Agricultural Systems最新文献_第3页

Develop a modelling framework to identify and optimize the dominant factors that limit cropland productivity 开发一个模型框架，以确定和优化限制农田生产力的主要因素

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-21 DOI: 10.1016/j.agsy.2026.104635

Xiaoyang Han , Changqing Song , Leina Zhang , Peichao Gao , Sijing Ye , Yakov Kuzyakov

Context

Analysing the influence mechanism of farming conditions (soil properties and agricultural infrastructure) on cropland productivity is a key prerequisite for increasing yields in low- to medium-quality land.

Objective

We proposed a modelling framework to identify key farming condition factors that limit cropland productivity and analyse the numerical ranges within which they exert a dominant influence. The responses of cropland productivity to changes in dominant farming conditions were simulated.

Methods

The framework consisted of processed long-term sequence earth observation data and random forest model. By filtering high-density cropland samples and increasing crop identification accuracy, gross primary production (GPP) was proven to be an appropriate indicator of cropland productivity in scenarios lacking high-precision crop yield data.

Results and conclusions

Farming conditions explained >60% of the spatial differences in the rice GPP and > 65% of those in the wheat GPP. Soil texture and pH were key factors limiting rice and wheat GPP. A decrease in sand content and a corresponding increase in clay content increased rice GPP. Soil nitrogen supply rapidly decreased when clay content approached 20%, decreasing rice GPP. Climate conditions influenced the preference of wheat for soil water retention and drainage-permeability, resulting in an increase wheat GPP in northern and decrease in southern regions with raising clay content. The annual total GPP of rice and wheat increased by up to 6.8% through adjusting clay and sand contents and increasing mean field size. In the northwestern and southeastern regions, small adjustments (−5% … +5%) to clay and sand contents led to annual GPP increases of >600 kg·C·ha⁻¹ for rice and > 800 kg·C·ha⁻¹ for paddy-wheat rotations.

Significance

The framework can provide support to optimize farming conditions in low- to medium-yield cropland renovation projects.

分析耕作条件（土壤性质和农业基础设施）对农田生产力的影响机制是提高中低质量土地产量的关键先决条件。目的：我们提出了一个模型框架，以确定限制农田生产力的关键农业条件因素，并分析它们发挥主导影响的数值范围。模拟了农田生产力对优势耕作条件变化的响应。方法采用处理后的长期序列地球观测数据和随机森林模型。通过对高密度农田样本进行过滤，提高作物识别精度，证明了在缺乏高精度作物产量数据的情况下，初级生产总值（GPP）是一个合适的农田生产力指标。结果与结论耕作条件解释了水稻GPP空间差异的60%和小麦GPP空间差异的65%。土壤质地和pH值是制约稻麦GPP的关键因素。砂含量降低，粘土含量相应增加，水稻GPP增加。当粘土含量接近20%时，土壤氮供应迅速减少，水稻GPP下降。气候条件影响了小麦对土壤保水性和透水性的偏好，导致北方小麦GPP随粘粒含量的增加而增加，南方小麦GPP随粘粒含量的增加而降低。通过调整粘土、砂粒含量和增加平均田面积，水稻和小麦的年总产值可提高6.8%。在西北和东南地区，粘土和砂含量的小幅调整（- 5% ~ +5%）导致水稻和水麦轮作的GPP年增幅分别为600 kg·C·ha - 1和800 kg·C·ha - 1。意义该框架可为中低产田改造项目优化耕作条件提供支持。

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引用次数: 0

Nitrogen dilemma in Chinese crop-livestock systems: Assessing mitigation potential and exploring optimization pathways from the perspectives of utilization efficiency and pollution hotspots 中国农牧系统氮素困境：从利用效率和污染热点角度评估缓解潜力及优化路径

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-19 DOI: 10.1016/j.agsy.2026.104642

Zhijian Wu , Han Liang , Zhong Liu , Haijiao Du , Liujie He , Zeyang Xie , Jinqi Zhu , Bofu Zheng , Wei Wan

CONTEXT

Crop-livestock systems in China have become the primary agricultural nitrogen (N) pollution source owing to fertilizer overuse and poor manure management. Yet city-scale analyses of nitrogen use efficiency (NUE) trends and loss hotspots remain insufficient. Current evaluations fail to fully account for spatial variations in farming practices, natural conditions, and sector-specific contributions to N losses.

OBJECTIVE

This study aims to quantify N flows, reveal NUE evolution, identify hotspots of N losses, and evaluate mitigation potentials and optimization paths for regionally differentiated N management.

METHODS

We improved the Nutrient Flows in Food chains, Environment, and Resources use (NUFER) model by innovatively introducing human excreta indicators and livestock localization parameters, establishing a city-scale comprehensive framework.

