Pub Date : 2025-12-25DOI: 10.1016/j.agsy.2025.104630
Jack H. Grant , Dorothee Scharpenberg , Louise Manning
CONTEXT
Algorithm-based fertiliser recommendations offer substantial potential to improve Nitrogen Use Efficiency (NUE) and support economic and environmental sustainability. However, adoption among farmers in the United Kingdom (UK) remains limited, partly due to algorithm aversion, i.e., the tendency to distrust or avoid algorithmic-generated recommendations, even when they provide benefits.
OBJECTIVE
This study examines algorithm aversion in fertiliser-related decision-making among UK farmers and agronomists. Aiming to identify key barriers to adopting decision-support tools (DSTs), improving understanding of stakeholder trust dynamics, and exploring strategies to improve uptake.
METHODS
An online survey of 50 farmers and 26 agronomists assessed confidence in algorithmic recommendations versus human advice, understanding of NUE, perceived adoption barriers, and openness to non-traditional fertiliser recommendations. A follow-up workshop with 10 participants in DSTs trials provided qualitative insights into trust and usability.
RESULTS AND CONCLUSIONS
Farmers reported significantly greater trust in human advice compared to algorithmic recommendations (median 8 vs. 6, p < .001), whereas agronomists showed the reverse pattern (median 8 vs. 7.0, p < .001). Perceived barriers included cost concerns, poor system integration, complexity, and confusion over metrics. Whilst some farmers showed low levels of NUE literacy, agronomists demonstrated higher NUE literacy. Farmers relied on advice grounded in social trust and shared beliefs, while agronomists viewed algorithmic outputs as complements to technical expertise. Workshop participants found DST dashboards informative but often overwhelming.
SIGNIFICANCE
Addressing algorithm aversion through improved interface design, transparency, and tailored education, particularly via trusted advisors, may bridge the trust gap and facilitate digital tool adoption.
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The agroecological transition underscores the need to rethink knowledge production in agriculture, especially in relation to experimentation. This includes involving a wider range of stakeholders and exploring diverse and complementary forms of experimentation.
Objective
This article aims to shed light on the diversity of existing collective experimentations, in order to document the ongoing renewal of experimental approaches and to propose benchmarks for understanding and supporting them.
Methods
We conducted 34 semi-structured interviews and 10 observant participations, leading to the identification of 28 case studies that we define as collective experimentations. We define collective experimentation as the process of implementing and monitoring an intervention with uncertain outcomes, which leads to the production of knowledge. We did a comprehensive analysis of these collective experimentations, to understand how and why they are conducted. To do so, our analysis considered both the physical design of the experimental setups and the questions addressed, as well as the collective organization of the actors involved.
Results and Conclusions
We propose six idealtypes of collective experimentations: Idealtype A: Replicating experimental situations to generate standardized data, Idealtype B: Integrating data from diverse experimental practices in a joint analysis, Idealtype C: Distributing questions to generate knowledge on a common topic, Idealtype D: Pooling a diversity of experiences to explore a common subject, Idealtype E: Distributing activities within a single experimental situation and Idealtype F: Gathering human and material resources on a single site to experiment jointly on several experimental situations.
Significance
These idealtypes shed light on the diversity of collective experimentation approaches in agriculture, which are often under described in the literature. By offering a set of structured reference points, it can support researchers, facilitators, and practitioners in recognizing, designing and valuing collective experimentations adapted to their contexts. It opens new perspectives for rethinking how experimental knowledge is produced, shared, and valued to support agroecological transitions.
{"title":"Revealing the diversity of collective experimentation in agriculture: Constructing idealtypes from French case studies","authors":"Maïté de Sainte Agathe , Chantal Loyce , Lorène Prost , Quentin Toffolini","doi":"10.1016/j.agsy.2025.104623","DOIUrl":"10.1016/j.agsy.2025.104623","url":null,"abstract":"<div><h3>Context</h3><div>The agroecological transition underscores the need to rethink knowledge production in agriculture, especially in relation to experimentation. This includes involving a wider range of stakeholders and exploring diverse and complementary forms of experimentation.</div></div><div><h3>Objective</h3><div>This article aims to shed light on the diversity of existing collective experimentations, in order to document the ongoing renewal of experimental approaches and to propose benchmarks for understanding and supporting them.</div></div><div><h3>Methods</h3><div>We conducted 34 semi-structured interviews and 10 observant participations, leading to the identification of 28 case studies that we define as collective experimentations. We define collective experimentation as the process of implementing and monitoring an intervention with uncertain outcomes, which leads to the production of knowledge. We did a comprehensive analysis of these collective experimentations, to understand how and why they are conducted. To do so, our analysis considered both the physical design of the experimental setups and the questions addressed, as well as the collective organization of the actors involved.</div></div><div><h3>Results and Conclusions</h3><div>We propose six idealtypes of collective experimentations: Idealtype A: Replicating experimental situations to generate standardized data, Idealtype B: Integrating data from diverse experimental practices in a joint analysis, Idealtype C: Distributing questions to generate knowledge on a common topic, Idealtype D: Pooling a diversity of experiences to explore a common subject, Idealtype E: Distributing activities within a single experimental situation and Idealtype F: Gathering human and material resources on a single site to experiment jointly on several experimental situations.</div></div><div><h3>Significance</h3><div>These idealtypes shed light on the diversity of collective experimentation approaches in agriculture, which are often under described in the literature. By offering a set of structured reference points, it can support researchers, facilitators, and practitioners in recognizing, designing and valuing collective experimentations adapted to their contexts. It opens new perspectives for rethinking how experimental knowledge is produced, shared, and valued to support agroecological transitions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104623"},"PeriodicalIF":6.1,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823136","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 : 2025-12-24DOI: 10.1016/j.agsy.2025.104626
Deyao Liu , Baobao Pan , Huarui Gong , Jing Li , Enli Wang , Jinxi Zhao , Yan Xu , Shu Kee Lam , Deli Chen
CONTEXT
Optimising crop calendars by adjusting sowing dates and the timing and frequency of key management practices can enhance crop productivity while reducing greenhouse gas (GHG) emissions. However, limited research has explored how farmers dynamically adapt crop calendars and practices in response to climate shifts to support climate-smart agriculture.
