Pub Date : 2025-11-25DOI: 10.1016/j.agsy.2025.104560
Simon Moakes , Philipp Oggiano , Jan Landert , Catherine Pfeifer , Laura de Baan
<div><h3>Context</h3><div>Agroecological innovations are seen as solutions to reduce environmental impacts of agriculture but can potentially lead to trade-offs with food production. Appropriate tools are needed to better understand synergies and trade-offs among environmental issues, resource efficiency and food production.</div></div><div><h3>Objective</h3><div>This study presents the FarmLCA tool, which models farms as interconnected crop-livestock systems and assesses environmental impacts from farms and farm-inputs. A mixed beef farm serves as case study to assess synergies and trade-offs of avoiding human edible feed in beef production.</div></div><div><h3>Methods</h3><div>FarmLCA allows the calculation of cradle-to-farm gate life cycle assessments (LCA). Emissions of environmentally harmful substances from crops and livestock are modelled based on the farm management. Upstream impacts from imported inputs (including fertilizer or feed) are accounted for with life cycle inventory data. Yields and nutrient requirements are checked for plausibility, based on management handbooks, while manure availability and composition are calculated based on livestock production. Environmental impacts, nutrient use efficiency and food production for a typical mixed beef farm in Scotland were calculated (<em>baseline</em>) and compared to alternative farm management scenarios: a <em>Feed-no-Food</em> scenario, avoiding concentrate feeds resulting in a smaller herd size and a <em>circular Feed-no-Food</em> scenario, additionally optimizing productivity and synergies between crop and livestock (e.g. more legumes in crop rotation, reduced replacement rate and feed waste).</div></div><div><h3>Results and conclusions</h3><div>In the <em>Feed-no-Food</em> scenario, the beef production was reduced by 25 %, but more calories and protein were produced overall due to cereal and legumes now being available for direct human consumption. However, slower growth of livestock led to increased environmental impact of beef, whilst reduced livestock numbers required more mineral fertilizer for crop production to replace on-farm manure. In the <em>circular Feed-no-Food</em> scenario, beef and overall calorie production were slightly reduced compared to the baseline, but 1.5 more high quality protein (expressed by the Digestible Indispensable Amino Acid Score, DIAAS), were produced. Environmental impacts of beef were reduced and nitrogen self-sufficiency improved due to increased legume share in the rotation.</div></div><div><h3>Significance</h3><div>Existing LCA approaches often fail to capture the complex dynamics of integrated crop-livestock systems and agroecological practices. FarmLCA addresses this by modelling both on-farm processes and upstream inputs, enabling a consistent assessment of environmental impacts, nutrient use efficiency, and food production. It offers a more holistic and systemic view of the consequences of agroecological innovations and enables the identi
{"title":"FarmLCA: A novel approach to assess agroecological innovations in Life Cycle Assessment","authors":"Simon Moakes , Philipp Oggiano , Jan Landert , Catherine Pfeifer , Laura de Baan","doi":"10.1016/j.agsy.2025.104560","DOIUrl":"10.1016/j.agsy.2025.104560","url":null,"abstract":"<div><h3>Context</h3><div>Agroecological innovations are seen as solutions to reduce environmental impacts of agriculture but can potentially lead to trade-offs with food production. Appropriate tools are needed to better understand synergies and trade-offs among environmental issues, resource efficiency and food production.</div></div><div><h3>Objective</h3><div>This study presents the FarmLCA tool, which models farms as interconnected crop-livestock systems and assesses environmental impacts from farms and farm-inputs. A mixed beef farm serves as case study to assess synergies and trade-offs of avoiding human edible feed in beef production.</div></div><div><h3>Methods</h3><div>FarmLCA allows the calculation of cradle-to-farm gate life cycle assessments (LCA). Emissions of environmentally harmful substances from crops and livestock are modelled based on the farm management. Upstream impacts from imported inputs (including fertilizer or feed) are accounted for with life cycle inventory data. Yields and nutrient requirements are checked for plausibility, based on management handbooks, while manure availability and composition are calculated based on livestock production. Environmental impacts, nutrient use efficiency and food production for a typical mixed beef farm in Scotland were calculated (<em>baseline</em>) and compared to alternative farm management scenarios: a <em>Feed-no-Food</em> scenario, avoiding concentrate feeds resulting in a smaller herd size and a <em>circular Feed-no-Food</em> scenario, additionally optimizing productivity and synergies between crop and livestock (e.g. more legumes in crop rotation, reduced replacement rate and feed waste).</div></div><div><h3>Results and conclusions</h3><div>In the <em>Feed-no-Food</em> scenario, the beef production was reduced by 25 %, but more calories and protein were produced overall due to cereal and legumes now being available for direct human consumption. However, slower growth of livestock led to increased environmental impact of beef, whilst reduced livestock numbers required more mineral fertilizer for crop production to replace on-farm manure. In the <em>circular Feed-no-Food</em> scenario, beef and overall calorie production were slightly reduced compared to the baseline, but 1.5 more high quality protein (expressed by the Digestible Indispensable Amino Acid Score, DIAAS), were produced. Environmental impacts of beef were reduced and nitrogen self-sufficiency improved due to increased legume share in the rotation.</div></div><div><h3>Significance</h3><div>Existing LCA approaches often fail to capture the complex dynamics of integrated crop-livestock systems and agroecological practices. FarmLCA addresses this by modelling both on-farm processes and upstream inputs, enabling a consistent assessment of environmental impacts, nutrient use efficiency, and food production. It offers a more holistic and systemic view of the consequences of agroecological innovations and enables the identi","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104560"},"PeriodicalIF":6.1,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593036","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 : 2025-11-24DOI: 10.1016/j.agsy.2025.104568
Longbo Ma , Qian Wang , Xiaoming Tan , Yaru Chen , Wenbin Jiang
CONTEXT
The sustainable management of cultivated land resources is essential for attaining the United Nations Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger) and SDG 15 (Life on Land). Rapid urbanization has posed significant challenges to cultivated land systems. Therefore, understanding the interaction mechanisms between new-type urbanization (NTU) and cultivated land use transition (CLUT) is vital for addressing resource constraints and promoting coordinated development of human and land systems.