RESULTS AND CONCLUSIONS

The system efficiencies showed marked improvement. From 2000 to 2022, NUE showed a relative increase of 39.91% (crop systems), 46.30% (livestock systems), and 43.47% (crop-livestock systems) compared to the 2000 levels, with pronounced spatial variation. High-performing crop systems (NUE > 50%) clustered in the Northeast China Plain and Huang-Huai-Hai Plain (HHHP), while inefficient livestock operations (NUE < 15%) predominated in western China and the Yunnan-Guizhou Plateau (YGP). Notably, fruits and vegetables (cash crops) showed significantly lower NUE than grain crops. Maize, vegetables, rice, fruits, and wheat contributed 82.29% of crop N losses, while beef cattle, pigs, and poultry accounted for 83.52% of livestock losses. Notably, fruits and dairy cattle showed the highest N loss intensities at 110.07 kg·ha⁻¹ and 31.72 kg·lu⁻¹, respectively. While NH₃ dominated most regions, runoff and erosion prevailed in the Sichuan Basin and Surrounding Regions (SBSR) and YGP. We identified concentrated hotspot regions – representing just 6.17% of Chinese land area but contributing 30.42% of national N losses - primarily located in: (i) the central and southern HHHP, (ii) the northern Middle-Lower Yangtze River Regions, and (iii) Central SBSR, Loess Plateau, and YGP. Scenario analysis demonstrated substantial mitigation potential. Integrated measures (precision fertilization, resource recycling, livestock structure optimization, and advanced manure management) could reduce synthetic N inputs by 22.64% while decreasing N losses by 5.03 Tg (31.38%).

SIGNIFICANCE

This study provides a scientific basis for spatially differentiated N management strategies in both Chinese and other countries' worldwide agricultural systems.

背景由于肥料过度使用和粪便管理不善，中国的作物-牲畜系统已成为农业氮污染的主要来源。然而，对氮素利用效率（NUE）趋势和损失热点的城市尺度分析仍然不足。目前的评估未能充分考虑耕作方式、自然条件和部门对氮损失的具体贡献的空间差异。目的量化氮素流量，揭示氮素利用效率演变，识别氮素损失热点，评价区域差别化氮素管理的缓解潜力和优化路径。方法通过创新引入人类排泄物指标和家畜定位参数，对食物链、环境和资源利用（NUFER）养分流模型进行改进，建立城市尺度的综合框架。结果与结论系统效率明显提高。2000 - 2022年，作物系统、畜牧系统和农牧系统的氮素利用效率分别比2000年增加了39.91%、46.30%和43.47%，且空间差异显著。高产作物系统（NUE < 50%）集中在东北平原和黄淮海平原（HHHP），而低效畜牧业（NUE < 15%）在中国西部和云贵高原（YGP）占主导地位。值得注意的是，水果和蔬菜（经济作物）的氮肥利用效率明显低于粮食作物。玉米、蔬菜、水稻、水果和小麦占作物氮损失的82.29%，肉牛、猪和家禽占牲畜氮损失的83.52%。其中，水果和奶牛的氮损失强度最高，分别为110.07 kg·ha - 1和31.72 kg·lu - 1。大部分地区NH3为主，四川盆地及周边地区（SBSR）和YGP以径流和侵蚀为主。我们确定了集中的热点地区——仅占中国陆地面积的6.17%，但贡献了全国氮损失的30.42%——主要位于：(i) HHHP中部和南部，（ii）长江中下游北部地区，（iii） SBSR中部、黄土高原和YGP。情景分析显示了巨大的缓解潜力。综合措施（精准施肥、资源循环利用、优化畜禽结构和先进粪肥管理）可使合成氮投入减少22.64%，氮损失减少5.03 Tg（31.38%）。意义本研究为中国及世界各国农业系统氮素空间分异管理策略提供了科学依据。

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引用次数: 0

Is the potential stability of forage resources under climate variability linked to transhumance patterns? An approach for sheep farming systems based on vegetation agroecological properties 草料资源在气候变率下的潜在稳定性是否与越牧模式有关？基于植被农业生态特性的绵羊养殖系统方法

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-16 DOI: 10.1016/j.agsy.2026.104641

Anne-Lyse Murro, Renaud Jaunatre, Emilie Crouzat, Grégory Loucougaray

Context

Climate change, and in particular increased climate variability, is challenging the functioning of agro-pastoral livestock farms by impacting the availability of forage resources. Transhumant agropastoral systems, based on year-round herd mobility, mobilize a diversity of forage resources across time and space, which can potentially be a key factor in the stability of these forage resources in the face of climatic variability.

Objective

This paper presents an original multiscale functional approach to evaluate the role of vegetation for forage resource stability in relation to herd mobility patterns (altitudinal and latitudinal gradients) in transhumant sheep systems (TSS) in the French Alps.

Methods

We developed a set of indices that can provide information on forage stability at the farm level. These indices are based on (i) agro-ecological properties (based on the taxonomic and functional composition of vegetation) at the plot level combined at the farm level by the relative area of the plots and the distribution of the values of these indices, and (ii) the diversity of vegetation types within the farm. This approach was implemented on 12 sheep transhumant farms, representing a diversity of mobility gradients. We then measured the relationship between four categories of forage stability indices and herd mobility patterns.

