Soil health investment and financial performance of crop farms

IF 6.2 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Agricultural Systems Pub Date : 2026-03-01 Epub Date: 2025-12-05 DOI:10.1016/j.agsy.2025.104601
Delide Joseph , Cesar Guareschi , Jennifer Ifft , Mathew Sanderson , Megan Hughes , Charles Rice
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引用次数: 0

Abstract

Soil health investments are promoted for their environmental benefits, but evidence on their financial returns for producers remains limited and mixed. This study examines the relationship between soil health practice adoption and farm profitability, while comparing three classification methods used to measure soil health investment intensity. We combine survey-reported soil health practice data with detailed financial records from 438 Kansas commercial crop farms. Three classification strategies are evaluated: (1) an expert-informed agronomic score grounded in regenerative principles, (2) a rule-based threshold system, and (3) a data-driven k-means clustering approach. We estimate ordinary least squares regressions linking these classifications to the net farm income ratio, controlling for farm and weather variables. Additional analyses explore yield and cost mechanisms, and robustness checks include ordered logit models and continuous treatment of adoption intensity. Only the agronomic score classification shows a statistically significant and positive association with profitability (p < 0.05): farms in the high-adoption group earned a 5.6 percentage point higher net farm income ratio than those in the low-adoption group. Other methods showed no significant relationship. The classification method influenced which farms were labeled high adopters, with only 10% consistent across all methods. Soil health practice adoption is modestly associated with improved financial outcomes, but results depend heavily on how adoption is measured. Expert-informed, context-sensitive classification approaches appear more predictive of profitability than rule-based or data-driven alternatives. Directly comparing classification methods to measure soil health investment intensity demonstrates how methodological choices can influence research findings on economic and policy relevance. The study provides actionable insights for researchers, practitioners, and policymakers designing sustainability incentives or certification programs.

Abstract Image

作物农场土壤健康投资与财务绩效
土壤健康投资因其环境效益而得到促进,但有关其给生产者带来的财务回报的证据仍然有限且参差不齐。本研究探讨了土壤健康措施采用与农场盈利之间的关系,并比较了用于衡量土壤健康投资强度的三种分类方法。我们将调查报告的土壤健康实践数据与堪萨斯州438个商业作物农场的详细财务记录相结合。本文评估了三种分类策略:(1)基于再生原则的专家农艺评分,(2)基于规则的阈值系统,以及(3)数据驱动的k-means聚类方法。我们估计了将这些分类与农场净收入比联系起来的普通最小二乘回归,控制了农场和天气变量。额外的分析探讨了收益和成本机制,鲁棒性检查包括有序logit模型和采用强度的连续处理。只有农艺评分分类与盈利能力有统计学上显著的正相关(p < 0.05):高采用率组的农场净收入比低采用率组的农场净收入比高5.6个百分点。其他方法无显著相关性。分类方法影响了哪些农场被标记为高采用者,所有方法中只有10%的一致性。土壤健康实践的采用与改善的财务结果有一定的联系,但结果在很大程度上取决于如何衡量采用情况。与基于规则或数据驱动的替代方案相比,专家信息、上下文敏感的分类方法似乎更能预测盈利能力。直接比较衡量土壤健康投资强度的分类方法表明,方法选择如何影响经济和政策相关性的研究结果。该研究为研究人员、从业人员和政策制定者设计可持续发展激励或认证项目提供了可行的见解。
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来源期刊
Agricultural Systems
Agricultural Systems 农林科学-农业综合
CiteScore
13.30
自引率
7.60%
发文量
174
审稿时长
30 days
期刊介绍: Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.
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