data collection method, employing component discrete choice experiments in place of traditional larger experimental designs,was proposedand compared to the traditional method to elicit yogurt consumer’s WTP for attributes in yogurt. The new WTP data collection method was designed with the objective of decreasing complexity by having respondents participate in fewer choice scenarios. Incidences of attribute non-attendance (ANA), a potential simplifying heuristic that results from complexity, occurred less frequently for all attributes in the new WTP data collection method with one exception. Exhibiting ANA for any attribute was negatively correlated with the time respondents took to complete the choice experiment.<br></div><div><br></div><div>Finally, through the use of a newbest-worst scaling(BWS)data collection method,consumer preferences for fluid dairy milk attributes were elicited and results as well as measures of data quality were compared to the traditional method of BWS. Nine attributes of fluid milk were included in this study: container material, rbST-free, price, container size, fat content, humane handling of cattle, brand, required pasture access for cattle, and cattle fed an organic diet. The top (price) and bottom (container material) attributes in terms of relative ranking did not change between the new BWS data collection method and the traditional BWS method. The new BWS data collection method resulted in fewer incidences of ANA for all attributes except one. There was not a statistical difference in the number of transitivity (an axiom of consumer theory) violators,between the new and traditional BWS methods.<br></div>

<p dir="ltr">The expected rapid development of renewable energy in the United States has raised concerns about its effects on farmland prices, yet there is little empirical evidence on the impact of solar energy development on farmland prices. This study aims to examine the heterogenous impact of commercial and utility-scale solar energy on farmland prices in Indi- ana. Drawing on farmland transactions from 2015 to 2020, we employ quantile and expectile hedonic price regressions to estimate the heterogeneous impact of proximity to solar energy facilities across the conditional price distribution. This study finds an inverse, non-linear relation between the proximity to solar energy and per acre land prices. We find that solar farms provide a premium to neighboring farmland parcels. However, this premium is heterogenous, with higher premiums on parcels with higher conditional prices. As we move across the higher conditional expectiles, we observe a price drop ranging from 0.8% (0.1 expectile) to 1.8% (0.9 expectile) for an additional mile increase from neighboring solar farms. Similarly, price premium for a proximity to solar energy is as high as 2.1% for 99th expectile farmland price. Thus, policymakers should consider the effect of solar energy to avoid potential damage on agricultural production and land price movements.</p>

The complex co-evolutionary systems approach -CCeSA - provides a well-suited framework for analysing agricultural systems, serving as a bridge between physical and socioeconomic sciences, alowing for the explaination of phenomena, and for the use of metaphors for thinking and action. By studying agricultural systems as self-generated, hierarchical, complex co-evolutionary farming systems - CCeFSs -, one can investigate the interconnections between the elements that constitute CCeFSs, along with the relationships between CCeFSs and other sytems, as a fundamental step to understanding sustainability as an emergent property of the system. CCeFSs are defined as human activity systems emerging from the purposes, gestalt, mental models, history and weltanschauung of the farm manager, and from his dynamic co-evolution with the environment while managing the resources at his hand to achieve his own multiple, conflicting, dynamic, semi-structured, and often incommensurable and conflicting purposes while performing above thresholds for failure, and enough flexibility to dynamically co-evolve with its changing biophysical and socioeconomic environment for a given future period. Fitness and flexibility are essential features of sustainable CCeFSs because they describe the systems' dynamic capacity to explore and exploit their dynamic phase space while co-evolving with it. This implies that a sustainable CCeFS is conceived as a set of dynamic, co-evolutionary processes, contrasting with the standard view of sustainability as an equilibrium or steady-state. Achieving sustainable CCeFSs is a semi-structured, constrained, multi-objective and dynamic optimisation management problem, with an intractable search space, that can be solved within CCeSA with the help of a multi-objective co-evolutionary optimisation tool. Carnico-ICSPEA2, a co-evolutionary navigator - CoEvoNav -used as a CCeSA's tool for harnessing the complexity of the CCeFS of interest and its environment towards sustainability, is introduced. The software was designed by its end-user - the farm manager and author of this thesis - as an aid for the analysis and optimisation of the San Francisco ranch, a beef cattle enterprise running on temperate pastures and fodder crops in the Central Plateau of Mexico. By combining a non-linear simulator and a multi-objective evolutionary algorithm with a deterministic and stochastic framework, the CoEvoNav imitates the co-evolutionary pattern of the CCeFS of interest. As such, the software was used by the farm manager to navigate through his CCeFS's co-evolutionary phase space towards achieving sustainability at farm level. The ultimate goal was to enhance the farm manager's decision-making process and co-evolutionary skills, through an increased understanding of his system, the co-evolutionary process between his mental models, the CCeFS, and the CoEvoNav, and the continuous discovery of new, improved sets of heuristics. An overview of the methodological, theoretical and philosophical framework of the thesis is introduced. Also, a survey of the Mexican economy, its agricultural sector, and a statistical review of the Mexican beef industry is presented. Concepts such as modern agriculture, the reductionist approach to agricultural research, models, the system's environment, sustainability, conventional and sustainable agriculture, complexity, evolution, simulators, and multi-objective optimisation tools are extensively reviewed. Issues concerning the impossibility of predicting the long-term future behaviour of CCeFSs, along with the use of simulators as decision support tools in the quest for sustainable CCeFSs are discussed. The rationale behind the simulator used for this study, along with that of the multi-objective evolutionary tools used as a makeup of Carnico-ICSPEA2 are explained. A description of the San Francisco ranch, its key on-farm sustainability indicators in the form of objective functions, constraints, and decision variables, and the semi-structured, multi-objective, dynamic, constrained management problem posed by the farm manager's planned introduction of a herd of bulls for fattening as a way to increase the fitness of his CCeFS via a better management of the system's feed surpluses and the acquisition of a new pick-up truck are described as a case study. The tested scenario and the experimental design for the simulations are presented as well. Results from using the CoEvoNav as the farm manager's extended phenotype to solve his multi-objective optimisation problem are described, along with the implications for the management and sustainability of the CCeFS. Finally, the approach and tools developed are evaluated, and the progress made in relation to methodological, theoretical, philosophical and conceptual notions is reviewed along with some future topics for research.

