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The article examines the scientific and practical problems of using mediation to resolve disputes in the sphere of providing state support to agriculture. The sub-branch of agricultural protection legislation is one of the most problematic in modern agrarian legislation of Ukraine. In particular, relations of support of agricultural commodity producers give rise to a significant number of disputes and conflicts. This is explained by several factors: a) a significant number of involved entities with different legal statuses; b) a wide range of agricultural protection legal mechanisms, which have different legal nature; c) a high degree of interest of subjects in receiving state support; d) the imperfection of legislative provisions, which creates fertile ground for controversial situations. Despite the fact that state support covers assistance measures, it should be emphasized that the conflict of these relations is quite high due to the competitive principles of provision, limited budgetary or other funding, short-term programs, etc. In this regard, the number of disputes in the field of agro-protection remains stable at a high level, requiring additional scientific and practical investigations in the direction of the formation of alternative ways of solving them. Taking into account the widespread tendency to in-depth study of mediation as the most well-known way to settle a dispute out of court, the question of the possibility and legality of applying this procedure to agro-protection disputes naturally arises. Based on the conducted research, some conclusions can be drawn. Disputes arising in the field of providing state support to agriculture, depending on the subjects and the legal nature of the relationship, are divided into three categories characterized by different degrees of the possibility of using mediation: a) institutional and functional category of disputes - disputes between subjects of power (non-mediable); b) power-administrative category of disputes - disputes between subjects of power (or special persons of public law) and private persons - recipients of support (limitedly mediatable); c) partner category of disputes - disputes that arise on the basis of contractual forms of providing state supp ort (conditionally mediated). [ABSTRACT FROM AUTHOR]

Hunger, food insecurity and the ill-informed use of natural resources are issues that concern the whole world, while the excessive use of chemicals, the increasing demands for food, climate change and political instability are posing significant challenges to existing food systems and sustainability. The Green New Deal (GND) seeks to resolve these problems and to support the positive transformation of the agriculture and food sectors. Turkey can be considered an ideal country for an analysis of the GND concept and for understanding its potential impact on the agricultural and food sectors, given its population in the region of 82 million, and its status as the second most populous Mediterranean country. The present study analyzes how the agricultural and food sectors will be affected by the GND, and clarifies the current status of the agricultural and food sectors in Turkey to understand what needs to be done to meet the GND goals. The adverse conditions in Turkey that are of particular note include the lack of R&D activity in the field of renewable energy; micro-scale food security issues; instability in agricultural policy; high inflation affecting food prices; and food losses and problems related to food fraud. [ABSTRACT FROM AUTHOR]

This paper analyses climate-smart agricultural (CSA) policies and strategies in sub-Saharan Africa, using a case study of Ngaka Modiri Molema District Municipality in South Africa. It is argued that the development and implementation of coherent policies is one of the approaches to offering effective responses to adaptation and to mitigating the influences of climate change. The results of the study, which drew on qualitative data gathered through participatory research, showed that 30%, 70%, 50%, and 60% of the community members, farmers, NGOs, and government participants were unaware of or did not understand climate-smart agriculture practices. Additionally, this study highlighted the absence of awareness and knowledge of CSA policies across all participants, indicating a significant gap in information dissemination and education on sustainable agricultural practices. These findings underscore the urgent need for targeted education and awareness initiatives to promote climate-smart agriculture in the region. Without a proper understanding and implementation of CSA practices, communities in Ngaka Modiri Molema District Municipality struggle to adapt to the changing climate and its impacts on agriculture. The results emphasise the necessity of raising awareness among different stakeholders in order to enhance the efficacy of agricultural practices' adaptations to climate change. In order to ensure sustainable agricultural practices in Ngaka Modiri Molema District Municipality, it is imperative that practices like collaboration, CSA technology, integration, financing, increased private sector involvement in CSA promotion, and sector-specific policies foster an environment that is favourable to CSA practices. [ABSTRACT FROM AUTHOR]

Investing in irrigation development has been a priority of agricultural policy in Benin since 1960. This has resulted in the development of several irrigation schemes in the country. This study assesses the impact of irrigation on food and nutrition security among rice producers in Benin. To do this, an endogenous switching regression model was used to control for the selection bias and endogeneity issues related to the participation in irrigation. The results show positive impact of participating in irrigation on dietary diversity and food consumption score. This confirms the potential of irrigation in improving food and nutrition security among rice farmers in Benin. Overall, the results call for public policies to further promote the development of irrigation schemes in Benin. [ABSTRACT FROM AUTHOR]

Previous research has shown that products labeled as 'Protected Designation of Origin' (PDO) correlate positively with indicators for landscape sustainability. However, specific factors that turn PDO products into sustainable landscape management tools remain vague. We analyze interviews from six European production systems to explore the links between PDO-labeled products and sustainable landscape management. All case studies were linked to extensive animal husbandry. We found that PDO products can contribute to sustainable landscape management if well-adapted incentives for agri-environmental measures supplement income. Successful products are further associated with local networks that use synergies between different stakeholder interests. Due to their promotion of social-ecological goals at the landscape level, PDO products can be a powerful addition to the EU's Green Deal and rural development strategy, and by introducing eligibility criteria that focus on social-ecological goals, PDO labeling could be classified as a sustainability standard. [ABSTRACT FROM AUTHOR]

Copyright of People & Nature is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Seeds are the building blocks of food security, and their free exchange amongst the farming community has formed the bedrock for maintaining genetic diversity in addition to food security and sovereignty. The appropriation of production, exchange, and marketing of seeds by the corporate over the past decades has altered the agricultural scene in the Global South. Given the conflicting perspectives, mandates, and practices of multiple stakeholders, this article attempts to critically evaluate seed policies in India considering the cultural, economic, and social undertones that characterise them. From the perspective of the sociology of science, this article attempts to trace the shifts in the decline of the 'rural', erosion of national agriculture, policy gaps, and why values matter in India's development narratives vis-à-vis science and technology solutions. Further, this article investigates, through a case study of Vrihi Community Seed Bank (CSB),1 located in the eastern state of Odisha, how CSBs are progressively being seen as a possible long-term solution to combat the diverse challenges posed by changing agro-climatic conditions, increasing corporatisation, and industrialisation of agricultural and allied practices of food production. [ABSTRACT FROM AUTHOR]

