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Precision dairy tools (PDT) can provide timely information on individual cow's physiological and behavioral parameters, which can lead to more efficient management of the dairy farm. Although the economic rationale behind the adoption of PDT has been extensively discussed in the literature, the socio-psychological aspects related to the adoption of these technologies have received far less attention. Therefore, this paper proposes a socio-psychological model that builds upon the theory of planned behavior and develops hypotheses regarding cognitive constructs, their interaction with the farmers' perceived risks and social networks, and their overall influence on adoption. These hypotheses are tested using a generalized structural equation model for (a) the adoption of automatic milking systems (AMS) on the farms and (b) the PDT that are usually adopted with the AMS. Results show that adoption of these technologies is affected directly by intention, and the effects of subjective norms, perceived control, and attitudes on adoption are mediated through intention. A unit increase in perceived control score is associated with an increase in marginal probability of adoption of AMS and PDT by 0.05 and 0.19, respectively. Subjective norms are associated with an increase in marginal probability of adoption of AMS and PDT by 0.009 and 0.05, respectively. These results suggest that perceived control exerts a stronger influence on adoption of AMS and PDT, particularly compared with their subjective norms. Technology-related social networks are associated with an increase in marginal probability of adoption of AMS and PDT by 0.026 and 0.10, respectively. Perceived risks related to AMS and PDT negatively affect probability of adoption by 0.042 and 0.16, respectively, by having negative effects on attitudes, perceived self-confidence, and intentions. These results imply that integrating farmers within knowledge-sharing networks, minimizing perceived risks associated with these technologies, and enhancing farmers' confidence in their ability to use these technologies can significantly enhance uptake. [ABSTRACT FROM AUTHOR]

• Constructed a farmer portrait model based on production performance segmentation. • Proposed and validated an optimized clustering algorithm (GASA-WFCM). • Designed a labeling system to realize the description of farmers' portraits. • Identified typical characteristics of farmers with different production performance. • Findings can provide decision support for improving farmers' production effect. To identify the typical characteristics of farmers with different production performance, this paper constructs a farmer portrait model from the perspective of production performance segmentation. Firstly, we constructed the evaluation index system of production performance and quantified grape farmers' production performance. Then, an optimized clustering algorithm (GASA-WFCM) was proposed to cluster the grape farmers based on their production performance, which was based on fuzzy C-mean algorithm, and incorporating the genetic simulated annealing algorithm to overcome the problem of sensitive initial clustering centers and tendency to fall into local optimum, and the ReliefF algorithm was also integrated to strengthen the contribution ability of effective features to clustering. Finally, we designed a labeling system and feature transformation quantification method, and combined with the visualization effects to realize the description of grape farmers' portraits. The results of models training indicated that the convergence speed and division accuracy of the optimized clustering algorithm were significantly improved. By comparing the clustering results on the typical UCI datasets, it was demonstrated that GASA-WFCM algorithm improved the accuracy, NMI and ARI by 3.0%, 7.2% and 6.1%, respectively. Moreover, the segmentation method was applied in grape farmers dataset, and the findings revealed that Chinese fresh grape farmers may be clustered into three groups, namely high-yield-driven grape farmers, high-input-driven grape farmers and high -income grape farmers, respectively. This paper provided a set of methods of users clustering analysis and portrait from a theoretical point of view. The findings and suggestions can help provide accurate and focused decision support for improving the effect of agricultural technology promotion and farmers' production performance. [ABSTRACT FROM AUTHOR]

Grain is not only the basic living materials of urban and rural residents, but an important strategic resource related to the national security. Therefore, grain security is an important aspect of national security. Farmers' willingness to grow grain is the key factor to guarantee food security. Based on the structural equation model, the main factors that influence the farmers' willingness to grow grain were studied in this paper by investigating 486 dispersed farmers in six counties (cities, districts) of three prefecture-level cities in Shandong Province. The study indicated that aside from the difficulty of measuring the influence of personal characteristic factors, the national grain subsidy policies, grain price, grain planting scale, other farmers' production behaviors, and promotion of agricultural technology affected the farmers' willingness to grow grain in varying degrees. Further regional multi-group analyses demonstrated that the farmers' willingness to grow grain showed an increasing trend from east to west in Shandong Province. Additionally, grain subsidy policies and family characteristic factors had obvious regional differences on the farmers' willingness to grow grain. Therefore, optimizing and improving the national grain subsidy policies, encouraging the management of a moderate scale, stabilizing prices of grain, increasing the propaganda of agricultural information and promoting agricultural technology were the key factors to increase the farmers' willingness to grow grain. • Establishing a comprehensive model to study the influencing factors of farmers' willingness to grow grain. • Six main factors influencing farmers' willingness to grow grain were studied. • Each factor has different effects on the farmers' willingness to grow grain and shows significant regional differences. • The farmers' willingness to grow grain shows an increasing trend from east to west in Shandong Province. [ABSTRACT FROM AUTHOR]