OBJECTIVE
This study developed a DNDC-based hybrid modelling framework to evaluate adaptive management strategies for supporting climate-smart agriculture under future climate scenarios.
METHODS
We assessed three management levels: fertiliser application rates (level 1); fertiliser rates combined with crop calendar adjustments, including fertiliser timing, frequency, as well as sowing and harvesting dates (level 2) and level 2 plus irrigation and residue retention (level 3). The framework was designed to optimise management under multiple objectives, including increasing crop yield, SOC sequestration, while simultaneously reducing N input and GHG emissions.
RESULTS AND CONCLUSIONS
From 1990 to 2100, the optimised crop calendars were identified: delaying wheat basal fertilisation (+5 d,) while advancing top-dressing (−5 d), postponing wheat sowing (+5 d) and advancing maize sowing (−9 d); advancing both fertilisation events in maize (−9 d, −3 d); aligning irrigation with fertilisation; and adding one irrigation event during the maize bell stage. Compared with historical practices, these adjustments increased annual crop yields and NUE by 4.2 % and 15.8 %, respectively, while reducing net GHG emissions and GHG intensity by 5.1 % and 8.5 %, respectively. The optimised management reduced N inputs, irrigation water and residue retention by 17.2 %, 6.7 % and 20.0 %, respectively.
SIGNIFICANCE
These findings demonstrate that adaptive crop calendars can significantly advance climate-smart agriculture and should be incorporated into climate change impact assessments.
{"title":"Optimising crop calendars with management practices promotes climate-smart agriculture in wheat-maize rotations of the North China Plain","authors":"Deyao Liu , Baobao Pan , Huarui Gong , Jing Li , Enli Wang , Jinxi Zhao , Yan Xu , Shu Kee Lam , Deli Chen","doi":"10.1016/j.agsy.2025.104626","DOIUrl":"10.1016/j.agsy.2025.104626","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Optimising crop calendars by adjusting sowing dates and the timing and frequency of key management practices can enhance crop productivity while reducing greenhouse gas (GHG) emissions. However, limited research has explored how farmers dynamically adapt crop calendars and practices in response to climate shifts to support climate-smart agriculture.</div></div><div><h3>OBJECTIVE</h3><div>This study developed a DNDC-based hybrid modelling framework to evaluate adaptive management strategies for supporting climate-smart agriculture under future climate scenarios.</div></div><div><h3>METHODS</h3><div>We assessed three management levels: fertiliser application rates (level 1); fertiliser rates combined with crop calendar adjustments, including fertiliser timing, frequency, as well as sowing and harvesting dates (level 2) and level 2 plus irrigation and residue retention (level 3). The framework was designed to optimise management under multiple objectives, including increasing crop yield, SOC sequestration, while simultaneously reducing N input and GHG emissions.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>From 1990 to 2100, the optimised crop calendars were identified: delaying wheat basal fertilisation (+5 d,) while advancing top-dressing (−5 d), postponing wheat sowing (+5 d) and advancing maize sowing (−9 d); advancing both fertilisation events in maize (−9 d, −3 d); aligning irrigation with fertilisation; and adding one irrigation event during the maize bell stage. Compared with historical practices, these adjustments increased annual crop yields and NUE by 4.2 % and 15.8 %, respectively, while reducing net GHG emissions and GHG intensity by 5.1 % and 8.5 %, respectively. The optimised management reduced N inputs, irrigation water and residue retention by 17.2 %, 6.7 % and 20.0 %, respectively.</div></div><div><h3>SIGNIFICANCE</h3><div>These findings demonstrate that adaptive crop calendars can significantly advance climate-smart agriculture and should be incorporated into climate change impact assessments.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104626"},"PeriodicalIF":6.1,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823105","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 : 2025-12-22DOI: 10.1016/j.agsy.2025.104624
Kalyan Roy , Marta Monjardino , Mohammed Mainuddin , Sukamal Sarkar , Krishnendu Ray , Poulami Sen , Srijan Samanta , Akash Panda , Sanchayeeta Misra , Argha Ghosh , Esmat Ara Begum , Rupak Goswami
Context
Sustainable Intensification (SI) aims to boost smallholder productivity while conserving natural resources. However, farm-level heterogeneity often limits equitable access to SI benefits. While most typology studies rely on quantitative methods, few use integrated mixed methods to develop scalable typologies from small samples, especially in fragile agroecosystems.