The paper presents an original application of economic complexity to the agricultural sector aiming to determine its suitability to measure and depict regional structural inequalities across Brazilian regions. Using census data, we calculate agricultural complexity indexes for products (PCI-Agro) and regions (ECI-Agro) and the agricultural product space. We show that higher PCI-Agro is associated with higher levels of productivity, education, income and human development. Also, we found that ECI-Agro is associated with higher productivity in agriculture. The econometric evidence points to an inverted 'U'-shape curve relationship between ECI-Agro and agricultural productivity, which has significant policy implications. [ABSTRACT FROM AUTHOR]

Accurate flow forecasting is crucial for effective basin management, regional agricultural policy development, environmental impact analysis, soil and water conservation studies, and flood protection planning. This study proposes a novel approach that integrates particle swarm optimization (PSO) with bidirectional long short-term memory (Bi-LSTM) and bidirectional gated recurrent unit (Bi-GRU) architectures, augmented by feature fusion and attention layers. Our approach consistently outperforms traditional methods across multiple datasets, including Ahmethacı, Büyükincirli, and Ersil, thereby achieving lower RMSE, MAE, and higher KGE and BF scores. Specifically, in Ahmethacı, our method yields an RMSE of 3.448, MAE of 1.224, and an R2 of 0.886. In Büyükincirli, it records an RMSE of 0.085, MAE of 0.040, and an R2 of 0.964. In Ersil, it achieves an RMSE of 1.495, MAE of 0.565, and R2 of 0.883. These results underscore the effectiveness of the proposed approach in flow forecasting. [ABSTRACT FROM AUTHOR]

Achieving economic and social sustainability is the goal of any policy when defining measures. We focus on the beef sector, where many challenges have arisen due to its structural characteristics, such as an unfavourable scale structure, high costs, low efficiency, and a low environmental footprint. This paper presents an example of the support provided by a mathematical programming model in the development of a Common Agricultural Policy Strategic Plan for the period 2023-2027. It is a model based on linear programming that allows such an ex-ante analysis by calculating production plans at the farm level and aggregating the results at the sector level. When defining the interventions, the question arose as to what the reform of the Common Agricultural Policy will bring and to what extent the sector should be supported in meeting these challenges. These were the concerns of agricultural policy that we sought to support by modelling different scenarios. The results show that the situation of the sector will worsen, especially for larger farms, but they also show the great importance of production-related payments to mitigate the negative trend. The applied approach proves to be suitable for supporting the design of agricultural policy and achieving greater economic and social sustainability in the sector. [ABSTRACT FROM AUTHOR]

Long‐run projections are crucial for climate change policies, food security, and agricultural productivity, yet these projections often overlook recently identified patterns in how trade policies and domestic support evolve as countries develop. The grain market projections over 50 or 100 years presented here take these policy patterns into account, as well as the risks of more significant trade policy disruptions. The results demonstrate that different assumptions about economic development can have far‐reaching effects on the market context, greenhouse gas emissions, and grain prices. [ABSTRACT FROM AUTHOR]

The article examines the peculiarities of the reform of agricultural protection legislation in Ukraine in the context of European integration obligations. It was concluded that the European agricultural protection model, in addition to substantive and formal components, also has a mandatory technical and legal part, which is represented by important legal mechanisms: a) land registration systems (IACS and LPIS); b) accounting and analytical networks (FADN); c) institutional and functional structures (national payment agencies). European integration transformations in the domestic agro-protection sphere should concern all three components at once: substantive component (specific support mechanisms), formal component (compliance with legislation), technical-legal component (creation of an implementation environment for successful implementation of legislative requirements). In the course of our research, the imbalance of the European integration reform of domestic agricultural protection legislation was recorded. Such an imbalance is manifested in the active anticipatory development of the technical and legal component and in the passivity of rule-making in relation to the substantive and formal parts of the agro-protection model. The identified disproportionality can lead to future legislative problems and conflicts. Perhaps the lawmaker is postponing the reform (or at least its conceptual outline), hoping that he will have time to do it relatively quickly, relying on agricultural protection regulations and EU directives. However, this task is not so simple, because each EU member country must develop its own national version of legislation on state support for agriculture, focusing on its own needs, opportunities and priorities. Given the specific circumstances of Ukraine becoming a candidate for EU membership and the ultra-crisis modern conditions of preparation for accession, Ukraine is once again taking a crooked path of European integration reform of agricultural protection legislation, which may have negative consequences. In this regard, the classic sequence of the European integration reform of legislation on state support for agriculture of Ukraine "from abstract to concrete" seems optimal, namely: 1) conceptual stage (theoretical development of a new system of agricultural protection legislation, selection of legal mechanisms and their legislative form, outline future system of legislation); 2) the rule-making stage (creating the regulatory framework for the functioning of the new support system); 3) technical stage (creation, testing, launch of necessary information products for proper implementation of legal requirements). [ABSTRACT FROM AUTHOR]

Limiting the impact of climate change on agriculture is a major goal of the European Union. This requires the evaluation of farm‐level adaptation measures, available within the Common Agricultural Policy. We investigate how the adoption of soil conservation measures by farms in Austrian arable regions affects their economic performance. By applying an endogenous switching regression model to panel data, we find that climatic conditions significantly influence the decision on whether to adopt soil conservation measures. The net revenue of adopters is less sensitive to long‐term temperature and precipitation changes than for non‐adopters. The measures are profitable for a majority of farms. However, profitability is linked to baseline climatic conditions, with negative effects in cool, wet regions and significantly greater positive effects in warm, dry regions. [ABSTRACT FROM AUTHOR]

Oil palm cultivation has experienced explosive expansion in recent decades. Although the oil palm boom has serious environmental and socioeconomic consequences, only environmental issues have garnered attention in public discussion and synthesis studies. In this study, we synthesize the literature on the socioeconomic impacts of oil palm expansion across various observation units and spatial and temporal scales, which is of significant relevance to policymakers, researchers, and the wider public. Our review demonstrates that oil palm expansion is a double-edged sword. On the one hand, it has significantly helped both producing and non-producing countries' economies by facilitating the (re)export of crude palm oil and its byproducts and by creating employment opportunities. This has stimulated rural economies, led to rural poverty reduction, and improved food security and diets for rural households in producer countries. On the other hand, it has increased conflicts and tension between local communities and agro-industrial companies, worsened workers' conditions, and widened domestic economic inequality between producing and non-producing areas within a given producer country. Monetary quantification of the costs of oil palm's negative environmental and social impacts indicates that the loss of ecosystem services and social services far outweighs the benefits derived from the increased production of oil palm. The direct income benefits through harvest sales and employment are more evident in the Southeast Asia production frontier, where oil palm cultivation and marketing are relatively advanced and well-integrated into global value chains. The negative outcomes are observed in all oil palm production regions, with more negative effects on food security in the African production frontiers. We propose multiple actionable research and policy recommendations that may jointly lead to inclusive and sustainable socioeconomic (and environmental) outcomes in oil palm cultivation. The socioeconomic consequences of oil palm expansion at the global level, in the African and American production frontiers, and the role of gender in oil palm production systems remain understudied. Hence, studies should be conducted. [ABSTRACT FROM AUTHOR]

