Pub Date : 2025-11-03DOI: 10.1016/j.agsy.2025.104547
Mohamed Ghali , Nejla Ben Arfa , Giffona Justinia , Soazig Di Bianco , Abdul Rahman Saili
<div><h3>CONTEXT</h3><div>Digital tools are increasingly recognized for their essential roles in enhancing farm productivity, sustainability, and competitiveness. However, their adoption remains uneven across different farming systems due to multiple structural and strategic constraints.</div></div><div><h3>OBJECTIVE</h3><div>This study analyzed the adoption of digital tools on French beef cattle, pig, and vegetable farms, three production systems that have received limited research attention. The objectives are twofold: to distinguish between farmers’ stated motives and the structural factors influencing adoption decisions and to formulate recommendations for targeted public policies.</div></div><div><h3>METHODS</h3><div>A mixed-methods approach was employed: semi-structured interviews with 49 farmers and logistic regression models using data from the 2020 French agricultural census. Two regions with a high prevalence of the three production systems - Pays de la Loire and Brittany- were selected and compared to the national level.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Qualitative analysis identified key motives such as improved productivity, reduced workload, and environmental sustainability. Quantitative results showed that adoption was more likely among larger farms, and farmers involved in collaborative networks and collectives that facilitate resource sharing, participation in expert groups, training, and knowledge exchange, as well as among farmers with higher education levels. Conversely, smaller farms and those engaged in short supply chains faced greater barriers, including high costs, technological complexity, and limited internet access. However, in certain cases—such as vegetable farming—adoption requires higher levels of education and advanced technical and digital skills, particularly for decision-support and automation tools where precision and responsiveness are critical. In contrast, in livestock sectors such as pig and beef production, automation tools are often adopted by older and less-educated farmers as a response to labor shortages, primarily to reduce drudgery and automate repetitive, low-value tasks rather than to transform management practices. The study underscores the need for differentiated policy strategies to support equitable digital transitions across farm types.</div></div><div><h3>SIGNIFICANCE</h3><div>The findings provide actionable insights for policymakers seeking to foster an inclusive and sustainable digital transition, which requires differentiated policy responses. Small farms, particularly those in vegetable production, need target financial and technical support to overcome cost-related and technological barriers. Beef and pig farms face structural and infrastructural constraints, underscoring the importance of broadband investment in rural areas.</div><div>The factors influencing the adoption of digital tools are highly context-dependent, varying across production sectors and tool types.
{"title":"Adoption of digital tools in french beef cattle, pig, and vegetable farming: A mixed-methods analysis of motives, barriers, and structural determinants","authors":"Mohamed Ghali , Nejla Ben Arfa , Giffona Justinia , Soazig Di Bianco , Abdul Rahman Saili","doi":"10.1016/j.agsy.2025.104547","DOIUrl":"10.1016/j.agsy.2025.104547","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Digital tools are increasingly recognized for their essential roles in enhancing farm productivity, sustainability, and competitiveness. However, their adoption remains uneven across different farming systems due to multiple structural and strategic constraints.</div></div><div><h3>OBJECTIVE</h3><div>This study analyzed the adoption of digital tools on French beef cattle, pig, and vegetable farms, three production systems that have received limited research attention. The objectives are twofold: to distinguish between farmers’ stated motives and the structural factors influencing adoption decisions and to formulate recommendations for targeted public policies.</div></div><div><h3>METHODS</h3><div>A mixed-methods approach was employed: semi-structured interviews with 49 farmers and logistic regression models using data from the 2020 French agricultural census. Two regions with a high prevalence of the three production systems - Pays de la Loire and Brittany- were selected and compared to the national level.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Qualitative analysis identified key motives such as improved productivity, reduced workload, and environmental sustainability. Quantitative results showed that adoption was more likely among larger farms, and farmers involved in collaborative networks and collectives that facilitate resource sharing, participation in expert groups, training, and knowledge exchange, as well as among farmers with higher education levels. Conversely, smaller farms and those engaged in short supply chains faced greater barriers, including high costs, technological complexity, and limited internet access. However, in certain cases—such as vegetable farming—adoption requires higher levels of education and advanced technical and digital skills, particularly for decision-support and automation tools where precision and responsiveness are critical. In contrast, in livestock sectors such as pig and beef production, automation tools are often adopted by older and less-educated farmers as a response to labor shortages, primarily to reduce drudgery and automate repetitive, low-value tasks rather than to transform management practices. The study underscores the need for differentiated policy strategies to support equitable digital transitions across farm types.</div></div><div><h3>SIGNIFICANCE</h3><div>The findings provide actionable insights for policymakers seeking to foster an inclusive and sustainable digital transition, which requires differentiated policy responses. Small farms, particularly those in vegetable production, need target financial and technical support to overcome cost-related and technological barriers. Beef and pig farms face structural and infrastructural constraints, underscoring the importance of broadband investment in rural areas.</div><div>The factors influencing the adoption of digital tools are highly context-dependent, varying across production sectors and tool types.","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104547"},"PeriodicalIF":6.1,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462627","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 : 2025-11-01DOI: 10.1016/j.agsy.2025.104541
Isabel Pinheiro , Pedro Moura , Leandro Rodrigues , Abílio Pereira Pacheco , Jorge Teixeira , António Valente , Mário Cunha , Filipe Neves dos Santos
In 2023, global kiwifruit production reached over 4.4 million tonnes, highlighting the crop’s significant economic importance. However, achieving high yields depends on adequate pollination. In Actinidia species, pollen is transferred by insects from male to female flowers on separate plants. Natural pollination faces increasing challenges due to the decline in pollinator populations and climate variability, driving the adoption of assisted pollination methods. This study examines the Portuguese kiwifruit sector, one of the world’s top 12 producers, using a novel mixed-methods approach that integrates both qualitative and quantitative analyses to assess the feasibility of robotic pollination. The qualitative study identifies the benefits and challenges of current methods and explores how robotic pollination could address these challenges. The quantitative analysis explores the cost-effectiveness and practicality of implementing robotic pollination as a product and service. Findings indicate that most farmers use handheld pollination devices but face pollen wastage and application timing challenges. Economic analysis establishes a break-even point of €685 per hectare for an annual single application, with a first robotic pollination of €17 146 becoming cost-effective for orchards of at least 3.5 hectares and a second robotic solution of €34 293 becoming cost-effective for orchards up to 7 hectares. A robotic pollination service priced at €685 per hectare per application presents a low-risk and a viable alternative for growers. This study provides robust economic insights supporting the adoption of robotic pollination technologies. This study is crucial to make informed decisions to enhance kiwifruit production’s productivity and sustainability through precise robotic-assisted pollination.