Climate services are integral to climate change adaptation in agriculture. Inclusive innovation prioritises inclusion of marginalised actors, grassroots knowledge and accessibility of use. Yet many innovation processes are multi-stakeholder, complex and may not prioritise inclusion from the outset. In these circumstances, researchers and designers may seek to influence existing projects towards greater inclusivity. This paper explores efforts to increase the inclusivity of existing innovation processes, focusing on the design of My Climate View, an online Australian climate services platform for agriculture. Findings relate to contemporary issues in inclusive innovation literature, including: (1) Who should be included in innovation processes (within given resourcing)?; (2) How requirements for inclusion or exclusion can emerge through the design and use of a technology; and (3) The influence of program level structures upon inclusivity and design. Our approach is informed by Responsible Innovation and Inclusive Innovation theory and enacted through user-centred design. Findings are synthesised from analysis of 60 semi-structured interviews with farmers, advisors and extension officers. We additionally draw on observations as researchers in the multi-actor My Climate View development team, where extensive engagement separate to research activities has included agricultural and Indigenous stakeholders. Engaging with a broad sample of potential target users enabled diverse and sometimes unexpected use cases. Customisation of interface parameters allowed the incorporation of tacit knowledge and positively affected the inclusivity of My Climate View, extending the value of the platform to growers of niche commodities outside of the original scope. Inclusivity in innovation can be impacted by diverse factors, including design team decisions, structural factors, budget and external factors. Requirements for inclusion and exclusion can emerge and evolve throughout a design process, supporting Responsible Innovation's framing of inclusivity alongside principles of reflexivity and responsiveness. The findings enrich the evidence base for climate services and broader agricultural technology development processes by providing insights for those seeking greater impact by practicing inclusivity in innovation. We provide four implications for increasing inclusivity in the design of climate services: (1) Maximising customisation and avoiding prescriptive interpretation enables greater flexibility of use; (2) Sampling broadly within target users to uncover unanticipated values and opportunities for inclusion and exclusion; (3) It is important to embed efforts towards inclusion alongside processes of reflexivity; and (4) Responsible and inclusive approaches to climate services design are valuable even if brought in once development has commenced. [Display omitted] • Explores the challenges of steering a largescale climate services innovation project towards greater inclusivity. • Maximising customisation options for users and avoiding prescriptive interpretation enables greater flexibility of use. • Responsible and inclusive approaches to climate services design are valuable even if adopted once development has commenced. [ABSTRACT FROM AUTHOR]

Summary It has now become almost a stylized fact that sustained agricultural growth is central to rapid poverty reduction and economic development. Yet, world poverty is largely concentrated in the agrarian societies, which have the potential for agricultural productivity growth. This is particularly true for Sub-Saharan African countries, where the gaps between potential and actual yields remain high. Minimizing this gap through the promotion of modern inputs—such as fertilizer and modern seeds—has been at the core of almost all development strategies in Ethiopia. Among other initiatives, the country has promoted microfinance institutions and member-owned financial cooperatives to alleviate credit constraints of the smallholder farmers. This paper analyzes the impacts of these institutions. Using household survey data and a propensity-score-matching technique, we examine the effects that institutional financial services have on farmers’ adoption of agricultural technology in Ethiopia. The results suggest that access to institutional finance has a significant positive impact on both the adoption and extent of technology use. However, when impacts are disaggregated by type of financial institution and farm size, heterogeneities are observed. In particular, financial cooperatives have a greater impact on technology adoption than microfinance institutions, and the results appear to vary depending on farm size and types of inputs. The paper concludes with implications for policies to promote adoption of modern agricultural inputs. [ABSTRACT FROM AUTHOR]

Under the strategy of rural vitalization, talent has become one of the main bottlenecks restricting the rural industries vitalization. Based on the analysis of the contradictory problem between the supply and demand of new professional farmers cultivation, this paper constructs a basic-elements set of new professional farmer cultivation, defines the contradictory problems, and solves the contradictory problems through extension transformation, and finally forms a new professional farmers cultivation supply models to promote the rapid development of rural vitalization. [ABSTRACT FROM AUTHOR]

Agricultural extension to improve yields of staple food crops and close the yield gap in Sub-Saharan Africa often entails general recommendations on soil fertility management that are distributed to farmers in a large growing area. Site-specific extension recommendations that are better tailored to the needs of individual farmers and fields, and enabled by digital technologies, could potentially bring about yield and productivity improvements. In this paper, we analyze farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. We use a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results. We find that farmers have strong preferences to switch from general to ICT-enabled site-specific soil fertility management recommendations which lend credence to the inclusion of digital technologies in agricultural extension. We find heterogeneity in preferences that is correlated with farmers' resource endowments and access to services. A first group of farmers are strong potential adopters; they are better-off, less sensitive to risk, and are more willing to invest in a high-input maize production system. A second group of farmers are weak potential adopters; they have lower incomes and fewer productive assets, are more sensitive to yield variability, and prefer less capital and labor intensive production techniques. Our empirical findings imply that improving the design of extension tools to enable provision of information on the riskiness of expected outcomes and flexibility in switching between low-risk and high-risk recommendations will help farmers to make better informed decisions, and thereby improve the uptake of extension advice and the efficiency of extension programs. • Choice experiement on farmer preferences for site-specific extension recommendations • High willingness to accept ICT-enabled and site-specific extension recommendations • Observed heterogeneity in farmers' willingness to intensify production systems • Information on riskiness of return crucial for improved design of extension tools [ABSTRACT FROM AUTHOR]