OBJECTIVE
This study analyzes the evolution of the coupling coordination degree (CCD) between NTU and CLUT in the Middle and Lower Reaches of the Yellow River region. It aims to identify key problematic areas and uncover the underlying factors driving their interaction.
METHODS
The study utilizes the entropy weight method and linear weighting approach to assess NTU and CLUT levels. A coupling coordination degree model (CCDM) is employed to quantify their relationship, complemented by a geographic detector analysis to identify primary drivers influencing the CCD.
RESULTS AND CONCLUSIONS
The results indicate that: (1) The NTU index increased from 0.26 in 2005 to 0.46 in 2020, displaying notable spatial and temporal heterogeneity characterized by higher levels in the southeast, moderate levels in the northwest, and lower levels centrally. Conversely, CLUT levels saw a modest rise from 0.37 to 0.41, with higher values concentrated mainly in inland cities of Shandong and Henan provinces. (2) The CCD improved from 0.55 to 0.65, following a pattern of rapid growth initially, then stabilization, with evident spatial clustering and limited inter-city disparities. (3) Diagnostic analysis identified over 15 areas with problematic coordination between 2005 and 2020, primarily along the middle reaches of the Yellow River, where CLUT lagged behind. (4) The CCD is influenced by a combination of economic, social, and governmental factors, with economic drivers—such as industrial clustering, fiscal investment, and infrastructure development—exerting the strongest effects. Interaction effects between two factors generally demonstrated greater influence than individual factors alone.
Significance: The Middle and Lower Reaches of the Yellow River serve as a representative region for understanding regional disparities, offering valuable insights into the key drivers of unbalanced development and strategies for achieving coordinated progress—lessons that are applicable to similar regions globally.
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Pub Date : 2025-11-22DOI: 10.1016/j.agsy.2025.104575
Jiuzhou Jin , Ruiyao Zhang , Pengpeng Dou, Rong Zhi, Ping Li
Abstract
Context
Pastoral systems in Inner Mongolia sustain livelihoods and ecosystem services but face degradation driven by overgrazing, tenure fragmentation, and market–climate stressors. Herder cooperatives have emerged as a policy-backed governance innovation to address these challenges.
Objective
Assess whether cooperatives achieve higher multidimensional efficiency—Ecological, economic, and social—Than large- and small-scale independent herders.
Methods
Guided by an integrated resource-based, institutional, and sustainable-livelihoods framework, we surveyed 223 households across four banners (2022). Household pastures were georeferenced to MODIS 500 m NPP and within-pasture quadrats (α-diversity). Eighteen indicators were winsorized, normalized, and combined via an entropy-weighted composite, with robustness checks against equal-weight and CRITIC schemes. Determinants were estimated with two-limit Tobit; mechanisms were tested using a parallel two-mediator model (assets, coordination) with bootstrap inference.
Results and conclusions
Cooperatives outperform both large- and small-scale independents in ecological and economic efficiency; social differences are modest. Composite efficiency is higher for cooperatives (0.229 vs. 0.217 and 0.210). Positive drivers include labor share, education, and fixed assets; herd size is not significant; non-livestock training is marginally negative. Mediation results show significant indirect effects via assets and via coordination, while the asset to coordination chain is unsupported; a small direct effect remains
SIGNIFICANCE: Cooperative governance can help reconcile production with ecological stewardship. Performance-linked support that lowers coordination costs and builds household assets may enhance sustainability in pastoral regions.
内蒙古牧区维持生计和生态系统服务，但面临过度放牧、权属破碎化和市场-气候压力导致的退化。牧民合作社已成为应对这些挑战的一种有政策支持的治理创新。评估合作社是否比大型和小规模独立牧民实现更高的多维效率——生态、经济和社会。方法在基于资源、制度和可持续生计的综合框架的指导下，我们调查了四个州（2022年）的223户家庭。家庭牧场以MODIS 500 m NPP和牧场内样方（α-多样性）为地理参考。通过熵加权组合对18个指标进行了winsorized、归一化和组合，并对等权方案和CRITIC方案进行了鲁棒性检查。用双极限Tobit估计行列式；机制测试使用并行双中介模型（资产，协调）与自举推理。结果与结论合作农户在生态效益和经济效益上均优于大型农户和小型农户；社会差异不大。合作社的综合效率更高（0.229比0.217和0.210）。正向驱动因素包括劳动收入占比、教育和固定资产；畜群规模不显著；非牲畜培训的影响微乎其微。中介结果显示，资产对中介的间接影响显著，而资产对中介的间接影响不显著；意义：合作治理有助于协调生产与生态管理之间的关系。与绩效挂钩的支持可以降低协调成本并建立家庭资产，从而提高牧区的可持续性。
{"title":"Herder cooperatives vs. independent herders in Inner Mongolia: A comparative analysis of multi-dimensional efficiency","authors":"Jiuzhou Jin , Ruiyao Zhang , Pengpeng Dou, Rong Zhi, Ping Li","doi":"10.1016/j.agsy.2025.104575","DOIUrl":"10.1016/j.agsy.2025.104575","url":null,"abstract":"<div><h3>Abstract</h3><div>Context</div><div>Pastoral systems in Inner Mongolia sustain livelihoods and ecosystem services but face degradation driven by overgrazing, tenure fragmentation, and market–climate stressors. Herder cooperatives have emerged as a policy-backed governance innovation to address these challenges.</div><div>Objective</div><div>Assess whether cooperatives achieve higher multidimensional efficiency—Ecological, economic, and social—Than large- and small-scale independent herders.</div><div>Methods</div><div>Guided by an integrated resource-based, institutional, and sustainable-livelihoods framework, we surveyed 223 households across four banners (2022). Household pastures were georeferenced to MODIS 500 m NPP and within-pasture quadrats (α-diversity). Eighteen indicators were winsorized, normalized, and combined via an entropy-weighted composite, with robustness checks against equal-weight and CRITIC schemes. Determinants were estimated with two-limit Tobit; mechanisms were tested using a parallel two-mediator model (assets, coordination) with bootstrap inference.</div><div>Results and conclusions</div><div>Cooperatives outperform both large- and small-scale independents in ecological and economic efficiency; social differences are modest. Composite efficiency is higher for cooperatives (0.229 vs. 0.217 and 0.210). Positive drivers include labor share, education, and fixed assets; herd size is not significant; non-livestock training is marginally negative. Mediation results show significant indirect effects via assets and via coordination, while the asset to coordination chain is unsupported; a small direct effect remains</div><div>SIGNIFICANCE: Cooperative governance can help reconcile production with ecological stewardship. Performance-linked support that lowers coordination costs and builds household assets may enhance sustainability in pastoral regions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104575"},"PeriodicalIF":6.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575494","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}
Crop production in the food basket of South Asia faces serious challenges of the water table and environmental sustainability driving to future food insecurity. Thus, the conventional rice-wheat (CTRW) system practices are no more sustainable in South Asia.
