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Related Experiment Video

Updated: Jan 29, 2026

Measuring Phosphorus Release in Laboratory Microcosms for Water Quality Assessment

Measuring Phosphorus Release in Laboratory Microcosms for Water Quality Assessment

Published on: July 22, 2019

Developing global pedotransfer functions to estimate available soil phosphorus.

Yones Khaledian¹, John N Quinton², Eric C Brevik³

¹Department of Agronomy, Iowa State University, Ames, IA, USA.

The Science of the Total Environment

|February 13, 2019

Summary

This summary is machine-generated.

This study developed cost-effective models to predict global soil phosphorus (P) availability using pedotransfer functions. Accurate predictions were achieved for New Zealand and acid oxalate methods, aiding agricultural and environmental assessments.

Keywords:

Genetic algorithm Simulation Soil properties Statistical models

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Area of Science:

Soil Science
Environmental Science
Agricultural Science

Background:

Global data on available soil phosphorus (P) is limited, hindering accurate assessments.
Developing low-cost, accurate methods to predict soil P is a significant global challenge.
Soil P is crucial for agricultural productivity and environmental health.

Purpose of the Study:

To conduct a global meta-analysis to develop pedotransfer functions for predicting available soil P.
To evaluate various soil properties as predictors for available soil P across different methods and regions.
To assess the efficacy of different methods (New Zealand, acid oxalate, Bray, Mehlich 3) in estimating soil P.

Main Methods:

A global meta-analysis of available soil P data from 738 sites (USA and 14 other countries).
Evaluation of soil properties including clay, silt, sand fractions, organic carbon, pH, and elemental composition (Ca, Mg, K, Fe, Al, Mn).
Development and comparison of pedotransfer functions for four different soil P determination methods.

Main Results:

The New Zealand (NZ) method showed the best model performance using a comprehensive set of covariates.
The acid oxalate method provided good estimates for USA and non-USA datasets separately, despite poor global performance.
Bray and Mehlich 3 methods demonstrated good predictive accuracy only for the non-USA dataset.

Conclusions:

Pedotransfer functions offer an efficient and cost-effective approach for estimating global soil P distributions.
Model performance varies significantly depending on the soil P determination method and geographical scope.
Accurate soil P estimation is vital for informed agricultural and environmental management decisions worldwide.