• The diffusion process of biogas technology among Mixed Crop and Livestock (MCL) farm households is evaluated. • Duration analysis is used to model the diffusion rate of biogas technology among MCL farmers. • Technological benefits, as well as the experience testing technologies, support the acceleration of individual adoption. • Technical assistance in the field is required to manage information and communicate biogas technical difficulties to farmers. Research on biogas technology adoption lacks information of the diffusion process in which included the acceleration of the adoption. In this paper, a duration analysis model is employed to model the speed of biogas technology adoption among small mixed crop and livestock farmers in Indonesia. A duration approach can model the adoption in a timely process to determine the biogas technology diffusion. Findings from this study indicate that there is an overall slow rate of biogas diffusion among farmers. There are however several ways to support the diffusion. It is revealed that 1) longer education, 2) higher farm income, 3) women involvement in the diffusion process and 4) access to financial support significantly accelerate the diffusion process. Farmer's perception of the relative advantages of biogas technology and their experience from testing the biogas technology also support the uptake of technology at the farm level. In addition, a technology dissemination strategy of stakeholders, especially local government is essential since the different regional regulations and policies have an important role to accelerate the diffusion process. [ABSTRACT FROM AUTHOR]

Highlights • We use field experiments in India to understand how farmers process information. • Most farmers simplify judgments by using only a portion of the information set. • Nearly 40% of farmers rely on first impressions to make subsequent judgments. • More than 36% of farmers use only the most recent piece of information. • Farmers who simplify judgments are less likely to cultivate rice hybrids. Abstract Much empirical research that has shown that an individual's decision to adopt a new technology is the result of learning – both in personal experimentation as well as observing the experimentation of others. Yet even casual observation would suggest significant heterogeneity learning processes, manifesting itself in widely varying patterns of adoption over space and time. In this paper we explore this heterogeneity in the context of early adoption of hybrid rice in rural India. Using specially-designed experiments conducted as part of a primary survey in the field, we are able to identify which of four broad learning heuristics most accurately reflects individuals' information processing strategies. Linking these learning heuristics with observed use of rice hybrids, we demonstrate that pure Bayesian learning is well suited for the tinkering and marginal adjustments that would be required to learn about a technology like hybrid rice, but is also more cognitively taxing, requiring a longer memory and more complex updating processes. Consequently, only about 25 percent of the farmers in our sample can be characterized as pure Bayesian learners. Present-biased learning and relying on first impressions will likely hinder adoption of a technology like hybrid rice, even after controlling for access to credit and a rudimentary proxy for intelligence. [ABSTRACT FROM AUTHOR]

• We appraise evidence on the uptake of decision support tools for site-specific nutrient management (SSNM-DSTs). • SSNM-DSTs still struggle to reach scale, despite evidence of benefits. • Scaling constraints vary by type of tool and user characteristics. • SSNM-DST address in-field heterogeneity, but not socioeconomic heterogeneity of users. • Future work should include institutional, economic and governance aspects of scaling. While many have extolled the potential impacts of digital advisory services for smallholder agriculture, the evidence for sustained uptake of such tools remains limited. This paper utilizes a survey of tool developers and researchers, as well as a systematic meta -analysis of prior studies, to assess the extent and challenges of scaling decision support tools for site-specific soil nutrient management (SSNM-DST) across smallholder farming systems, where "scaling" is defined as a significant increase in tool usage beyond pilot levels. Our evaluation draws on relevant literature, expert opinion and apps available in different repositories. Despite their acclaimed yield benefits, we find that SSNM-DST have struggled to reach scale over the last few decades and, with strong heterogeneity in adoption among intended stakeholders and tools. For example, the log odds of a SSNM-DST reaching 5–10 % of the target farmers compared with reaching none, decreases by ∼200% when a technical problem is stated as a reason for the tools' failure to be used at scale. We find a similar decrease in odds ratios when technical, socioeconomic, policy, and R&D constraints were identified as barriers to scaling by national extension and private systems. Meta-regression analysis indicates that the response ratio of using SSNM-DST over Farmer Fertilizer Practice (FFP) varies by non-tool related covariates, such as initial crop yield potential under FFP, current and past crop types, acidity class of the soil, temperature and rainfall regimes, and the amount of input under FFP. In general, the SSNM-DST have moved one step forward compared with the traditional 'blanket' fertilizer recommendation by accounting for in-field heterogeneities in soil and crop characteristics, while remaining undifferentiated in terms of demographic and socioeconomic heterogeneities among users, which potentially constrains adoption at scale. The SSNM-DSTs possess reasonable applicability and can be labeled 'ready' from purely scientific viewpoints, although their readiness for system-level uptake at scale remains limited, especially where socio-technical and institutional constraints are prevalent. [ABSTRACT FROM AUTHOR]

The agricultural sector in Lao PDR is forecast to move from subsistence rice production to a more modernized and market-oriented sector with greater focus on commercialization of agricultural production. Intensification of agricultural production in the southern and central rice growing regions of Lao PDR is problematic as dryland farmers rely on rainfall and soils are poor, yet rural households have been experiencing rapid change in their farming and livelihood systems. This paper employs Q methodology techniques to explore 35 farmers' viewpoints when contemplating their production goals and potential to adopt technologies to improve productivity. Findings describe the two emerging viewpoints among farmers as ‘labour saving productivity maximization’ and ‘traditional labour productivity using improved techniques’. The two viewpoints describe the different issues currently guiding production decisions. While the Lao Government forecasts substantial increases in rice production in the southern plains, farmers will require specialized and tailored support, accounting for their envisaged livelihood and production goals, to allow the sector transformation that many stakeholders currently envisage. [ABSTRACT FROM AUTHOR]