OBJECTIVE
To design and develop alternative, optimal crop management options and assess their scalability through comprehensive system optimization practices (SOP), ensuring high productivity and profitability with lower environmental footprints along with potential for carbon credit generation.
METHODS
Field experiments were conducted at the four locations of farmer's fields in Karnal districts of Haryana, India. We evaluated SOP with CTR-zero-tillage (ZT) wheat-mungbean (CTR-ZTWMb) and direct seeded rice-ZT wheat-mungbean (DSR-ZTWMb) and triple ZT (raised bed) systems of maize-wheat-mungbean (ZTMWMb), maize-mustard-mungbean and soybean-wheat-mungbean (ZTSWMb).
RESULTS AND CONCLUSIONS
The system productivity enhanced by 26.4–29.2 and 26.9–36.9 % with enhanced net returns of 483–553 and 847–1006 US$/ha in rice-based and diversified (ZTMWMb, ZTMMuMb, and ZTSWMb) SOP, respectively over conventional rice-wheat system (CTRW). The diversified SOP had significantly lesser water use by 1023 to 1102 ha-mm with reduced global warming potential (GWP) by 4611–5100 kg CO2 eq./ha (∼5 carbon credit) over CTRW. Based on our study, the adoption of diversified SOP on 0.1 m ha and CTR-ZTWMb on 1.7 m ha can produce additional 0.27–1.23 m t alternate crops with additional net revenue of 906–921 million US$/year and reduction of the GWP by 564–603 million kg CO2 eq./year over CTRW. Additionally, the non-renewable energy saving from one ha of diversified SOP could help in CTR-ZTWMb adoption on 42–56 ha over CTRW. The on-farm study evidenced that crop production with system optimization practices of legume inclusion and zero tillage could be scaled up in the non-basmati conventional rice-wheat system to achieve higher productivity and profitability as well as environmental stewardship in the North-Western Indo-Gangetic Plains and similar agro-ecologies.
SIGNIFICANCE
The system optimization practices adoption in conventional rice-wheat system of North-Western Indo-Gangetic plains could help in enhancing farm profitability and lowering environmental footprint with generation of 5–6 carbon credit.
{"title":"System optimization practices for profitable and agro-ecologically sustainable agriculture in North-Western Indo-Gangetic Plains","authors":"Radheshyam , Shankar Lal Jat , Mangi Lal Jat , Hanuman Sahay Jat , Aditya Kumar Singh , Deep Mohan Mahala , Chiter Mal Parihar , Rajbir Singh , Deepak Bijarniya , Kailash Chandra Kalvaniya , Smruti Ranjan Padhan","doi":"10.1016/j.agsy.2025.104579","DOIUrl":"10.1016/j.agsy.2025.104579","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Crop production in the food basket of South Asia faces serious challenges of the water table and environmental sustainability driving to future food insecurity. Thus, the conventional rice-wheat (CTRW) system practices are no more sustainable in South Asia.</div></div><div><h3>OBJECTIVE</h3><div>To design and develop alternative, optimal crop management options and assess their scalability through comprehensive system optimization practices (SOP), ensuring high productivity and profitability with lower environmental footprints along with potential for carbon credit generation.</div></div><div><h3>METHODS</h3><div>Field experiments were conducted at the four locations of farmer's fields in Karnal districts of Haryana, India. We evaluated SOP with CTR-zero-tillage (ZT) wheat-mungbean (CTR-ZTWMb) and direct seeded rice-ZT wheat-mungbean (DSR-ZTWMb) and triple ZT (raised bed) systems of maize-wheat-mungbean (ZTMWMb), maize-mustard-mungbean and soybean-wheat-mungbean (ZTSWMb).</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The system productivity enhanced by 26.4–29.2 and 26.9–36.9 % with enhanced net returns of 483–553 and 847–1006 US$/ha in rice-based and diversified (ZTMWMb, ZTMMuMb, and ZTSWMb) SOP, respectively over conventional rice-wheat system (CTRW). The diversified SOP had significantly lesser water use by 1023 to 1102 ha-mm with reduced global warming potential (GWP) by 4611–5100 kg CO2 eq./ha (∼5 carbon credit) over CTRW. Based on our study, the adoption of diversified SOP on 0.1 m ha and CTR-ZTWMb on 1.7 m ha can produce additional 0.27–1.23 m t alternate crops with additional net revenue of 906–921 million US$/year and reduction of the GWP by 564–603 million kg CO<sub>2</sub> eq./year over CTRW. Additionally, the non-renewable energy saving from one ha of diversified SOP could help in CTR-ZTWMb adoption on 42–56 ha over CTRW. The on-farm study evidenced that crop production with system optimization practices of legume inclusion and zero tillage could be scaled up in the non-basmati conventional rice-wheat system to achieve higher productivity and profitability as well as environmental stewardship in the North-Western Indo-Gangetic Plains and similar agro-ecologies.</div></div><div><h3>SIGNIFICANCE</h3><div>The system optimization practices adoption in conventional rice-wheat system of North-Western Indo-Gangetic plains could help in enhancing farm profitability and lowering environmental footprint with generation of 5–6 carbon credit.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104579"},"PeriodicalIF":6.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621990","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}
