Pub Date : 2025-10-15DOI: 10.1016/j.agsy.2025.104532
Ting Deng , Zeeda F. Mohamad
CONTEXT
Global agriculture is facing mounting pressures from climate change, resource degradation, and socio-economic inequalities. These challenges emphasize the urgent need for sustainable agricultural practices that foster long-term resilience. Agricultural Sustainability Assessment (ASA) tools, which integrate environmental, economic, and social dimensions, are essential in guiding policy development and assessing the sustainability of agricultural practices. However, the ASA tools show various limitations in terms of local adaptability.
OBJECTIVE
This study systematically reviews ASA frameworks, with a particular focus on how well these tools incorporate local adaptation criteria. The aim is to evaluate existing frameworks' strengths, limitations, and their ability to adapt to diverse agricultural contexts.
METHODS
This review applies the PRISMA 2020 methodology for systematic reviews and integrated with PICO framework (Population, Intervention, Comparison, Outcome) to propose three research questions. A total of 33 peer-reviewed articles were analyzed, focusing on ASA tools across different agricultural systems. The study identifies key criteria for local adaptation, assessing the performance of various tools against these standards.
RESULTS AND CONCLUSIONS
The review found significant variability across ASA tools in terms of their local adaptation capabilities. Indicator-Based Frameworks (IBFs) tend to perform well in providing standardized comparisons but fall short in addressing dynamic, local needs. In contrast, Decision Support Tools (DSTs) excel in integrating real-time data and scenario modeling, but often lack effective stakeholder participation and feedback mechanisms. Tools like MOTIFS, SAFA, and FSA showed strength in multi-stakeholder collaboration and user-driven flexibility, while SENSE Tool and APEX demonstrated robustness in real-time data integration and scenario simulation. The findings underscore the need for hybrid models that combine the strengths of both structured and non-structured optimizations to create ASA tools that are both scientifically rigorous and adaptable to local conditions. Enhancing stakeholder collaboration and feedback mechanisms will further improve the local relevance and practical usability of ASA tools.
SIGNIFICANCE
This study provides pathways for improving local adaptation in ASA tools, ensuring that they can better address the heterogeneity of agricultural systems across different regions. By incorporating dynamic, local data, and fostering participatory design, future ASA tools can offer more accurate and context-sensitive sustainability assessments.
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Pub Date : 2025-10-13DOI: 10.1016/j.agsy.2025.104528
Masoumeh Arabollah Firozjah , Azar Sheikhzeinoddin , Mohammad Bakhshoodeh , Gholam R. Amin
<div><h3>CONTEXT</h3><div>Pasture-based livestock systems are essential to the agricultural economy of countries, where they play a crucial role in food production and the well-being of rural communities. However, unsustainable grazing practices have led to widespread pasture degradation, threatening long-term productivity and environmental health. This study addresses the critical challenge of balancing the economic benefits of livestock production with the need to protect pastures and minimize environmental harm.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to address key objectives in sustainable livestock management: (1) evaluating the environmental efficiency of pastoralists, assessing the impact of grazing intensity and herd size on pasture degradation; (2) developing a DEA optimization model to explore economic-environmental strategies for reducing pasture degradation and grazing control to promote sustainability while maintaining environmental efficiency; (3) assessing the potential for reducing pasture degradation and its economic implications; and (4) providing policy recommendations for herd size regulation, feed subsidies, and grazing control to promote sustainability.</div></div><div><h3>METHODS</h3><div>Data for this study were collected from pastoralists in Mazandaran Province, Iran. Environmental efficiency was assessed using data envelopment analysis (DEA), focusing on grazing intensity, herd size, and pasture degradation. An inverse DEA model was developed to evaluate an integrated economic-environmental strategy, including reducing herd size, increasing government feed distribution, and limiting total digestible nutrients (TDN) harvested.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings in this study indicate that implementing an integrated economic-environmental strategy significantly reduces pasture degradation while maintaining or improving environmental efficiency. The analysis shows that environmental efficiency decreases with increasing herd size and grazing intensity, and the strategy's key benefit lies in reducing pasture degradation, particularly in inefficient units and high-grazing-intensity pastures. The study suggests that improvements in pasture management, including herd size reduction and better feed distribution, can enhance sustainability. Policymakers should consider compensating pastoralists for short-term losses while promoting long-term benefits such as ecosystem preservation and increased livestock productivity. The results underscore the need for a balanced approach that incorporates economic and environmental goals for sustainable pasture-based livestock systems.</div></div><div><h3>SIGNIFICANCE</h3><div>This study introduces an innovative application of inverse DEA for evaluating sustainability strategies in pasture-based livestock systems. The findings offer methodological contributions to the environmental efficiency literature and provide actionable insights for policymake
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Pub Date : 2025-10-10DOI: 10.1016/j.agsy.2025.104529
K. Soma , G. Brunori , C. Giagnocavo , F. Meulman , M. Ryan , R.M. Heredia Hortigüela , C. Iliopoulos , M. Paulus , A. Ferrari , E. Kilis , S. Grando , V. Bellon-Maurel , A. Knierim , A. Gobrecht , T. Selnes , L. Ortolani , M. Bacco , C. Mannari
Context
The digital transformation of agriculture is widely promoted as a pathway to sustainability, yet the actual outcomes of digitalisation remain uncertain and context-dependent. As such, technology uptake among businesses can have positive impacts on individual farms, while the aggregated outcomes of digitalisation involving multiple farms and multi-actors in associated networks are fully uncertain. The novelty of this research is the introduction of an approach to investigate costs and benefits in different contexts at different levels of digitalisation.