Climate change threatens agricultural production and the food security of developing countries in complex ways that demand environmentally friendly innovations. Climate-smart agriculture provides a response to climate change whilst enhancing livelihood of farmers. Climate-smart agricultural technological innovations at farm level have the potential to address climate-related challenges. However, inadequate adoption of these technologies remains a problem. This paper identifies available climate-smart agricultural technological innovations in South Africa and explores their characteristics and context of use using an exploratory research approach. An overview of climate change risks and variability in South Africa and a framework to classify the technological innovations is established based on a literature review. Interviews with expert stakeholders are used to characterise and collect information on available technologies. Results indicate that Conservation Agriculture, Rainwater Harvesting and Seed Varieties that are Drought Tolerant and Early Maturing may be the most suited technologies for climate-smart agriculture in South Africa, particularly for smallholder farmers. However, high initial investment costs, additional labour requirements and management intensity associated with conservation agriculture and rainwater harvesting may pose problems within the South African context. Drought Tolerant and Early Maturing Seed Varieties were noted as less costly and less management intensive, creating better prospects for adoption. This study serves as an initial assessment through the exploration of the available climate-smart agricultural technologies in South Africa. This is essential given that the agricultural sector is faced with the dilemma of responding to climate change related challenges whilst increasing the productivity of farmers. [ABSTRACT FROM AUTHOR]

Agricultural cooperatives remain a significant component of the food and agriculture industry to help the stakeholders to provide services and have opportunities for themselves. One of the aims of an agricultural cooperative is to answer to the needs within the communities of the farmers. Agricultural cooperatives enable individual farmers to increase productivity and maximise their social welfare. Together the farmer members of an agricultural cooperative can buy input supplies cheaper and sell more of their products in larger markets at higher prices, which is not possible for an individual smallholder farmer otherwise. Some studies have shown that farmers who were members of cooperatives have gained higher revenue for their products and spent less on input. However, organising the hundreds of farmers into smaller groups to perform collective farming and marketing is crucial to strengthening their position in the food and agriculture industry. Thereby, in our work, we consider an agricultural cooperative of smallholder farmers as a multi-agent based coalitional model, where coalitions are formed based on the similarity among the smallholder farmers. In this paper, we propose a model and implement a heuristic-based algorithm to find the disjoint partition of the agents set. We evaluate the model and the algorithm based on the following criteria: (i) individual gain, (ii) runtime analysis, (iii) solution quality, and (iv) scalability. We theoretically prove that our coalitional model of an agricultural cooperative has conciseness, expressiveness and efficiency properties. Experimental results confirm that our algorithm is time efficient and scalable. We show, both empirically and theoretically, that our algorithm generates a solution within a bound of the optimal solution. We also show that our coalition model generates positive revenue for the smallholder farmers and the payoff division rule is individual rational. In addition, we generate a new dataset in the context of an agricultural cooperative to show the effectiveness and efficiency of the proposed coalitional model of the cooperative. • Agent-based coalitional model of agricultural cooperative of smallholder farmers. • The novel algorithm forms coalition based on similarity of smallholder farmers. • Simulations demonstrate significant improvements in social welfare. • Presentation of how the coalition formation technique is applied to a real-world scenario. [ABSTRACT FROM AUTHOR]

• Digital technologies draw together knowledge, practice and self-care in novel and productive ways. • Digital curation provides young farmers with the agency to connect or disconnect from others. • Digital mediation encourages young farmers to critically reflect on their own practices of digital self-care. This paper explores the geographies of digital curation and self-care among young farmers in the UK, examining how virtual and digital spaces are having a significant impact on how young farmers negotiate their identities, (dis)connection and self-care within their everyday lives. Drawing on interviews with 28 young famers in the UK, we observe how farming identities are (re)produced and practiced online, via carefully curated social media, and how these might constitute practices of self-care in overcoming issues such as disconnection and rural isolation. Our analysis reveals how social media posts are more than simple connections, they are curations of the self that are complexly bound up in the emotional, spatial and temporal contexts of the author's identities. We examine how digital curation is not just an act of the self, but something drawn relationally to others. Attention is given not just to what is posted, but how others are (dis)engaged with, and how posts of others are reacted to, or endorsed, implicitly or explicitly. Through our examination of young farmers' social identities, we therefore argue that digital identities are produced, practiced, managed and understood in very specific ways 'online', in ways that carefully overlap with other geographical identities. [ABSTRACT FROM AUTHOR]

Assemblage thinking is an increasingly influential approach in critical studies of food and farming, and particularly in research on new agri-food technology such as precision agriculture (PA). This research is important in highlighting the distributed forms of power and agency through which farming worlds are assembled, and what these engender for more sustainable and equitable farming futures. However, to date, there has been limited attention to assembling PA from the perspective of farmers, what Legun and Burch (2021) refer to as 'deliberative assembling'. This paper contributes to knowledge in this area by applying post actor network theoretical work to investigate across case studies in Australia, the Netherlands and France, the forms of tinkering by which farmers attempt to make PA workable, and what these engender for farmer agency. Through our analysis, we show that much of the tinkering by farmers is aimed at holding together their own priorities, routines, and experiences with practices inscribed in PA technology, such as dependence on commercial advice, data-driven knowledge, and commitment to a single technological platform/company. Integral to this tinkering work are support networks that include agronomists, advisors, machinery dealers and/or farmer discussion groups. We argue that whilst these support networks are critical to holding together different practices, and making PA workable, they also play a more diverse and nuanced role in PA implementation than what has previously been recognised. Our case studies provide insights into three key forms of tinkering used by farmers in navigating support networks to make PA workable – disconnection, experimentation and trial-and-error, and trade-offs and compromises – and the specific distributions of agency which these tinkering practices engender. In conclusion, we argue that a tinkering lens provides a valuable approach for enabling agri-food scholars to tease out in greater depth deliberative assembling practices and how these variously open-up or foreclose options for farmers in making PA workable. • Farmers use tinkering to make precision agriculture (PA) workable. • Analysis of PA tinkering happens in Australia, The Netherlands and France. • Principal forms of tinkering are holding together, separation, experimentation. • Support networks are critical to tinkering in PA implementation. • Appropriateness of this PA implementation support is a key consideration. [ABSTRACT FROM AUTHOR]