The pressure on the public agricultural extension organisation in Ghana to improve its responsiveness to meet the needs of farmers has increased since the globalisation of trade in the early 1990s. To improve agricultural productivity and the livelihood security of farm households, the Ministry of Food and Agriculture in Ghana decentralised its extension service in 1997. Although this was a critical change in agricultural policy, the extension service has struggled to implement this policy effectively. Further improvement in the situation is hampered because there has been little research published in this area. To provide this understanding, a single-case study of a successful decentralised district level extension organisation in Ghana was used to identify the factors, processes and outcomes that contribute to its performance. The case organisation is an example of a district agricultural extension organisation that operates under a decentralisation system at the level of deconcentration, with a high farmer-to-extension agent ratio and limited and uncertain levels of Government funding. The results of the study emphasised the importance of the effects of both external and internal (or organisational) factors on the performance of the case organisation. The external factors included: (1) the political will to decentralise, (2) the level of decentralisation of other government departments, (3) the provision of a clear legal framework for decentralisation and (4) the existence of established institutions that are willing to support the decentralisation process. New external factors that were identified in this study were (1) the type and drivers of decentralisation, (2) stakeholders' willingness and commitment to support the decentralisation process and (3) the community characteristics in terms of land tenure arrangements and gender roles. The results confirmed the importance of the organisational factors prescribed in the literature: (1) stakeholder participation, (2) managerial and technical capacity, (3) operational funding and (4) accountability. However, the study also identified five other interrelated organisational factors that influenced the success of the case organisation that had not been previously reported in the literature. These included the needs to: (1) develop a needs-based extension programme, (2) expand the extension service focus and roles, (3) foster a cross-sector pluralistic extension approach (4) use needs-based groups for service delivery, and (5) extension staff attitudinal change. Multistakeholder (farmer and other organisations) participation was critical for the development of a needs-based extension programme. The case organisation had modified the traditional extension programme planning process to involve stakeholders at different levels of participation. Similarly, the case organisation involved stakeholders in its multilevel monitoring and evaluation processes. Stakeholder participation in planning and evaluation, although aimed ultimately at efficient and effective programme implementation and improvement, did enhance accountability. Because the case organisation had taken on a broader livelihood security focus to extension, the definition of farmer needs was extended to encompass on-farm and off-farm needs that have impact on the contribution agriculture makes to the livelihood security of farm households in the district. This broader livelihood security focus to extension required the case organisation to take on additional roles from those it traditionally held. In the study, a typology of such roles was developed and a role selection process used by the case organisation during its programme planning process was described. Similarly, because of this broader focus, the case organisation had to work both across sectors and with other extension providers from within the sector to meet the needs of farmers. Again, the multistakeholder programme planning process was central to fostering coordination and collaboration amongst the various extension providers in the district. Decentralisation has placed greater managerial responsibility on management staff of the case organisation. In addition, the livelihood security focus has required technical staff and attitudinal changes to develop and seek for a much broader range of skills and knowledge - meaning that the development of both managerial and technical capacity was important for the case organisation. Needs-based training, the development of a learning environment and the enhancement of staff motivation were critical for the development of staff capacity. As with other extension organisations in developing countries, the funding for the case organisation was limited and uncertain. To overcome these constraints, the case organisation had in place mechanisms to ensure its resources were used efficiently and that it could mobilise additional resources from outside the organisation. Resource efficiency was improved through an intensive monitoring system and the use of stable needs-based groups. Additional resources were mobilised by lobbying government and international donors for funds for projects that would meet the needs of farmers. Further resources were obtained through collaboration with other stakeholder organisations. Again, the multistakeholder planning process provided a platform for collaboration. Networking and special issue forums also provided mechanisms for enhancing collaboration within the district. Decentralisation was introduced into Ghana in 1997 with the aim of eventually developing a demand-driven extension system. Although viewed as successful, the case organisation has yet to achieve the level of farmer participation (i.e. self-mobilisation) that is required for a demand-driven extension system. Currently, after six years of decentralisation, the level of farmer participation can be classified as somewhere between consultation and collaboration. Therefore, the results of this study suggest that the transition from a top-down to a demand-driven extension system will take considerable time and resources.