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine learning and deep learning to predict maize yields in specific regions with high accuracy. However, existing methods typically have two limitations. One is that they ignore the extensive correlation in maize planting data, such as the association of maize yields between adjacent planting locations and the combined effect of meteorological features and maize traits on maize yields. The other issue is that the performance of existing models may suffer significantly when some data in maize planting records is missing, or the samples are unbalanced. Therefore, this paper proposes an end-to-end bipartite graph neural network-based model for trait data imputation and yield prediction. The maize planting data is initially converted to a bipartite graph data structure. Then, a yield prediction model based on a bipartite graph neural network is developed to impute missing trait data and predict maize yield. This model can mine correlations between different samples of data, correlations between different meteorological features and traits, and correlations between different traits. Finally, to address the issue of unbalanced sample size at each planting location, we propose a loss function based on the gradient balancing mechanism that effectively reduces the impact of data imbalance on the prediction model. When compared to other data imputation and prediction models, our method achieves the best yield prediction result even when missing data is not pre-processed. [ABSTRACT FROM AUTHOR]

Good agricultural practices (GAP) are guidelines designed to ensure the production of high-quality agricultural products that meet specified standards while optimizing resource use. This study aimed to examine the challenges and success factors in implementing a holistic system of GAP in hydroponic vegetable business management and to enhance the efficiency of Thailand's policies on safe agricultural standards. In this study, a qualitative research methodology was used, using in-depth interviews, semi-structured interviews, and observations with 36 intermediaries and consumers in Thailand. Data analysis was conducted using descriptive statistics. The study revealed that key challenges to successful GAP implementation include unsupportive government policies and a lack of in-depth knowledge among farmers on how to effectively apply GAP principles. For successful implementation, it is crucial that farmers who lead these efforts thoroughly understand the methods and prioritize safe and proper farming practices. This knowledge can then be leveraged to prepare and educate farmers, producers, and entrepreneurs to produce high-quality agricultural products. GAP for crops include policies, benchmarks, and audit processes that adhere to international standards, providing a framework for controlling and promoting product quality throughout the agricultural production process, including post-certification maintenance. The study suggests that cooperation across all relevant sectors, from upstream to downstream, is essential for the successful implementation of GAP. Such collaboration would significantly enhance the quality and safety of Thailand's agricultural standards. [ABSTRACT FROM AUTHOR]

References to agroecology have gradually started appearing in national and international public policies. We examine the extent to which agroecology is becoming a frame of reference for public action in the French national and regional context. Using textual statistics, we analyzed institutional documents concerning agroecology put out by public policy actors between 2008 and the summer of 2021, and conducted interviews with key actors of the Agroecological Project for France (PAEF, Projet Agroécologique pour la France). Our analysis shows that agroecology invoked in framing texts is reclassified in the vocabulary of triple performance, dominated by the notion of economic performance. A comparative analysis of the national and regional texts reveals mismatches, especially in terms of the level of autonomy of the actors concerned, and in the processes of knowledge transfer and support for changes in agricultural practices. [ABSTRACT FROM AUTHOR]

In the EU, policies towards territorial development and the sustainability of agri-food systems are exemplified above all in Pillar II of the Common Agricultural Policy (CAP). However, policies for the promotion of sustainable food systems and networks are mainly driven by municipalities and large cities. In order to understand multi-level configurations of policies to promote Sustainable Food Systems (SFS), this paper strives to identify the challenges that municipal policymakers face in implementing sustainable agri-food policies, from a multi-level governance perspective. To this end, and through in-depth interviews and secondary documentation analysis, the policies implemented in 10 different municipalities of the Madrid Region (Spain) are studied and the challenges these municipalities are facing are analysed from a multi-scale and territorialised perspective. The following research objectives are addressed: (1) description of the type of policies implemented for the promotion of SFS and the narrative frameworks in which they are shaped; (2) identification of challenges of local policies to support SFS especially governance challenges; and (3) proposals for the promotion of sustainable food systems through a multi-level, territorialised governance perspective. The paper identifies three main axes of tension and discoordination—municipal Vs regional competences; agricultural vs. food policies; and rural vs. urban territories—that constrains the sustainability potential of multi-level agro food policies. Finally, we provide a comprehensive, sustainable scheme to assess local agri-food governance throughout a multi-level and multi-actor approach, setting interrelations between the different levels, actors and agencies involved to overcome the lock-ins identified. [ABSTRACT FROM AUTHOR]

Winter wheat is one of the major crops for global food security. Accurate statistics of its planting area play a crucial role in agricultural policy formulation and resource management. However, the existing semantic segmentation methods for remote sensing images are subjected to limitations in dealing with noise, ambiguity, and intra-class heterogeneity, posing a negative impact on the segmentation performance of the spatial distribution and area of winter wheat fields in practical applications. In response to the above challenges, we proposed an improved HRNet-based semantic segmentation model in this paper. First, this model incorporates a semantic domain module (SDM), which improves the model's precision of pixel-level semantic parsing and reduces the interference from noise through multi-confidence scale class representation. Second, a nested attention module (NAM) is embedded, which enhances the model's capability of recognizing correct correlations in pixel classes. The experimental results show that the proposed model achieved a mean intersection over union (mIoU) of 80.51%, a precision of 88.64%, a recall of 89.14%, an overall accuracy (OA) of 90.12%, and an F1-score of 88.89% on the testing set. Compared to traditional methods, our model demonstrated better segmentation performance in winter wheat semantic segmentation tasks. The achievements of this study not only provide an effective tool and technical support for accurately measuring the area of winter wheat fields, but also have important practical value and profound strategic significance for optimizing agricultural resource allocation and achieving precision agriculture. [ABSTRACT FROM AUTHOR]