<div><h3>CONTEXT</h3><div>Pakistan's agricultural system, ranked among the world's most water-stressed, demonstrates a critical resource utilization challenge. Despite a 21.8 % expansion in harvested area since 1991 and consuming 90 % of national freshwater resources, wheat productivity remains stagnant at half the global average. This disconnect between input use and output is further exacerbated by 50 % groundwater over-extraction, declining irrigation efficiency, and increasing reliance on chemical inputs. Collectively, these trends reveal the systemic fragility of input-driven growth and underscore the urgent need for an integrated water-energy-food (WEF) nexus approach to reconcile productivity with sustainability.</div></div><div><h3>OBJECTIVE</h3><div>This study has three key objectives: (1) quantify dynamic relationships between five critical agricultural inputs and productivity, (2) project sustainability thresholds under current practices, and (3) develop transferable optimization frameworks for water-scarce agricultural systems.</div></div><div><h3>METHODS</h3><div>We employ Autoregressive Distributed Lag (ARDL) cointegration analysis to examine long-term relationships and short-term dynamics between annual agricultural productivity (AAP) and five key inputs: agricultural water withdrawal (AWW), energy utilization (TEU), cultivated land area (THA), pesticide use (TPU), and fertilizer use (TFU) over a 30-year peroids (1991–2021). Additionally, Autoregressive Integrated Moving Average (ARIMA) forecasting models were employed to project future scenarios (2022−2031) for both inputs and AAP. The approach validates cointegration through rigorous diagnostic testing (ADF/PP, CUSUM), ensuring robust model performance for forecasting productivity (AAP) under varying input scenarios.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings reveal unsustainable input trajectories: a projected 15.1 % increase in productivity by 2031 would require continued expansion of land (+21.8 % compared with 1991), pesticide use (+82.25 %) and fertilizer application (+19 %). Meanwhile agricultural water (−4.22 %) and energy availability (−6.15 %) are declining, highlighting that these critical resources are becoming increasingly limited. This combination of rising input demands and decreasing essential resources highlights the urgent need for policy interventions such as precision irrigation, integrated nutrient management, and pesticide regulation to avoid ecological collapse.</div></div><div><h3>SIGNIFICANCE</h3><div>This research provides the first quantitative framework demonstrating the infeasibility of area-expansion strategies in Pakistan's agriculture. The findings call for immediate policy shifts toward precision irrigation, renewable energy integration, regulated agrochemical use and strengthened institutional coordination across water, energy, and agricultural sectors. The proposed WEF nexus framework offers scalable, evidence-based solutio
{"title":"Optimizing the water-energy-food Nexus for sustainable agriculture in Pakistan: A systems analysis with global implications","authors":"Hassan Iqbal , Chen Yaning , Syed Turab Raza , Sona Karim","doi":"10.1016/j.agsy.2025.104572","DOIUrl":"10.1016/j.agsy.2025.104572","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Pakistan's agricultural system, ranked among the world's most water-stressed, demonstrates a critical resource utilization challenge. Despite a 21.8 % expansion in harvested area since 1991 and consuming 90 % of national freshwater resources, wheat productivity remains stagnant at half the global average. This disconnect between input use and output is further exacerbated by 50 % groundwater over-extraction, declining irrigation efficiency, and increasing reliance on chemical inputs. Collectively, these trends reveal the systemic fragility of input-driven growth and underscore the urgent need for an integrated water-energy-food (WEF) nexus approach to reconcile productivity with sustainability.</div></div><div><h3>OBJECTIVE</h3><div>This study has three key objectives: (1) quantify dynamic relationships between five critical agricultural inputs and productivity, (2) project sustainability thresholds under current practices, and (3) develop transferable optimization frameworks for water-scarce agricultural systems.</div></div><div><h3>METHODS</h3><div>We employ Autoregressive Distributed Lag (ARDL) cointegration analysis to examine long-term relationships and short-term dynamics between annual agricultural productivity (AAP) and five key inputs: agricultural water withdrawal (AWW), energy utilization (TEU), cultivated land area (THA), pesticide use (TPU), and fertilizer use (TFU) over a 30-year peroids (1991–2021). Additionally, Autoregressive Integrated Moving Average (ARIMA) forecasting models were employed to project future scenarios (2022−2031) for both inputs and AAP. The approach validates cointegration through rigorous diagnostic testing (ADF/PP, CUSUM), ensuring robust model performance for forecasting productivity (AAP) under varying input scenarios.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings reveal unsustainable input trajectories: a projected 15.1 % increase in productivity by 2031 would require continued expansion of land (+21.8 % compared with 1991), pesticide use (+82.25 %) and fertilizer application (+19 %). Meanwhile agricultural water (−4.22 %) and energy availability (−6.15 %) are declining, highlighting that these critical resources are becoming increasingly limited. This combination of rising input demands and decreasing essential resources highlights the urgent need for policy interventions such as precision irrigation, integrated nutrient management, and pesticide regulation to avoid ecological collapse.</div></div><div><h3>SIGNIFICANCE</h3><div>This research provides the first quantitative framework demonstrating the infeasibility of area-expansion strategies in Pakistan's agriculture. The findings call for immediate policy shifts toward precision irrigation, renewable energy integration, regulated agrochemical use and strengthened institutional coordination across water, energy, and agricultural sectors. The proposed WEF nexus framework offers scalable, evidence-based solutio","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104572"},"PeriodicalIF":6.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567421","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 : 2025-11-21DOI: 10.1016/j.agsy.2025.104576
Xinlin Li , Zezhu Wei , Jianhang Cui , Ruoyan Yao , Puyu Feng , De Li Liu , Chengcheng Yuan , Yong Chen
CONTEXT
Climate warming and elevated atmospheric CO₂ concentrations, coupled with an ongoing transition from double-cropping rice systems (DCRS) to single-cropping rice systems (SCRS), are reshaping yield and hydrological processes in the subtropical monsoon regions of southern China. These concurrent shifts intensify the tension between yield stability and water sustainability under future climate scenarios.