Objectives
This study aimed to: a) classify heterogenous farms using participatory and statistical methods; b) construct a flexible decision support tree to scale out farm typologies to locations beyond initial study area; and c) examine the validity and usefulness of the scalable farm types through stakeholder engagement.
Methods
A mixed-methods design was used. First, Focus Group Discussions in four villages used a participatory card-sorting exercise where farmers classified 202 beneficiary households by eight visualized parameters (cropping pattern, landholding, off-farm income, etc.). The resulting farmer-defined groups formed the basis for respondent sampling in the questionnaire survey. Quantitative data from survey were subjected to Principal Component Analysis and Cluster Analysis to identify statistical farm types. Farm types were characterized using the household data and five-year recall data on changing livelihoods trends. For wider application, a Classification and Regression Tree (CRT) analysis was performed to generate a decision tree, using the identified farm types as target variable The tree was refined and successfully applied in new locations, with validation from local experts. Yield differences of SI technology (Zero-Tillage Potato) across farm types were compared between expert and empirical classifications.
Results and conclusions
Statistical analysis identified five dynamic farm types, including a distinct landless group, ranging from resource-rich to resource-poor. The CRT classified seven types with 86.6 % accuracy using binary splits on landholding, livestock, income, irrigation, and crop diversity, with additional branches for unique configurations. Expert validation showed strong concordance. Field testing revealed yield differences across farm types, aligning with expert classifications. The typology illustrates a progression from low-input systems to diversified, resource-rich farms integrating crops, livestock, fisheries, and innovations in water, nutrients, mechanization, and markets.
Significance
The study demonstrates the utility of typologies not only for classification but also for effectively targeting SI interventions. This scalable, context-sensitive framework supports innovation upscaling in heterogeneous agroecosystems, especially where longitudinal data are unavailable.
{"title":"Developing scalable farm typologies to guide sustainable intensification in the fragile agroecosystems of the Indian Sundarbans","authors":"Kalyan Roy , Marta Monjardino , Mohammed Mainuddin , Sukamal Sarkar , Krishnendu Ray , Poulami Sen , Srijan Samanta , Akash Panda , Sanchayeeta Misra , Argha Ghosh , Esmat Ara Begum , Rupak Goswami","doi":"10.1016/j.agsy.2025.104624","DOIUrl":"10.1016/j.agsy.2025.104624","url":null,"abstract":"<div><h3>Context</h3><div>Sustainable Intensification (SI) aims to boost smallholder productivity while conserving natural resources. However, farm-level heterogeneity often limits equitable access to SI benefits. While most typology studies rely on quantitative methods, few use integrated mixed methods to develop scalable typologies from small samples, especially in fragile agroecosystems.</div></div><div><h3>Objectives</h3><div>This study aimed to: a) classify heterogenous farms using participatory and statistical methods; b) construct a flexible decision support tree to scale out farm typologies to locations beyond initial study area; and c) examine the validity and usefulness of the scalable farm types through stakeholder engagement.</div></div><div><h3>Methods</h3><div>A mixed-methods design was used. First, Focus Group Discussions in four villages used a participatory card-sorting exercise where farmers classified 202 beneficiary households by eight visualized parameters (cropping pattern, landholding, off-farm income, etc.). The resulting farmer-defined groups formed the basis for respondent sampling in the questionnaire survey. Quantitative data from survey were subjected to Principal Component Analysis and Cluster Analysis to identify statistical farm types. Farm types were characterized using the household data and five-year recall data on changing livelihoods trends. For wider application, a Classification and Regression Tree (CRT) analysis was performed to generate a decision tree, using the identified farm types as target variable The tree was refined and successfully applied in new locations, with validation from local experts. Yield differences of SI technology (Zero-Tillage Potato) across farm types were compared between expert and empirical classifications.</div></div><div><h3>Results and conclusions</h3><div>Statistical analysis identified five dynamic farm types, including a distinct landless group, ranging from resource-rich to resource-poor. The CRT classified seven types with 86.6 % accuracy using binary splits on landholding, livestock, income, irrigation, and crop diversity, with additional branches for unique configurations. Expert validation showed strong concordance. Field testing revealed yield differences across farm types, aligning with expert classifications. The typology illustrates a progression from low-input systems to diversified, resource-rich farms integrating crops, livestock, fisheries, and innovations in water, nutrients, mechanization, and markets.</div></div><div><h3>Significance</h3><div>The study demonstrates the utility of typologies not only for classification but also for effectively targeting SI interventions. This scalable, context-sensitive framework supports innovation upscaling in heterogeneous agroecosystems, especially where longitudinal data are unavailable.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104624"},"PeriodicalIF":6.1,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837423","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 : 2025-12-22DOI: 10.1016/j.agsy.2025.104614
Yifan Gu , Zixin Bian , Qianqian Shi , Ziyi Zhao , Haixia Li , Rui Li , He Peng , Ming Yang , Qingbin Yuan , Yufeng Wu
BACKGROUND
Plastic mulching film (PMF) is extensively applied in cotton cultivation to enhance yields, yet its comprehensive environmental consequences remain inadequately quantified.