Objective
The main objective is to introduce a systems-based approach for assessing sustainable digitalisation by differentiating outcomes across multiple levels of analysis. This approach is designed to address the common pitfall of generalising impacts such as assuming large-scale effects based on evidence limited to the farm level.
Methods
This research is based on a scoping literature review in the European Union Horizon Europe project called CODECS, which is highly suited for interdisciplinary research with multiple topics.
Results and conclusion
A framework has been designed to clarify the needs for distinguishing costs and benefits of digitalisation across three interconnected system levels: digitised socio-physical systems, socio-cyber-physical systems, and governance-cyber-ecological systems. To deal with complexities at each level, the framework integrates internal and external drivers, contextual conditions, and value-based perspectives, which all will influence outcomes of sustainability assessments.
Significance
The framework offers a practical tool for researchers, policymakers, and innovation actors, to deal with the complexities of digital transitions in agriculture, to reach at sustainable digitalisation outcomes in a long term regionally, as well as in a short-term locally, by enhanced understanding of the needs for distinguished sustainability assessment applications to reach at more accurate costs and benefits.
{"title":"Sustainable digitalisation - a system thinking approach for determining costs and benefits in the agri-sector","authors":"K. Soma , G. Brunori , C. Giagnocavo , F. Meulman , M. Ryan , R.M. Heredia Hortigüela , C. Iliopoulos , M. Paulus , A. Ferrari , E. Kilis , S. Grando , V. Bellon-Maurel , A. Knierim , A. Gobrecht , T. Selnes , L. Ortolani , M. Bacco , C. Mannari","doi":"10.1016/j.agsy.2025.104529","DOIUrl":"10.1016/j.agsy.2025.104529","url":null,"abstract":"<div><h3>Context</h3><div>The digital transformation of agriculture is widely promoted as a pathway to sustainability, yet the actual outcomes of digitalisation remain uncertain and context-dependent. As such, technology uptake among businesses can have positive impacts on individual farms, while the aggregated outcomes of digitalisation involving multiple farms and multi-actors in associated networks are fully uncertain. The novelty of this research is the introduction of an approach to investigate costs and benefits in different contexts at different levels of digitalisation.</div></div><div><h3>Objective</h3><div>The main objective is to introduce a systems-based approach for assessing sustainable digitalisation by differentiating outcomes across multiple levels of analysis. This approach is designed to address the common pitfall of generalising impacts such as assuming large-scale effects based on evidence limited to the farm level.</div></div><div><h3>Methods</h3><div>This research is based on a scoping literature review in the European Union Horizon Europe project called CODECS, which is highly suited for interdisciplinary research with multiple topics.</div></div><div><h3>Results and conclusion</h3><div>A framework has been designed to clarify the needs for distinguishing costs and benefits of digitalisation across three interconnected system levels: digitised socio-physical systems, socio-cyber-physical systems, and governance-cyber-ecological systems. To deal with complexities at each level, the framework integrates internal and external drivers, contextual conditions, and value-based perspectives, which all will influence outcomes of sustainability assessments.</div></div><div><h3>Significance</h3><div>The framework offers a practical tool for researchers, policymakers, and innovation actors, to deal with the complexities of digital transitions in agriculture, to reach at sustainable digitalisation outcomes in a long term regionally, as well as in a short-term locally, by enhanced understanding of the needs for distinguished sustainability assessment applications to reach at more accurate costs and benefits.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104529"},"PeriodicalIF":6.1,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-10DOI: 10.1016/j.agsy.2025.104526
Rajashree Naha , Tim Cowan , Matthew C. Wheeler , Jyoteshna Owens , David Cobon , Chelsea Jarvis , Peter O’Reagain
Context
In northern Australia, livestock production relies heavily on dryland pastures, whose growth is strongly controlled by wet season rainfall. Knowledge of the likely timing of the first productive pasture after the long dry season – marked by the green cover onset (GCO) - can help graziers establish an appropriate stocking rate based on the available fodder at the end of the previous growing season.
Objective
This study focuses on the ‘green break of season' date (GBOS), defined as the first day after 1 September when a threshold amount of rainfall (e.g., 50 mm) is accumulated over a 3-day period. This rainfall-based metric aims to coincide with the annual onset of effective pasture growth (GCO) in northern Australia.
Methods
Using robust model-derived estimates of green pasture cover at a representative location in northeastern Queensland we compute the Green Cover Onset (GCO), defined as the first day after 1 October on which modelled green cover reaches or exceeds a specific threshold. This study explores the relationship between GCO and the GBOS for different 3-day accumulated rainfall thresholds (10–80 mm, in increments of 10 mm). We further explore the ‘green date’ (GD), defined as the 70th percentile of the distribution of GBOS dates, calculated over a long historical period (1900–2023) in northern Australia using daily rainfall observations from the Scientific Information for Land Owners (SILO). We then analyse, how the phase of the El Niño-Southern Oscillation (ENSO) influences the GBOS distribution.