This paper aims to assess the use of WhatsApp Group for participatory monitoring in a System of Rice Intensification – Farmer Field School (SRI-FFS) program involving the rice farming community in the rural Bidayuh village of Tebaro in Sarawak, Malaysia. Descriptive analysis was performed on a 182-day WhatsApp Group chat taking place from 17 September 2019 to 16 March 2020. The data were analyzed using two online softwares to generate data visualizations. The study revealed that the strengths of participatory monitoring using WhatsApp Group were found in the principles of flexibility and methodologically eclectic. For flexibility, four factors indicated were technical sharing, personal sharing, comments on current events, and the addition of new members. The methodologically eclectic elements were identified as messages in the forms of texts, media, emoji and links. Limitations for participatory monitoring were in the elements of participation and negotiation due to the role-based group structure. To effectively promote the use of digital platforms, agricultural policies must promote inclusiveness and prioritize equitable access to ICT devices and facilities. Current findings show that social media can enhance active multi-stakeholder participation but should be complemented with non-ICT means of communication for rural farming communities. [ABSTRACT FROM AUTHOR]

Identifying rice cultivation areas in a timely and accurate manner holds great significance in comprehending the overall distribution pattern of rice and formulating agricultural policies. The remote sensing observation technique provides a convenient means to monitor the distribution of rice cultivation areas on a large scale. Single-source or single-temporal remote sensing images are often used in many studies, which makes the information of rice in different types of images and different growth stages hard to be utilized, leading to unsatisfactory identification results. This paper presents a rice cultivation area identification method based on a deep learning model using multi-source and multi-temporal remote sensing images. Specifically, a U-Net based model is employed to identify the rice planting areas using both the Landsat-8 optical dataset and Sentinel-1 Polarimetric Synthetic Aperture Radar (PolSAR) dataset; to take full into account of the spectral reflectance traits and polarimetric scattering traits of rice in different periods, multiple image features from multi-temporal Landsat-8 and Sentinel-1 images are fed into the network to train the model. The experimental results on China's Sanjiang Plain demonstrate the high classification precisions of the proposed Multi-Source and Multi-Temporal Rice Identification U-Net (MSMTRIU-NET) and that inputting more information from multi-source and multi-temporal images into the network can indeed improve the classification performance; further, the classification map exhibits greater continuity, and the demarcations between rice cultivation regions and surrounding environments reflect reality more accurately. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: All US commercial maize (Zea mays) is a single race, "Corn Belt Dent," and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations. Summary: Recommendations by the Maize Crop Germplasm Committee to the United States Department of Agriculture (USDA) for a molecular based vulnerability assessment on the US standing maize (Zea mays) crop have not been acted on because of intellectual property and licensing restrictions. This research explores maize diversity experts' access to data and perceptions and analysis of the standing crop.The data come from semi‐structured interviews conducted with 44 maize diversity experts in the public and private sectors.Experts explain that genetic data blanks restrict non‐industry research, describe public sector concerns that standing diversity is narrow(ing), and find historic sources of pedigree data in Plant Variety Protection and patent records are no longer reliable. Some interviewees perceive that industry monitoring of standing diversity is in their best financial interest. Industry participants describe concentration in US maize allows them to control diversity over time, while public researchers discuss efficiency of scale narrowing genetic diversity and global concentration spreading this trend.Knowledge gaps about genetic diversity in US commercial maize are designed through patents, contracts, non‐disclosure agreements, and confidentiality agreements by patent holders who do not want their inbred lines genotyped by competitors. This restricts research and knowledge flow about genetic information into public networks. The Maize Crop Germplasm Committee is a node for knowledge flow; however, the lack of mechanisms for action suggests it is performative. We recommend all protections used on seed include exemptions for research, breeding, and seed saving; an independent assessment of how industry monitors standing diversity; and a molecular analysis of the standing crop conducted by the USDA. All US commercial maize (Zea mays) is a single race, "Corn Belt Dent," and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular‐based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations. [ABSTRACT FROM AUTHOR]

How do discursive fields influence support for climate policies? The European Green Deal (EGD) has gained media attention in part because it was presented as a cross-sectorial strategy aiming to 'transform the European economy'. Our analysis focuses on two specific policy proposals of the EGD: the carbon border adjustment mechanism and the reform for a greener Common Agricultural Policy. By comparing their discourse network structure, we aim to understand policy (dis)continuity introduced with the EGD. We use an original longitudinal dataset and discourse network analysis to map framing dynamics over time and understand how particular frames can gather support in policy networks. Our study shows that two elements favor policy change, namely the resonance of new frames with the discursive field and the presence of brokers connecting previously disconnected actors or coalitions. This paper is relevant for scholars interested in the discursive layer of policy networks as well as (dis)continuity in policy debates. [ABSTRACT FROM AUTHOR]

This study investigates the determinants of farmers intentions to invest in green farming technologies in Tamil Nadu, India. Using Structural Equation Modelling (SEM), we analysed data from 380 beneficiaries of the Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) programme across three districts. The research examined the impact of socioeconomic factors, psychological variables, and external influences on farmers adoption of green farming practices. Results indicate that family influence, perceived necessity, peer influence, and perceived orientation towards agriculture significantly affect farmers intentions to invest in green technologies. The model explained 64.1% of the variance in farmers intentions. Contrary to expectations, agricultural decision-making behaviour, risk-taking ability and technology influence did not show significant relationships with intention to invest. These findings provide valuable insights for policymakers and agricultural extension services to promote the adoption of sustainable farming practices, emphasizing the importance of social networks and farmers' perceptions in driving technology adoption. [ABSTRACT FROM AUTHOR]

The cultivation of rye as a niche crop is gaining increasing importance in Ukraine. However, the rising cost of mineral fertilisers necessitates forecasting and market modelling to mitigate risks and enhance the economic efficiency of production. This study aimed to assess the current state of supply and demand in the rye market, which is considered a niche grain crop, and to forecast the effects of changes in mineral fertiliser costs on key market parameters under probable scenarios. The research employed comparative analysis, tabular representation, statistical economic approaches, abstract-logical reasoning, and econometric modelling. In particular, the econometric partial equilibrium model AGMEMOD has been utilised. The potential of rye as a niche crop has been revealed, the current state of its production has been analysed, and the key factors influencing the formation of supply and demand in the Ukrainian rye market have been identified; the dynamics of the supply and demand balance in the rye market, taking into account various economic and other factors, have been analysed; a forecast has been made of the consequences of changes in the cost of mineral fertilisers on the main parameters of the development of the rye market in Ukraine under several probable scenarios. The forecast extended to 2026 and evaluated the effects of different changes on yields, sown areas, gross production, and the economic efficiency of rye cultivation. The research provided a foundation for improving the efficiency of decision-making and implementation of management strategies, contributing to the achievement of national agricultural policy objectives, including ensuring food security. The proposed methodological approaches and research findings may be valuable for public and sectoral authorities in developing priority measures aimed at enhancing the performance of the domestic grain sector. [ABSTRACT FROM AUTHOR]