OBJECTIVE
This study aims to quantify the multi-dimensional impacts of PMF on cotton production across 18 Chinese provinces by developing a yield–biomass–water–environment (YBWE) nexus analysis model.
METHODS
Integrating the WOFOST crop model, mixed regression, and life cycle assessment (LCA), we evaluated effects across 35 cross-cutting promotion scenarios, accounting for provincial disparities in natural conditions and agricultural practices.
RESULTS AND DISCUSSION
PMF promotion is projected to increase China's average cotton yield from 2.41 t/ha to 3.21 t/ha by 2050, with the most significant gains in the northwest inland region. While improving water use efficiency, PMF exacerbates water scarcity in arid areas, increasing consumption by 564.93 t/ha in the northwest. A “V-shaped” PMF residue belt will form, raising aggregate environmental impacts by 74.74 % compared to 2021. Economically, PMF boosts profits—especially in the northwest (up to USD 1890.61/ha)—but over 50 % of provinces face net ecological losses. The optimal scenario couples high-intensity PMF promotion in low-income regions with high-strength PMF application, reducing environmental impacts by over 40 % and avoiding USD 1.83 trillion in ecological costs.
SIGNIFICANCE
This study provides a scientifically supported strategy for PMF promotion that balances yield growth with environmental sustainability, informing policy for coordinated agricultural and ecological development.
{"title":"The yield-biomass-water-environment nexus model unravels the plastic mulching film dilemma: Yield gains vs. environmental cascades in China’s cotton systems","authors":"Yifan Gu , Zixin Bian , Qianqian Shi , Ziyi Zhao , Haixia Li , Rui Li , He Peng , Ming Yang , Qingbin Yuan , Yufeng Wu","doi":"10.1016/j.agsy.2025.104614","DOIUrl":"10.1016/j.agsy.2025.104614","url":null,"abstract":"<div><h3>BACKGROUND</h3><div>Plastic mulching film (PMF) is extensively applied in cotton cultivation to enhance yields, yet its comprehensive environmental consequences remain inadequately quantified.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to quantify the multi-dimensional impacts of PMF on cotton production across 18 Chinese provinces by developing a yield–biomass–water–environment (YBWE) nexus analysis model.</div></div><div><h3>METHODS</h3><div>Integrating the WOFOST crop model, mixed regression, and life cycle assessment (LCA), we evaluated effects across 35 cross-cutting promotion scenarios, accounting for provincial disparities in natural conditions and agricultural practices.</div></div><div><h3>RESULTS AND DISCUSSION</h3><div>PMF promotion is projected to increase China's average cotton yield from 2.41 t/ha to 3.21 t/ha by 2050, with the most significant gains in the northwest inland region. While improving water use efficiency, PMF exacerbates water scarcity in arid areas, increasing consumption by 564.93 t/ha in the northwest. A “V-shaped” PMF residue belt will form, raising aggregate environmental impacts by 74.74 % compared to 2021. Economically, PMF boosts profits—especially in the northwest (up to USD 1890.61/ha)—but over 50 % of provinces face net ecological losses. The optimal scenario couples high-intensity PMF promotion in low-income regions with high-strength PMF application, reducing environmental impacts by over 40 % and avoiding USD 1.83 trillion in ecological costs.</div></div><div><h3>SIGNIFICANCE</h3><div>This study provides a scientifically supported strategy for PMF promotion that balances yield growth with environmental sustainability, informing policy for coordinated agricultural and ecological development.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104614"},"PeriodicalIF":6.1,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837422","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 : 2025-12-19DOI: 10.1016/j.agsy.2025.104618
Qiankun Niu , Mika Jalava , Vilma Sandström , Kpade O.L. Hounkpatin , Sina Masoumzadeh Sayyar , Dandan Zhao , Matias Heino , Matti Kummu
CONTEXT
As part of sustainable crop intensification, multiple cropping has emerged as a promising solution for enhancing agricultural productivity without expanding cropland. Although existing studies have explored conditions required for multiple cropping adoption, a comprehensive, global assessment of the potential for transition from single to multiple cropping remains lacking.
OBJECTIVE
This study aims to i) identify the most influential determinants affecting global cropping systems from biophysical, agricultural input-related, and socio-economic perspectives; ii) quantify their associations with single versus multiple cropping at 30 arc-min resolution; and iii) assess the potential for adopting multiple cropping on cropland currently under single cropping for maize, wheat, rice, and soybean.
METHODS
We employed eXtreme Gradient Boosting (XGBoost) to quantify relationships between cropping systems and global variables, including climate, water, environment, agriculture, and socio-economics with consistent temporal coverage (1998–2002). To delineate potential transition zones, we applied K-means clustering to these variable groups across four crops, comparing the similarities and differences in growing conditions in single and multiple cropping systems.
RESULTS AND CONCLUSIONS
Climate variations and agricultural inputs are the most important sets of variables shaping multiple cropping potential. Single cropping systems on 80 million hectares (8 % of global single-cropped land) could transition to multiple cropping across the four crops. Transition potential is, on average, 35 % higher in irrigated systems than in rainfed systems, and the area suitable for transition is 1.7 times larger in irrigated systems. These areas are concentrated in North America, Southeast Asia, and Southern Europe.