Results and conclusions
The strongest relationship between GBOS and GCO is found defining the GBOS as the first occurrence of 50 mm of rainfall accumulated over 3 days (R2 > 0.94). This correlation is stronger than that between the commonly used Northern Rainfall Onset (50 mm accumulated after 1 September) and GCO (R2 = 0.62), with a regression slope closer to 1 and a y-intercept closer to zero, indicating a better one-to-one relationship with the GCO. This suggests that the GBOS is a more effective indicator for estimating the onset of productive pastures. Additionally, our analysis reveals that during El Niño years, the reliable GBOS (the 70th percentile of GBOS for ENSO-influenced years) occurs slightly later than the GD for all years, with no significant difference. In contrast, during La Niña years, it occurs significantly earlier. This pattern is consistent across regions in northern Australia, showing that El Niño delays and La Niña advances the northern wet season.
Significance
This study paves the way for the development of a seasonal GBOS prediction product, which will help livestock producers in making more informed and effective management decisions.
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Pub Date : 2025-10-10DOI: 10.1016/j.agsy.2025.104536
Dagmar J.M. Braamhaar , Benjamin van Selm , Jan van der Lee , Simon J. Oosting
Context
East Africa is one of the world's most food-insecure regions, emphasizing the need for increased animal-source food (ASF) consumption while minimizing environmental impact. Circular food systems enable livestock to convert low-opportunity-cost feed (LOCF) into ASF, potentially enhancing food security.
Objective
This study assessed livestock's role in circular food systems in Nakuru County, Kenya, by identifying livestock types, LOCF allocation, and potential ASF output when relying solely on LOCF.
Methods
The feed-allocation model FEEDSOM was adapted to allocate available LOCF among livestock while maximizing ASF output. LOCF availability was based on current crop and forage production and existing livestock conditions. Three scenarios were tested: incorporating protein-rich co-products, converting food losses and waste into insects, and adopting high-performance livestock breeds.
Results
Using LOCF provided 18.4 g of animal-source protein (ASP) per capita per day while reducing total livestock numbers. However, a shortage of high-quality ingredients limited LOCF utilization, as shown by increased ASP/capita/day when protein-rich co-products (+4.4 g) or BSF larvae meal (+1.6 g) were included. High-performance breeds were unsuited to the tropics when relying solely on LOCF, resulting in a reduced ASP/capita/day (− 11.5 g). Constraints such as limited high-quality feed, inefficient use of bulky, low-quality LOCF, and the exclusion of certain livestock types due to nutrient deficiencies highlight challenges in transitioning to circular food systems.
Significance
This research introduces circular food system modelling in East Africa and highlights key constraints, offering insights for future studies on resource allocation and sustainable livestock production.
东非是世界上粮食最不安全的地区之一，因此需要增加动物源食品消费，同时尽量减少对环境的影响。循环粮食系统使牲畜能够将低机会成本饲料（LOCF）转化为ASF，从而有可能加强粮食安全。本研究评估了肯尼亚纳库鲁县牲畜在循环粮食系统中的作用，通过确定牲畜类型、LOCF分配以及仅依赖LOCF时潜在的非洲猪瘟产量。方法采用饲料分配模型FEEDSOM，在最大限度地提高ASF产量的同时，将可利用的LOCF分配给牲畜。可获得的土地资源是根据目前的作物和饲料生产以及现有的牲畜状况而定的。试验了三种方案：纳入富含蛋白质的副产品，将粮食损失和浪费转化为昆虫，以及采用高性能牲畜品种。结果使用LOCF可提供18.4 g / d的动物源蛋白（ASP），同时减少牲畜总数。然而，优质原料的短缺限制了LOCF的利用，这表明，当添加富含蛋白质的副产物（+4.4 g）或BSF幼虫饲料（+1.6 g）时，ASP/人均/d增加。当仅依赖于LOCF时，高性能品种不适合热带地区，导致ASP/人均/天降低（- 11.5 g）。高质量饲料有限、体积大、质量低的lof使用效率低下以及由于营养缺乏而排除某些牲畜类型等制约因素突出了向循环粮食系统过渡的挑战。本研究介绍了东非的循环粮食系统模型，并强调了关键制约因素，为未来的资源分配和可持续畜牧生产研究提供了见解。
{"title":"Circular food systems in Kenya: Exploring the role of livestock","authors":"Dagmar J.M. Braamhaar , Benjamin van Selm , Jan van der Lee , Simon J. Oosting","doi":"10.1016/j.agsy.2025.104536","DOIUrl":"10.1016/j.agsy.2025.104536","url":null,"abstract":"<div><h3>Context</h3><div>East Africa is one of the world's most food-insecure regions, emphasizing the need for increased animal-source food (ASF) consumption while minimizing environmental impact. Circular food systems enable livestock to convert low-opportunity-cost feed (LOCF) into ASF, potentially enhancing food security.</div></div><div><h3>Objective</h3><div>This study assessed livestock's role in circular food systems in Nakuru County, Kenya, by identifying livestock types, LOCF allocation, and potential ASF output when relying solely on LOCF.</div></div><div><h3>Methods</h3><div>The feed-allocation model FEEDSOM was adapted to allocate available LOCF among livestock while maximizing ASF output. LOCF availability was based on current crop and forage production and existing livestock conditions. Three scenarios were tested: incorporating protein-rich co-products, converting food losses and waste into insects, and adopting high-performance livestock breeds.</div></div><div><h3>Results</h3><div>Using LOCF provided 18.4 g of animal-source protein (ASP) per capita per day while reducing total livestock numbers. However, a shortage of high-quality ingredients limited LOCF utilization, as shown by increased ASP/capita/day when protein-rich co-products (+4.4 g) or BSF larvae meal (+1.6 g) were included. High-performance breeds were unsuited to the tropics when relying solely on LOCF, resulting in a reduced ASP/capita/day (− 11.5 g). Constraints such as limited high-quality feed, inefficient use of bulky, low-quality LOCF, and the exclusion of certain livestock types due to nutrient deficiencies highlight challenges in transitioning to circular food systems.</div></div><div><h3>Significance</h3><div>This research introduces circular food system modelling in East Africa and highlights key constraints, offering insights for future studies on resource allocation and sustainable livestock production.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104536"},"PeriodicalIF":6.1,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-09DOI: 10.1016/j.agsy.2025.104525
Alexander Buritica, Mary Ngaiwi, Manuel Moreno, Carolina Gonzalez, Augusto Castro-Nunez
Context
Deforestation and unsustainable agricultural practices, particularly extensive cattle ranching, have significantly contributed to carbon emissions and biodiversity loss globally. The Colombian Amazon, specifically the Caquetá region, faces high deforestation pressure due to pasture expansion for cattle. Silvopastoral Systems (SPS) integrate livestock, trees, and grasses, offering a sustainable alternative to traditional ranching practices. However, adoption rates of SPS remain low due to financial and technical barriers.