In their efforts to understand why and how farmers adopt new technologies, techniques and programmes, rural sociologists and geographers have typically focused on the social and cultural relations in which farming knowledge and practices are embedded. However, limited scholarly attention has been given to the important ways in which materials and materiality are a constitutive element in how farmers come to know and engage with technology. This paper addresses this issue through the application of theoretical work on ordering, which focuses on the materially heterogeneous processes and implicit strategies that hold together and perform particular social and organisational arrangements. Drawing upon qualitative data from a research project on adoption of precision agriculture (PA) in the Australian rice industry, we identify two principal modes of ordering: (1) commercial-technological, in which lack of compatibility between technologies produced by different machinery manufacturers creates challenges for farmers in integrating and adapting PA to existing farming practices and systems; and (2) biophysical , where drought and low water allocations create uncertainty and a reluctance by farmers to make large capital outlays for PA technology. While these modes of ordering constrain rice growers’ capacities to adopt PA technology, we argue that growers also engage in their own alternative ordering practices to negotiate, work with, and work around these constraints. We refer to this work as tinkering and argue that it is a powerful, yet little recognised, form of ordering enabling growers to take advantage of the material benefits of PA in a way that is flexible, adaptable, and fits their immediate farming circumstances. In concluding, we contend that an ordering approach provides a fruitful way forward in recognising the more-than-cultural dimensions through which farmers engage with technology, and particularly the complex ways in which materiality intertwines with, shapes, and is shaped by, farming knowledge and practices. [ABSTRACT FROM AUTHOR]

There is much existing knowledge about the factors that influence adoption of new practices in agriculture but few attempts have been made to construct predictive quantitative models of adoption for use by those planning agricultural research, development, extension and policy. ADOPT (Adoption and Diffusion Outcome Prediction Tool) is the result of such an attempt, providing predictions of a practice's likely rate and peak level of adoption as well as estimating the importance of various factors influencing adoption. It employs a conceptual framework that incorporates a range of variables, including variables related to economics, risk, environmental outcomes, farmer networks, characteristics of the farm and the farmer, and the ease and convenience of the new practice. The ability to learn about the relative advantage of the practice, as influenced by characteristics of both the practice and the potential adopters, plays a central role. Users of ADOPT respond to 22 questions related to: a) characteristics of the practice that influence its relative advantage, b) characteristics of the population influencing their perceptions of the relative advantage of the practice, c) characteristics of the practice influencing the ease and speed of learning about it, and d) characteristics of the potential adopters that influence their ability to learn about the practice. ADOPT provides a prediction of the diffusion curve of the practice and sensitivity analyses of the factors influencing the speed and peak level of adoption. In this paper the model is described and its ability to predict the diffusion of agricultural practices is demonstrated using examples of new crop types, new cropping technology and grazing options. As well as providing predictions, ADOPT is designed to increase the conceptual understanding and consideration of the adoption process by those involved in agricultural research, development, extension and policy. [ABSTRACT FROM AUTHOR]

The study aims to identify the antecedents responsible for sustaining quality control in the context of under-studied agriculture value chains. There is a pressing need to understand the dynamics of technology implementation in an emerging economy context. The conceptual model is designed from complexity, and collective action theory perspectives. An empirical study validates the model and considers the role of traceability, collective action, big data predictive capability, and behavioral uncertainties in sustaining quality in agriculture value chains (AVCs). The paper addresses the call for in-depth deliberations on exploring the factors of AVC quality. The empirical validation of the theoretical model shows a significant positive relationship among the antecedents. The path coefficients and effect size have been derived from understanding the regression equations of cause and effect groups. It also identifies the avenues for improving quality in value chains. This is a pioneering study to design a new operation model for sustaining the quality of AVCs. It also adds a new theoretical debate to AVC technology deployment in the context of an emerging economy. The study is limited to recognizing a few antecedents from the literature in the Indian context. The deliberations contribute significantly to minimizing agricultural waste in developing countries through quality control. [ABSTRACT FROM AUTHOR]

Research and development in agricultural sector are becoming a crucial issue, especially to answer to growing global market needs and, in general, for rural innovation development. The innovation process involves stakeholders of all levels and rural development requires both personal farmers' characteristics along with favourable socio-political and infrastructural environment. Many countries and governments have executed innovation projects for agricultural firms, involving a number of actors from the public and private sectors. However, the literature lacks of studies that investigate the identification of the main factors that determine the agricultural entrepreneurs' probability to adopt new technologies during a crisis context. Thus, through the adoption of the Extended Theory of Planned Behaviour, this study aims at filling this lack. More specifically, the exploratory empirical analysis focuses on a sample of 130 agricultural entrepreneurs operating in a rural developing Italian region, during the historical context of global pandemic crisis of COVID-19. The results provided several insights showing the factors that influence the adoption of technologies, such as the Attitude to Environmental-Economic Sustainability and the Planned Behavioural Control. An important role is also assumed by the past farmer's technological experience. The paper offers implications for entrepreneurs and public government. • Agricultural entrepreneurs are alert to the sustainability in the adoption of new technologies. • A closed innovation model is widespread. • Agricultural entrepreneurs who have adopted new technologies in the last 5 years are unlikely to adopt them in the future. [ABSTRACT FROM AUTHOR]