SIGNIFICANCE
Our findings highlight both promising targets for sustainable intensification and critical data gaps under current climatic conditions, thereby helping to prioritize regions for subsequent, site-specific analysis and targeted interventions toward sustainable food systems under a changing climate.
{"title":"Assessing the global potential for transition from single to multiple cropping","authors":"Qiankun Niu , Mika Jalava , Vilma Sandström , Kpade O.L. Hounkpatin , Sina Masoumzadeh Sayyar , Dandan Zhao , Matias Heino , Matti Kummu","doi":"10.1016/j.agsy.2025.104618","DOIUrl":"10.1016/j.agsy.2025.104618","url":null,"abstract":"<div><h3>CONTEXT</h3><div>As part of sustainable crop intensification, multiple cropping has emerged as a promising solution for enhancing agricultural productivity without expanding cropland. Although existing studies have explored conditions required for multiple cropping adoption, a comprehensive, global assessment of the potential for transition from single to multiple cropping remains lacking.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to i) identify the most influential determinants affecting global cropping systems from biophysical, agricultural input-related, and socio-economic perspectives; ii) quantify their associations with single versus multiple cropping at 30 arc-min resolution; and iii) assess the potential for adopting multiple cropping on cropland currently under single cropping for maize, wheat, rice, and soybean.</div></div><div><h3>METHODS</h3><div>We employed eXtreme Gradient Boosting (XGBoost) to quantify relationships between cropping systems and global variables, including climate, water, environment, agriculture, and socio-economics with consistent temporal coverage (1998–2002). To delineate potential transition zones, we applied K-means clustering to these variable groups across four crops, comparing the similarities and differences in growing conditions in single and multiple cropping systems.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Climate variations and agricultural inputs are the most important sets of variables shaping multiple cropping potential. Single cropping systems on 80 million hectares (8 % of global single-cropped land) could transition to multiple cropping across the four crops. Transition potential is, on average, 35 % higher in irrigated systems than in rainfed systems, and the area suitable for transition is 1.7 times larger in irrigated systems. These areas are concentrated in North America, Southeast Asia, and Southern Europe.</div></div><div><h3>SIGNIFICANCE</h3><div>Our findings highlight both promising targets for sustainable intensification and critical data gaps under current climatic conditions, thereby helping to prioritize regions for subsequent, site-specific analysis and targeted interventions toward sustainable food systems under a changing climate.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104618"},"PeriodicalIF":6.1,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784899","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 : 2025-12-18DOI: 10.1016/j.agsy.2025.104621
Boru Douthwaite , Gary Goggins , Andy Bleasdale , Pamela Boyle , Ciara Carberry , Patrick Crushell , Brian Delaney , Brendan Dunford , Catherine Keena , Victoria McArthur , James Moran , John Muldowney , Barry O'Donoghue , Caroline Sullivan , Derek McLoughlin
CONTEXT
Prescription-based agri-environmental schemes have demonstrated poor return on investment, prompting exploration of alternative mechanisms including results-based and hybrid approaches. Ireland's decision to mainstream Results-Based agri-environmental Payment Schemes (RBPS) in its 2023–2027 Common Agricultural Policy (CAP) Strategic Plan represents Europe's largest implementation of RBPS in agricultural policy.
OBJECTIVES
To analyze the policy decision-making process behind Ireland's mainstreaming of RBPS, examining how this innovative agri-environmental policy was developed and the factors that enabled its large-scale implementation within the CAP framework.
METHODS
The study employed three complementary analytical perspectives: historical timeline analysis, complex adaptive systems theory, and policy windows theory. Data collection involved interviews with 14 key stakeholders, a validation workshop and analysis of relevant literature.
RESULTS AND CONCLUSIONS
RBPS emerged through a 20-year evolutionary process involving pilot projects, evidence building, and sustained advocacy by a ‘coalition of the willing’. Pilot projects played a crucial role in providing proof of concept, building implementation capacity, and developing methodologies. Policy change resulted from the strategic combination of ongoing advocacy efforts with the effective utilization of policy windows, particularly CAP cycles. However, scaling RBPS nationally presents implementation challenges, especially concerning IT systems and administrative capacity.
SIGNIFICANCE
This research contributes to understanding how innovative agri-environmental policies can be effectively developed and implemented at scale. Multiple analytical perspectives provide valuable insights for future policy development in complex governance domains. Key recommendations for strengthening future implementation include upgrading technical infrastructure, enhancing farmer engagement, improving training programs, refining payment structures, and better advance planning.