Objective
This study aims to evaluate the impact of SPS adoption on livestock productivity and environmental outcomes in Caquetá, Colombia. Specifically, it investigates the effects of SPS on herd size, weight gain, deforestation rates, and income generation. The study uses robust econometric approaches to provide empirical evidence of the potential of SPS to enhance sustainability in agricultural systems.
Methods
The research employs a difference-in-differences (DiD) methodology to analyze longitudinal data from 149 farms surveyed in 2016 (baseline) and 2019 (endline) under the Sustainable Amazonian Landscape (SAL) and Sustainable Land Use Systems (SLUS) projects. The analysis includes farm-level productivity metrics and rural property-level deforestation data. Propensity score matching (PSM) was used to address selection bias, and satellite imagery provided deforestation trends.
Results and conclusions
SPS adoption resulted in a 21 percentage-point reduction in deforestation and modest but significant increases in income from livestock sales and animal welfare indicators, including an average weight gain of 169 kg for young heifers. While SPS interventions improved paddock management and rotational grazing, the overall adoption rate remained low. The findings underscore the dual benefits of SPS in enhancing agricultural productivity and mitigating environmental degradation.
Significance
This study highlights the critical role of SPS as a climate-smart agricultural practice that aligns productivity with environmental sustainability. Policymakers must address adoption barriers through financial incentives, capacity-building, and technical support to scale SPS implementation. The results contribute to global efforts to balance livestock production with ecological conservation, particularly in high-deforestation regions like the Colombian Amazon.
{"title":"Advancing sustainable Silvopastoral practices for achieving zero deforestation in the Colombian Amazon","authors":"Alexander Buritica, Mary Ngaiwi, Manuel Moreno, Carolina Gonzalez, Augusto Castro-Nunez","doi":"10.1016/j.agsy.2025.104525","DOIUrl":"10.1016/j.agsy.2025.104525","url":null,"abstract":"<div><h3>Context</h3><div>Deforestation and unsustainable agricultural practices, particularly extensive cattle ranching, have significantly contributed to carbon emissions and biodiversity loss globally. The Colombian Amazon, specifically the Caquetá region, faces high deforestation pressure due to pasture expansion for cattle. Silvopastoral Systems (SPS) integrate livestock, trees, and grasses, offering a sustainable alternative to traditional ranching practices. However, adoption rates of SPS remain low due to financial and technical barriers.</div></div><div><h3>Objective</h3><div>This study aims to evaluate the impact of SPS adoption on livestock productivity and environmental outcomes in Caquetá, Colombia. Specifically, it investigates the effects of SPS on herd size, weight gain, deforestation rates, and income generation. The study uses robust econometric approaches to provide empirical evidence of the potential of SPS to enhance sustainability in agricultural systems.</div></div><div><h3>Methods</h3><div>The research employs a difference-in-differences (DiD) methodology to analyze longitudinal data from 149 farms surveyed in 2016 (baseline) and 2019 (endline) under the Sustainable Amazonian Landscape (SAL) and Sustainable Land Use Systems (SLUS) projects. The analysis includes farm-level productivity metrics and rural property-level deforestation data. Propensity score matching (PSM) was used to address selection bias, and satellite imagery provided deforestation trends.</div></div><div><h3>Results and conclusions</h3><div>SPS adoption resulted in a 21 percentage-point reduction in deforestation and modest but significant increases in income from livestock sales and animal welfare indicators, including an average weight gain of 169 kg for young heifers. While SPS interventions improved paddock management and rotational grazing, the overall adoption rate remained low. The findings underscore the dual benefits of SPS in enhancing agricultural productivity and mitigating environmental degradation.</div></div><div><h3>Significance</h3><div>This study highlights the critical role of SPS as a climate-smart agricultural practice that aligns productivity with environmental sustainability. Policymakers must address adoption barriers through financial incentives, capacity-building, and technical support to scale SPS implementation. The results contribute to global efforts to balance livestock production with ecological conservation, particularly in high-deforestation regions like the Colombian Amazon.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104525"},"PeriodicalIF":6.1,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-09DOI: 10.1016/j.agsy.2025.104534
Yue Zhao , Jiafa Luo , Ling Liu , Xiangbo Xu , Shuqin Jin , Xiaoming Yang , Zhaohai Bai , Lin Ma
CONTEXT
Pig farming significantly impacts environmental and human health due to nitrogen (N) losses, particularly ammonia (NH3) emissions, especially in regions with high concentration of pig production. In China, national policies regulate the spatial distribution of pig farming, leading to regional variations that influence product distribution and environmental outcomes. However, our understanding of how regional policy responses affect N emissions and the associated socioeconomic costs of pig production remains limited.