Organic farming takes on particular importance in the context of implementing the sustainable development concept as it combines environmentally safe farming methods with (as a general assumption) producing pollution-free food. Hence, environmental conditions might play a role in determining the development pace of that type of farming. The key objective of this paper is therefore to identify the scope and direction of multidimensional relationships between the development level of organic farming and environmental conditions. This was performed with the canonical analysis. The research process included the structuring of the authors' own synthetic metrics used in assessing the condition of the environment and the development level of organic farming. The study covered European Union countries and all 380 Polish districts (Poland is one of the very few Union members where organic farming development is currently inconsistent with the expected trends adopted under the Common Agricultural Policy). It follows from the analyses that when the variables relating to environmental conditions are known, they can explain only less than 10% of variance in the set of variables used in describing the development level of Polish organic farming. In turn, the analysis at Union level suggests that a positive—but not stronger than moderate—correlation exists between the two phenomena. [ABSTRACT FROM AUTHOR]

In the context of global and national carbon reduction targets, agricultural carbon emissions have become a critical focus. As global food demand increases, numerous agricultural policies have been implemented. Faced with limited policy resources, evaluating the impact of these policies on agricultural carbon emissions and production is essential. This study examined the relationship between food production and agricultural carbon emissions during the stage of agricultural development in Shandong Province, one of China's major grain-producing regions, using the decoupling model. Additionally, the coupled coordination model was employed to assess the specific influence of agricultural policy clusters on this transformation. The results indicate that Shandong is transitioning from high-input, extensive farming to green, low-carbon, modern agriculture, with most cities shifting from strong negative decoupling to strong decoupling. Over time, the role of agricultural policies in driving this shift has grown more significant. Future policymaking should prioritize the overall quality of agricultural producers and maintain a continuous focus on sustainable, green development. Ensuring that policy directions align with evolving stages of agricultural development and adjusting them in real-time will be crucial. [ABSTRACT FROM AUTHOR]

Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test. [ABSTRACT FROM AUTHOR]

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The present study aims at investigating the potential impacts of agricultural policies on GHG emissions from agriculture across the European Union. The study begins by providing evidence on how the key CAP reforms contributed to the structural changes the European agriculture faced in the past. Based on these facts, we introduce the context of implementation of the 2014–2022 Common Agricultural Policy (CAP), within which many interventions were designed to improve sustainability and increase competitiveness, and we formulate hypotheses on how CAP instruments can contribute differently to influencing GHG emissions from agriculture. The hypotheses formulated concern the following: (1) the influence of the income support payment on land prices and, consequently, on land distribution between small and large landowners; (2) the influence of the coupled payment on agricultural specialization; (3) the influence of agri-environmental-climate measures on the sustainable management of agricultural lands. These causalities can have direct and indirect effects on GHG emissions from agriculture. The method of qualitative comparative analysis (QCA) is used to investigate the above-mentioned causalities and to cluster observations based on similar combinations of conditions (i.e., drivers) and outcomes (i.e., positive or negative variations in GHG emissions from agriculture between the end and the beginning of the CAP programming period). The results reveal that the increase in GHG emissions from agriculture over the study period is mainly attributable to the low share of agricultural land under management contracts targeting climate change mitigation and carbon sequestration through the CAP. CAP payments coupled with production were found to contribute to further increasing GHG emissions from agriculture in some eastern and northern EU countries. Livestock concentrations, income support payments and the high price of agricultural land drive the increase in GHG emissions for other central and eastern EU countries. The paper concludes by addressing existing shortcomings due to conflicting interventions in the current CAP strategic plans. [ABSTRACT FROM AUTHOR]

Long‐term agricultural field experiments (LTFEs) have been conducted for nearly 150 years. Yet lack of coordination means that synthesis across such experiments remains rare, constituting a missed opportunity for deriving general principles of agroecosystem structure and function. Here, we introduce the Diverse Rotations Improve Valuable Ecosystem Services (DRIVES) project, which uses legacy data from North American LTFEs to address research questions about the multifunctionality of agriculture. The DRIVES Project is a network of researchers who have compiled a database of primary (i.e., observations) and secondary (i.e., transformed observations or modeling results) data from participating sites. It comprises 21 LTFEs that evaluate how crop rotational diversity impacts cropping system performance. The Network consists of United States Department of Agriculture, university, and International Maize and Wheat Improvement Center scientists (20 people) who manage and collect primary data from LTFEs and a core team (nine people) who organize the network, curate network data, and synthesize cross‐network findings. As of 2024, the DRIVES Project database contains 495 site‐years of crop yields, daily weather, soil analysis, and management information. The DRIVES database is findable, accessible, interoperable, and reusable, which allows integration with other public datasets. Initial research has focused on how rotational diversity impacts resilience in the face of adverse weather, nutritional quality, and economic feasibility. Our collaborative approach in handling LTFE data has established a model for data organization that facilitates broader synthesis studies. We openly invite other sites to join the DRIVES network and share their data. Core Ideas: Long‐term agricultural field experiments are critical for understanding the multifunctionality of agroecosystems.The DRIVES (Diverse Rotations Improve Valuable Ecosystem Services) network synthesizes data across long‐term experiments to understand the role of crop rotation diversity.The DRIVES Network has constructed a publicly available database containing daily weather and crop yield observations. [ABSTRACT FROM AUTHOR]

The 2003 reform of the Common Agricultural Policy, which decoupled farm subsidies from production, was expected to increase farmers' market orientation and to positively impact farm productivity. This theoretical effect of decoupling on farm performance has been verified in a few ex-post analyses. However, these studies lack important aspects of farm-level policy impact evaluations. First, they do not use a well-defined counterfactual scenario, second they do not account for farm heterogeneity when measuring performance and third they do not assess farm performance in a comprehensive manner. We address these shortcomings by combining quasi-experimental empirical methods with a latent-class production function. Using UK and French farm-level data, we show that farms indeed operate with distinct production technologies and that decoupling had positive and significant effects on productivity. Our results further show that under decoupling, farmers tend to diversify their businesses while keeping environmental pressure at a similar level as with coupled support. [ABSTRACT FROM AUTHOR]