OBJECTIVE
This study aims to evaluate the differential responses of DCRS and SCRS to future climate change, with a particular focus on rice yield and hydrological dynamics, in order to identify resilient cropping strategies under warming and CO₂ enrichment.
METHODS
An integrated modeling framework was developed for the Zishui River Basin (ZRB), a representative DCRS region in southern China. This framework combined high-resolution paddy field mapping, an enhanced Soil and Water Assessment Tool (SWAT) incorporating dynamic CO₂ response mechanisms, and multi-scenario climate projections from Coupled Model Intercomparison Project (CMIP6). Simulations were conducted under three Shared Socioeconomic Pathways (SSP) scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5) for the periods 2041–2070 and 2071–2100.
RESULTS AND CONCLUSIONS
Under SSP5–8.5 by the end of the century, the SCRS exhibited up to 29.9 % yield loss, primarily due to heat-induced phenological shortening. In contrast, the DCRS demonstrated greater climate resilience: early rice consistently benefited from elevated CO₂ and increased thermal accumulation, resulting in robust gains in yield, while late rice, though more heat-sensitive, maintained stable productivity under moderate warming. Overall, the DCRS outperformed the SCRS, highlighting its systemic advantage in balancing water inputs with grain production.
SIGNIFICANCE
These findings emphasize the importance of embedding climate resilience into future rice production systems. Promoting double-cropping practices presents a viable adaptation pathway to enhance regional food–water sustainability under climate change.
{"title":"Future climate resilience in rice systems of southern China: Double-cropping outperforms single-cropping in water-food sustainability","authors":"Xinlin Li , Zezhu Wei , Jianhang Cui , Ruoyan Yao , Puyu Feng , De Li Liu , Chengcheng Yuan , Yong Chen","doi":"10.1016/j.agsy.2025.104576","DOIUrl":"10.1016/j.agsy.2025.104576","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Climate warming and elevated atmospheric CO₂ concentrations, coupled with an ongoing transition from double-cropping rice systems (DCRS) to single-cropping rice systems (SCRS), are reshaping yield and hydrological processes in the subtropical monsoon regions of southern China. These concurrent shifts intensify the tension between yield stability and water sustainability under future climate scenarios.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to evaluate the differential responses of DCRS and SCRS to future climate change, with a particular focus on rice yield and hydrological dynamics, in order to identify resilient cropping strategies under warming and CO₂ enrichment.</div></div><div><h3>METHODS</h3><div>An integrated modeling framework was developed for the Zishui River Basin (ZRB), a representative DCRS region in southern China. This framework combined high-resolution paddy field mapping, an enhanced Soil and Water Assessment Tool (SWAT) incorporating dynamic CO₂ response mechanisms, and multi-scenario climate projections from Coupled Model Intercomparison Project (CMIP6). Simulations were conducted under three Shared Socioeconomic Pathways (SSP) scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5) for the periods 2041–2070 and 2071–2100.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Under SSP5–8.5 by the end of the century, the SCRS exhibited up to 29.9 % yield loss, primarily due to heat-induced phenological shortening. In contrast, the DCRS demonstrated greater climate resilience: early rice consistently benefited from elevated CO₂ and increased thermal accumulation, resulting in robust gains in yield, while late rice, though more heat-sensitive, maintained stable productivity under moderate warming. Overall, the DCRS outperformed the SCRS, highlighting its systemic advantage in balancing water inputs with grain production.</div></div><div><h3>SIGNIFICANCE</h3><div>These findings emphasize the importance of embedding climate resilience into future rice production systems. Promoting double-cropping practices presents a viable adaptation pathway to enhance regional food–water sustainability under climate change.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104576"},"PeriodicalIF":6.1,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560041","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 : 2025-11-21DOI: 10.1016/j.agsy.2025.104567
Kexin Li , Yanan Jiang , Ang Li , Xiangzhe Tian , Jiatong Lu , Tingting Wei , Jiangfeng Xiangli , Xifeng Huang , Yongmin Li , Shikun Sun
CONTEXT
The imbalance between crop water demand and supply often exerts negative impacts on local agricultural development in climate variability sensitive areas with increasing extreme weather conditions. Optimizing irrigation strategies is essential for alleviating irrigation water scarcity and promoting sustainable agriculture.
OBJECTIVE
The main objective of this work is to propose an Integrated Meteorological Adaptive Simulation-Optimization (IMASO) framework for crop irrigation strategies, enabling within-season real-time optimization of irrigation strategies and leveraging perfect weather forecasts to enhance irrigation guidance and maximize irrigation water productivity (IWP).
METHODS
The (IMASO) framework combines both short (5 days) -and medium (15 days) - term perfect weather forecast with Dynamic Time Warping (DTW) algorithm, AquaCrop-OSPy model, and NSGA-III multi-objective optimization algorithm (with a population size of 200, 150 generations) for the first time. This work focuses on winter wheat, the crop model was calibrated and validated using experimental data. Four different maximum single irrigation amounts were considered, and an optimal fixed irrigation strategy was developed by optimizing for maximum average yield, minimum irrigation water use, and highest water productivity over multiple years, serving as the baseline scenario. The IMASO framework was applied during a typical growing season to assess real-time optimization performance.
