Agricultural Systems最新文献

{"title":"Climate change impacts on the suitability of lowland and upland crop systems in Lao PDR","authors":"Jonas L. Appelt ,&nbsp;Thatheva Saphangthong ,&nbsp;Peter H. Verburg ,&nbsp;Jasper van Vliet","doi":"10.1016/j.agsy.2025.104316","DOIUrl":"10.1016/j.agsy.2025.104316","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Climate change is a major driver of changes in agricultural systems, with effects playing out differently across crop types and biophysical conditions. Studies have so far not investigated differences between lowland and upland crop systems when projecting consequences of climate change on agricultural production in Southeast Asia.</div></div><div><h3>OBJECTIVE</h3><div>To model the change in crop suitability under different climate scenarios for major crops in Lao PDR and analyse differentiated impacts across lowland and upland crop systems.</div></div><div><h3>METHODS</h3><div>We use a modified version of the EcoCrop suitability model, adding additional considerations for precipitation seasonality, to project the change in crop suitability in Lao PDR under different climate scenarios for the medium term future (2041–2070). The analysis compares impacts across lowland and upland village areas for six major crops: Paddy rice, upland rice, maize, cassava, banana, and rubber. Further, we contextualize the results with data from a survey of eight lowland and four upland villages in Savannakhet Province.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>For all the included crops, we find that changes in climatic suitability will be significantly more negative (higher decrease or smaller increase) in lowland village areas than in upland village areas. In particular, rice suitability is projected to decrease considerably in lowland areas due to increases in heat and variability in wet season precipitation, while higher temperatures improve the suitability of non-rice crops in upland areas due to lower cold stress, with the largest increases being for maize, cassava, and banana. Local crop data from Savannakhet Province further reveals how climate change impacts can increase the risks to production and food security in rice focused systems in lowland areas.</div></div><div><h3>SIGNIFICANCE</h3><div>These results indicate that upland crop systems in Lao PDR may fare better than lowland systems under future climate change and highlight the importance of differentiating between agricultural production systems when projecting impacts of climate change in Southeast Asia.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104316"},"PeriodicalIF":6.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of reduced livestock density on European agriculture and the environment","authors":"Maria Bielza ,&nbsp;Franz Weiss ,&nbsp;Jordan Hristov ,&nbsp;Thomas Fellmann","doi":"10.1016/j.agsy.2025.104299","DOIUrl":"10.1016/j.agsy.2025.104299","url":null,"abstract":"<div><h3>CONTEXT</h3><div>The European Green Deal (EGD) and Common Agricultural Policy (CAP) reforms aim to achieve substantial environmental and climate objectives, requiring changes in agricultural practices. Livestock density limits could be one of the measures to reduce adverse environmental impacts associated with intensive livestock production, particularly nitrogen pollution and greenhouse gas (GHG) emissions.</div></div><div><h3>OBJECTIVE</h3><div>This study examines the effects of imposing maximum limits on livestock units (LSU) per hectare of utilized agricultural area (UAA) across the EU. The analysis focuses on both the economic and environmental impacts of livestock density restrictions, with particular emphasis on their influence on production, nitrogen surplus, ammonia emissions, nitrate leaching, and GHG emissions.</div></div><div><h3>METHODS</h3><div>Using the Common Agricultural Policy Regional Impact Analysis (CAPRI) model, a detailed agricultural sector model, the study simulates impacts of different livestock density thresholds (2 LSU/ha and 1.4 LSU/ha) at regional and grid levels. The model facilitates an evaluation of the potential changes in production, market prices, trade dynamics, and environmental indicators, providing a comprehensive view of the policy's potential outcomes.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Implementing livestock density limits results in reduced EU livestock numbers, particularly affecting the pig sector, with subsequent decreases in production of animal products and increases in market prices. Farming practices shift toward extensification, with environmental benefits including reductions in ammonia emissions, nitrates leaching, and nitrogen surplus. However, a considerable amount of GHG emissions reduction in the EU could be offset by emission leakage to non-EU regions, diminishing the net global environmental benefits.</div></div><div><h3>SIGNIFICANCE</h3><div>The study's findings offer insights for EU policymakers and agricultural stakeholders into the complexities associated with enforcing livestock density limits. The results underscore the importance of balancing agricultural production with environmental sustainability and highlight the need for comprehensive strategies that account for both local and global environmental impacts. The study suggests that integrated measures are essential to achieving the EGD's ambitious environmental objectives.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104299"},"PeriodicalIF":6.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592169","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}