OBJECTIVES
This study aims to analyze changes in the spatial distribution of N emissions and the associated socioeconomic costs resulting from provincial responses to central pig production policies. Guangdong and Zhejiang, as the main pig marketing areas in China, and Hebei, as a major pig-production area, were selected to represent different regional responses. These provinces adopted distinct strategies to maintain production while mitigating environmental impacts.
METHODS
The study integrates consistent county-level pig production data from 2000 to 2021 with the NUFER (nutrient fluxes in food chains, environment, and resource use)-animal model. Spatial and temporal patterns of N emissions were analyzed using geostatistical methods, and socioeconomic costs were quantified based on environmental health impact assessments. The policy-driven changes in pig production distribution were evaluated to assess their effectiveness in mitigating environmental impacts while maintaining production levels.
RESULTS & CONCLUSIONS
Our findings reveal that Guangdong strategically relocated pig production from densely populated to less populated areas to maintain pork self-sufficiency, leading to a 15 % increase in socioeconomic costs. Zhejiang closed many pig farms and relocated others away from watercourses to protect water quality, reducing pig production by 60 % and NH3-related costs by 20 %. Hebei province maintained its pig production levels in densely populated areas to secure pork supplies for Beijing and other surrounding cities, which led to a 25 % increase in socioeconomic costs. These results highlight that despite strong central governance, provinces in China respond differently to national regulations. Provincial spatial planning is more effective than uniform policies in balancing ecological preservation and agricultural productivity.
SIGNIFICANCE
This study reveals how differentiated provincial responses to national policies have shaped spatial patterns of N emissions and their socioeconomic impacts. Future policies should build on strategies like Guangdong's intra-provincial relocation approach, which balanced production with ecological capacity. Governments should strengthen spatial planning tools and establish fiscal mechanisms that compensate regions bearing higher
{"title":"Policy responses and spatial adjustments in China's pig production: Impacts on nitrogen losses and socioeconomic costs","authors":"Yue Zhao , Jiafa Luo , Ling Liu , Xiangbo Xu , Shuqin Jin , Xiaoming Yang , Zhaohai Bai , Lin Ma","doi":"10.1016/j.agsy.2025.104534","DOIUrl":"10.1016/j.agsy.2025.104534","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Pig farming significantly impacts environmental and human health due to nitrogen (N) losses, particularly ammonia (NH<sub>3</sub>) emissions, especially in regions with high concentration of pig production. In China, national policies regulate the spatial distribution of pig farming, leading to regional variations that influence product distribution and environmental outcomes. However, our understanding of how regional policy responses affect N emissions and the associated socioeconomic costs of pig production remains limited.</div></div><div><h3>OBJECTIVES</h3><div>This study aims to analyze changes in the spatial distribution of N emissions and the associated socioeconomic costs resulting from provincial responses to central pig production policies. Guangdong and Zhejiang, as the main pig marketing areas in China, and Hebei, as a major pig-production area, were selected to represent different regional responses. These provinces adopted distinct strategies to maintain production while mitigating environmental impacts.</div></div><div><h3>METHODS</h3><div>The study integrates consistent county-level pig production data from 2000 to 2021 with the NUFER (nutrient fluxes in food chains, environment, and resource use)-animal model. Spatial and temporal patterns of N emissions were analyzed using geostatistical methods, and socioeconomic costs were quantified based on environmental health impact assessments. The policy-driven changes in pig production distribution were evaluated to assess their effectiveness in mitigating environmental impacts while maintaining production levels.</div></div><div><h3>RESULTS & CONCLUSIONS</h3><div>Our findings reveal that Guangdong strategically relocated pig production from densely populated to less populated areas to maintain pork self-sufficiency, leading to a 15 % increase in socioeconomic costs. Zhejiang closed many pig farms and relocated others away from watercourses to protect water quality, reducing pig production by 60 % and NH<sub>3</sub>-related costs by 20 %. Hebei province maintained its pig production levels in densely populated areas to secure pork supplies for Beijing and other surrounding cities, which led to a 25 % increase in socioeconomic costs. These results highlight that despite strong central governance, provinces in China respond differently to national regulations. Provincial spatial planning is more effective than uniform policies in balancing ecological preservation and agricultural productivity.