{"title":"Economic benchmarking of assisted pollination methods for kiwifruit flowers: Assessment of cost-effectiveness of robotic solution","authors":"Isabel Pinheiro , Pedro Moura , Leandro Rodrigues , Abílio Pereira Pacheco , Jorge Teixeira , António Valente , Mário Cunha , Filipe Neves dos Santos","doi":"10.1016/j.agsy.2025.104541","DOIUrl":"10.1016/j.agsy.2025.104541","url":null,"abstract":"<div><div>In 2023, global kiwifruit production reached over 4.4 million tonnes, highlighting the crop’s significant economic importance. However, achieving high yields depends on adequate pollination. In Actinidia species, pollen is transferred by insects from male to female flowers on separate plants. Natural pollination faces increasing challenges due to the decline in pollinator populations and climate variability, driving the adoption of assisted pollination methods. This study examines the Portuguese kiwifruit sector, one of the world’s top 12 producers, using a novel mixed-methods approach that integrates both qualitative and quantitative analyses to assess the feasibility of robotic pollination. The qualitative study identifies the benefits and challenges of current methods and explores how robotic pollination could address these challenges. The quantitative analysis explores the cost-effectiveness and practicality of implementing robotic pollination as a product and service. Findings indicate that most farmers use handheld pollination devices but face pollen wastage and application timing challenges. Economic analysis establishes a break-even point of €685 per hectare for an annual single application, with a first robotic pollination of €17 146 becoming cost-effective for orchards of at least 3.5 hectares and a second robotic solution of €34 293 becoming cost-effective for orchards up to 7 hectares. A robotic pollination service priced at €685 per hectare per application presents a low-risk and a viable alternative for growers. This study provides robust economic insights supporting the adoption of robotic pollination technologies. This study is crucial to make informed decisions to enhance kiwifruit production’s productivity and sustainability through precise robotic-assisted pollination.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104541"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412346","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 : 2025-11-01DOI: 10.1016/j.agsy.2025.104551
Fatemeh Yaghoubi, Mohammad Bannayan
Context
Climate change poses significant challenges to food security, especially in arid and semi-arid regions like Iran. Identifying resilient crops and effective adaptation strategies is crucial to maintaining agricultural productivity.
Objective
This study aims to evaluate the viability of quinoa, a stress-tolerant and nutritionally rich crop, as a climate-resilient alternative in Iran's diverse agro-climatic zones under projected climate change scenarios.
Methods
Ten CMIP6 global climate models (GCMs) were assessed for their performance in simulating historical climate data (1990–2014) across 25 sites. Seven high-skill models were selected and downscaled under SSP2–4.5 and SSP5–8.5 pathways to project future climate in Iran through 2100. The CROPGRO-quinoa model simulated yield responses with and without elevated CO₂. The effect of planting date adjustment as an adaptation measure was also analyzed.
Results and conclusions
The CROPGRO-quinoa accurately simulated yields (R2 = 0.95; NSE = 0.94) under existing weather in Iran. Without CO₂ enrichment, quinoa yields declined on average by 22.6 % (SSP2–4.5) and 19.8 % (SSP5–8.5) during 2026–2050, though reductions eased over time relative to the 1990–2014 baseline. Accounting for CO₂ effects alleviated yield losses, with a potential average gain of 4.7 % under SSP5–8.5 in 2076–2100. Optimizing planting dates improved yields across most zones, demonstrating its value as a practical adaptation measure.
Significance
This research supports quinoa as a promising crop for climate adaptation in dryland agriculture. It offers actionable insights for policymakers and practitioners aiming to enhance agricultural resilience and implement climate-smart strategies in similar vulnerable regions.