Organic farming plays a pivotal role in the recent initiative to develop a sustainable economy in the Kyrgyz Republic (Kyrgyzstan). Key national policy documents support a green agricultural development path and highlight the potential of organic agricultural production and exports. This study therefore elicited perspectives on organic farming from organic farmers and stakeholders in Kyrgyzstan, focusing on the role of Participatory Guarantee Systems (PGS) in its promotion. Interviews held with these two groups revealed that, whereas organic farmers are primarily motivated by personal and family health concerns despite unfair market prices and insufficient governmental support, stakeholders prioritize environmental protection and view the inclusion of PGS in national legislation as a milestone in organic certification. Also, the recent COVID-19 pandemic has influenced farmers' motivation for organic conversion owing to increased health concerns and food safety. The study's findings highlight the potential of PGS to foster cooperation within local communities and familiarize farmers with organic principles and methods. PGS can be used as a framework to strengthen social and economic links within local farming communities and preserve traditional local knowledge and farming practices that are crucial for climate change mitigation and sustainable agriculture. Moreover, PGS may be applied in business as a model for establishing collaboration with other sectors at both domestic and international levels. The findings underscore the significance of PGS in the sustainable development of organic farming in Kyrgyzstan. However, challenges such as inadequate infrastructure and knowledge need to be addressed through the government's increased involvement and through cooperation among actors within the organic sector. Overall, the PGS approach may be used by policymakers as a relevant and feasible tool for introducing organic principles within agricultural policies and disseminating organic practices across the country. [ABSTRACT FROM AUTHOR]

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine learning and deep learning to predict maize yields in specific regions with high accuracy. However, existing methods typically have two limitations. One is that they ignore the extensive correlation in maize planting data, such as the association of maize yields between adjacent planting locations and the combined effect of meteorological features and maize traits on maize yields. The other issue is that the performance of existing models may suffer significantly when some data in maize planting records is missing, or the samples are unbalanced. Therefore, this paper proposes an end-to-end bipartite graph neural network-based model for trait data imputation and yield prediction. The maize planting data is initially converted to a bipartite graph data structure. Then, a yield prediction model based on a bipartite graph neural network is developed to impute missing trait data and predict maize yield. This model can mine correlations between different samples of data, correlations between different meteorological features and traits, and correlations between different traits. Finally, to address the issue of unbalanced sample size at each planting location, we propose a loss function based on the gradient balancing mechanism that effectively reduces the impact of data imbalance on the prediction model. When compared to other data imputation and prediction models, our method achieves the best yield prediction result even when missing data is not pre-processed. [ABSTRACT FROM AUTHOR]

Dwindling groundwater supplies threaten food security and livelihoods. Output subsidies for farmers are a ubiquitous agricultural policy tool, yet their contribution to growing groundwater stress remains poorly quantified. We show how output subsidies guaranteeing the purchase of crops at higher than market prices may have contributed substantially to declining water tables in India. Our analysis suggests that these policies may have led to a 30% over-production of water intensive crops. In the northwestern state of Punjab, rice procurement can potentially account for at least 50% of the groundwater table decline over 34 years. In the central state of Madhya Pradesh, wheat procurement adopted in the late 2000s appears to have driven a 5.3 percentage point increase in dry wells and a consequent 3.4 percentage point increase in deep tubewells. These results suggest that well-intentioned but poorly designed subsidies can impose harmful externalities on the environment and undermine long-term sustainable development. The study shows that India's agricultural subsidies have driven significant groundwater depletion by incentivizing overproduction of water-intensive crops like rice and wheat. This impact is evident in both Punjab's alluvial aquifers and Madhya Pradesh's hard rock aquifers. [ABSTRACT FROM AUTHOR]

The second pillar of the European Union's (EU) Common Agricultural Policy (CAP) aims at supporting rural areas by meeting the economic, environmental and social challenges. To deal with these challenges, countries are faced with the question of selecting the best tools among a large set of policy instruments. The problem of choosing the best policy instruments is aggravated by the very heterogeneous character of the societal demands that differ among member countries with very different economic and institutional structures. This study aims to introduce the agent-based modelling platforms that have been widely used in the impact analysis of recent rural development policies in the EU in a comparative manner. It also aims to explain how the above-mentioned sources of heterogeneity are handled in these models. To achieve the stated objectives, the study first examines the historical development of rural development policies within the EU. Subsequently, it proceeds to analyse several agent-based platforms that have been employed for the purpose of assessing the impact of agricultural policies with respect to certain features such as integration of land market, modelling unit, decision rule, rules of exit, labour market and price formation. To conclude, it is observed that as the rural development policies are formulated on farmbasis and as farms have a heterogeneous structure within themselves, in addition, the expansion of databases and the development of empirical analysis tools and technologies have led to a shift in empirical analyses towards agent-based models. However, these modelling platforms still embody various problems, especially in terms of database adjustments and parameterization and calibration of the model. [ABSTRACT FROM AUTHOR]

Background: Despite the high average per capita income and the Human Development Index for the Kingdom of Saudi Arabia, the average area of organic farms does not exceed 23.5 thousand hectares during the period 2018-2022. Therefore, this study aimed to measure the impact of potential expansion in organic agriculture on self-sufficiency and production inputs (chemical fertilizers and pesticides). Methods: This study relied on secondary data from the FAOSTAT website and the statistical book issued by the Ministry of Environment, Water and Agriculture, in addition to studies and research related to organic agriculture. In achieving its objectives, this study also relied on economic and statistical analysis. Result: This study showed that the productivity of organic farms is lower than that estimated for conventional farms, with rates ranging from a minimum of 19.2% for green fodder crops to a maximum of 74.8% for palm trees. With the doubling of the area of organic farms, a small relative decline in both total production and self-sufficiency of food products is expected. This is due to the modest average area of organic farms and their low productivity compared to conventional farms and most of the area of organic farms is planted with palm trees and fruits. It was also found that with the increase in organic farms by 100%, the amount of savings in chemical fertilizers and pesticides is estimated at 17041.8, 464.0 tons for each, respectively. Finally, the agricultural policy put the producer in front of two options: Namely organic agriculture and good agricultural practices. Therefore, this study recommends the need to compare organic agriculture with good agricultural practices from the point of view of the producer, the country and environmental sustainability. [ABSTRACT FROM AUTHOR]

Over the past two decades, China's remarkable economic growth has brought forth opportunities and challenges, including unsustainable food systems. Policies are pivotal in driving sustainable development, facilitating a balance between food supply, consumer demands, and environmental goals, thereby promoting a more sustainable food system. This study delves into the role of national policies from 2000 to 2022 in addressing these challenges, intending to reveal policy characteristics and potential impacts on agriculture and food. The research employs heat-map analysis, neural networks analysis, and topic analysis to explore policy concepts and themes, with findings underscoring the significance of rural development and food safety within agri-food policies. The presence of policy duplication and complementarity across different ministries provides valuable insights into the intricate dynamics of policy and their implications for sustainable agri-food systems in China and global sustainability endeavors. [ABSTRACT FROM AUTHOR]