</div></div><div><h3>SIGNIFICANCE</h3><div>This study reveals how differentiated provincial responses to national policies have shaped spatial patterns of N emissions and their socioeconomic impacts. Future policies should build on strategies like Guangdong's intra-provincial relocation approach, which balanced production with ecological capacity. Governments should strengthen spatial planning tools and establish fiscal mechanisms that compensate regions bearing higher ","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104534"},"PeriodicalIF":6.1,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-08DOI: 10.1016/j.agsy.2025.104523
Donghui Liu , Pengfei Li , Jiarui Lv , Zhilei Liu , Cailian Yu , Xianlong Peng
<div><h3>Context</h3><div>Understanding the relationship between rice yield and carbon footprint (CF) is crucial for optimizing nutrient management in rice production system. Identifying the primary constraints in rice production and determining how these factors influence both yield and CF can help design more effective strategies for sustainable agricultural practices. However, quantitative research on this relationship is still scarce, particularly in regions like Northeast China, one of the most important rice-producing regions.</div></div><div><h3>Objective</h3><div>This study aims to first quantify the relationship between rice yield and CF, and identify key limiting factors in rice production; then, determine how management practices can reduce yield and CF gaps and improve overall rice production efficiency.</div></div><div><h3>Methods</h3><div>Structured interviews were conducted to collect data in Heilongjiang Province, a major rice-producing region in Northeast China. Rice CF was calculated using the life cycle assessment (LCA) approach. Boundary line method was applied to explore the relationship between rice yield and CF, as well as to identify the primary production limiting factors.</div></div><div><h3>Results and conclusions</h3><div>The average actual yield and CF in the surveyed region were 8.03 t ha<sup>−1</sup> and 0.99 kg CO₂ eq kg<sup>−1</sup>, respectively. With 4.98 t ha<sup>−1</sup> yield gap and 0.36 kg CO₂ eq kg<sup>−1</sup> CF gap compared to the maximum potential yield and CF. Based on the boundary line performance under different limiting factors, when rice yield exceeded 90 % maximum predicted yield and CF was lower than 55 % average predicted CF, we recommend management ranges for key production constraints: nitrogen (N) fertilizer application between 106 and 189 kg ha<sup>−1</sup>, phosphorus (P₂O₅) between 56 and 152 kg ha<sup>−1</sup>, potassium (K₂O) between 50 and 175 kg ha<sup>−1</sup>, flooding duration between 90 and 114 days, tillage depth between 13 and 22 cm, planting density and seeding rate between 20 and 26 hills m<sup>−2</sup> and 42–132 kg ha<sup>−1</sup>. If adjust all production-limiting factors into these recommended ranges, 19.9 % yield gap and 30.6 % CF gap could be closed. Besides that, N fertilizer application rate, tillage depth, flooding duration and planting density were considered the primary limiting factors influencing both yield and CF.</div></div><div><h3>Significance</h3><div>Our findings underscore the importance of implementing scientifically-based nutrient management strategies. By adjusting the primary limiting factors, both yield and CF gaps can be significantly reduced, fostering the sustainable development of rice production systems. These results offer valuable insights for future research and precision farming practices. Provide actionable guidance to adopt precision farming techniques, helping to align global food security objectives with efforts to mitigate climate change.
了解水稻产量与碳足迹之间的关系对优化水稻生产系统的养分管理具有重要意义。确定水稻生产的主要制约因素并确定这些因素如何影响产量和CF可以帮助设计更有效的可持续农业实践战略。然而，对这种关系的定量研究仍然很少，特别是在像中国最重要的水稻产区之一东北这样的地区。目的首先定量分析水稻产量与CF之间的关系，找出制约水稻生产的关键因素；然后，确定管理实践如何能够减少产量和CF差距，并提高水稻的整体生产效率。方法采用结构化访谈法对东北水稻主产区黑龙江省进行数据收集。水稻CF采用生命周期评价（LCA）方法计算。采用边界线法探讨水稻产量与CF之间的关系，并确定主要的生产限制因素。结果与结论调查区平均实际产量为8.03 t ha - 1，平均CF为0.99 kg CO₂eq kg - 1。与最大潜在产量和CF相比，产量差距为4.98 tha−1，CF差距为0.36 kg CO₂eq kg−1。根据不同限制因素下边界线的表现，当水稻产量超过最大预测产量的90%，CF低于平均预测CF的55%时，我们推荐了关键生产约束的管理范围：氮肥施用量在106至189公斤公顷- 1之间，磷（P₂O₅）在56至152公斤公顷- 1之间，钾（K₂O）在50至175公斤公顷- 1之间，淹水持续时间在90至114天之间，耕作深度在13至22厘米之间，种植密度和播种率在20至26丘米- 2和42-132公斤公顷- 1之间。如果将所有限制生产的因素调整到推荐的范围内，可以弥补19.9%的产量缺口和30.6%的CF缺口。此外，氮肥施用量、耕作深度、淹水时间和种植密度是影响产量和生物量的主要限制因素。通过调整主要限制因素，可以显著缩小产量和CF差距，促进水稻生产系统的可持续发展。这些结果为未来的研究和精准农业实践提供了有价值的见解。为采用精准农业技术提供可操作的指导，帮助将全球粮食安全目标与减缓气候变化的努力结合起来。