{"title":"ProbApple – A probabilistic model to forecast apple yield and quality","authors":"Christine Schmitz ,&nbsp;Lars Zimmermann ,&nbsp;Katja Schiffers ,&nbsp;Martin Balmer ,&nbsp;Eike Luedeling","doi":"10.1016/j.agsy.2025.104298","DOIUrl":"10.1016/j.agsy.2025.104298","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Fruit yield and quality are critical determinants of the economic performance of apple orchards. However, these economic metrics are highly uncertain due to various quality-reducing factors during the growing season, and fruit growers would greatly benefit from reliable predictions.</div></div><div><h3>OBJECTIVE</h3><div>In this study, we aim at developing a new tool to support fruit growers in anticipating yield and potential quality losses under the specific conditions of their orchards. The tool should allow application at four key time points during the growing season (at full bloom, before fruit thinning, after June drop, and four weeks before harvest) and capture uncertainty in the quality-reducing factors and the resulting yield parameters.</div></div><div><h3>METHODS</h3><div>Using expert knowledge, we designed and parameterized the probabilistic ‘ProbApple’ model and conducted Monte Carlo simulations to project probability distributions for total and high-quality apple yield for a ‘Gala’ orchard in the German Rhineland. We compared scenarios with and without anti-hail netting to demonstrate the use of the model for predicting apple yield.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Applying the model four weeks before harvest, the median forecasted apple yield was 50.4 t/ha (25 %-quantile: 44.0; 75 %-quantile: 57.8 t/ha) with anti-hail netting and 49.3 t/ha (25 %-quantile: 42.7; 75 %-quantile: 56.5 t/ha) without. The forecasted high-quality yield was 34.9 t/ha (25 %-quantile: 27.5; 75 %-quantile: 41.6 t/ha) with the protection measure and 30.0 t/ha (25 %-quantile: 15.8; 75 %-quantile: 38.7 t/ha) without. These results are in line with commonly achieved ‘Gala’ apple yields in the Rhineland region.</div></div><div><h3>SIGNIFICANCE</h3><div>We show that ProbApple is a customizable tool for forecasting apple yield and quality, offering producers valuable insights for operational planning and informed management decisions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104298"},"PeriodicalIF":6.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agronomic measures improve crop yield and water and nitrogen use efficiency under brackish water irrigation: A global meta-analysis","authors":"Ruopu Wang ,&nbsp;Heli Cao ,&nbsp;Shaozhong Kang ,&nbsp;Taisheng Du ,&nbsp;Ling Tong ,&nbsp;Jian Kang ,&nbsp;Jia Gao ,&nbsp;Risheng Ding","doi":"10.1016/j.agsy.2025.104304","DOIUrl":"10.1016/j.agsy.2025.104304","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Brackish groundwater irrigation presents a feasible solution to alleviate water scarcity; however, it also induces salt stress in crops. The effects of agronomic measures on crop yield, water use efficiency (WUE), irrigation water use efficiency (IWUE) and nitrogen use efficiency (NUE) under brackish water irrigation are still unclear.</div></div><div><h3>OBJECTIVE</h3><div>The objectives of this study were to: (i) systematically analyze the effects of brackish water irrigation on yield, WUE, IWUE and NUE of cotton and grain crops across different climates and soil types; (ii) investigate how agronomic measures such as irrigation amounts, fertilizer application, and biochar addition affect crop yield, WUE, and NUE under brackish water irrigation; (iii) explore the effects of meteorological conditions, soil properties, and agronomic measures on yield, WUE, IWUE and NUE using random forest model and correlation analyses.</div></div><div><h3>METHODS</h3><div>This study conducted a comprehensive meta–analysis of 636 comparisons from 81 global studies on brackish water irrigation. In addition, machine learning was used to assess the effects of environmental conditions and agronomic measures on crop yield, WUE, IWUE and NUE under brackish water irrigation, as well as to determine the relative importance of different influencing factors.