{"title":"Toward climate-resilient agriculture in Iran: Modeling quinoa viability under future climate scenarios","authors":"Fatemeh Yaghoubi, Mohammad Bannayan","doi":"10.1016/j.agsy.2025.104551","DOIUrl":"10.1016/j.agsy.2025.104551","url":null,"abstract":"<div><h3>Context</h3><div>Climate change poses significant challenges to food security, especially in arid and semi-arid regions like Iran. Identifying resilient crops and effective adaptation strategies is crucial to maintaining agricultural productivity.</div></div><div><h3>Objective</h3><div>This study aims to evaluate the viability of quinoa, a stress-tolerant and nutritionally rich crop, as a climate-resilient alternative in Iran's diverse agro-climatic zones under projected climate change scenarios.</div></div><div><h3>Methods</h3><div>Ten CMIP6 global climate models (GCMs) were assessed for their performance in simulating historical climate data (1990–2014) across 25 sites. Seven high-skill models were selected and downscaled under SSP2–4.5 and SSP5–8.5 pathways to project future climate in Iran through 2100. The CROPGRO-quinoa model simulated yield responses with and without elevated CO₂. The effect of planting date adjustment as an adaptation measure was also analyzed.</div></div><div><h3>Results and conclusions</h3><div>The CROPGRO-quinoa accurately simulated yields (R<sup>2</sup> = 0.95; NSE = 0.94) under existing weather in Iran. Without CO₂ enrichment, quinoa yields declined on average by 22.6 % (SSP2–4.5) and 19.8 % (SSP5–8.5) during 2026–2050, though reductions eased over time relative to the 1990–2014 baseline. Accounting for CO₂ effects alleviated yield losses, with a potential average gain of 4.7 % under SSP5–8.5 in 2076–2100. Optimizing planting dates improved yields across most zones, demonstrating its value as a practical adaptation measure.</div></div><div><h3>Significance</h3><div>This research supports quinoa as a promising crop for climate adaptation in dryland agriculture. It offers actionable insights for policymakers and practitioners aiming to enhance agricultural resilience and implement climate-smart strategies in similar vulnerable regions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104551"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412072","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>Reducing greenhouse gas (GHG) emissions from rice fields involves complex decision-making processes that require evaluating multiple conflicting criteria. Multi-criteria decision making (MCDM) provides a structured approach for comparing mitigation strategies, considering diverse parameters and criteria. Quantifying these parameters gives the result in the form of rankings to provide the best-suited mitigation strategy.</div></div><div><h3>OBJECTIVE</h3><div>This study applied different MCDM techniques to rank the best GHG mitigation strategy for methane (CH<sub>4</sub>), and nitrous oxide (N<sub>2</sub>O), based on site-specific soil and plant parameters (criteria) and field emission data from two consecutive seasons from flooded rice paddy systems of Assam, India. It was hypothesized that the MCDM approach could provide a ranking-based, detailed analysis of different site-specific management practices (agrotechnologies) based on select criteria in the study area. This ranking will have the dual objectives of maximizing yield and reducing emissions for sustainable rice cultivation.</div></div><div><h3>METHODS</h3><div>Field experiment on CH<sub>4</sub> and N<sub>2</sub>O emissions was studied under the impact of six climate smart agro-technological treatments, namely farmer's practices (FP), recommended dose of fertilisers (RDF), direct-seeded rice (DSR), intermittent wetting and drying (IWD), methanotroph application (MTH), and ammonium sulphate (AS) management, for two seasonal cropping cycles (Boro and Sali seasons). In our study, six criteria were considered among the six treatments, and a specific weightage was given to them by using six different weight criteria methods (CRITIC, Entropy, MEREC, CILOS, IDOCRIW, and equal weight). These obtained weights were recalculated by IDOCRIW to improve accuracy. The weighted values so obtained were then subjected to rank determination by TOPSIS, EC-TOPSIS, COPRAS, and WSM.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The study found that IWD was ranked the highest (1<sup>st</sup> rank) among the six treatments in terms of overall GHG mitigation and yield efficiency. And this was observed for both the Boro and Sali seasons. The MCDM analysis also validated the experimental data, which also showed IWD having the least CH<sub>4</sub> efflux and maximum yield in both seasons. MCDM took into consideration a variety of causes or factors (criteria) that can affect the outcome. It not only validated the experimental design and work but also provided an understanding of the associated parameters within the treatments and among the treatments.</div></div><div><h3>SIGNIFICANCE</h3><div>The research highlights how MCDM could tackle unique challenges in rice farming, such as balancing yield security with emission cuts and adapting region-specific solutions, ultimately paving the way for sustainable agriculture. Although certain methodological limitations, such as sensitivity to no
{"title":"Seasonal comparison of the impacts of climate-smart agrotechnologies on greenhouse gas mitigation in flooded rice fields: Application of multi-criteria decision making (MCDM) technique","authors":"Manas Protim Rajbonshi , Debaditya Gupta , Sudip Mitra","doi":"10.1016/j.agsy.2025.104550","DOIUrl":"10.1016/j.agsy.2025.104550","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Reducing greenhouse gas (GHG) emissions from rice fields involves complex decision-making processes that require evaluating multiple conflicting criteria. Multi-criteria decision making (MCDM) provides a structured approach for comparing mitigation strategies, considering diverse parameters and criteria. Quantifying these parameters gives the result in the form of rankings to provide the best-suited mitigation strategy.</div></div><div><h3>OBJECTIVE</h3><div>This study applied different MCDM techniques to rank the best GHG mitigation strategy for methane (CH<sub>4</sub>), and nitrous oxide (N<sub>2</sub>O), based on site-specific soil and plant parameters (criteria) and field emission data from two consecutive seasons from flooded rice paddy systems of Assam, India. It was hypothesized that the MCDM approach could provide a ranking-based, detailed analysis of different site-specific management practices (agrotechnologies) based on select criteria in the study area. This ranking will have the dual objectives of maximizing yield and reducing emissions for sustainable rice cultivation.</div></div><div><h3>METHODS</h3><div>Field experiment on CH<sub>4</sub> and N<sub>2</sub>O emissions was studied under the impact of six climate smart agro-technological treatments, namely farmer's practices (FP), recommended dose of fertilisers (RDF), direct-seeded rice (DSR), intermittent wetting and drying (IWD), methanotroph application (MTH), and ammonium sulphate (AS) management, for two seasonal cropping cycles (Boro and Sali seasons). In our study, six criteria were considered among the six treatments, and a specific weightage was given to them by using six different weight criteria methods (CRITIC, Entropy, MEREC, CILOS, IDOCRIW, and equal weight). These obtained weights were recalculated by IDOCRIW to improve accuracy. The weighted values so obtained were then subjected to rank determination by TOPSIS, EC-TOPSIS, COPRAS, and WSM.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The study found that IWD was ranked the highest (1<sup>st</sup> rank) among the six treatments in terms of overall GHG mitigation and yield efficiency. And this was observed for both the Boro and Sali seasons. The MCDM analysis also validated the experimental data, which also showed IWD having the least CH<sub>4</sub> efflux and maximum yield in both seasons. MCDM took into consideration a variety of causes or factors (criteria) that can affect the outcome. It not only validated the experimental design and work but also provided an understanding of the associated parameters within the treatments and among the treatments.</div></div><div><h3>SIGNIFICANCE</h3><div>The research highlights how MCDM could tackle unique challenges in rice farming, such as balancing yield security with emission cuts and adapting region-specific solutions, ultimately paving the way for sustainable agriculture. Although certain methodological limitations, such as sensitivity to no","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104550"},"PeriodicalIF":6.1,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-29DOI: 10.1016/j.agsy.2025.104548
Min Kang , Dongzheng Zhang , Yuan Cao , Liujun Xiao , Liang Tang , Leilei Liu , Weixing Cao , Yan Zhu , Bing Liu
CONTEXT
Global wheat production faces growing threats from climate change, particularly rising temperatures, necessitating region-specific adaptive strategies. In China, a key wheat producer and consumer, these challenges vary by region due to differences in climate, soil, and management practices.