Results and conclusions

At farm level, we found positive correlations between the diversity of vegetation types and the range of altitudinal mobility, as well as between indices of distribution of vegetation functional characteristics (e.g., mean leaf dry matter content of plots) and the range of latitudinal mobility.

Our results support the idea that differences in mobility gradients, whether along latitudinal or altitudinal gradients, provide access to different forms of complementarity that contribute to forage resource stability. However, our results also reveal trade-offs at the farm level between different dimensions of forage stability - particularly between productivity-related and those capturing plot's functional complementarity stability indices. Thus, forage resource stability in the face of climatic variability appears to be multidimensional, depending on the combination of different properties carried by the vegetation - no single indicator of forage potential stability prevails across all systems. Our framework highlights various pathways to forage resilience in a context of increasing climate variability.

Significance

This multiscale methodology, combining functional indices and scaling-up processes, offers a transferable framework to assess resource stability. It can be applied beyond transhumant livestock systems and mobilized in research projects addressing the resilience of diverse socio-ecological systems under climate variability.

气候变化，特别是气候变率的增加，通过影响饲料资源的可得性，正在挑战农牧养殖场的功能。基于牧群全年流动的迁移农牧系统调动了不同时间和空间的牧草资源多样性，这可能是这些牧草资源在面对气候变化时保持稳定性的关键因素。目的提出了一种新颖的多尺度功能方法，以评价法国阿尔卑斯牧群迁移模式（海拔和纬度梯度）对牧草资源稳定性的影响。方法建立了一套能反映牧场牧草稳定性的指标体系。这些指数基于(i)样地水平的农业生态特性（基于植被的分类和功能组成），结合样地水平的相对面积和这些指数值的分布，以及（ii）农场内植被类型的多样性。该方法在12个羊迁移农场实施，代表了不同的流动性梯度。然后，我们测量了四类牧草稳定性指数与牧群流动模式的关系。结果与结论在农田水平上，植被类型多样性与海拔移动度呈显著正相关，植被功能特征分布指数（样地平均叶干物质含量）与海拔移动度呈显著正相关。我们的研究结果支持这样一种观点，即流动性梯度的差异，无论是沿着纬度还是海拔梯度，都提供了不同形式的互补，有助于草料资源的稳定性。然而，我们的结果也揭示了在农场层面上不同维度的饲料稳定性之间的权衡-特别是在生产力相关和那些捕获地块功能互补稳定性指数之间。因此，面对气候变化，牧草资源的稳定性似乎是多维的，取决于植被所携带的不同特性的组合——没有单一的牧草潜在稳定性指标适用于所有系统。我们的框架强调了在气候变化日益增加的背景下，牧草恢复力的各种途径。这种多尺度方法，结合了功能指数和规模过程，提供了一个可转移的框架来评估资源稳定性。它可以应用于迁移牲畜系统之外，并在研究气候变化下不同社会生态系统的复原力的研究项目中加以动员。

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引用次数: 0

Quantifying crop-livestock integration for the green transition of herbivorous livestock farmers: Development of a novel index and its application in Northwest China 草食性养殖户绿色转型的量化农牧结合：新指标的构建及其在西北地区的应用

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-15 DOI: 10.1016/j.agsy.2026.104640

Dan Liu , Jianjun Jin , Zanlu Zou , Jie Yang , Chenyang Zhang

CONTEXT

The decoupling of crop and livestock production has intensified resource inefficiencies and environmental pressures in smallholder farming systems. Opposing this trend, crop–livestock cooperation at farm, community, and regional levels is increasingly promoted as a pathway toward sustainable agriculture. However, despite its expansion, the strength of such integration remains difficult to measure due to the absence of reliable and scalable indicators.

OBJECTIVE

This study aims to develop a spatially weighted Crop–Livestock Integration Index (CLII) and evaluate its green transition implications in herbivorous livestock systems in northwest China.

METHODS

CLII was put in relation with a composite green transition index resulting from the aggregation of normalized greenhouse gas (GHG) emission and feed cost efficiency. Life cycle assessment (LCA) was employed to calculate GHG emissions from six key production stages. Feed cost efficiency and the composite green transition performance index were also evaluated.

RESULTS AND CONCLUSIONS

The results for beef cattle households in Yuanzhou, Ningxia showed that CLII values ranged from 0 to 1, reflecting high variability across households. The average CLII was only 0.36, indicating a generally low level of integration, particularly in Yanglang Village where the mean value was 0.09. Higher CLII was associated with lower purchased feed costs and reduced GHG emissions from enteric fermentation, manure management, composting and transport. A regression analysis confirmed that CLII significantly improved green transition performance at the household level.

SIGNIFICANCE

The CLII method offers a spatially sensitive, data-efficient tool for measuring integration intensity and sustainability outcomes. It enables evidence-based policy design for promoting regionally adapted, low-carbon livestock development pathways.