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Brackish water irrigation significantly reduced crop yield, WUE, IWUE, and NUE compared to freshwater irrigation. Cotton showed the strongest adaptability to brackish water, followed by wheat, while maize exhibited the poorest adaptability. Acidic soil with low bulk density and loamy texture were most conducive to brackish water irrigation, particularly in semi–arid and semi–humid regions. Increasing irrigation amount by 25–50 % can both increase crop yields and maintain high WUE. Although increased nitrogen application enhanced grain yields and WUE, it was also associated with the risk of significant decline in NUE. Random forest model analysis suggested that prioritizing nitrogen application is essential for cotton under brackish water irrigation, while increasing irrigation water is more critical for wheat and maize.</div></div><div><h3>SIGNIFICANCE</h3><div>This study provided valuable insights into the response of crop production indicators under brackish water irrigation and offered recommendations for its rational application.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104304"},"PeriodicalIF":6.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592170","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}

{"title":"Unveiling the influence of agricultural mechanization on greenhouse gas emission intensity: Insights from China using causal machine learning model","authors":"Lulu Wang,&nbsp;Jie Lyu,&nbsp;Shanshan Wang,&nbsp;Junyan Zhang","doi":"10.1016/j.agsy.2025.104307","DOIUrl":"10.1016/j.agsy.2025.104307","url":null,"abstract":"<div><h3>Context</h3><div>The ongoing agricultural mechanization in China contributes considerably to increased efficiency and productivity. However, its mitigation potential of greenhouse gas emissions intensity (GHGI) and underlying mechanisms are still unclear. Debate regarding the influence of agricultural mechanization on GHGI is gaining significance to guarantee that agricultural modernization corresponds with sustainable development goals.</div></div><div><h3>Objective</h3><div>This study attempts to provide quantitative evidence of agricultural mechanization on reducing GHGI from a fresh perspective of factor allocation.</div></div><div><h3>Methods</h3><div>The village-level dataset, involving 895 farmers across three northeastern provinces in China, was employed to confirm the theoretical analysis. The causal effect was estimated using a newly developed causal inference approach by incorporating double machine learning models. More explicitly, this research delved into the specific mechanism of factor allocation from three channels involving land transfer and operation scale, labor inputs, and agrochemical use intensity.</div></div><div><h3>Results and conclusions</h3><div>Empirical results show that GHGI generally decreases as agricultural mechanization increases. Among various field operations, the harvesting operation exerts the most significant influence on GHGI. The disparity in impact between mechanized plowing and mechanized harvesting is relatively minor. Further, the results of robustness tests using instrumental variable methods and recursive models strongly confirm the existence of this causal relationship.</div></div><div><h3>Significance</h3><div>Overall, these findings suggest advancing environmentally friendly mechanization and implementing targeted policies to reduce GHGI in agriculture along with enhanced factor provisions through optimizing allocation.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104307"},"PeriodicalIF":6.1,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580132","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}

{"title":"Hard-seeded annual pasture legume phases are a profitable and low risk option in mixed farming regions with low to medium rainfall","authors":"Dean T. Thomas ,&nbsp;Sadeeka L. Jayasinghe ,&nbsp;Chris Herrmann ,&nbsp;Robert J. Harrison ,&nbsp;Bonnie M. Flohr ,&nbsp;Roger A. Lawes","doi":"10.1016/j.agsy.2025.104302","DOIUrl":"10.1016/j.agsy.2025.104302","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Diversified cropping rotations mitigate key challenges associated with continuous or mono-cropping, including soil fertility depletion, increased pest pressure, and reduced economic resilience due to limited diversification opportunities. However, an effective rotation sequence depends on a mix of agronomic and economic factors.</div></div><div><h3>OBJECTIVE</h3><div>This study aimed to assess the profitability and risk levels associated with rotations integrating non-traditional hard-seeded annual pasture legumes (NHL) in the mixed farming zone of southern Australia.</div></div><div><h3>METHODS</h3><div>Utilizing the Land Use Sequence Optimizer (LUSO), a study was conducted over a 30-year period (1991–2020) across three locations to compare the profit and conditional value at risk (CvaR) of rotations comparing two levels of biotic stress (high or low).