The complex co-evolutionary systems approach -CCeSA - provides a well-suited framework for analysing agricultural systems, serving as a bridge between physical and socioeconomic sciences, alowing for the explaination of phenomena, and for the use of metaphors for thinking and action. By studying agricultural systems as self-generated, hierarchical, complex co-evolutionary farming systems - CCeFSs -, one can investigate the interconnections between the elements that constitute CCeFSs, along with the relationships between CCeFSs and other sytems, as a fundamental step to understanding sustainability as an emergent property of the system. CCeFSs are defined as human activity systems emerging from the purposes, gestalt, mental models, history and weltanschauung of the farm manager, and from his dynamic co-evolution with the environment while managing the resources at his hand to achieve his own multiple, conflicting, dynamic, semi-structured, and often incommensurable and conflicting purposes while performing above thresholds for failure, and enough flexibility to dynamically co-evolve with its changing biophysical and socioeconomic environment for a given future period. Fitness and flexibility are essential features of sustainable CCeFSs because they describe the systems' dynamic capacity to explore and exploit their dynamic phase space while co-evolving with it. This implies that a sustainable CCeFS is conceived as a set of dynamic, co-evolutionary processes, contrasting with the standard view of sustainability as an equilibrium or steady-state. Achieving sustainable CCeFSs is a semi-structured, constrained, multi-objective and dynamic optimisation management problem, with an intractable search space, that can be solved within CCeSA with the help of a multi-objective co-evolutionary optimisation tool. Carnico-ICSPEA2, a co-evolutionary navigator - CoEvoNav -used as a CCeSA's tool for harnessing the complexity of the CCeFS of interest and its environment towards sustainability, is introduced. The software was designed by its end-user - the farm manager and author of this thesis - as an aid for the analysis and optimisation of the San Francisco ranch, a beef cattle enterprise running on temperate pastures and fodder crops in the Central Plateau of Mexico. By combining a non-linear simulator and a multi-objective evolutionary algorithm with a deterministic and stochastic framework, the CoEvoNav imitates the co-evolutionary pattern of the CCeFS of interest. As such, the software was used by the farm manager to navigate through his CCeFS's co-evolutionary phase space towards achieving sustainability at farm level. The ultimate goal was to enhance the farm manager's decision-making process and co-evolutionary skills, through an increased understanding of his system, the co-evolutionary process between his mental models, the CCeFS, and the CoEvoNav, and the continuous discovery of new, improved sets of heuristics. An overview of the methodological, theoretical and philosophical framework of the thesis is introduced. Also, a survey of the Mexican economy, its agricultural sector, and a statistical review of the Mexican beef industry is presented. Concepts such as modern agriculture, the reductionist approach to agricultural research, models, the system's environment, sustainability, conventional and sustainable agriculture, complexity, evolution, simulators, and multi-objective optimisation tools are extensively reviewed. Issues concerning the impossibility of predicting the long-term future behaviour of CCeFSs, along with the use of simulators as decision support tools in the quest for sustainable CCeFSs are discussed. The rationale behind the simulator used for this study, along with that of the multi-objective evolutionary tools used as a makeup of Carnico-ICSPEA2 are explained. A description of the San Francisco ranch, its key on-farm sustainability indicators in the form of objective functions, constraints, and decision variables, and the semi-structured, multi-objective, dynamic, constrained management problem posed by the farm manager's planned introduction of a herd of bulls for fattening as a way to increase the fitness of his CCeFS via a better management of the system's feed surpluses and the acquisition of a new pick-up truck are described as a case study. The tested scenario and the experimental design for the simulations are presented as well. Results from using the CoEvoNav as the farm manager's extended phenotype to solve his multi-objective optimisation problem are described, along with the implications for the management and sustainability of the CCeFS. Finally, the approach and tools developed are evaluated, and the progress made in relation to methodological, theoretical, philosophical and conceptual notions is reviewed along with some future topics for research.