For decades, the Japanese Ministry of Agriculture has implemented various measures to ensure a stable food supply, considering food security a top priority due to the increasing uncertainty of the global economy. However, the ministry's food security policy has evolved substantially with a disproportionate focus on the domestic production of specific food products. This policy change occurred without being widely recognized by the public, media, or intellectuals. Why has the Agricultural Ministry's policy changed even though its goal has remained the same? By applying both qualitative and quantitative research methods, we investigated the context behind this obscure policy transition. Our findings reveal that, contrary to conventional understanding, this policy shift occurred not so much due to political pressure from the agricultural sector, but mainly because of a change in the definition of a key policy concept (i.e., the food self‐sufficiency rate) in the late 1980s. [ABSTRACT FROM AUTHOR]

As an important path to breaking the urban-rural dual system and promoting agricultural modernisation in China, the process of urbanisation might have a strong influence on promoting agricultural economic resilience (AER). Using panel data from provincial-level administrative regions of China’s mainland, we constructed a novel indicator system to measure AER, and employ the system generalised method of moments model to examine the impact of urbanisation on AER and the moderating roles of land transfer and heterogeneous human capital. Our study yielded three notable findings. First, the urbanisation process can significantly enhance AER. This finding remained robust after conducting multiple robustness tests and addressing endogeneity using the instrumental variable method. Second, the influencing mechanism analysis results indicated that land transfer and human capital had significant moderating roles, and the level of land transfer and educational improvement can enhance the positive impact of urbanisation on AER, while the migratory human capital weakened this positive effect. Third, the heterogeneity analysis revealed regional differences in the impact of urbanisation on AER, demonstrating that the promotional effect of urbanisation was much greater in the major grain-producing areas. Our study offers a new perspective and evidence for researchers and policymakers investigating how to enhance AER. [ABSTRACT FROM AUTHOR]

In a competitive economy, agricultural policy must be implemented with a balanced sustainability approach by supporting producers in agricultural production. In recent years, it has been argued that global climate change, local/international marketing dynamics and local/international agricultural policy changes have more impact on the agricultural sector. Governments and international organizations are making intense efforts to develop sustainable policies in the agricultural sector to accelerate progress towards the Sustainable Development Goals (SDGs). While research on the adoption of new practices and new strategies in agriculture continues to grow and develop, agricultural policy practices offer new opportunities for agricultural marketing. The main purpose of this study is to determine and rank the importance level weights of the criteria affecting agricultural policy for sustainable agricultural marketing. In determining the criteria weights, the Best Worst method (BWM) from the multi-criteria decision making (MCDM) methods was preferred. The research proposes a framework for determining the weights of the appropriate criteria for agricultural policy strategy selection through a combined approach of multi-criteria decision making involving relevant stakeholders in an environment of uncertainty. According to the research results, project costs were determined to be the most important criterion for decision makers. This was followed by social benefits and employment opportunities criteria, respectively. When determining agricultural policy strategies for sustainable agricultural marketing, economic, social and environmental criteria may influence the evaluation of policy makers and stakeholders. Therefore, when determining strategies in agricultural policy, more importance should be given to sustainability approaches, taking into account all these factors. [ABSTRACT FROM AUTHOR]

Digital livestock technologies (DLTs) are presented as solutions to grand challenges in post‐Brexit British agricultural policy, such as climate change and food security. Evidence suggests technological solutions to agricultural challenges will be more effective with stakeholder and public engagement, yet there is little known about stakeholder views on these emerging technologies. We drew on responsible research and innovation, to analyse stakeholder perspectives on three case studies of DLT development through anticipatory focus groups with expert stakeholders in British animal agriculture. We found that stakeholders from broadly agroecological approaches to farming are at risk of exclusion from DLT development and policy, with negative implications for the ability of DLTs to resolve grand challenges in animal agriculture. We propose a heuristic framework of purpose, practicality and effects as key considerations for inclusive and responsible DLT development that contributes to ensuring effective solutions to grand challenges while avoiding wasted investments. [ABSTRACT FROM AUTHOR]

This paper provides policy recommendations for accelerating the adoption of Fossil-Energy-Free Technologies and Strategies (FEFTS) in the EU agricultural sector. Faster adoption of these technologies and strategies is crucial to achieving the medium- and long-term sustainability targets laid out in EU policy. The prepared policy recommendations originate out of the key outputs and findings of the Horizon 2020 project "AgroFossilFree", including an assessment and evaluation of the current energy use status in EU agriculture, survey results on farmers' needs, ideas and interests on the adoption of FEFTS, FEFTS categories identified through an online inventory of FEFTS called the AgEnergy platform, and key innovative processes through national and transnational workshops that combine expertise from hundreds of keys stakeholders (researchers, innovation brokers, policymakers, farmers, and industry representatives). The policy recommendations are synthesized and presented in the form of 19 policy briefs split into three main categories: those that are related to energy issues in farming and can be applied to any farm and FEFTS type; those that are specific to certain agricultural production systems; and those that are necessary for FEFTS integration in agriculture in general. [ABSTRACT FROM AUTHOR]

Beekeeping has faced increasing difficulties during the past decades, among which is the decline in floral resources. Agriculture provides essential floral resources for beekeeping, but some farming practices have also been shown to be responsible for their decline. To provide floral resources for beekeeping, what type of agricultural transformation should be promoted, and how? To answer these questions, we still lack knowledge about the floral resources that are used by beekeeping and about the technical-economic obstacles that farmers face in implementing more favorable farming practices, particularly in agropastoral settings. To help fill these gaps, we develop a novel approach that frames both agropastoral farming and beekeeping as farming systems, by characterizing the beekeeping systems of a given place, the floral resources they use, and the impacts these farming systems have on floral resources. This approach is applied to the agropastoral landscapes of Mount Lozère, southern France, using a methodology based on semi-structured interviews with farmers and beekeepers addressing the agronomical functioning of their farms. We demonstrate that the floral resources used by beekeepers on Mount Lozère are threatened by the current dominant agricultural development paths, which seek to maximize the material productivity of labor. Such paths lead to the intensification of agricultural practices in harvested areas and the extensification of rangelands. These pathways are reinforced by the low remuneration of agropastoral labor and by the current rules of the European Union Common Agricultural Policy. "Frugal" farming, a farming system based on reduced inputs and investments, and labor-intensive practices, namely, a labor-intensive use of pasture, seems an effective way to produce floral resources. Both, agropastoral farmers and beekeepers, would benefit from an increase in the number of agricultural workers in agropastoral landscapes. This calls for public policies that promote a better remuneration of agropastoral labor, either directly or by driving market mechanisms. [ABSTRACT FROM AUTHOR]