作物和畜牧业生产的脱钩加剧了小农农业系统的资源效率低下和环境压力。与这一趋势相反，农场、社区和区域各级的作物-牲畜合作日益被作为实现可持续农业的途径而得到推广。然而，尽管扩大了，但由于缺乏可靠和可扩展的指标，这种整合的强度仍然难以衡量。目的建立作物-牲畜空间加权综合指数（CLII），并评价其对西北地区草食性牲畜生态系统绿色转型的影响。方法将sclii与标准化温室气体（GHG）排放和饲料成本效率综合得出的绿色转型综合指数相关联。采用生命周期评价法（LCA）计算了6个关键生产阶段的温室气体排放量。并对饲料成本效率和绿色过渡综合性能指标进行了评价。结果与结论宁夏元州肉牛农户CLII值范围为0 ~ 1，农户间差异较大。CLII均值仅为0.36，一体化程度普遍较低，其中阳郎村的均值为0.09。较高的CLII与较低的购买饲料成本以及肠道发酵、粪肥管理、堆肥和运输产生的温室气体排放减少有关。回归分析证实，CLII显著提高了家庭层面的绿色转型绩效。意义CLII方法为测量一体化强度和可持续性结果提供了一种空间敏感、数据高效的工具。它使基于证据的政策设计能够促进适应区域的低碳畜牧业发展路径。

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引用次数: 0

Analyzing the disruption of agricultural systems by conflict: A case study of sunflower production in eastern Ukraine 冲突对农业系统的破坏分析：以乌克兰东部向日葵生产为例

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-13 DOI: 10.1016/j.agsy.2026.104636

Junjie Qiu , Yuekai Hu , Dailiang Peng , Haijian Liu , Weichun Tao , Bin Xie , Tangao Hu , Jiake Wang , Xiao Liang , Tao Chen , Junfeng Xu

Sunflower is a critical oilseed crop that underpins global food security. As the world's largest exporter of sunflower oil, Ukraine produced 6.89 million tons in 2021, accounting for approximately one-third of global production. However, the ongoing Russia–Ukraine conflict has severely disrupted the local agricultural system, and the specific impacts on sunflower production dynamics remain unclear. To address this, we constructed a comprehensive monitoring framework by integrating Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical imagery. First, we mapped annual sunflower cultivation distributions from 2019 to 2023 using an automated sample extraction method coupled with a Random Forest model, achieving an overall classification accuracy of 94.35%. Second, we implemented grid-based production prediction to capture fine-scale agricultural productivity heterogeneity. The results reveal a 49.5% decline in sunflower cultivation area between 2021 and 2022, accompanied by severe landscape fragmentation. Notably, the loss pattern exhibited a distinct “strip-like” distribution along the conflict frontline. Regarding production, while total output collapsed, the trend in unit yields diverged from the drastic reduction in cultivated areas, suggesting a potential shift in the agricultural production mode toward concentration. Finally, analysis based on multi-source indicators confirmed that farmland destruction, personnel loss, and water source damage were the drivers of agricultural decline in the region. These findings highlight the high vulnerability of agricultural systems under armed conflict and provide critical insights for post-conflict agricultural recovery and sustainable land use policymaking.

向日葵是一种重要的油籽作物，支撑着全球粮食安全。作为世界上最大的葵花籽油出口国，乌克兰在2021年生产了689万吨葵花籽油，约占全球产量的三分之一。然而，持续的俄罗斯-乌克兰冲突严重破坏了当地的农业系统，对向日葵生产动态的具体影响尚不清楚。为了解决这一问题，我们将Sentinel-1合成孔径雷达（SAR）和Sentinel-2光学图像整合在一起，构建了一个全面的监测框架。首先，我们使用自动样本提取方法结合随机森林模型绘制了2019 - 2023年向日葵的年度种植分布，总体分类精度为94.35%。其次，我们实现了基于网格的生产预测，以捕捉精细尺度的农业生产率异质性。结果显示，2021 - 2022年间，向日葵种植面积减少49.5%，景观破碎化严重。值得注意的是，损失模式沿冲突前线呈现明显的“条形”分布。在生产方面，虽然总产量大幅下降，但单位产量的趋势与耕地面积的急剧减少背道而驰，这表明农业生产方式可能向集中化转变。最后，基于多源指标的分析证实，农田破坏、人员损失和水源破坏是该地区农业衰退的驱动因素。这些发现凸显了武装冲突下农业系统的高度脆弱性，并为冲突后农业恢复和可持续土地利用政策制定提供了重要见解。

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引用次数: 0

Participatory modelling for agroecological transitions: Engaging stakeholders in transformative pathways 农业生态转型的参与式建模：让利益相关者参与变革途径

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-13 DOI: 10.1016/j.agsy.2026.104634

A. Bourceret , A. Barbe , C. Robert

CONTEXT

The worldwide use of synthetic pesticides has been rising for decades. Agroecology offers a promising alternative, but its adoption requires support from public policy and multi-scale institutional and social levers. Recent policy approaches integrate levers promoting collective and territorial collaboration, recognizing the local scale as crucial for agroecological transitions. These levers involve mobilizing territorial stakeholders and implementing context-specific levers.