OBJECTIVE
This study aims to evaluate how adaptive strategies—adjusting sowing dates, anthesis dates, and enhancing heat tolerance—can mitigate the adverse impacts of warming on wheat yields across China's diverse wheat-producing subregions.
METHODS
The improved WheatGrow model, incorporating heat stress effects, was used to simulate wheat yield responses under future warming scenarios. Strategies assessed include advancing sowing and anthesis dates and improving heat tolerance, tailored to subregions like Southwestern Winter Wheat Subregion (SWS), Yangtze River Winter Wheat Subregion (MYS), Northern Winter Wheat Subregion (NS), and Huang-Huai Winter Wheat Subregion (HHS).
RESULTS AND CONCLUSIONS
Advancing sowing dates can better mitigate the negative effects of warming in the SWS and MYS. Advancing anthesis date can increase yields in the NS, HHS and MYS, significantly reducing yield losses caused by heat stress. Additionally, improving heat tolerance in wheat cultivars can lead to higher yield improvements in the NS and HHS. Under the three warming scenarios, comprehensive adaptation strategies significantly reduced yield losses in all four subregions. Under the 1.5 °C HAPPI scenario, the total wheat production in China increased by 0.67 % with the optimal comprehensive adaptation strategy.
SIGNIFICANCE
These findings highlight the importance of region-specific adaptations to sustain wheat productivity in China amid climate change, offering actionable insights for policymakers and farmers to enhance food security.
{"title":"Integrative adaptation strategies for stabilizing wheat productivity with rising temperatures in China","authors":"Min Kang , Dongzheng Zhang , Yuan Cao , Liujun Xiao , Liang Tang , Leilei Liu , Weixing Cao , Yan Zhu , Bing Liu","doi":"10.1016/j.agsy.2025.104548","DOIUrl":"10.1016/j.agsy.2025.104548","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Global wheat production faces growing threats from climate change, particularly rising temperatures, necessitating region-specific adaptive strategies. In China, a key wheat producer and consumer, these challenges vary by region due to differences in climate, soil, and management practices.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to evaluate how adaptive strategies—adjusting sowing dates, anthesis dates, and enhancing heat tolerance—can mitigate the adverse impacts of warming on wheat yields across China's diverse wheat-producing subregions.</div></div><div><h3>METHODS</h3><div>The improved WheatGrow model, incorporating heat stress effects, was used to simulate wheat yield responses under future warming scenarios. Strategies assessed include advancing sowing and anthesis dates and improving heat tolerance, tailored to subregions like Southwestern Winter Wheat Subregion (SWS), Yangtze River Winter Wheat Subregion (MYS), Northern Winter Wheat Subregion (NS), and Huang-Huai Winter Wheat Subregion (HHS).</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Advancing sowing dates can better mitigate the negative effects of warming in the SWS and MYS. Advancing anthesis date can increase yields in the NS, HHS and MYS, significantly reducing yield losses caused by heat stress. Additionally, improving heat tolerance in wheat cultivars can lead to higher yield improvements in the NS and HHS. Under the three warming scenarios, comprehensive adaptation strategies significantly reduced yield losses in all four subregions. Under the 1.5 °C HAPPI scenario, the total wheat production in China increased by 0.67 % with the optimal comprehensive adaptation strategy.</div></div><div><h3>SIGNIFICANCE</h3><div>These findings highlight the importance of region-specific adaptations to sustain wheat productivity in China amid climate change, offering actionable insights for policymakers and farmers to enhance food security.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104548"},"PeriodicalIF":6.1,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145382521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-29DOI: 10.1016/j.agsy.2025.104546
Xingyu Guo , Shulan Wang , Hao Wang , Naeem Ahmad , Xiaoli Wang , Jun Li , Rui Wang
Context
Meeting global food security demands while maintaining environmental sustainability is a critical challenge for agricultural production systems. Population growth and global warming necessitate land management practices that simultaneously increase agricultural productivity and mitigate climate change.
Objective
This study aimed to evaluate different tillage practices within a complex framework of various indicators (crop production, environmental footprint and soil health) to determine the optimal practice for ensuring long-term sustainability in agricultural production.
Methods
We performed a 12-year (2007–2019) field study to examine the effects of plowing/no-tillage rotation (CN), continuous no-tillage (NT) and continuous plowing tillage (CT) on a winter wheat–spring maize rotation in the Loess Plateau, with focus on their yield, greenhouse gas (GHG) emissions, carbon footprint (CF), and net ecosystem economic benefit (NEEB). The comprehensive evaluation index (CEI) was used to assess the synergies and trade-offs among the productive, economic and environmental aspects of the three tillage practices based on Entropy-TOPSIS method.
