巴基斯坦旁遮普省灌溉农业生态区的土壤质量评估:卢恩伯格指标法

IF 4.5 3区 经济学 Q1 AGRICULTURAL ECONOMICS & POLICY
Asjad Tariq Sheikh, Atakelty Hailu, Amin Mugera, Ram Pandit, Stephen Davies
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引用次数: 0

摘要

本文介绍了利用巴基斯坦旁遮普省三个灌溉农业生态区(即水稻-小麦区、玉米-小麦混合区和棉花-混合区)的作物产量、非土壤投入和土壤剖面数据构建卢恩贝格尔土壤质量指标(SQI)的方法。通过在数据包络分析(DEA)框架内估计方向距离函数,利用地块级数据构建土壤质量指标。我们发现,SQI 与作物产量的关系表现出改善土壤质量水平的收益递减。利用构建的 SQI 值,我们估算了线性回归模型以生成权重,这些权重可直接用于将单个土壤属性汇总为土壤质量指标,而无需对作物产量数据进行前沿拟合。在小麦和水稻生产中,我们发现 SQI 对土壤导电率(EC)和钾(K)的变化最为敏感。SQI 与具体地点的决策问题直接相关,决策者需要对土地资源和保护服务进行定价,以实现农业和环境目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan: The Luenberger indicator approach

Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan: The Luenberger indicator approach

This article describes the construction of the Luenberger soil quality indicator (SQI) using data on crop yield, non-soil inputs, and soil profile from three irrigated agroecological zones of Punjab, Pakistan, namely, rice–wheat, maize–wheat–mix, and cotton–mix zones. Plot level data are used to construct a soil quality indicator by estimating directional distance functions within a data envelopment analysis (DEA) framework. We find that the SQI and crop yield relationships exhibit diminishing returns to improving soil quality levels. Using the constructed SQI values, we estimate linear regression models to generate weights that could be used directly to aggregate individual soil attributes into soil quality indicators without the necessity of fitting a frontier to the crop production data. For wheat and rice production, we find that SQI is most sensitive to changes in soil electrical conductivity (EC) and potassium (K). The SQI has direct relevance for site-specific decision-making problems where policymakers need to price land resources and conservation services to achieve agricultural and environmental goals.

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来源期刊
Agricultural Economics
Agricultural Economics 管理科学-农业经济与政策
CiteScore
7.30
自引率
4.90%
发文量
62
审稿时长
3 months
期刊介绍: Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.
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