OBJECTIVE

Our objective is to better understand territorial levers that support agroecological transformation and associated practice change dynamics. We engaged with stakeholders using a generic territorial socio-ecological model to identify local levers and potential agroecological transition pathways.

METHODS

In the Barrois region (Eastern France), a participatory modelling initiative involved stakeholders from a farming territory aiming to reduce pesticide use. Three participatory workshops were organized to: (1) identify context-relevant levers; (2) calibrate the model based on the territory's current state; and (3) explore agricultural trajectories and supporting levers.

RESULTS AND CONCLUSIONS

The use of the model highlights the dynamic and multi-factor nature of transitions. The workshops fostered rich dialogue and proposals, playing a central role in co-construction. Participants collectively identified levers such as awareness-raising, training initiatives, new stakeholder networks, and evolving advisory services. However, these levers vary depending on farmers' sensitivities and production types. Discussions emphasized the importance of involving not only farmers but also consumers and supply chains to drive change.

SIGNIFICANCE

This participatory approach produced a more realistic model and created learning opportunities for all participants (researchers and agricultural stakeholders), despite challenges like communicating complex theoretical concepts and vocabulary.

几十年来，世界范围内合成农药的使用量一直在上升。生态农业提供了一个很有希望的替代方案，但它的采用需要公共政策以及多尺度机构和社会杠杆的支持。最近的政策方法综合了促进集体和地区合作的手段，认识到地方规模对农业生态转型至关重要。这些杠杆包括动员地区利益相关者和实施针对具体情况的杠杆。我们的目标是更好地了解支持农业生态转型和相关实践变化动态的地域杠杆。我们使用一个通用的地域社会生态模型与利益相关者接触，以确定当地的杠杆和潜在的农业生态转型途径。方法在巴罗斯地区（法国东部），一项参与式建模倡议涉及来自农业地区的利益相关者，旨在减少农药使用。组织了三个参与性讲习班，以：(1)确定与环境相关的杠杆；(2)根据领土的现状对模型进行校准；(3)探索农业发展轨迹和支撑杠杆。结果与结论该模型的使用突出了过渡的动态性和多因素性。讲习班促进了丰富的对话和建议，在共建中发挥了核心作用。与会者共同确定了诸如提高认识、培训计划、新的利益相关者网络和不断发展的咨询服务等杠杆。然而，这些杠杆因农民的敏感性和生产类型而异。讨论强调了让农民、消费者和供应链参与推动变革的重要性。这种参与式方法产生了一个更现实的模型，并为所有参与者（研究人员和农业利益相关者）创造了学习机会，尽管存在沟通复杂理论概念和词汇等挑战。

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引用次数: 0

Quantifying the opportunity costs of nature-inclusive agriculture in the Netherlands 量化荷兰自然包容性农业的机会成本

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-10 DOI: 10.1016/j.agsy.2026.104633

Jaap Sok , Tom Kisters , Argyris Kanellopoulos

CONTEXT

Although nature-inclusive agriculture (NIA) has gained attention in Dutch policy, its adoption in dairy systems remains limited due to economic trade-offs. This challenge arises against a backdrop of farm intensification and increasingly stringent environmental regulations that restrict further expansion.

OBJECTIVE

This paper quantifies the economic trade-offs of adopting NIA practices by estimating their opportunity costs. Assessing the variability in opportunity costs among farms is also policy-relevant, as it highlights which farms face higher economic barriers and informs where targeted support or compensation may be necessary.

METHODS

We employed an empirical bio-economic model with 407 predefined farm plans from the 2018 Dutch Farm Accountancy Data Network (FADN). For each farm, we determined the income-maximizing farm plan and then used the shadow price from a re-optimized farm plan as a proxy for the opportunity cost of each NIA practice. To assess how structural and policy-related factors shape these costs, we examined four scenarios representing different levels of managerial flexibility.

RESULTS AND CONCLUSION

Opportunity costs of NIA adoption vary substantially across farms and practices. More extensive strategies can achieve higher levels of adoption but often come with higher costs. Sunk costs and capital lock-in significantly limit farmers' flexibility to adapt their systems. Long-term adoption of NIA practices requires not only financial compensation but also attention to structural, institutional, and behavioural factors.

SIGNIFICANCE

This study provides a basis for designing more efficient, differentiated, and farm-specific compensation schemes. It also highlights the need for broader public support to fairly reward farmers for providing both agricultural goods and ecosystem services. The findings offers new insights to inform policy design for balancing agricultural productivity and environmental sustainability in European farming systems.

尽管自然包容性农业（NIA）在荷兰政策中得到了关注，但由于经济权衡，其在乳制品系统中的采用仍然有限。这一挑战是在农业集约化和日益严格的环境法规限制进一步扩张的背景下出现的。

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引用次数: 0

Exploring entry points to circularity in food production from a farming system perspective 从农业系统的角度探索粮食生产循环的切入点

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-09 DOI: 10.1016/j.agsy.2025.104625

Jana Firse , Veera Naukkarinen , Marjaana Toivonen , Carl Timler , Jeroen Groot , Rogier Schulte , Kari Koppelmäki

Background

Redesigning food systems for circularity has been proposed as a strategy to reduce environmental impacts, reliance on external inputs, and to support a shift towards healthy diets. Finland's specialised and input-reliant food production systems combined with efforts to curb agricultural emissions and transition to more plant-based diets motivate exploration of future food system scenarios.