Precision agriculture technologies (PATs) hold promise for improving resource usage and agricultural profitability. This paper examines the adoption of automatic section control, Global Positioning Systems and autosteer, satellite imagery, variable rate nitrogen application, and variable rate seeding by farm operators in North Dakota. Survey data are analyzed using a double-hurdle model. The double-hurdle model allows operators' adoption and usage decisions to be examined separately. Results indicate that larger operations are more likely to adopt PATs, suggesting that economies of scale exist among PAT adopters. Several PATs have complementary effects on the adoption of other technologies. These effects are most noticeable for variable rate technologies. Cropping patterns are related to the adoption of PATs, as corn production is positively associated with the adoption of multiple PATs while wheat production is negatively associated with adoption of variable rate technologies. These results have implications for farm managers, precision agriculture dealers and service providers, and policy makers. • Precision agriculture is emerging as a key part of North Dakota's economy. • Precision agriculture technologies exhibit complementary adoption. • Economies of scale exist for precision agriculture technology adopters. • Cropping patterns and practices determine technology adoption and usage. [ABSTRACT FROM AUTHOR]

Despite decades of research into the negative impacts of synthetic pesticides, farmers in Latin America continue to use pesticides at high levels and at a high cost to social and environmental sustainability. In this paper, we present a case study of pest management strategies in small-scale agriculture, focusing on the unsustainable technological lock-in of synthetic pesticides. Of the 196 smallholder farmers we surveyed in the coastal Mala and Omas Valleys of Perú, 22% of respondents experienced pesticide poisoning themselves or by an immediate family member. Additionally, the two most common pesticide categories reported in use are potent neurotoxins. We hypothesized that the farmers in the valleys were locked into synthetic pesticides due to uncertainty, coordination and learning associated with adopting an alternative strategy. Logistic regressions revealed gender (male), consulting an agro-chemical technician, quantity of cultivated land, and apple as a primary crop to be important predictors of synthetic pesticide use. Our findings suggest that these predictors represent the lock-in of synthetic pesticides through network externalities, learning economies and adaptive expectations. We conclude with opportunities to transition to sustainable pest management strategies at the local level in Latin American communities through interventions countering the lock-in of synthetic pesticides. [ABSTRACT FROM AUTHOR]

Summary The challenge of increasing irrigation prices while increasing farmers’ income exists not only in China but in other countries as well. The overall goal of this paper is to evaluate whether a win–win strategy can be realized in a pilot reform in Hebei, China. The data came from a two-round field survey in 2009 and 2012, which indicated that the key mechanism of the pilot reform was that farmers received similar returns (including reallocated, increased irrigation fees and a government subsidy), but paid different irrigation fees; the difference between the returned money and payment was treated as an incentive for farmers to reduce their use of irrigation. The econometric results showed that in pilot reformed villages, local farmers’ groundwater application for irrigating wheat and cotton could decrease by 21% each. If no subsidies are granted, roughly half of the region’s farmers would lose money due to the reform. However, most farmers who receive subsidies were able to earn money in the pilot reformed villages. If several issues are properly resolved (such as selecting more representative villages, increasing the subsidy value, and negatively linking the subsidy with water use), it would be possible for more regions to realize a win–win price reform strategy. [ABSTRACT FROM AUTHOR]

Agricultural science and technology (AST) is of great significance to the development of rural China. In order to boost farmers' demands for AST, possible influential factors affecting the demands are analyzed by this study. With regard to multiple types of AST for Chinese main agricultural industries-breeding and planting, the study discusses farmer families' demands instead of farmer individual demands. Using linear regression analysis, variables of the possible influential factors are categorized in four groups: family characteristics, farmers' operational status, farmers' attitudes toward AST and government service. Based on 3669 valid questionnaires collected from 15 towns of Anhui Province in China, the paper does the factor analysis and reliability test as well as examines the significance of possible influential factors, indicating that labor saving in farmers' attitudes group is the most important factor for planting industrial AST, and showing that capital support in government service group has the most crucial effect for breeding industrial AST. Hence, differences do exist among diverse factors, and the most significant factors affecting the demands for breeding and planting industrial AST are disparate. According to these results, suggestions concerning the most significant factors are specifically given to the Chinese government on how to expand the demands for AST and how to stimulate rural development. [ABSTRACT FROM AUTHOR]