Results and conclusion
Compared with CT, CN and NT significantly increased by 10.3 % and 3.9 % for grain yield, and 39.4 % and 26.4 % for energy production, respectively. Carbon footprint (CF) was significantly higher in CT (5799 kg CO2-eq ha−1), followed by CN (3477 kg CO2-eq ha−1), and NT (2468 kg CO2-eq ha−1). Similarly, water footprint (WF) was also higher in CT (3.2 m3 kg−1), followed by CN (3.0 m3 kg−1), and NT (2.8 m3 kg−1). However, CN and NT achieved lower yield-scale CF by 53.2 % and 59.0 %, and yield-scale WF by 10.1 % and 5.9 % compared to CT, respectively, and it resulted in a net ecosystem economic benefit (NEEB) increased of 37.8 % and 31.4 %, respectively. Thus, it is recognized there is a trade-off of grain yield improvement and GHG emissions in CN and NT. Notably, CN improved soil quality index (SQI) and has contributed to an overall improvement in soil structure and soil nutrients.
Significance
This study demonstrates that CN achieve a trade-off among improves crop productivity, environmental sustainability and resource conservation, positioning it as a climate-smart agricultural practice well-suited to the challenges associated with semi-arid regions. These findings provide valuable insights for farmers and policymakers seeking to promote sustainable agriculture in similar ecological contexts.
在保持环境可持续性的同时满足全球粮食安全需求是农业生产系统面临的重大挑战。人口增长和全球变暖需要同时提高农业生产力和减缓气候变化的土地管理措施。本研究旨在在各种指标（作物产量、环境足迹和土壤健康）的复杂框架内评估不同的耕作方式，以确定确保农业生产长期可持续性的最佳做法。方法通过12年（2007-2019）的田间研究，研究了旱作/免耕轮作（CN）、连续免耕（NT）和连续耕（CT）对黄土高原冬小麦-春玉米轮作的影响，重点研究了它们的产量、温室气体（GHG）排放、碳足迹（CF）和净生态系统经济效益（NEEB）。基于熵- topsis法，采用综合评价指数（CEI）对三种耕作方式在生产、经济和环境方面的协同效应和权衡进行了评价。结果与结论与CT相比，CN和NT的粮食产量分别提高10.3%和3.9%，能源产量分别提高39.4%和26.4%。碳足迹（CF）显著高于CT (5799 kg CO2-eq ha - 1)，其次是CN （3477 kg CO2-eq ha - 1）和NT （2468 kg CO2-eq ha - 1）。同样，CT的水足迹（WF）也较高（3.2 m3 kg−1），其次是CN （3.0 m3 kg−1）和NT （2.8 m3 kg−1）。然而，与CT相比，CN和NT的产量规模CF分别降低了53.2%和59.0%，WF分别降低了10.1%和5.9%，净生态系统经济效益（NEEB）分别提高了37.8%和31.4%。因此，我们认识到在华北和华北地区，粮食产量的提高与温室气体排放之间存在权衡关系。值得注意的是，华北地区改善了土壤质量指数（SQI），并有助于土壤结构和土壤养分的整体改善。本研究表明，CN在提高作物生产力、环境可持续性和资源保护之间实现了平衡，将其定位为一种气候智能型农业实践，非常适合半干旱地区的相关挑战。这些发现为寻求在类似生态环境下促进可持续农业的农民和政策制定者提供了有价值的见解。
{"title":"Integrated assessment reveals plowing/no-tillage rotation as the trade-off considering crop yield and environmental performance in the Loess Plateau","authors":"Xingyu Guo , Shulan Wang , Hao Wang , Naeem Ahmad , Xiaoli Wang , Jun Li , Rui Wang","doi":"10.1016/j.agsy.2025.104546","DOIUrl":"10.1016/j.agsy.2025.104546","url":null,"abstract":"<div><h3>Context</h3><div>Meeting global food security demands while maintaining environmental sustainability is a critical challenge for agricultural production systems. Population growth and global warming necessitate land management practices that simultaneously increase agricultural productivity and mitigate climate change.</div></div><div><h3>Objective</h3><div>This study aimed to evaluate different tillage practices within a complex framework of various indicators (crop production, environmental footprint and soil health) to determine the optimal practice for ensuring long-term sustainability in agricultural production.</div></div><div><h3>Methods</h3><div>We performed a 12-year (2007–2019) field study to examine the effects of plowing/no-tillage rotation (CN), continuous no-tillage (NT) and continuous plowing tillage (CT) on a winter wheat–spring maize rotation in the Loess Plateau, with focus on their yield, greenhouse gas (GHG) emissions, carbon footprint (CF), and net ecosystem economic benefit (NEEB). The comprehensive evaluation index (<em>CEI</em>) was used to assess the synergies and trade-offs among the productive, economic and environmental aspects of the three tillage practices based on Entropy-TOPSIS method.</div></div><div><h3>Results and conclusion</h3><div>Compared with CT, CN and NT significantly increased by 10.3 % and 3.9 % for grain yield, and 39.4 % and 26.4 % for energy production, respectively. Carbon footprint (CF) was significantly higher in CT (5799 kg CO<sub>2</sub>-eq ha<sup>−1</sup>), followed by CN (3477 kg CO<sub>2</sub>-eq ha<sup>−1</sup>), and NT (2468 kg CO<sub>2</sub>-eq ha<sup>−1</sup>). Similarly, water footprint (WF) was also higher in CT (3.2 m<sup>3</sup> kg<sup>−1</sup>), followed by CN (3.0 m<sup>3</sup> kg<sup>−1</sup>), and NT (2.8 m<sup>3</sup> kg<sup>−1</sup>). However, CN and NT achieved lower yield-scale CF by 53.2 % and 59.0 %, and yield-scale WF by 10.1 % and 5.9 % compared to CT, respectively, and it resulted in a net ecosystem economic benefit (NEEB) increased of 37.8 % and 31.4 %, respectively. Thus, it is recognized there is a trade-off of grain yield improvement and GHG emissions in CN and NT. Notably, CN improved soil quality index (SQI) and has contributed to an overall improvement in soil structure and soil nutrients.</div></div><div><h3>Significance</h3><div>This study demonstrates that CN achieve a trade-off among improves crop productivity, environmental sustainability and resource conservation, positioning it as a climate-smart agricultural practice well-suited to the challenges associated with semi-arid regions. These findings provide valuable insights for farmers and policymakers seeking to promote sustainable agriculture in similar ecological contexts.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104546"},"PeriodicalIF":6.1,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145382519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.agsy.2025.104549
Guang Han , Jingjing Wang , J.G. Arbuckle , Jinhuan Zhong
Context
Precision agriculture technologies hold significant potential for enhancing resource efficiency and agricultural sustainability. The Chinese government has proactively developed policies to promote the uptake of precision agriculture technologies.