RESULTS AND CONCLUSIONS
Results show that incorporating short-term perfect weather forecasts can delay or reduce irrigation events. Considering medium-term perfect weather forecasts for real-time dynamic optimization of irrigation strategies allowed better adaptation to current seasonal conditions. The IMASO framework significantly reduced irrigation water use (by 26 %–57 %) while simultaneously maintaining crop yield. IWP improvements across different maximum single irrigation amounts ranged from 0.19 to 0.66 kg/m3.
SIGNIFICANCE
The IMASO framework enables within-season real-time optimization of irrigation strategies by dynamically adapting to weather changes. Ensuring efficient water use while maintaining agricultural productivity.
{"title":"An integrated meteorological adaptive simulation-optimization framework for real-time irrigation scheduling considering perfect weather forecasts","authors":"Kexin Li , Yanan Jiang , Ang Li , Xiangzhe Tian , Jiatong Lu , Tingting Wei , Jiangfeng Xiangli , Xifeng Huang , Yongmin Li , Shikun Sun","doi":"10.1016/j.agsy.2025.104567","DOIUrl":"10.1016/j.agsy.2025.104567","url":null,"abstract":"<div><h3>CONTEXT</h3><div>The imbalance between crop water demand and supply often exerts negative impacts on local agricultural development in climate variability sensitive areas with increasing extreme weather conditions. Optimizing irrigation strategies is essential for alleviating irrigation water scarcity and promoting sustainable agriculture.</div></div><div><h3>OBJECTIVE</h3><div>The main objective of this work is to propose an Integrated Meteorological Adaptive Simulation-Optimization (IMASO) framework for crop irrigation strategies, enabling within-season real-time optimization of irrigation strategies and leveraging perfect weather forecasts to enhance irrigation guidance and maximize irrigation water productivity (IWP).</div></div><div><h3>METHODS</h3><div>The (IMASO) framework combines both short (5 days) -and medium (15 days) - term perfect weather forecast with Dynamic Time Warping (DTW) algorithm, AquaCrop-OSPy model, and NSGA-III multi-objective optimization algorithm (with a population size of 200, 150 generations) for the first time. This work focuses on winter wheat, the crop model was calibrated and validated using experimental data. Four different maximum single irrigation amounts were considered, and an optimal fixed irrigation strategy was developed by optimizing for maximum average yield, minimum irrigation water use, and highest water productivity over multiple years, serving as the baseline scenario. The IMASO framework was applied during a typical growing season to assess real-time optimization performance.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Results show that incorporating short-term perfect weather forecasts can delay or reduce irrigation events. Considering medium-term perfect weather forecasts for real-time dynamic optimization of irrigation strategies allowed better adaptation to current seasonal conditions. The IMASO framework significantly reduced irrigation water use (by 26 %–57 %) while simultaneously maintaining crop yield. IWP improvements across different maximum single irrigation amounts ranged from 0.19 to 0.66 kg/m<sup>3</sup>.</div></div><div><h3>SIGNIFICANCE</h3><div>The IMASO framework enables within-season real-time optimization of irrigation strategies by dynamically adapting to weather changes. Ensuring efficient water use while maintaining agricultural productivity.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104567"},"PeriodicalIF":6.1,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567437","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 : 2025-11-19DOI: 10.1016/j.agsy.2025.104569
Ismail I. Garba , Wolfram Buss , Enli Wang , Cathryn A. O’Sullivan , Vadakattu V.S.R. Gupta , Alison R. Bentley , Kirsten Verburg
CONTEXT
Retaining nitrogen (N) in soils in the form of ammonium (NH4+) by inhibiting nitrification has been proposed as a strategy to reduce N gaseous losses and nitrate (NO3-) leaching. Biological nitrification inhibition (BNI) involves the release of natural metabolites from crop roots that suppress nitrifying microbes. Unlike synthetic nitrification inhibitors BNIs act directly in the rhizosphere and may provide a more spatially and temporally sustained inhibition. Because BNI effectiveness depends on crop species, and interactions with biophysical factors, a systems modelling approach is needed to assess its plausible benefits in cropping systems.
OBJECTIVE
(1) develop a BNI model suitable for integration into systems models, enabling simulation of BNI release, fate, and bioactivity within cropping systems, and (2) use the model in-silico to illustrate how system interactions influence BNI impacts.
METHODS
A BNI subroutine was developed and integrated into the Agricultural Production Systems sIMulator (APSIM) Next Generation to model BNI exudation, bioactivity, fate, and persistence in soil. Simulations for wheat, canola and sorghum were conducted to assess its plausible effects on N cycling and crop productivity.
RESULTS AND CONCLUSIONS
Four prerequisite conditions under which within-season plausible N loss and yield benefits may be realized from BNI: (i) adequate root growth and BNI release achieving effective bioactivity, (ii) BNI persistence with slow degradation at most 50% daily degradation to ensure longevity of inhibition, (iii) the crop being able to take up N in both NH4+ and NO3- forms ensuring that ‘saved N’ is assimilated and (iv) occurrence of N loss events when BNI is active. When these conditions co-occurred, simulated systems showed decreased N loss, and/or yield responses.
SIGNIFICANCE
The integrated APSIM-BNI framework provides a tool for exploring where and when BNI may deliver agronomic and environmental benefits and guiding future field experiment and trait improvement efforts.