Aims

We explored two entry points to circular food production, localised food systems and the production of plant-based foods, and analysed their potential to enhance the environmental performance of Finnish farms. We further aimed to complement larger scale studies on circularity with a farm level perspective that accounts for heterogeneity and the farmers' perspective.

Methods

We generated alternative farm configurations for eight specialised arable farms in Finland. This explorative modelling study was based on three scenarios: (i) farm development based on the farmers' preferences, (ii) a localised farming system increasing nutrient and biomass cycling, (iii) maximising the production of plant-based foods.

Results

Localised and plant-based scenarios resulted in distinctly different production systems. While scenario (ii) reduced food production but lowered environmental impacts and input reliance, scenario (iii) led to highest reductions of greenhouse gas emissions and increases in overall food production. Farmer-led redesigns (i) showed large variability in perceived options for change reflecting farm-specific lock-ins and opportunities.

Conclusions

Our results underline the role of supporting objectives, such as self-sufficiency or dietary change in designing circular food systems. The heterogeneity across farms calls for a context-specific approach in supporting farmers to deliver on environmental goals.

已提出重新设计粮食系统以实现循环，作为减少对环境影响、对外部投入的依赖和支持向健康饮食转变的一种战略。芬兰的专业化和依赖投入的粮食生产系统，加上遏制农业排放和向更多植物性饮食过渡的努力，激发了对未来粮食系统情景的探索。我们探索了循环食品生产的两个切入点，本地化食品系统和植物性食品生产，并分析了它们提高芬兰农场环境绩效的潜力。我们进一步的目标是用农场层面的视角来补充更大规模的循环研究，这一视角考虑了异质性和农民的视角。方法对芬兰的8个专业耕地农场进行了不同的农场配置。这项探索性建模研究基于三种情景：(i)基于农民偏好的农场发展，（ii）增加养分和生物质循环的本地化农业系统，（iii）最大限度地提高植物性食品的生产。结果本地化和基于植物的情景导致了明显不同的生产系统。虽然情景（二）减少了粮食生产，但降低了环境影响和对投入的依赖，但情景（三）导致温室气体排放量减少最多，粮食总产量增加最多。农民主导的重新设计(i)显示，在可感知的变化选择方面存在很大差异，反映了特定农场的锁定和机会。结论研究结果强调了自给自足或饮食改变等支持目标在设计循环食品系统中的作用。农场之间的异质性要求在支持农民实现环境目标方面采取具体的方法。

{"title":"Exploring entry points to circularity in food production from a farming system perspective","authors":"Jana Firse , Veera Naukkarinen , Marjaana Toivonen , Carl Timler , Jeroen Groot , Rogier Schulte , Kari Koppelmäki","doi":"10.1016/j.agsy.2025.104625","DOIUrl":"10.1016/j.agsy.2025.104625","url":null,"abstract":"<div><h3>Background</h3><div>Redesigning food systems for circularity has been proposed as a strategy to reduce environmental impacts, reliance on external inputs, and to support a shift towards healthy diets. Finland's specialised and input-reliant food production systems combined with efforts to curb agricultural emissions and transition to more plant-based diets motivate exploration of future food system scenarios.</div></div><div><h3>Aims</h3><div>We explored two entry points to circular food production, localised food systems and the production of plant-based foods, and analysed their potential to enhance the environmental performance of Finnish farms. We further aimed to complement larger scale studies on circularity with a farm level perspective that accounts for heterogeneity and the farmers' perspective.</div></div><div><h3>Methods</h3><div>We generated alternative farm configurations for eight specialised arable farms in Finland. This explorative modelling study was based on three scenarios: (i) farm development based on the farmers' preferences, (ii) a localised farming system increasing nutrient and biomass cycling, (iii) maximising the production of plant-based foods.</div></div><div><h3>Results</h3><div>Localised and plant-based scenarios resulted in distinctly different production systems. While scenario (ii) reduced food production but lowered environmental impacts and input reliance, scenario (iii) led to highest reductions of greenhouse gas emissions and increases in overall food production. Farmer-led redesigns (i) showed large variability in perceived options for change reflecting farm-specific lock-ins and opportunities.</div></div><div><h3>Conclusions</h3><div>Our results underline the role of supporting objectives, such as self-sufficiency or dietary change in designing circular food systems. The heterogeneity across farms calls for a context-specific approach in supporting farmers to deliver on environmental goals.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"233 ","pages":"Article 104625"},"PeriodicalIF":6.1,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920753","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}

引用次数: 0

Export-attributed carbon footprint of cotton production in arid China: A life cycle and driver analysis 中国干旱地区棉花生产的出口碳足迹：生命周期和驱动因素分析

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2026-01-02 DOI: 10.1016/j.agsy.2025.104632