Objective
To increase the adoption of precision agriculture among Chinese farmers, it is critical to understand the underlying decision-making mechanisms that influence farmers' adoption of precision agriculture technologies.
Methods
This study employed an extended unified theory of acceptance and use of technology (UTAUT) model to investigate key factors influencing Chinese farmers' adoption of precision agriculture technologies. Drawing on survey data from 413 farmers in Jiangsu Province, seven hypotheses were formulated and tested using partial least squares structural equation modeling (PLS-SEM).
Results and conclusions
The findings reveal that the latent constructs technology perception, policy perception, need motivation, and environmental awareness are critical direct drivers of precision agriculture adoption. These results underscore the importance of multifaceted strategies to foster technology uptake. Policymakers should prioritize strengthening agricultural extension services and outreach programs to enhance farmers' technical proficiency and firsthand experience with advanced tools. Additionally, targeted educational initiatives aimed at elevating farmers' environmental awareness can reinforce adoption rates and align with sustainability goals. Furthermore, agricultural technology developers are advised to prioritize designing intuitive, user-friendly equipment to lower barriers to entry and reduce the learning curve.
Significance
This study bridges theoretical and practical insights by illuminating the dynamic interplay among technology, policy, environmental awareness, individual motivation, and self-efficacy variables that can influence precision agriculture adoption. The findings provide actionable suggestions for government and stakeholders to collaboratively advance precision agriculture development in China.
{"title":"Understanding the adoption of precision agriculture technologies by farmers in China: Insights from the unified theory of acceptance and use of technology","authors":"Guang Han , Jingjing Wang , J.G. Arbuckle , Jinhuan Zhong","doi":"10.1016/j.agsy.2025.104549","DOIUrl":"10.1016/j.agsy.2025.104549","url":null,"abstract":"<div><h3>Context</h3><div>Precision agriculture technologies hold significant potential for enhancing resource efficiency and agricultural sustainability. The Chinese government has proactively developed policies to promote the uptake of precision agriculture technologies.</div></div><div><h3>Objective</h3><div>To increase the adoption of precision agriculture among Chinese farmers, it is critical to understand the underlying decision-making mechanisms that influence farmers' adoption of precision agriculture technologies.</div></div><div><h3>Methods</h3><div>This study employed an extended unified theory of acceptance and use of technology (UTAUT) model to investigate key factors influencing Chinese farmers' adoption of precision agriculture technologies. Drawing on survey data from 413 farmers in Jiangsu Province, seven hypotheses were formulated and tested using partial least squares structural equation modeling (PLS-SEM).</div></div><div><h3>Results and conclusions</h3><div>The findings reveal that the latent constructs technology perception, policy perception, need motivation, and environmental awareness are critical direct drivers of precision agriculture adoption. These results underscore the importance of multifaceted strategies to foster technology uptake. Policymakers should prioritize strengthening agricultural extension services and outreach programs to enhance farmers' technical proficiency and firsthand experience with advanced tools. Additionally, targeted educational initiatives aimed at elevating farmers' environmental awareness can reinforce adoption rates and align with sustainability goals. Furthermore, agricultural technology developers are advised to prioritize designing intuitive, user-friendly equipment to lower barriers to entry and reduce the learning curve.</div></div><div><h3>Significance</h3><div>This study bridges theoretical and practical insights by illuminating the dynamic interplay among technology, policy, environmental awareness, individual motivation, and self-efficacy variables that can influence precision agriculture adoption. The findings provide actionable suggestions for government and stakeholders to collaboratively advance precision agriculture development in China.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104549"},"PeriodicalIF":6.1,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-27DOI: 10.1016/j.agsy.2025.104543
Amr Adel , Reddy Pullanagari , Noor H.S. Alani , Mohammad Al-Rawi , Syeda Fouzia , Bettina Berger
CONTEXT
The adoption of drones within Agriculture 5.0 is transforming farming into a service-oriented and data-driven system. This study provides a state-of-art review of Drone-as-a-Service (DaaS), evaluating applications across crop monitoring, soil assessment, livestock surveillance, harvest forecasting, and post-harvest logistics.
OBJECTIVE
This review propose a systems-level framework to guide future research, regulation, and deployment of drones within Agriculture 5.0.
METHODS
The study synthesises datasets from published technical standards, communication protocols, interoperability studies, and agricultural service platforms, complemented by tabulated evidence on drone functions, integration challenges, and regulatory frameworks.
RESULTS AND CONCLUSIONS
Analysis of these datasets highlights both the operational advantages of drones, such as precision in resource allocation and enhanced scalability, and the persistent barriers of fragmented standards, high costs, and regulatory constraints, alongside service model aspects of the study.
SIGNIFICANCE
Unlike existing literature that largely emphasises hardware, this study shifts focus to the service model, identifying how DaaS can democratise drone access for small- and medium-scale farms. The findings reveal knowledge gaps in interoperability, cost–benefit analysis, and policy readiness.