{"title":"A modelling framework for assessing the plausible impacts of biological nitrification inhibition in cropping systems","authors":"Ismail I. Garba , Wolfram Buss , Enli Wang , Cathryn A. O’Sullivan , Vadakattu V.S.R. Gupta , Alison R. Bentley , Kirsten Verburg","doi":"10.1016/j.agsy.2025.104569","DOIUrl":"10.1016/j.agsy.2025.104569","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Retaining nitrogen (N) in soils in the form of ammonium (NH<sub>4</sub><sup>+</sup>) by inhibiting nitrification has been proposed as a strategy to reduce N gaseous losses and nitrate (NO<sub>3</sub><sup>-</sup>) leaching. Biological nitrification inhibition (BNI) involves the release of natural metabolites from crop roots that suppress nitrifying microbes. Unlike synthetic nitrification inhibitors BNIs act directly in the rhizosphere and may provide a more spatially and temporally sustained inhibition. Because BNI effectiveness depends on crop species, and interactions with biophysical factors, a systems modelling approach is needed to assess its plausible benefits in cropping systems.</div></div><div><h3>OBJECTIVE</h3><div>(1) develop a BNI model suitable for integration into systems models, enabling simulation of BNI release, fate, and bioactivity within cropping systems, and (2) use the model in-<em>silico</em> to illustrate how system interactions influence BNI impacts.</div></div><div><h3>METHODS</h3><div>A BNI subroutine was developed and integrated into the Agricultural Production Systems sIMulator (APSIM) Next Generation to model BNI exudation, bioactivity, fate, and persistence in soil. Simulations for wheat, canola and sorghum were conducted to assess its plausible effects on N cycling and crop productivity.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Four prerequisite conditions under which within-season plausible N loss and yield benefits may be realized from BNI: (i) adequate root growth and BNI release achieving effective bioactivity, (ii) BNI persistence with slow degradation at most 50% daily degradation to ensure longevity of inhibition, (iii) the crop being able to take up N in both NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup> forms ensuring that ‘saved N’ is assimilated and (iv) occurrence of N loss events when BNI is active. When these conditions co-occurred, simulated systems showed decreased N loss, and/or yield responses.</div></div><div><h3>SIGNIFICANCE</h3><div>The integrated APSIM-BNI framework provides a tool for exploring where and when BNI may deliver agronomic and environmental benefits and guiding future field experiment and trait improvement efforts.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104569"},"PeriodicalIF":6.1,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145537363","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 : 2025-11-19DOI: 10.1016/j.agsy.2025.104573
Lanping Tang , Peter H. Verburg , Xinli Ke , Chengcheng Wang , Shaohua Wu , Wuyan Li , Jinxia Zhu
<div><h3>CONTEXT</h3><div>Global food security remains a pressing concern, with rising undernourishment rates exacerbated by urbanization, climate change, and soil degradation. Understanding the dynamics of cropland systems is therefore crucial for enhancing grain production, particularly in countries like China, which supports a significant portion of the world's population with limited cropland resources.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to analyze spatial variability in cropland intensification at the prefectural scale in China from 1980 to 2018. It further reveals the spatial-temporal changes of the cropland management systems by combining cropland-use intensity and spatial variability in cropland intensification. This focuses on the relationship between changes in cropland area and intensification and evaluates their relative contributions to grain production.</div></div><div><h3>METHODS</h3><div>A K-means clustering algorithm was adopted to identify distinct cropland management systems. The LMDI (Logarithmic Mean Divisia Index) method was applied to quantify the contribution of changes in cropland area and intensification to grain production.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results indicate a sharp rise in agricultural input intensity, particularly pesticide and fertilizer, alongside a notable decline in time investment by laborers. Six distinct cropland management systems were identified, with Type 1 and Type 3 being the most prevalent. Type 1, predominantly observed in the northeast and northwest, exhibited low initial intensity with a slight input growth and a minor time investment decrease. Type 3, concentrated in the south, demonstrated stable input increases accompanied by a moderate drop in time investment. Furthermore, expansion of cropland area and intensification co-occur in 58 % of the prefectures. Intensification drove 79 % of grain production growth, yet with clear spatial disparities: large gains in northeastern and central prefectures contrasted with declines in southeastern coastal areas due to cropland loss. The study underscores the pivotal role of cropland intensification in enhancing grain production. These findings advocate for targeted, region-specific strategies to support sustainable intensification and labor-saving technologies, thereby ensuring long-term food security amid urbanization and rising labor costs.</div></div><div><h3>SIGNIFICANCES</h3><div>This study offers a novel, long-term analysis of cropland system dynamics in China—integrating cropland intensification and area changes—at a fine spatial scale and examines their collective impact on grain production. The study not only helps to understand that production can be increased through area expansion or intensification, but also to understand which pathway dominates where, to what degree, and in what combination. The study provides critical insights for policymakers and stakeholders, contributing to the discou
{"title":"Spatio-temporal changes in cropland system and its impacts on grain production in China","authors":"Lanping Tang , Peter H. Verburg , Xinli Ke , Chengcheng Wang , Shaohua Wu , Wuyan Li , Jinxia Zhu","doi":"10.1016/j.agsy.2025.104573","DOIUrl":"10.1016/j.agsy.2025.104573","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Global food security remains a pressing concern, with rising undernourishment rates exacerbated by urbanization, climate change, and soil degradation. Understanding the dynamics of cropland systems is therefore crucial for enhancing grain production, particularly in countries like China, which supports a significant portion of the world's population with limited cropland resources.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to analyze spatial variability in cropland intensification at the prefectural scale in China from 1980 to 2018. It further reveals the spatial-temporal changes of the cropland management systems by combining cropland-use intensity and spatial variability in cropland intensification. This focuses on the relationship between changes in cropland area and intensification and evaluates their relative contributions to grain production.</div></div><div><h3>METHODS</h3><div>A K-means clustering algorithm was adopted to identify distinct cropland management systems. The LMDI (Logarithmic Mean Divisia Index) method was applied to quantify the contribution of changes in cropland area and intensification to grain production.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results indicate a sharp rise in agricultural input intensity, particularly pesticide and fertilizer, alongside a notable decline in time investment by laborers. Six distinct cropland management systems were identified, with Type 1 and Type 3 being the most prevalent. Type 1, predominantly observed in the northeast and northwest, exhibited low initial intensity with a slight input growth and a minor time investment decrease. Type 3, concentrated in the south, demonstrated stable input increases accompanied by a moderate drop in time investment. Furthermore, expansion of cropland area and intensification co-occur in 58 % of the prefectures. Intensification drove 79 % of grain production growth, yet with clear spatial disparities: large gains in northeastern and central prefectures contrasted with declines in southeastern coastal areas due to cropland loss. The study underscores the pivotal role of cropland intensification in enhancing grain production. These findings advocate for targeted, region-specific strategies to support sustainable intensification and labor-saving technologies, thereby ensuring long-term food security amid urbanization and rising labor costs.</div></div><div><h3>SIGNIFICANCES</h3><div>This study offers a novel, long-term analysis of cropland system dynamics in China—integrating cropland intensification and area changes—at a fine spatial scale and examines their collective impact on grain production. The study not only helps to understand that production can be increased through area expansion or intensification, but also to understand which pathway dominates where, to what degree, and in what combination. The study provides critical insights for policymakers and stakeholders, contributing to the discou","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104573"},"PeriodicalIF":6.1,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578129","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 : 2025-11-19DOI: 10.1016/j.agsy.2025.104566
Mina Devkota , Krishna Prasad Devkota , Mohie El Din Omar , Samar Attaher , Ajit Govind , Vinay Nangia
CONTEXT
Wheat (Triticum aestivum) is Egypt's staple crop, crucial for national food security. However, the country remains heavily reliant on imports to meet domestic demand. Enhancing production sustainably requires a systematic assessment of attainable yield and profit gaps along with the identification of key factors driving.