</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Rotations including NHL pasture were more profitable and exhibited lower risk compared to traditional improved annual pasture-legumes (TIL) or continuous cropping. These findings were consistent across various climate conditions. However, at one location (Condobolin), continuous cropping slightly outperformed the NHL rotation sequence in terms of both profit and lower risk. This was attributed to higher rainfall and temperature, where extended spring rainfall boosted canola and wheat yields. Despite greater fluctuations, overall moisture and warmth favoured continuous cropping. In contrast, at the other locations (Corrigin and Lameroo), NHL rotations were more profitable and less risky than continuous cropping.</div></div><div><h3>SIGNIFICANCE</h3><div>Rotations incorporating NHL pastures consistently showed resilience in locations prone to high biotic stress across all three sites. The inclusion of NHL pasture phases in mixed farming rotations improves profit and reduces risk, particularly in drier, variable regions, by withstanding dry periods and enhancing soil moisture. This is particularly beneficial in areas with variable rain-fed production, such as southern Australia's low- to medium rainfall regions. These findings highlight the ecological and economic advantages of incorporating NHL into rotations, contributing to contributing to more diversified and resilient farming systems.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104302"},"PeriodicalIF":6.1,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580131","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}

{"title":"Unlocking China's grain yield potential: Harnessing technological and spatial synergies in diverse cropping systems","authors":"Zhen-Zhong Dai ,&nbsp;Sen Chang ,&nbsp;Guo-Rong Zhao ,&nbsp;Jia-Jia Duan ,&nbsp;Hao-Yuan Liang ,&nbsp;Zhi-Yuan Zhu ,&nbsp;Sheng-Li Liu ,&nbsp;Yong-Zhong Feng ,&nbsp;Xing Wang","doi":"10.1016/j.agsy.2025.104308","DOIUrl":"10.1016/j.agsy.2025.104308","url":null,"abstract":"<div><h3>Context</h3><div>Diversified cropping patterns (CPs) offer significant technical advantages in improving crop yields and enhancing resource efficiency. Achieving high-precision, multi-objective spatial optimization of CPs layouts is essential for implementing precise food security policies and building sustainable agricultural systems.</div></div><div><h3>Objective</h3><div>This study aims to analyze and predict the spatiotemporal evolution trends of seven CPs for maize, rice, and wheat in China from 2015 to 2030. It seeks to identify high-precision potential yield enhancement zones and multi-season cropping restoration zones and propose spatial optimization plans and technical optimization strategies for CPs.</div></div><div><h3>Methods</h3><div>Using the PLUS-Bayesian network-Geodetector framework, this study predicts the spatial layout of CPs in 2030, conducts multi-objective spatial layout optimization, and determines technical directions for CPs in key application regions.</div></div><div><h3>Results and conclusions</h3><div>From 2015 to 2030, the application area of staple CPs declined significantly, with non-grain cropping and single-season grain cropping trends persisting. Multi-objective optimization results show that optimizing CP technologies in yield zones and promoting multi-season cropping in restoration zones could increase grain yields by over 100 million tons, reduce nitrogen fertilizer use, and improve water management efficiency. Regional differences in CPs evolution and yield-influencing factors were identified, and zoning optimization plans and technical directions for 2030 were proposed.</div></div><div><h3>Significance</h3><div>This study presents a high-precision, multi-objective spatial optimization method for cropping patterns, offering practical solutions for increasing crop yields, improving resource efficiency, and supporting sustainable agriculture in China. It also provides new ideas and methods for building a sustainable global agricultural development framework.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104308"},"PeriodicalIF":6.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580130","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}