Value-added (VA) technologies can help farmers in the specialty crop industry generate new products, increase off-season income sources, expand market access, and improve overall profitability. These technologies can support the development of rural economies through the generation of new businesses and job creation. The USDA defines VA products as those 1) changed physical, 2) produced in a manner that enhances their value, and 3) physically segregated in a manner that results in enhancement of their value. Drawing from this definition, this study investigated VA technologies such as drying, cutting into customer-ready portions, washing and labeling specialty crops. The objectives of this study are threefold. First, we analyze how market access and diversification drive specialty crop farmers to adopt VA technologies. Second, we address the potential endogeneity between the adoption of VA technologies (vertical diversification) and the number of crops (horizontal diversification). Lastly, we investigate how market access drives farmers to utilize food labels for VA products. Data for this study came from a 2019 web-based survey of specialty crop farmers. A total of 766 farmers completed the survey, with a response rate of 21.5%. The questionnaire included questions related to farmer’s demographics (i.e., educational attainment, gender, farming experience), farm characteristics (i.e., crops, markets, and growing technologies), and farmers’ beliefs regarding their farm system. Results suggest that market access is a significant driver of VA technology adoption. Also, the size of the farm, networks, farmer’s perceptions, and employment growth influence adopting VA technologies. The results also show us that farmers adopting VA technologies tend to experience economic growth.

<p>Information about the conditions of specific fields and assets is critical for farm managers to make operational decisions. Location, rainfall, windspeed, soil moisture, and temperature are examples of metrics that influence the ability to perform certain tasks. Monitoring these events in real time and being able to store historical data can be done using Internet of Things (IoT) devices such as sensors. The abilities of this technology have previously been communicated, yet few farmers have adopted these connected devices into their work. A lack of reliable internet connection, the high annual cost of current on-market systems, and a lack of technical awareness have all contributed to this disconnect. One technology that can better meet the demand of farmers is LoRaWAN because of its long range, low power, and low cost. To assist farmers in implementing this technology on their farms the goal was to build a LoRaWAN network with several sensors to measure metrics such as weather data, distribute these systems locally, and provide context to the operation of IoT networks. By leveraging readily available commercial hardware and opens source software two examples of standalone networks were created with sensor data stored locally and without a dependence on internet connectivity. The first use case was a kit consisting of a gateway and small PC mounted to a tripod with 6 individual sensors and cost close to $2200 in total. An additional design was prepared for a micro-computer-based version using a Raspberry Pi, which made improvements to the original design. These adjustments included a lower cost and complication of hardware, software with more open-source community support, and cataloged steps to increase approachability. Given outside factors, the PC architecture was chosen for mass distribution. Over one year, several identical units were produced and given to farms, extension educators, and vocational agricultural programs. From this series of deployments, all units survived the growing season without damage from the elements, general considerations about the chosen type of sensors and their potential drawbacks were made, the practical observed average range for packet acceptance was 3 miles, and battery life among sensors remained usable after one year. The Pi-based architecture was implemented in an individual use case with instructions to assist participation from any experience level. Ultimately, this work has introduced individuals to the possibilities of creating and managing their own network and what can be learned from a reasonably simple, self-managed data pipeline.</p>

<p>    </p> <p>This study’s purpose is to examine the relationship between broadband and online agriculture job postings. While rural broadband has been a wide studied topic, little attention has been focused on broadband’s relationship to agricultural job demand. This research uses a spatial count model that estimates agriculture and digital agriculture jobs by U.S. counties. Data was collected using the Google Jobs API developed by SerpAPI. Job advertisements were collected monthly from June 2021 through June 2022 and again in November 2022. Digital agriculture jobs postings were extracted as a subset from the overall dataset. By searching for key terms in job advertisements, context analysis filtered and identified digital agriculture jobs. Digital agriculture job openings were identified in order to examine how broadband relates to data intensive jobs in agriculture. Jobs focused in digital agriculture require increased levels of technology and increased data throughput. We hypothesized that occurrences of digital agriculture job openings would likely be reliant on broadband. Broadband data in this study represents average download speeds, average upload speeds, the percentage of households with internet access, and the percentage of the population with internet speeds at and above 100 over 20 megabits per second. The approach for modeling this data requires a hurdle negative binomial regression model as our count data encountered many zero observations and suffered from overdispersion. Spatial effects were incorporated into the model to alleviate spatial autocorrelation and help define agricultural job openings among surrounding counties. Our findings support the funding of broadband policies in agriculture. While controlling for outside factors such as demographics and county production, we found that agriculture job openings were positively influenced by broadband. However, we determined that broadband metrics show no relationship with the presence of digital agriculture job openings likely due to rarity and potential seasonality in the data. This information aids as a steppingstone for increasing the knowledge of broadband’s impact on agriculture. This study may aid in supporting future studies that seek to define causal relationships between broadband and agriculture jobs. </p>