OBJECTIVES
This study aims to identify major determinants of wheat yield and profit gaps across different governorates in New and Old Lands; to develop context-specific integrated agronomic solutions for sustainably closing these gaps while reducing environmental footprints.
MATERIALS AND METHODS
We used random field survey samples of 2042 individual wheat fields across 23 wheat-growing governorates covering New and Old Lands during 2021/2022 growing season. Based on crop yield, farmers were categorized into three groups, and attainable yield and profit gaps were calculated from difference between mean yield of top 10th decile and average farmers' yield. Random Forest model is used to analyze data and identify major factors affecting yield, profit, and nitrogen use efficiency (NUE). Sustainability of wheat production was assessed using various indicators. Comparative analyses were conducted to evaluate differences in yield, input use efficiency, and profitability between Old and New Land, as well as across different yield gap categories.
RESULTS AND DISCUSSION
Analysis revealed significant yield and profit gaps between average and high-yielding farmers in both Old and New Lands. In Old Land, high-yield farmers (10th decile) achieved average yields of 8.4 t ha−1 and net profits of US$1097 ha−1, compared with 6.5 t ha−1 and US$675 ha−1 for medium-yield farmers. In the New Lands, the yield gap was more pronounced, with high-yield farmers achieving average yields of 7.5 t ha−1 compared to 4.63 t ha−1 for medium-yield farmers, highlighting a significant opportunity to increase productivity. Determinants for yield and profit varied across governorates, indicating need for governorate-specific strategies to sustainably close yield and profit gaps. Water productivity, NUE, and labor productivity were notably lower, while production cost showed no strong correlation with yield and was negatively correlated with greenhouse gas emission intensity (GHGI). Raised bed planting improved NUE by 29 %, increased water productivity by 18 %, and reduced GHGI by 15 % compared with conventional flat planting.
SIGNIFICANCE
Adopting context-specific agronomic practices that combine integrated-fertilization, efficient irrigation, suitable varieties, and raised-bed planting can enhance agronomic gains while reducing environmental footprints. When tailored to local yield-limiting factors, these solutions provide a sustainable pathway to narrow
小麦（Triticum aestivum）是埃及的主要作物，对国家粮食安全至关重要。然而，该国仍然严重依赖进口来满足国内需求。可持续地提高生产需要系统地评估可实现的产量和利润差距，并确定关键驱动因素。本研究旨在确定新旧土地不同省份小麦产量和利润差距的主要决定因素；制定针对具体情况的综合农艺解决方案，以可持续地缩小这些差距，同时减少环境足迹。材料与方法在2021/2022年小麦生长季，我们对23个小麦种植省份的2042块单独的麦田进行了随机调查。根据作物产量将农户分为三类，通过前十分之一农户平均产量与农户平均产量之差计算可得产量和利润差距。采用随机森林模型对数据进行分析，找出影响产量、利润和氮素利用效率的主要因素。利用各种指标对小麦生产的可持续性进行了评价。通过比较分析，评价了新旧土地之间以及不同产量缺口类别之间在产量、投入物利用效率和盈利能力方面的差异。结果与讨论分析表明，在新旧土地上，平均产量和高产农民之间存在显著的产量和利润差距。在Old Land，高产农民（10十分之一）的平均产量为8.4 t hm2，净利润为1097 hm2，而中等产量农民的平均产量为6.5 t hm2，净利润为675 hm2。在新地，产量差距更为明显，高产农民的平均产量为7.5吨/公顷，而中等产量农民的平均产量为4.63吨/公顷，这表明提高生产力的机会很大。产量和利润的决定因素因省而异，这表明需要针对省的具体战略来持续缩小产量和利润差距。水分生产力、氮肥利用效率和劳动生产率显著降低，生产成本与产量的相关性不强，与温室气体排放强度呈负相关。与传统平面种植相比，垄作床种植提高了29%的氮肥利用效率，提高了18%的水分生产力，并减少了15%的温室气体排放。采用结合综合施肥、高效灌溉、适宜品种和高床种植的因地制宜的农艺措施可以提高农业效益，同时减少环境足迹。当针对当地的产量限制因素进行定制时，这些解决方案提供了一条缩小产量和利润差距的可持续途径。在有利的政策和有效的推广系统的支持下，扩大数据驱动的解决方案为加强埃及和类似干旱灌溉地区的小麦自给提供了可行的选择。
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