{"title":"Pilots, proponents and policy windows: How Results-Based Payment Schemes (RBPS) became mainstream in Irish agri-environmental policy","authors":"Boru Douthwaite , Gary Goggins , Andy Bleasdale , Pamela Boyle , Ciara Carberry , Patrick Crushell , Brian Delaney , Brendan Dunford , Catherine Keena , Victoria McArthur , James Moran , John Muldowney , Barry O'Donoghue , Caroline Sullivan , Derek McLoughlin","doi":"10.1016/j.agsy.2025.104621","DOIUrl":"10.1016/j.agsy.2025.104621","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Prescription-based agri-environmental schemes have demonstrated poor return on investment, prompting exploration of alternative mechanisms including results-based and hybrid approaches. Ireland's decision to mainstream Results-Based agri-environmental Payment Schemes (RBPS) in its 2023–2027 Common Agricultural Policy (CAP) Strategic Plan represents Europe's largest implementation of RBPS in agricultural policy.</div></div><div><h3>OBJECTIVES</h3><div>To analyze the policy decision-making process behind Ireland's mainstreaming of RBPS, examining how this innovative agri-environmental policy was developed and the factors that enabled its large-scale implementation within the CAP framework.</div></div><div><h3>METHODS</h3><div>The study employed three complementary analytical perspectives: historical timeline analysis, complex adaptive systems theory, and policy windows theory. Data collection involved interviews with 14 key stakeholders, a validation workshop and analysis of relevant literature.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>RBPS emerged through a 20-year evolutionary process involving pilot projects, evidence building, and sustained advocacy by a ‘coalition of the willing’. Pilot projects played a crucial role in providing proof of concept, building implementation capacity, and developing methodologies. Policy change resulted from the strategic combination of ongoing advocacy efforts with the effective utilization of policy windows, particularly CAP cycles. However, scaling RBPS nationally presents implementation challenges, especially concerning IT systems and administrative capacity.</div></div><div><h3>SIGNIFICANCE</h3><div>This research contributes to understanding how innovative agri-environmental policies can be effectively developed and implemented at scale. Multiple analytical perspectives provide valuable insights for future policy development in complex governance domains. Key recommendations for strengthening future implementation include upgrading technical infrastructure, enhancing farmer engagement, improving training programs, refining payment structures, and better advance planning.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104621"},"PeriodicalIF":6.1,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787443","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 : 2025-12-17DOI: 10.1016/j.agsy.2025.104620
Zhaoqiang Jin , Qianqian Chen , Meilin Chen , Matthew Tom Harrison , Shijie Shi , Ke Liu , Liying Huang , Xiaohai Tian , Yunbo Zhang , Lixiao Nie
Context
In contemporary Chinese agriculture, rice production relies heavily on intensive water and nitrogen inputs. However, the scientific literature lacks comprehensive assessments of the carbon footprint and net ecosystem economic benefits of rice under varying water‑nitrogen management scenarios.
Objective
This study aims to systematically evaluate the effects of water‑nitrogen coupling on the carbon footprint and net ecosystem economic benefits of rice cultivation.
Methods
A field experiment with three water management practices (rainfed, alternating wet and dry irrigation, and flooded irrigation) and four nitrogen fertilizer application levels (0, 50, 100, and 150 kg N ha−1) was conducted in 2021 and 2022. This study comprehensively assessed the effects of different water and nitrogen management practices on greenhouse gas emissions, carbon footprint, and net ecosystem economic benefits of black rice production.
Results and conclusions
Results showed that rainfed conditions reduced the global warming potential, greenhouse gas intensity, and carbon footprint of rice by 37.57 %, 27.85 %, and 20.82 % relative to alternating wet and dry irrigation, and by 49.64 %, 41.58 %, and 35.96 % compared to flooded irrigation. Concurrently, net ecosystem economic benefits decreased by 22.76 % and 15.53 % under rainfed conditions relative to alternating wet and dry irrigation and flooded irrigation, respectively. Nitrogen fertilization also exhibited differential effects; for ≤100 kg ha−1, incremental nitrogen inputs enhanced net ecosystem economic benefits without commensurate increases in greenhouse gas intensity and carbon footprint. Applications exceeding 100 kg ha−1 significantly increased carbon footprint and greenhouse gas intensity, diminishing net ecosystem economic benefits. Diesel fuel, nitrogen fertilizers, and agricultural machinery were primary contributors to greenhouse gas emissions in rice production, underscoring the necessity of reducing irrigation water and nitrogen application rates for effective greenhouse gas mitigation. We conclude that the alternating wet and dry irrigation with a nitrogen application rate of 100 kg ha−1 treatment optimized environmental and economic outcomes, achieving lower carbon footprint and higher net ecosystem economic benefits.
Significance
The findings provide valuable insights for achieving the balance between environmental sustainability and economic benefits of rice production, which is of great significance for the establishment of a green and efficient rice production technology system and the formulation of related agricultural production policies in China.