Jian Liu , Yu Zhang , Cun Chang , Shuai Wu , Wei Yan , Yonglong Han , Yonghui Wang , Xiaofei Ma

<div><h3>Context</h3><div>Cotton is a globally traded commodity with disproportionately large environmental costs. Although its land share is modest, input use and energy demand are high in arid irrigated systems. The Tarim River Basin (TRB) in Xinjiang, China—one of the country's principal cotton-producing regions—remains underrepresented in long-term, spatially explicit carbon accounting, particularly with respect to responsibilities embedded in international trade. An assessment that connects farm-level processes, export attribution, and driver diagnosis is needed to guide equitable and efficient decarbonization.</div></div><div><h3>Objective</h3><div>Quantify the carbon footprint of cotton production in the TRB on 1 km grids for 2000–2020; develop and apply a transparent export-attribution framework that assigns to the region an equitable share of emissions embedded in cotton trade from China; and isolate principal biophysical and socioeconomic drivers using ridge regression and structural equation modeling (SEM) to identify policy-sensitive levers for mitigation.</div></div><div><h3>Methods</h3><div>We conducted a cradle-to-farm-gate life-cycle assessment (LCA) at a 1 km spatial resolution from 2000 to 2020. We compiled activity data and emission factors to derive product-, area-, and value-based indicators, including <span><math><mi>CF</mi><mo>_</mo><mi>Y</mi></math></span> (kg CO₂-eq·kg<sup>−1</sup>), <span><math><mi>CF</mi><mo>_</mo><mi>A</mi></math></span> (kg CO₂-eq·hm<sup>−2</sup>), and carbon economic efficiency (<span><math><mi>CEE</mi></math></span>; kg CO₂-eq·CNY<sup>−1</sup>; CNY denotes the Chinese yuan). A national-proportional export-attribution scheme was applied to allocate export-embedded carbon emissions to the TRB. Based on this allocation, trade-intensity metrics were calculated, including <span><math><mi>CF</mi><mo>_</mo><msub><mi>Y</mi><mi>export</mi></msub></math></span> and <span><math><msub><mi>CEE</mi><mi>export</mi></msub></math></span>. Drivers were quantified through ridge regression and a confirmatory SEM spanning land use, vegetation condition, topography, climate, and socioeconomic context; direct and indirect effects were decomposed. Uncertainty was examined via sensitivity tests on key activity data and emission factors.</div></div><div><h3>Results and Conclusions</h3><div>Total emissions more than doubled from 2000 to 2020. In contrast, the intensity indicators changed differently: <span><math><mi>CF</mi><mo>_</mo><mi>Y</mi></math></span> remained near 2.83 kg CO₂-eq·kg<sup>−1</sup>, <span><math><mi>CEE</mi></math></span> decreased from 0.25 to 0.14 kg CO₂-eq·CNY<sup>−1</sup>, and <span><math><mi>CF</mi><mo>_</mo><mi>A</mi></math></span> increased from about 3900 to 5200 kg CO₂-eq·hm<sup>−2</sup>, indicating increasing land-based emission intensity. Dominant sources were labor (34.4 %), electricity (23.8 %), and diesel (14.8 %), highlighting priorities to modernize labor structure and decarbonize irrigation

棉花是一种全球交易的商品，其环境成本高得不成比例。尽管其土地份额不大，但干旱灌溉系统的投入物使用和能源需求很高。中国新疆的塔里木河流域（TRB）是中国主要的棉花产区之一，但在长期的、空间明确的碳核算中，特别是在国际贸易中所包含的责任方面，其代表性仍然不足。需要进行一项将农场层面的过程、出口归因和驱动因素诊断联系起来的评估，以指导公平和有效的脱碳。目的量化2000-2020年内蒙古自治区棉花生产的碳足迹。制定并应用透明的出口归因框架，在中国棉花贸易中公平分配该地区的排放份额；并利用脊回归和结构方程模型（SEM）分离主要的生物物理和社会经济驱动因素，以确定政策敏感的缓解杠杆。方法2000 - 2020年在1 km空间分辨率下进行了从摇篮到农场的生命周期评价。我们收集了活动数据和排放因子，得出了基于产品、面积和价值的指标，包括CF_Y （kg CO₂-eq·kg - 1）、CF_A （kg CO₂-eq·hm - 2）和碳经济效率（CEE; kg CO₂-eq·CNY - 1； CNY表示人民币）。采用国家比例出口归因方案将出口隐含碳排放分配给TRB。基于这一分配，计算了贸易强度指标，包括CF_Yexport和CEEexport。通过山脊回归和验证性SEM对驱动因素进行量化，包括土地利用、植被条件、地形、气候和社会经济背景；对直接效应和间接效应进行了分解。通过对关键活动数据和排放因子的敏感性测试来检查不确定性。结果与结论从2000年到2020年，总排放量增加了一倍多。相比之下，强度指标发生了不同的变化：CF_Y保持在2.83 kg CO₂-eq·kg - 1附近，CEE从0.25 kg CO₂-eq·CNY - 1下降到0.14 kg CO₂-eq·CNY - 1， CF_A从约3900 kg CO₂-eq·hm - 2增加到5200 kg CO₂-eq·hm - 2，表明陆基排放强度增加。主要能源来源为劳动力（34.4%）、电力（23.8%）和柴油（14.8%），突出了劳动力结构现代化和灌溉能源脱碳的重点。针对亚洲目的地的出口归因排放量累计达到2.70 × 109千克二氧化碳当量，各市场单位出口强度存在很强的异质性。驱动因素分析表明，优化的土地利用和社会经济升级与较低的足迹相关，而在缺乏先进管理的情况下，植被活动和气候变率的增加可能会增加排放。通过整合网格化的LCA、可复制的出口归因协议和驱动因素建模，该框架确定了可操作的热点，分配了供应链上的责任，并确定了清洁灌溉能源、定向机械化和优化土地分配等杠杆，以实现干旱、出口导向型农业的快速、公平减排。