{"title":"Assessing the link between rice yield and carbon footprint with boundary line method in major rice-producing region, China","authors":"Donghui Liu , Pengfei Li , Jiarui Lv , Zhilei Liu , Cailian Yu , Xianlong Peng","doi":"10.1016/j.agsy.2025.104523","DOIUrl":"10.1016/j.agsy.2025.104523","url":null,"abstract":"<div><h3>Context</h3><div>Understanding the relationship between rice yield and carbon footprint (CF) is crucial for optimizing nutrient management in rice production system. Identifying the primary constraints in rice production and determining how these factors influence both yield and CF can help design more effective strategies for sustainable agricultural practices. However, quantitative research on this relationship is still scarce, particularly in regions like Northeast China, one of the most important rice-producing regions.</div></div><div><h3>Objective</h3><div>This study aims to first quantify the relationship between rice yield and CF, and identify key limiting factors in rice production; then, determine how management practices can reduce yield and CF gaps and improve overall rice production efficiency.</div></div><div><h3>Methods</h3><div>Structured interviews were conducted to collect data in Heilongjiang Province, a major rice-producing region in Northeast China. Rice CF was calculated using the life cycle assessment (LCA) approach. Boundary line method was applied to explore the relationship between rice yield and CF, as well as to identify the primary production limiting factors.</div></div><div><h3>Results and conclusions</h3><div>The average actual yield and CF in the surveyed region were 8.03 t ha<sup>−1</sup> and 0.99 kg CO₂ eq kg<sup>−1</sup>, respectively. With 4.98 t ha<sup>−1</sup> yield gap and 0.36 kg CO₂ eq kg<sup>−1</sup> CF gap compared to the maximum potential yield and CF. Based on the boundary line performance under different limiting factors, when rice yield exceeded 90 % maximum predicted yield and CF was lower than 55 % average predicted CF, we recommend management ranges for key production constraints: nitrogen (N) fertilizer application between 106 and 189 kg ha<sup>−1</sup>, phosphorus (P₂O₅) between 56 and 152 kg ha<sup>−1</sup>, potassium (K₂O) between 50 and 175 kg ha<sup>−1</sup>, flooding duration between 90 and 114 days, tillage depth between 13 and 22 cm, planting density and seeding rate between 20 and 26 hills m<sup>−2</sup> and 42–132 kg ha<sup>−1</sup>. If adjust all production-limiting factors into these recommended ranges, 19.9 % yield gap and 30.6 % CF gap could be closed. Besides that, N fertilizer application rate, tillage depth, flooding duration and planting density were considered the primary limiting factors influencing both yield and CF.</div></div><div><h3>Significance</h3><div>Our findings underscore the importance of implementing scientifically-based nutrient management strategies. By adjusting the primary limiting factors, both yield and CF gaps can be significantly reduced, fostering the sustainable development of rice production systems. These results offer valuable insights for future research and precision farming practices. Provide actionable guidance to adopt precision farming techniques, helping to align global food security objectives with efforts to mitigate climate change.","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104523"},"PeriodicalIF":6.1,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1016/j.agsy.2025.104531
Xinxueqi Han , En Hua , Xinchun Cao , Bernie A. Engel , Shikun Sun , Yubao Wang
CONTEXT
Sustainable management of the Water-Energy-Food (WEF) nexus is challenged by resource scarcity, environmental pressures, and fragmented governance. Despite progress in understanding WEF, gaps remain in quantifying multi-dimensional synergies and trade-offs.
OBJECTIVE
This study aims to develop a systems-level framework that captures interactions and environmental constraints across the WEF nexus to assess WEF synergies.
METHODS
This study proposes a multi-level synergy framework based on symbiosis theory, integrating four dimensions—symbiotic units, relationships, interfaces, and environment—and apply it to the Yellow River Basin (YRB).
RESULTS AND CONCLUSIONS
WEF synergy in the YRB improved over 2000 to 2020; however, regional disparities persist due to uneven endowments, limited cross-sector coordination, and rising pressures. Symbiotic relationship synergies strengthened, but intensified water–food and water–energy interface stresses destabilized the system. The symbiotic environment increased from −0.03 to 0.13 and the grey water footprint declined by 23.44 %, whereas carbon emissions rose by 470.16 %. High‑carbon regions (e.g., Ordos, Yulin) exhibited constrained environmental adaptability, underscoring the need for policy intervention and multi-scale governance.
SIGNIFICANCES
This study provides a transferable tool to evaluate WEF synergies and environmental constraints, offering integrated planning supports evidence-based policymaking and contributes to sustainable agricultural and environmental systems.