在当代中国农业中，水稻生产严重依赖于密集的水和氮投入。然而，科学文献缺乏对不同水氮管理情景下水稻的碳足迹和净生态系统经济效益的综合评估。目的系统评价水氮耦合对水稻种植碳足迹和净生态系统经济效益的影响。方法在2021年和2022年分别进行3种水管理方式（雨养、干湿交替灌溉和淹水灌溉）和4个氮肥施用水平（0、50、100和150 kg N ha−1）的田间试验。本研究综合评价了不同水氮管理措施对黑米生产温室气体排放、碳足迹和净生态系统经济效益的影响。结果与结论结果表明，旱作条件下水稻的全球变暖潜势、温室气体强度和碳足迹分别比干湿交替灌溉降低了37.57%、27.85%和20.82%，比淹水灌溉分别降低了49.64%、41.58%和35.96%。与干湿交替灌溉和淹水灌溉相比，雨养条件下的生态系统净经济效益分别下降22.76%和15.53%。施氮也表现出差异效应；在≤100 kg ha−1的情况下，增加的氮投入增加了生态系统的净经济效益，而温室气体强度和碳足迹没有相应增加。施用超过100 kg ha - 1显著增加了碳足迹和温室气体强度，降低了生态系统的净经济效益。柴油燃料、氮肥和农业机械是水稻生产中温室气体排放的主要来源，这突出表明，为了有效减少温室气体排放，必须减少灌溉用水和氮肥施用量。综上所述，施氮量为100 kg ha - 1的干湿交替灌溉优化了环境和经济效益，实现了更低的碳足迹和更高的净生态系统经济效益。研究结果为实现水稻生产的环境可持续性与经济效益之间的平衡提供了有价值的见解，对中国建立绿色高效的水稻生产技术体系和制定相关农业生产政策具有重要意义。
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Pub Date : 2025-12-17DOI: 10.1016/j.agsy.2025.104616
Jean Hercher-Pasteur , Ronaldo Vibart , Andre Mazzetto , Maria Paz Tieri , Claudia Faverin , Sofia Stirling , Dirk Wallace , Verónica Ciganda , Santiago Fariña , Alvaro Romera
CONTEXT
This study investigates the integration potential of crop-livestock systems within dairy production in Uruguay, New Zealand, and Argentina, addressing the dual challenges of increasing food production and enhancing environmental sustainability.
OBJECTIVE
The objective is to explore integration strategies for dairy farm systems in order to increase food output and circularity, reduce GHG-e, nutrient losses and improve production system resiliency.
METHODS
We developed a framework and modeled four progressive scenarios for each country's dairy systems, focusing on energy flows, carbon emissions, and nitrogen balance.
RESULTS AND CONCLUSIONS
The results indicate that higher levels of integration significantly reduce environmental impacts and increase resilience. Specifically, as integration increases, the Energy Return on Investment (EROI) improves due to enhanced self-sufficiency and reduced reliance on external feed sources. For instance, the transition from conventional to ecosystem-based practices led to notable reductions in greenhouse gas (GHG) emissions, achieving lower carbon footprint through increased diversification and the incorporation of agroforestry. Nitrogen use efficiency also showed marked improvements as nitrogen surpluses decreased across scenarios, primarily due to better management of animal excretions and the integration of crops. Despite the promising outcomes, challenges remain, including farmers' capacity to diversify and the substantial investments in infrastructure and management required to facilitate such transitions.
SIGNIFICANCE
Ultimately, this study underscores the importance of integrating crop-livestock systems to address the complexities of sustainable dairy production, while also urging further exploration into practical strategies that can support farmers in adapting to environmental and economic pressures.
{"title":"Integrated crop-ruminant livestock systems as a strategy to increase energy, carbon and nutrient circularity: Exploring scenarios in dairy production systems across the southern hemisphere","authors":"Jean Hercher-Pasteur , Ronaldo Vibart , Andre Mazzetto , Maria Paz Tieri , Claudia Faverin , Sofia Stirling , Dirk Wallace , Verónica Ciganda , Santiago Fariña , Alvaro Romera","doi":"10.1016/j.agsy.2025.104616","DOIUrl":"10.1016/j.agsy.2025.104616","url":null,"abstract":"<div><h3>CONTEXT</h3><div>This study investigates the integration potential of crop-livestock systems within dairy production in Uruguay, New Zealand, and Argentina, addressing the dual challenges of increasing food production and enhancing environmental sustainability.</div></div><div><h3>OBJECTIVE</h3><div>The objective is to explore integration strategies for dairy farm systems in order to increase food output and circularity, reduce GHG-e, nutrient losses and improve production system resiliency.</div></div><div><h3>METHODS</h3><div>We developed a framework and modeled four progressive scenarios for each country's dairy systems, focusing on energy flows, carbon emissions, and nitrogen balance.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results indicate that higher levels of integration significantly reduce environmental impacts and increase resilience. Specifically, as integration increases, the Energy Return on Investment (EROI) improves due to enhanced self-sufficiency and reduced reliance on external feed sources. For instance, the transition from conventional to ecosystem-based practices led to notable reductions in greenhouse gas (GHG) emissions, achieving lower carbon footprint through increased diversification and the incorporation of agroforestry. Nitrogen use efficiency also showed marked improvements as nitrogen surpluses decreased across scenarios, primarily due to better management of animal excretions and the integration of crops. Despite the promising outcomes, challenges remain, including farmers' capacity to diversify and the substantial investments in infrastructure and management required to facilitate such transitions.</div></div><div><h3>SIGNIFICANCE</h3><div>Ultimately, this study underscores the importance of integrating crop-livestock systems to address the complexities of sustainable dairy production, while also urging further exploration into practical strategies that can support farmers in adapting to environmental and economic pressures.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104616"},"PeriodicalIF":6.1,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787827","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 : 2025-12-16DOI: 10.1016/j.agsy.2025.104610
Julius Juma Okello , Sylvester Okoth Ojwang , David Jakinda Otieno , Robert O.M. Mwanga , Benard Yada , Hugo Campos , Simon Heck