{"title":"How opportunity and cognition improve family farms' low-carbon production behavior: Evidence from China","authors":"Lei Zhu,&nbsp;Shaocong Yan,&nbsp;Lili Geng,&nbsp;Xiaomeng Liang,&nbsp;Yongji Xue","doi":"10.1016/j.agsy.2025.104296","DOIUrl":"10.1016/j.agsy.2025.104296","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Climate warming is widely regarded as a crucial driver of numerous global challenges, posing a significant threat to human survival and development. Among the various factors contributing to climate warming, the greenhouse gas emissions from high-carbon agricultural practices—such as the excessive use of fertilizers, pesticides, and plastic films—are particularly concerning. Therefore, it is essential to study the low-carbon production decision-making behaviors of agricultural producers to mitigate the negative impacts of agriculture on climate change.</div></div><div><h3>OBJECTIVE</h3><div>To investigate whether the implementation of low-carbon production behaviors in family farms is driven by individual emotional willingness or by external environmental opportunities, this study constructs a decision-making model of low-carbon production behaviors in family farms to analyze the factors that directly or indirectly drive the implementation of low-carbon production behaviors, and then more accurately describes and explains the behavioral choices of agricultural producers.</div></div><div><h3>METHODS</h3><div>This study links the Motivation-Opportunity-Ability model with the Cognitive-Affective-Conative model to form a comprehensive theoretical framework for decision-making on low-carbon production behavior in family farms. Meanwhile, this study empirically tested the hypothesized model using the partial least squares structural equation modeling analysis technique.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Low-carbon production opportunity and has a direct and positive effect on low-carbon production behavior. Low-carbon production cognition also affects low-carbon production behavior, but this effect is positive and indirect. Low-carbon production ability, low-carbon production motivation, low-carbon production affection, and low-carbon production intention play a mediating role in all hypotheses. Therefore, this study concludes that low-carbon production opportunity rather than cognition is the crucial element that directly triggers the behavioral response to low-carbon production in family farms. However, the internalization process of low-carbon production cognition still plays an important role in low-carbon production decision-making on family farms.</div></div><div><h3>SIGNIFICANCE</h3><div>Based on the dual identity attributes of “economic man” and “social man” in family farms, this study not only expands the theoretical framework for analyzing low-carbon production behaviors in agriculture but also emphasizes the positive impacts of the individual's emotional will and external environmental opportunities on the implementation of low-carbon production in family farms.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"226 ","pages":"Article 104296"},"PeriodicalIF":6.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562038","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}

{"title":"From rural to urban: Exploring livestock farming practices in urbanizing landscapes","authors":"Dagmar J.M. Braamhaar ,&nbsp;Jan van der Lee ,&nbsp;Bockline O. Bebe ,&nbsp;Simon J. Oosting","doi":"10.1016/j.agsy.2025.104297","DOIUrl":"10.1016/j.agsy.2025.104297","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Urbanization in Kenya continues to accelerate, reshaping the agricultural landscape and impacting livestock farming practices.</div></div><div><h3>OBJECTIVE</h3><div>This study investigated the spatial variation of livestock farming systems across urban, peri-urban, and rural areas in Nakuru County to assess the impact of urbanization on resource use, nutrient cycling, and livestock diversification.</div></div><div><h3>METHODS</h3><div>A multi-stage cluster sampling method was used to interview 241 households selected from four sub-counties: Nakuru East (urban), Naivasha (urban), Njoro (peri-urban), and Kuresoi North (rural). In each sub-county, three wards were selected, with four selected roads per ward. A structured questionnaire was administered to collect data on farm size, herd size and diversity, feeding practices, manure management, and market access.</div></div><div><h3>RESULTS</h3><div>The total herd size, including all animal species present on the farm, was lower in the urban area of Nakuru East than in all other areas (<em>P</em> &lt; 0.001). However, the numbers of individual species (i.e., dairy cattle, dairy goats, and chickens) per farm did not differ among areas and were not significantly correlated to land size. On average, farmers kept 4.6 dairy cattle, 6.2 dairy goats, and 49.1 chickens if they had those species. In the urban areas of Nakuru East, land scarcity led to limited space for forage production. The other areas prioritized land use for crop production over that for forage production for their livestock. Our findings indicate high stocking rates across all areas: urban areas averaged 41.8 TLU/ha and peri-urban and rural areas averaged over 6 TLU/ha. The high stocking rates and low forage production explain the overall dependency on feed purchases. Agricultural supply stores were present in all areas, providing opportunities for feed and other input purchases. Peri-urban and rural farms relied more on compound feeds, while urban farms purchased specific energy- and protein-rich ingredients for their livestock diets. Due to the high dependency on feed purchases and small land size, farms face nutrient accumulation in the form of manure, creating risks of environmental hazards. Overall, our research reveals that urbanization has created a shift towards more intensive and market-oriented farming across all areas.