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引用次数: 0

Greenhouse gas emission characteristics of farmland in the Guanzhong region under varied water-nitrogen management measures based on the DNDC model 基于DNDC模型的关中地区不同水氮管理措施下农田温室气体排放特征

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems

Pub Date : 2025-12-29 DOI: 10.1016/j.agsy.2025.104628

Siya Wang , Jiaxin Lu , Shikun Sun , Ruoqing Hu , Jiabei Li , Jie Pang , Yuxin Yang

Context

Irrigation and nitrogen application are essential agronomic practices for enhancing crop yields, yet they also represent potential levers for mitigating agricultural greenhouse gas (GHG) emissions in cropping systems.

Objective

This study aimed to identify optimal water‑nitrogen management strategies that maximize grain yield while minimizing GHG emissions in winter wheat-summer maize rotations within the Guanzhong Plain.

Methods

The Denitrification-Decomposition (DNDC) model was rigorously calibrated and validated using empirical field datasets. Individual and synergistic effects of irrigation levels (spanning 0–120 % field capacity, FC) and nitrogen application rates (0–300 kg N ha⁻¹) on GHG emissions were evaluated through systematic simulations of 88 distinct water‑nitrogen management scenarios.

Results and Conclusions

Maximum yields were achieved at 85 % FC irrigation coupled with 225 kg N ha⁻¹ for winter wheat (8431 kg ha⁻¹) and 85 % FC irrigation with 250 kg N ha⁻¹ for summer maize (9806 kg ha⁻¹), beyond which yields plateaued. Cumulative N₂O emissions ranged from 0.07 to 0.75 kg N ha⁻¹ (wheat) and 0.10–1.37 kg N ha⁻¹ (maize). CO₂ emissions initially increased with inputs before stabilizing at 3050 kg C ha⁻¹ (wheat) and 2464 kg C ha⁻¹ (maize) under optimal regimes. Precision management (85 % FC + crop-specific N) synchronizes yield optimization with GHG mitigation, achieving 18–22 % emission reduction relative to conventional practices while maintaining 95–97 % of maximum yield potential.

Significance

This work establishes a scientifically validated framework for climate-smart cereal production in semi-arid regions. The identified water‑nitrogen regimes (85 % FC + 225 kg N ha⁻¹ wheat; 85 % FC + 250 kg N ha⁻¹ maize) enable sustainable intensification by concurrently addressing food security and decarbonization goals in global cropping systems.

灌溉和施氮是提高作物产量的基本农艺措施，但它们也代表了减少种植系统中农业温室气体（GHG）排放的潜在杠杆。目的研究关中平原冬小麦-夏玉米轮作的最佳水氮管理策略，以实现粮食产量最大化和温室气体排放最小化。方法对反硝化分解（DNDC）模型进行了严格的标定，并利用现场经验数据进行了验证。通过系统模拟88种不同的水氮管理情景，评估了灌溉水平（0 - 120%田间容量）和氮肥施用量（0-300 kg N ha - 1）对温室气体排放的个体效应和协同效应。结果与结论85% FC灌溉配以225 kg N ha - 1的冬小麦产量最高（8431 kg ha - 1）， 85% FC灌溉配以250 kg N ha - 1的夏玉米产量最高（9806 kg ha - 1），超过这一水平产量持平。N2O累积排放量为0.07 ~ 0.75 kg N ha - 1（小麦）和0.10 ~ 1.37 kg N ha - 1（玉米）。二氧化碳排放量最初随着投入的增加而增加，然后在最佳制度下稳定在3050千克碳公顷−1（小麦）和2464千克碳公顷−1（玉米）。精确管理（85% FC +作物特定氮）使产量优化与温室气体减排同步，相对于传统做法实现减排18 - 22%，同时保持最高产量潜力的95 - 97%。本研究为半干旱地区气候智能型谷物生产建立了一个经过科学验证的框架。确定的水氮制度（85% FC + 225公斤氮肥- 1小麦；85% FC + 250公斤氮肥- 1玉米）通过同时解决全球种植系统的粮食安全和脱碳目标，实现了可持续集约化。

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引用次数: 0