Broiler houses are an important source of particulate matter (PM) in the Netherlands. High concentrations of PM can threaten the environment and pose health risks to humans and animals. To address these problems, the Dutch government aims to reduce PM 10 emissions originating from broiler houses by 50% between 2020 and 2030. This paper explored broiler farmers' investment preferences for different PM 10 abatement techniques and how they relate to socio-economic characteristics and perceived obstacles for business development. The results of our discrete choice experiment indicate that farmers were reluctant to invest in PM 10 abatement techniques. When they did invest, they had a general preference for techniques with a medium to high (31–52%) rather than a very high PM 10 reduction efficiency (80%). Social factors and perceived obstacles for business development explained heterogeneity in farmers' preferences for PM 10 abatement techniques and their willingness to invest. When investing in abatement techniques, farmers attached a higher relative importance to an exemption from future PM 10 legislation than to a subsidy. The findings imply that more policy-related certainty as well as financial compensation can incentivize farmers to invest in PM 10 abatement. [Display omitted] • Preferences for particulate matter abatement technique attributes were quantified. • Dutch broiler farmers were reluctant to invest in these techniques. • When they did invest, they preferred techniques with a medium reduction efficiency. • They attached a higher relative importance to policy certainty than to a subsidy. • Social factors and perceived obstacles explained heterogeneity in preferences. [ABSTRACT FROM AUTHOR]

Under small-scale farming operations, farmers' willingness in arable land protection cooperation (FWALPC) is a feasible way to realize the trinity protection of arable land in China. However, farmers often fall into the dilemma of collective action due to lack of motivation and free-riding behavior. On the basis of the configuration perspective, this paper conducted a questionnaire survey on 197 farmers in Xingning City by using the fuzzy set qualitative comparative analysis (fsQCA) method to explore the causal complex mechanism of the seven antecedent conditions of perceived benefits and policy incentives on the FWALPC. Results show the following: (1) Among individual factors, perceived economic benefits, policy subsidies, and government propaganda constitute the necessary conditions for the FWALPC. (2) The drive path of high-level FWALPC can be divided into four types: perceived ecological benefits leading type, perceived social benefits leading type, perceived emotional benefit–government regulation leading type, and government propaganda leading type. (3) The driving path of low-level FWALPC has one type and has a causal asymmetry relationship with high-level FWALPC. This research enriches and develops the relevant theories of collective action behavior of small farmers, and provides a new perspective for how land managers can improve FWALPC. [ABSTRACT FROM AUTHOR]

Climate smart agriculture (CSA) technologies and practices are important for achieving soil moisture conservation, erosion reduction, soil fertility enhancement, increasing and stabilizing crop yield and livelihoods, enhancing ecosystem services, achieving food security, tackling climate change problems, and improving the climate change resilience of farming ecosystems. Awareness (and subsequent adoption) of these technologies by farmers depends heavily upon a number of factors related to the farmer and the farming environment. There are very few studies that investigate how such factors influence awareness levels of CSA technologies in urban farming households, as most completed studies are on determinants of adoption of the technologies, especially by rural farmers. Yet urban agriculture is an important economic activity in many cities, especially in developing countries. This paper evaluates the factors that influence levels of awareness of CSA technologies among urban farmers in Kuje town (Nigeria), using data collected from 491 farming households. The results showed that the farmers that are more educated; older; having larger family sizes, income sources and economic assets; with greater climate change experience and local knowledge; and having farmlands with better physical conditions have more awareness of CSA adaptation strategies. Eleven other factors (namely marital status, tribal inclination, gender, religion, extension service, capacity building, security of tenure, institutional support, farmer organisational affiliation, distance to farmlands, and availability of loans and incentives) have no significant influence on the farmers' awareness levels of CSA adaptation strategies in the study area. Some ideas were given on how to improve these explanatory factors to help more awareness in the area learn about the CSA. • Climate smart agriculture (CSA) technologies and practices are important for promoting sustainable crop yield increases, environmental conservation and addressing climate change challenges. • To promote use of such technologies by farmers, there is the need to properly understand the key variables that determine the extent to which the farmers are aware of the technologies. • Ten (10) major variables related to socio-economic and environmental characteristics of farming households were found to be influencing households' levels of awareness of CSA technologies in Kuje, Abuja, Nigeria. • Eleven (11) others found not to significantly be influencing the awareness, and six (6) of them particularly need to be strengthened to increase the awareness levels of the households. [ABSTRACT FROM AUTHOR]

This paper introduces a relative entropy based image processing approach for the non-destructive prediction of the maturity of oil palm fresh fruit bunches (FFB) which enables the determination of the correct time for harvesting. The results of an experimental study of applying the Kullback–Leibler distance to the problem of oil palm classification are presented. It is shown that the proposed algorithm has an excellent accuracy and it can be computed very fast. The overall proposed system is simple and useful for oil palm farmers and entrepreneurs. [ABSTRACT FROM AUTHOR]

Digitalisation is promoted by both private and public actors as a way of contributing to the ecologisation of agriculture. However, this idea remains controversial. The debate is all the more crucial, as different ecologisation models exist, and as agriculture is experiencing new levels of industrialisation. In the literature, use of digital technology in agriculture has mainly been approached from a linear perspective of adoption but is rarely linked to ecologisation. In this paper, we aim to define digital use profiles of farmers and explain how they relate to ecologisation models. We distinguish production and information technologies. Based on 98 interviews with crop farmers in Occitanie (France), we show that there is a diversity of digital profiles. Through a mixed-method, we relate these profiles to a set of variables representing ecological and economic transformation in agriculture. It highlights links between some digital profiles and the further industrialisation of agriculture intertwined with weak or symbolic ecologisation. However, some digital uses associate with new forms of ecologisation that are based on input substitution. Digital use does not appear to support stronger ecologisation of farming. This study highlights the risk of a single model of digitalisation that only promotes one type of ecologisation pathway. • A diversity of digital technology use profiles exists. • Some digital uses are linked to the industrialisation of farming models. • Some digital uses are associated with the industrial development of organic farming. • Digital technology for information helps ecologisation changes already underway. [ABSTRACT FROM AUTHOR]