{"title":"Drones-of-the-Future in Agriculture 5.0 – Automation, integration, and optimisation","authors":"Amr Adel , Reddy Pullanagari , Noor H.S. Alani , Mohammad Al-Rawi , Syeda Fouzia , Bettina Berger","doi":"10.1016/j.agsy.2025.104543","DOIUrl":"10.1016/j.agsy.2025.104543","url":null,"abstract":"<div><h3>CONTEXT</h3><div>The adoption of drones within Agriculture 5.0 is transforming farming into a service-oriented and data-driven system. This study provides a state-of-art review of Drone-as-a-Service (DaaS), evaluating applications across crop monitoring, soil assessment, livestock surveillance, harvest forecasting, and post-harvest logistics.</div></div><div><h3>OBJECTIVE</h3><div>This review propose a systems-level framework to guide future research, regulation, and deployment of drones within Agriculture 5.0.</div></div><div><h3>METHODS</h3><div>The study synthesises datasets from published technical standards, communication protocols, interoperability studies, and agricultural service platforms, complemented by tabulated evidence on drone functions, integration challenges, and regulatory frameworks.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Analysis of these datasets highlights both the operational advantages of drones, such as precision in resource allocation and enhanced scalability, and the persistent barriers of fragmented standards, high costs, and regulatory constraints, alongside service model aspects of the study.</div></div><div><h3>SIGNIFICANCE</h3><div>Unlike existing literature that largely emphasises hardware, this study shifts focus to the service model, identifying how DaaS can democratise drone access for small- and medium-scale farms. The findings reveal knowledge gaps in interoperability, cost–benefit analysis, and policy readiness.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104543"},"PeriodicalIF":6.1,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-25DOI: 10.1016/j.agsy.2025.104540
Fazli Hameed , Muhammad Mannan Afzal , Anis Ur Rehman Khalil , Junzeng Xu , Shah Fahad Rahim , Raheel Osman , Khalil Ahmad , Yongqiang Li , Tangyuan Ning
CONTEXT
Evidence on how alternate wetting and drying (AWD) irrigation and nitrogen management together influence rice yield and resource efficiency under climate variability is still limited, yet such knowledge is critical for climate-smart agricultural planning. Climate change and inefficient agronomic practices increasingly threaten the sustainability of rice production systems by intensifying water scarcity and lowering nitrogen use efficiency (NUE).
OBJECTIVE
The objective of this study was to assess the combined effects of irrigation regimes, continuous flooding (CF) and AWD, and nitrogen application strategies on rice yield, nitrogen uptake, and resource use efficiency under projected climate change scenarios using the ORYZA (v3) model.
METHODS
The ORYZA (v3) crop growth model was used to simulate rice growth, water consumption (ET), irrigation water requirements (IR), water use efficiency (WUE) and nitrogen use efficiencies (NUE) under historical and future climate scenarios (RCP2.6 to RCP8.5). Two irrigation strategies: CF and AWD, and multiple nitrogen application schedules were tested.
RESULTS AND CONCLUSIONS
Future climate scenarios projected substantial yield reductions, reaching up to 36 % under CF and 43 % under AWD in the 2080s under RCP 8.5. The difference between regimes was small under moderate scenarios but became more pronounced with extreme heat and water stress. Water productivity also declined sharply, with WUE dropping by up to 58 % and irrigation water use efficiency (IWUE) by 72 %. Nitrogen use efficiencies consistently decreased at higher application rates, though moderate N input (150–190 kg ha−1) with split applications sustained relatively better performance. AWD reduced irrigation water demand by 7–70 % compared with CF, but its yield advantage diminished under severe climate stress. Elevated CO₂ modestly improved efficiencies but could not counteract overall declines. Overall, these findings highlight that combining AWD with moderate nitrogen rates offers a practical pathway for sustaining rice production while conserving resources under changing climate conditions.
SIGNIFICANCE
These findings provide evidence that combining AWD with moderate nitrogen inputs can guide policies and farm practices aimed at sustaining rice yields, conserving water, and improving input efficiency under a changing climate.
在气候变率条件下，干湿交替灌溉和氮肥管理如何共同影响水稻产量和资源效率的证据仍然有限，但这些知识对于气候智能型农业规划至关重要。气候变化和低效的农艺做法加剧了水资源短缺，降低了氮素利用效率，从而日益威胁着水稻生产系统的可持续性。本研究的目的是利用ORYZA （v3）模型评估在预测的气候变化情景下，灌溉制度、连续淹水（CF）和连续淹水（AWD）以及施氮策略对水稻产量、氮吸收和资源利用效率的综合影响。方法采用ORYZA （v3）作物生长模型，模拟历史和未来气候情景（RCP2.6 ~ RCP8.5）下水稻生长、水分消耗（ET）、灌溉需水量（IR）、水分利用效率（WUE）和氮利用效率（NUE）。试验了CF和AWD两种灌溉策略和多种氮肥施用量。结果与结论未来气候情景预测，到2080年代，在RCP 8.5条件下，CF条件下产量将大幅下降36%，AWD条件下产量将下降43%。在温和的情况下，两种情况之间的差异很小，但在极端高温和缺水的情况下，差异变得更加明显。水分生产力也急剧下降，用水效率下降58%，灌溉用水效率（IWUE）下降72%。在较高的施氮量下，氮素利用效率持续下降，但中等施氮量（150-190 kg ha - 1）的分施能保持相对较好的表现。AWD比CF减少灌溉需水量7 ~ 70%，但在严重气候胁迫下产量优势减弱。二氧化碳浓度的升高适度地提高了效率，但不能抵消整体的下降。总之，这些发现突出表明，在气候变化条件下，将AWD与适度施氮结合为维持水稻生产同时节约资源提供了一条切实可行的途径。这些发现提供了证据，表明在气候变化条件下，将AWD与适度氮投入相结合可以指导旨在维持水稻产量、节约用水和提高投入效率的政策和农业实践。
{"title":"Integrated water and nitrogen management sustains rice yield and efficiency under changing climate scenarios","authors":"Fazli Hameed , Muhammad Mannan Afzal , Anis Ur Rehman Khalil , Junzeng Xu , Shah Fahad Rahim , Raheel Osman , Khalil Ahmad , Yongqiang Li , Tangyuan Ning","doi":"10.1016/j.agsy.2025.104540","DOIUrl":"10.1016/j.agsy.2025.104540","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Evidence on how alternate wetting and drying (AWD) irrigation and nitrogen management together influence rice yield and resource efficiency under climate variability is still limited, yet such knowledge is critical for climate-smart agricultural planning. Climate change and inefficient agronomic practices increasingly threaten the sustainability of rice production systems by intensifying water scarcity and lowering nitrogen use efficiency (NUE).