Extensive farmland in Europe hosts high biodiversity levels but is threatened by land use changes associated with market and agricultural policy drivers. We show that a nationwide replacement of rainfed cereals in favor of beef production in Portugal has coincided with a nearly 80% decline in the population of a ground‐nesting raptor, the Montagu's harrier Circus pygargus, since 2002. Reduced cereal crop cover led to nesting attempts occurring mostly in fodder crops, the predominant habitat with suitable sward structure at the onset of breeding. This results in a twofold ecological trap: early hay harvesting destroys first nesting attempts, whereas late cereal harvesting destroys replacement clutches. This double phenological mismatch prevents any breeding success and likely explains the country's observed population decline of Montagu's harriers and other key farmland birds. Reforming current agroenvironmental schemes to promote practices compatible with wild population phenology is paramount to revert these changes. [ABSTRACT FROM AUTHOR]

Plastic mulches made from nonbiodegradable polymers (e.g., polyethylene) provide an essential service in commercial horticultural production systems by enhancing crop productivity through weed suppression, soil moisture conservation, and moderating soil and canopy temperature conditions. Plastic mulches are particularly important in organic agriculture because weed management options are limited. Nevertheless, there is increasing concern about addressing the negative environmental impacts of plastic mulch waste. Soil-biodegradable plastic mulch (BDM) films that are designed to biodegrade in soils after incorporation are promising alternatives to nonbiodegradable plastic mulch. However, although the US organic standards technically permit the use of BDM films, no commercially available products meet National Organic Program (NOP) requirements for 100% biobased content and 90% degradation after 2 years following soil incorporation (7 Code of Federal Regulations, section 205.2). Other concerns about biodegradable film mulches include high perceived cost, esthetics, and uncertainties regarding the impacts of soil incorporation. New mulch technologies have emerged to diversify sustainable mulch options and overcome barriers associated with BDM film use in organic production. The objective of this study was to provide an overview of alternative and emerging mulch technologies, with an emphasis on biodegradable mulches, including water-based sprayable mulches such as hydromulch and foam mulch, and biobased agrotextiles. Information about how these mulch technologies contribute to organic and sustainable agriculture is provided, along with definitions, opportunities, challenges, and recommended areas for future research. [ABSTRACT FROM AUTHOR]

Crop type maps are essential in informing agricultural policy decisions by providing crucial data on the specific crops cultivated in given regions. The generation of crop type maps usually involves the collection of ground truth data of various crop species, which can be challenging at large scales. As an alternative to conventional field observations, street view images offer a valuable and extensive resource for gathering large-scale crop type ground truth through imaging the crops cultivated in the roadside agricultural fields. Yet our ability to systematically retrieve crop type labels at large scales from street view images in an operational fashion is still limited. The crop type retrieval is usually at the pixel level with uncertainty seldom considered. In our study, we develop a novel deep learning-based CropSight modeling framework to retrieve the object-based crop type ground truth by synthesizing Google Street View (GSV) and PlanetScope satellite images. CropSight comprises three key components: (1) A large-scale operational cropland field-view imagery collection method is devised to systematically acquire representative geotagged cropland field-view images of various crop types across regions in an operational manner; (2) UncertainFusionNet, a novel Bayesian convolutional neural network, is developed to retrieve high-quality crop type labels from collected field-view images with uncertainty quantified; (3) Segmentation Anything Model (SAM) is fine-tuned and employed to delineate the cropland boundary tailored to each collected field-view image with its coordinate as the point prompt using the PlanetScope satellite imagery. With four agricultural dominated regions in the US as study areas, CropSight consistently shows high accuracy in retrieving crop type labels of multiple dominated crop species (overall accuracy around 97 %) and in delineating corresponding cropland boundaries (F1 score around 92 %). UncertainFusionNet outperforms the benchmark models (i.e., ResNet-50 and Vision Transformer) for crop type image classification, showing an improvement in overall accuracy of 2–8 %. The fine-tuned SAM surpasses the performance of Mask-RCNN and the base SAM in cropland boundary delineation, achieving a 4–12 % increase in F1 score. The further comparison with the benchmark crop type product (i.e., cropland data layer (CDL)) indicates that CropSight is a promising alternative to crop type mapping products for providing high-quality, object-based crop type ground truth of diverse crop species at large scales. CropSight holds considerable promise to extrapolate over space and time for operationalizing large-scale object-based crop type ground truth retrieval in a near-real-time manner. [ABSTRACT FROM AUTHOR]

The focus on environment and climate-friendly farming is increasingly important in the European Union (EU) Common Agricultural Policy (CAP). Activities of the Measure M10 "Agri-environment and Climate" of the Rural Development Programme (RDP) 2014–2020 were those policy instruments that pursued environmental and climate goals over large areas under agricultural activities, but their effectiveness is still being questioned. After evaluating implementation successes and failures of the activities of the Measure M10 "Agri-environment and Climate" of the Lithuanian RDP 2014–2020, we aim to contribute to policy instruments that are better designed, more effective, and more attractive for farmers to achieve environmental and climate goals. This research was conducted in several stages: (1) a thorough analysis of the Measure M10 and its implementation; (2) analysis of the Measure M10 activities' contribution to the policy target areas; (3) multi-criteria evaluation of the activities; (4) survey of beneficiaries and discussions in the focus groups. The data available from the Ministry of Agriculture of the Republic of Lithuania, Agricultural Data Center, and National Paying Agency under Ministry of Agriculture of the Republic of Lithuania was used for the analysis. Analysis of the strategic documents and data on the implementation of Measure M10 was supplemented with results from studies focused on the environmental impact of the implementation of Measure M10 in Lithuania. Multi-criteria evaluation methods were used to arrange the activities of the Measure with respect to the selected indicators. The results from the survey of beneficiaries and discussions in the focus groups let us better clarify the motives, experiences, and preferences of farmers' participation in the activities of Measure M10. The questionnaire was distributed to 2455 beneficiaries through the National Paying Agency and 342 answers were received back, i.e., 13.9%. Five discussions in focus groups, formed from farmers participating and not participating in the activities, representatives of implementing institutions, and employees of consulting and scientific institutions, were organized. The research has revealed areas for improvement in Measure M10, and suggestions for improvement were prepared to better achieve environmental and climate objectives. [ABSTRACT FROM AUTHOR]