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 con...

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Veröffentlicht in:Agricultural economics 2024-05, Vol.55 (3), p.531-553
Hauptverfasser: Sheikh, Asjad Tariq, Hailu, Atakelty, Mugera, Amin, Pandit, Ram, Davies, Stephen
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creator Sheikh, Asjad Tariq
Hailu, Atakelty
Mugera, Amin
Pandit, Ram
Davies, Stephen
description 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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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). 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subjects Agricultural production
agroecological zones
Cotton
Crop production
Crop yield
Crops
Data envelopment analysis
Decision making
directional distance function
Electrical conductivity
Electrical resistivity
Land conservation
Land resources
Quality assessment
Regression analysis
Regression models
Rice
soil attributes
Soil conductivity
Soil improvement
Soil profiles
Soil properties
Soil quality
soil quality indicator
Wheat
title Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan: The Luenberger indicator approach
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