</div></div><div><h3>OBJECTIVE</h3><div>The objective of this study was to assess the combined effects of irrigation regimes, continuous flooding (CF) and AWD, and nitrogen application strategies on rice yield, nitrogen uptake, and resource use efficiency under projected climate change scenarios using the ORYZA (v3) model.</div></div><div><h3>METHODS</h3><div>The ORYZA (v<sub>3</sub>) crop growth model was used to simulate rice growth, water consumption (ET), irrigation water requirements (IR), water use efficiency (WUE) and nitrogen use efficiencies (NUE) under historical and future climate scenarios (RCP2.6 to RCP8.5). Two irrigation strategies: CF and AWD, and multiple nitrogen application schedules were tested.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Future climate scenarios projected substantial yield reductions, reaching up to 36 % under CF and 43 % under AWD in the 2080s under RCP 8.5. The difference between regimes was small under moderate scenarios but became more pronounced with extreme heat and water stress. Water productivity also declined sharply, with WUE dropping by up to 58 % and irrigation water use efficiency (IWUE) by 72 %. Nitrogen use efficiencies consistently decreased at higher application rates, though moderate N input (150–190 kg ha<sup>−1</sup>) with split applications sustained relatively better performance. AWD reduced irrigation water demand by 7–70 % compared with CF, but its yield advantage diminished under severe climate stress. Elevated CO₂ modestly improved efficiencies but could not counteract overall declines. Overall, these findings highlight that combining AWD with moderate nitrogen rates offers a practical pathway for sustaining rice production while conserving resources under changing climate conditions.</div></div><div><h3>SIGNIFICANCE</h3><div>These findings provide evidence that combining AWD with moderate nitrogen inputs can guide policies and farm practices aimed at sustaining rice yields, conserving water, and improving input efficiency under a changing climate.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104540"},"PeriodicalIF":6.1,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145358702","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}
In sub-Saharan Africa, where most farmers rely on rain-fed agriculture, climate change poses serious threats. Agroforestry offers a promising adaptation strategy, with well-documented ecological and economic benefits. Yet, evidence on its role in enhancing household-level resilience to adverse weather events, such as drought, remains limited.
Objective
We assess how decreases in rainfall affect cocoa yield among agroforestry adopters and non-adopters in Ghana and examine whether these effects vary by regional climatic suitability.
Methods
We combine a two-wave panel data set of 365 cocoa-producing households with satellite-based climate data. We use a correlated random effects model to estimate the differential effects of reduced rainfall on yield by agroforestry status. To test for heterogeneity, we re-estimate the model for two subsamples located in climatically suitable and less suitable cocoa-growing regions.
Results and conclusions
We find that on average, agroforestry adopters are less severely affected by reduced rainfall. A one-millimeter decrease in rainfall significantly reduces yield by 2.17 kg/ha for adopters and 2.84 kg/ha for non-adopters. However, when disaggregating between regions, this effect only holds in climatically suitable regions. In less suitable, drier regions, we do not find any significant effects. Our findings suggest that agroforestry could be used as a strategy for adapting to climate change, although more research is needed to understand the conditions under which it would be most effective.
Significance
We are among the first to use household panel data to econometrically assess the effects of reduced rainfall on yield based on agroforestry adoption in the cocoa sector.
{"title":"Agroforestry as a climate change adaptation strategy: Evidence from Ghana's cocoa sector","authors":"Marlene Yu Lilin Wätzold , Katharina Krumbiegel , Pascal Tillie , Meike Wollni","doi":"10.1016/j.agsy.2025.104519","DOIUrl":"10.1016/j.agsy.2025.104519","url":null,"abstract":"<div><h3>Context</h3><div>In sub-Saharan Africa, where most farmers rely on rain-fed agriculture, climate change poses serious threats. Agroforestry offers a promising adaptation strategy, with well-documented ecological and economic benefits. Yet, evidence on its role in enhancing household-level resilience to adverse weather events, such as drought, remains limited.</div></div><div><h3>Objective</h3><div>We assess how decreases in rainfall affect cocoa yield among agroforestry adopters and non-adopters in Ghana and examine whether these effects vary by regional climatic suitability.</div></div><div><h3>Methods</h3><div>We combine a two-wave panel data set of 365 cocoa-producing households with satellite-based climate data. We use a correlated random effects model to estimate the differential effects of reduced rainfall on yield by agroforestry status. To test for heterogeneity, we re-estimate the model for two subsamples located in climatically suitable and less suitable cocoa-growing regions.</div></div><div><h3>Results and conclusions</h3><div>We find that on average, agroforestry adopters are less severely affected by reduced rainfall. A one-millimeter decrease in rainfall significantly reduces yield by 2.17 kg/ha for adopters and 2.84 kg/ha for non-adopters. However, when disaggregating between regions, this effect only holds in climatically suitable regions. In less suitable, drier regions, we do not find any significant effects. Our findings suggest that agroforestry could be used as a strategy for adapting to climate change, although more research is needed to understand the conditions under which it would be most effective.</div></div><div><h3>Significance</h3><div>We are among the first to use household panel data to econometrically assess the effects of reduced rainfall on yield based on agroforestry adoption in the cocoa sector.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104519"},"PeriodicalIF":6.1,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145358701","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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