As one of the main focuses of agricultural development research, changes in agricultural technology are a dynamic reflection of the economic environment. This paper uses the Meta-analysis method to conduct a comprehensive analysis of 77 empirical studies to reveal the influence factors, sources of heterogeneity, and influence effects of farmers on the adoption behavior of pro-environmental agricultural technology over time. The results show the following: (1) Influencing factors of farmer's pro-environmental agricultural technology adoption behavior are not completely homogeneous. Among the factors, age, farming population, family income, farm income ratio, number of plots, and land transfer have a regulating effect. Most of the observed heterogeneity relates to the research areas, funding levels and models used. (2) Age, off-farm income ratio, and land fragmentation have a significantly negative impact on farmers' adoption of pro-environmental agricultural technologies. We find no impact on household size, farming population, and village cadres. Farm income ratio, farmland protection policy awareness, land transfer, and government subsidies have significantly positive effects. (3) Over time, only land transfer has a significantly positive impact on the adoption of pro-environmental agricultural technologies by farmers, and the impact has gradually increased. The farming population, technical understanding, and number of plots have no significant impact, but their effects have weakened to varying degrees. Therefore, policymakers and other stakeholders need to consider geographical differences and farming systems, the technology needs of different farmers and affordable costs, in addition to focusing on common variables, when designing policies to encourage the adoption of agricultural technologies in China. Meanwhile, improve the development level of the land rental market, strengthen publicity, training, and subsidies, and increase farmers' information awareness. • We study farmer adoption of pro-environmental agricultural technologies (PEATs) in China. • Meta-analysis is used to explore the influencing factors of farmers' PEATs. • Age, off-farm income ratio, and land fragmentation are negatively related to farmers' adoption of PEATs. • Farm income ratio, farmland protection policy awareness and land transfer have significantly positive effects. • Only land transfer has a positive effect on farmers' adoption of PEATs over time. [ABSTRACT FROM AUTHOR]

Increasing agricultural productivity through irrigation technologies is recognized as an effective way to improve smallholders' livelihoods and food security in developing countries. However, most smallholder farmers do not have access to irrigation technologies. Using a double-bounded contingent valuation survey data from smallholders in Ethiopia and probit and bivariate probit models, this paper analyzes smallholder farmers' demand for agricultural water lifting technologies (WLTs) and the factors affecting the demand for these technologies. Assessment of farmers' preferences among three water lifting technologies available in local markets (motorized pump, rope and washer and pulley) show that farmers prefer motorized pumps to pulley or rope and washer technologies. Use of motorized pumps is more efficient and save labour than pulley or rope and washer technologies. However, results show that smallholders are constrained by inadequate access to financing options to adopt more efficient and labour-saving water lifting technology and hence operate below the production possibility frontier. Enhanced access to finance could help ease this constraint and allow smallholders to acquire more efficient irrigation technologies, enhance adoption and improve productivity. With a growing population pressure and land fragmentation in rural Ethiopia, the livelihoods of smallholders depend mainly on the meagre land endowment they possess. Increasing the productivity of land using yield enhancing technologies, particularly multiple cropping per year via small-scale irrigation is key to improve their livelihoods. Targeted interventions are thus warranted to mitigate the key adoption constraints such as improving access to credit and technical know-how of smallholders. • We analyze smallholder farmers demand for irrigation water lifting technologies. • Supply and demand side credit-constraints are key determinants of adoption and demand for irrigation technologies. • Farmers prefer motorized water pumps to pulley and rope and wash technologies. • Farmers with smaller landholdings require targeted interventions for improving their access to irrigation technologies and land productivity. [ABSTRACT FROM AUTHOR]

A common avenue to enable adoption of technologies and practices by small-scale producers is by means of farmer clusters. These are achieved by building networks and partnerships between farmers and other actors within the supply chain. This paper examines the role that farmer clusters play in the adoption of practices and technologies by shrimp farmers in Vietnam. Understanding the decisions that lead to adoption is important because these have a key impact on sustainable land use in aquaculture. We report on two complementary studies that test the role of farmer clusters in accessing different sources of knowledge and the trust associated with each of the knowledge sources. First, a survey (N = 193) tested the relationship between cluster membership and adoption, and showed that shrimp farmers who are members of farmer clusters are more likely to adopt three types of pond management practices (i.e. water quality management, feed input, and disease control practices). Furthermore, frequency of interaction with, and trust related to, key stakeholder actors could partly explain this relationship. Second, focus group discussions further zoomed into the dynamics that underlie the adoption of technologies and practices by cluster farmers and non-cluster farmers, respectively. We found that input retailers, buyers and hatcheries were only valued for their input on specific products and issues, but not trusted, as the information always needed being verified through testing by, amongst others, neighbors. Consequently, trust relations with these actors can be described as strongly calculative. Farmer clusters increase trust and tighten relationships between members. As a result, members trust each other when verifying information or sharing knowledge acquired from less trusted sources. On the basis of these results, we argue that reliance on existing farmer networks (i.e. clusters) is a viable tool to improve adoption of sustainable technologies and achieve land use planning objectives. Further implications for research and policy are discussed. • Membership in a farmer cluster facilitates adoption of practices and technologies. • Increased frequency of interaction improves how much a source is trusted. • Trust is specific to the type of source of knowledge and information. • Farmer clusters can be a tool to achieve sustainable aquaculture practices. [ABSTRACT FROM AUTHOR]