</div></div><div><h3>SIGNIFICANCE</h3><div>Understanding the interaction between urbanization and livestock farming practices is crucial for developing sustainable agricultural production and marketing strategies that can accommodate the changing landscape of urbanizing areas.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"225 ","pages":"Article 104297"},"PeriodicalIF":6.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Agronomic Solutions to Close Wheat Yield Gaps and Achieve Self-Sufficiency in Uzbekistan","authors":"Krishna Prasad Devkota ,&nbsp;Mina Devkota ,&nbsp;Hasan Boboev ,&nbsp;Diyor Juraev ,&nbsp;Sherzod Dilmurodov ,&nbsp;Ram C. Sharma","doi":"10.1016/j.agsy.2025.104291","DOIUrl":"10.1016/j.agsy.2025.104291","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;CONTEXT&lt;/h3&gt;&lt;div&gt;Agriculture is a cornerstone of Uzbekistan's economy, accounting for 25 % to the national gross domestic product and employing 26 % of the workforce. Since independence, wheat intensification has been a national priority, with cultivated land expanding from 0.63 million hectares (Mha) to 1.24 Mha and productivity increasing from 1.66 t ha&lt;sup&gt;−1&lt;/sup&gt; in 1991 to 4.55 t ha&lt;sup&gt;−1&lt;/sup&gt; in 2023. However, on-farm yields remain below attainable yield, leading to a reliance on wheat imports to meet domestic demand. Closing this yield gap is critical for achieving national wheat self-sufficiency.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVES&lt;/h3&gt;&lt;div&gt;This study aims to identify key yield-limiting factors and develop evidence-based, agroecologically optimized bundled solutions to enhance wheat productivity in Uzbekistan. By integrating multiple analytical approaches, the research seeks to provide targeted agronomic recommendations for improving sustainability and self-sufficiency.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;A combination of systematic reviews, crop modeling, and machine learning was used to analyze wheat yield gaps and optimize agronomic practices. Agricultural Production Systems sIMulator (APSIM) -Wheat model was calibrated, validated and used to simulate wheat yields over 36-years across four agro-ecological zones (AEZs): Khorezm (arid saline lowland), Kashkadarya (semi-arid highland), Samarkand (semi-arid mid-altitude), and Jizzakh (arid high-altitude). The simulations optimized seeding dates, nitrogen fertilizer rates, cultivar selection, and water management practices. Additionally, a meta-analysis of 90 studies and machine learning were employed to identify key determinants of wheat yield variation.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS AND CONCLUSIONS&lt;/h3&gt;&lt;div&gt;To achieve self-sufficiency, Uzbekistan requires an average wheat yield of 6.62 t ha&lt;sup&gt;−1&lt;/sup&gt;, necessitating a 45 % (2.07 t ha&lt;sup&gt;−1&lt;/sup&gt;) increase from current levels (4.55 t ha&lt;sup&gt;−1&lt;/sup&gt;), while the yield gap of 3.25 t ha&lt;sup&gt;−1&lt;/sup&gt; exists. The study identified nitrogen fertilization, irrigation, rainfall, cultivar selection, and seeding dates as the primary determinants of yield. Wheat yield declined significantly when plant-available water content dropped below 50 %, establishing a critical threshold for sustainable productivity. Precision nutrient management included applying 150–180 kg N ha&lt;sup&gt;−1&lt;/sup&gt;, up to 120 kg P₂O₅ ha&lt;sup&gt;−1&lt;/sup&gt;, and 75 kg K₂O ha&lt;sup&gt;−1&lt;/sup&gt;. Conservation agriculture showed a 26 % increase in yields compared to conventional tillage. High-yielding, stress-tolerant wheat varieties released after 2010 increased wheat productivity by up to 22 %. Seeding between September 15 and October 15 maximized yields, while delayed sowing reduced yield by up to 57 kg ha&lt;sup&gt;−1&lt;/sup&gt; day&lt;sup&gt;−1&lt;/sup&gt;. Seed rates of 160–180 kg ha&lt;sup&gt;−1&lt;/sup&gt; improved plant density and yields, preventing excessive competition or underutilization.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;SIGN","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"225 ","pages":"Article 104291"},"PeriodicalIF":6.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552052","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}