{"title":"Deciphering water-energy-food synergies through a multi-level symbiosis framework: Insights from the Yellow River Basin","authors":"Xinxueqi Han , En Hua , Xinchun Cao , Bernie A. Engel , Shikun Sun , Yubao Wang","doi":"10.1016/j.agsy.2025.104531","DOIUrl":"10.1016/j.agsy.2025.104531","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Sustainable management of the Water-Energy-Food (WEF) nexus is challenged by resource scarcity, environmental pressures, and fragmented governance. Despite progress in understanding WEF, gaps remain in quantifying multi-dimensional synergies and trade-offs.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to develop a systems-level framework that captures interactions and environmental constraints across the WEF nexus to assess WEF synergies.</div></div><div><h3>METHODS</h3><div>This study proposes a multi-level synergy framework based on symbiosis theory, integrating four dimensions—symbiotic units, relationships, interfaces, and environment—and apply it to the Yellow River Basin (YRB).</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>WEF synergy in the YRB improved over 2000 to 2020; however, regional disparities persist due to uneven endowments, limited cross-sector coordination, and rising pressures. Symbiotic relationship synergies strengthened, but intensified water–food and water–energy interface stresses destabilized the system. The symbiotic environment increased from −0.03 to 0.13 and the grey water footprint declined by 23.44 %, whereas carbon emissions rose by 470.16 %. High‑carbon regions (e.g., Ordos, Yulin) exhibited constrained environmental adaptability, underscoring the need for policy intervention and multi-scale governance.</div></div><div><h3>SIGNIFICANCES</h3><div>This study provides a transferable tool to evaluate WEF synergies and environmental constraints, offering integrated planning supports evidence-based policymaking and contributes to sustainable agricultural and environmental systems.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104531"},"PeriodicalIF":6.1,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1016/j.agsy.2025.104517
Tadesse Tolera Ejeta , Xiuguang Bai
Context
Adopting agricultural green production technologies (AGPTs) is an efficient approach for achieving sustainable food production. The relationship between AGPTs and eco-efficiency is still ambiguous.
Objective
This study examines the direct, indirect, and heterogeneous effects of AGPTs adoption on eco-efficiency in wheat production.
Methods
Farm-level data from 506 wheat farmers were utilized. A structured survey questionnaire with a focus group discussion was conducted. The study utilized super-SBM, multinomial endogenous switching regression, causal mediation, and quantile regression models to attain its objectives. This paper outlines the adoption of AGPTs for organic fertilizer, green pest control, and soil improvement, both individually and in combination.
Results and conclusions
The findings demonstrate that the adoption of AGPTs can significantly enhance the eco-efficiency of wheat production, with the combined AGPTs exhibiting the most substantial impact, which is 20 % for adopters and 15.43 % for non-adopters. The heterogeneity analysis results reveal that the impact of AGPTs adoption on eco-efficiency is particularly significant among large landholders, farmers with poorer eco-efficiency, and those located in resource-endowed production zones. Reductions in fertilizers and pesticides, along with enhancements in farmer income, are effective mechanisms by which AGPTs improve environmental efficiency. Robustness assessments and sensitivity analyses validate the aforementioned conclusions.
Significance
Through addressing both economic and ecological outcomes, the study offers essential insights into the transformative potential of adopting multiple AGPTs. Such findings inform investments in eco-efficient technologies that optimize resource use while minimizing environmental repercussions, thus advancing the objectives of sustainable agricultural development. The study provides a deeper understanding of how and why AGPTs' adoption enhances sustainable food production, and thereby identifies leverage points where interventions can amplify positive outcomes. In contrast to previous studies, we adopt a contemporary causal mediation model to assess the causal roles of mediators. It further enriches a broader and context-specific understanding of how the adoption of AGPTs influences eco-efficiency in diverse ways.
{"title":"Does the adoption of agricultural green production technologies improve eco-efficiency? Evidence from wheat farmers in Ethiopia","authors":"Tadesse Tolera Ejeta , Xiuguang Bai","doi":"10.1016/j.agsy.2025.104517","DOIUrl":"10.1016/j.agsy.2025.104517","url":null,"abstract":"<div><h3>Context</h3><div>Adopting agricultural green production technologies (AGPTs) is an efficient approach for achieving sustainable food production. The relationship between AGPTs and eco-efficiency is still ambiguous.</div></div><div><h3>Objective</h3><div>This study examines the direct, indirect, and heterogeneous effects of AGPTs adoption on eco-efficiency in wheat production.</div></div><div><h3>Methods</h3><div>Farm-level data from 506 wheat farmers were utilized. A structured survey questionnaire with a focus group discussion was conducted. The study utilized super-SBM, multinomial endogenous switching regression, causal mediation, and quantile regression models to attain its objectives. This paper outlines the adoption of AGPTs for organic fertilizer, green pest control, and soil improvement, both individually and in combination.</div></div><div><h3>Results and conclusions</h3><div>The findings demonstrate that the adoption of AGPTs can significantly enhance the eco-efficiency of wheat production, with the combined AGPTs exhibiting the most substantial impact, which is 20 % for adopters and 15.43 % for non-adopters. The heterogeneity analysis results reveal that the impact of AGPTs adoption on eco-efficiency is particularly significant among large landholders, farmers with poorer eco-efficiency, and those located in resource-endowed production zones. Reductions in fertilizers and pesticides, along with enhancements in farmer income, are effective mechanisms by which AGPTs improve environmental efficiency. Robustness assessments and sensitivity analyses validate the aforementioned conclusions.</div></div><div><h3>Significance</h3><div>Through addressing both economic and ecological outcomes, the study offers essential insights into the transformative potential of adopting multiple AGPTs. Such findings inform investments in eco-efficient technologies that optimize resource use while minimizing environmental repercussions, thus advancing the objectives of sustainable agricultural development. The study provides a deeper understanding of how and why AGPTs' adoption enhances sustainable food production, and thereby identifies leverage points where interventions can amplify positive outcomes. In contrast to previous studies, we adopt a contemporary causal mediation model to assess the causal roles of mediators. It further enriches a broader and context-specific understanding of how the adoption of AGPTs influences eco-efficiency in diverse ways.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104517"},"PeriodicalIF":6.1,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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