<div><h3>CONTEXT</h3><div>Conventional breeding programs have hitherto been farmer-centric, prioritizing improvement of agronomic traits while neglecting trait preferences of other value chain actors. The supply-side focus may lead to low adoption of new varieties and food insecurity. Inclusive breeding is vital for meeting diverse customer needs.</div></div><div><h3>OBJECTIVE</h3><div>This study characterizes the multifunctional roles of sweetpotato actors and systematically assesses differences in varietal trait preferences among actors across the entire sweetpotato value chain in Uganda. It is premised on the CGIAR Excellence in Breeding platform's guide to inclusive demand-driven breeding that espouses the need to involve a broad range of stakeholders in breeding program design, hence innovation development. It provides useful insights on varietal trait preferences and needs of actors that are essential to produce future fit-for-purpose market preferred innovations.</div></div><div><h3>METHODS</h3><div>The study used a sequential mixed methods approach involving, first, systematic value chain-wide multidisciplinary consultations to elicit preferred sweetpotato traits. Second, collection of quantitative survey data from 1333 stakeholders identified primarily as producers (992), seed multipliers (68), processors (18), traders (97), and consumers (158). Third, a rigorous quantitative analysis to examine drivers of and trade-offs in varietal trait preferences by actor category.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings demonstrate the multifunctional roles of the actors and their varying trait preferences across the value chain. Actors with singular roles prioritize traits based on their immediate needs and commercial interests while those with joint roles exhibit a broader range of trait preferences. However, actors in both production and trading/consumption roles seek a balance between agronomic and quality traits, blending commercial and personal preferences. Regression analysis finds a higher preference for quality traits than agronomic traits as one moves downstream from producers to consumers. Mealiness is consistently preferred over agronomic and other quality traits. Also, overall, women have a balanced preference for both categories of traits.</div></div><div><h3>SIGNIFICANCE</h3><div>The study demonstrates a rigorous participatory research process for eliciting strategic information for decision-making in breeding. It supports the need for systematic market intelligence in crop breeding systems to make them more pluralistic and responsive to evolving trait preferences across the value chain. Embracing multi-actor preferences with fit-for-purpose crop breeding innovations/products can foster uptake of the new varieties and benefit all value chain actors once the mix of trait preferences is fully accounted for in breeding programs and necessary efforts are put in place to ensure the new varieties are successful.</d
{"title":"Incorporating multifunctional value chain actors' varietal trait preferences in sweetpotato breeding programs: A pathway towards inclusive innovation","authors":"Julius Juma Okello , Sylvester Okoth Ojwang , David Jakinda Otieno , Robert O.M. Mwanga , Benard Yada , Hugo Campos , Simon Heck","doi":"10.1016/j.agsy.2025.104610","DOIUrl":"10.1016/j.agsy.2025.104610","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Conventional breeding programs have hitherto been farmer-centric, prioritizing improvement of agronomic traits while neglecting trait preferences of other value chain actors. The supply-side focus may lead to low adoption of new varieties and food insecurity. Inclusive breeding is vital for meeting diverse customer needs.</div></div><div><h3>OBJECTIVE</h3><div>This study characterizes the multifunctional roles of sweetpotato actors and systematically assesses differences in varietal trait preferences among actors across the entire sweetpotato value chain in Uganda. It is premised on the CGIAR Excellence in Breeding platform's guide to inclusive demand-driven breeding that espouses the need to involve a broad range of stakeholders in breeding program design, hence innovation development. It provides useful insights on varietal trait preferences and needs of actors that are essential to produce future fit-for-purpose market preferred innovations.</div></div><div><h3>METHODS</h3><div>The study used a sequential mixed methods approach involving, first, systematic value chain-wide multidisciplinary consultations to elicit preferred sweetpotato traits. Second, collection of quantitative survey data from 1333 stakeholders identified primarily as producers (992), seed multipliers (68), processors (18), traders (97), and consumers (158). Third, a rigorous quantitative analysis to examine drivers of and trade-offs in varietal trait preferences by actor category.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings demonstrate the multifunctional roles of the actors and their varying trait preferences across the value chain. Actors with singular roles prioritize traits based on their immediate needs and commercial interests while those with joint roles exhibit a broader range of trait preferences. However, actors in both production and trading/consumption roles seek a balance between agronomic and quality traits, blending commercial and personal preferences. Regression analysis finds a higher preference for quality traits than agronomic traits as one moves downstream from producers to consumers. Mealiness is consistently preferred over agronomic and other quality traits. Also, overall, women have a balanced preference for both categories of traits.</div></div><div><h3>SIGNIFICANCE</h3><div>The study demonstrates a rigorous participatory research process for eliciting strategic information for decision-making in breeding. It supports the need for systematic market intelligence in crop breeding systems to make them more pluralistic and responsive to evolving trait preferences across the value chain. Embracing multi-actor preferences with fit-for-purpose crop breeding innovations/products can foster uptake of the new varieties and benefit all value chain actors once the mix of trait preferences is fully accounted for in breeding programs and necessary efforts are put in place to ensure the new varieties are successful.</d","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104610"},"PeriodicalIF":6.1,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787441","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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