A new method for soil health assessment based on Analytic Hierarchy Process and meta-analysis

Abstract

Understanding soil health condition is essential to the sustainability and stability of the entire ecosystem of farmland. The primary objective of this study was to improve the soil health index (SHI) based on principle component analysis (PCA) and develop a new analysis method for soil health assessment based on Meta-Analytic Hierarchy Process (Meta-AHP), which provides consistent minimum data sets (MDS), weight and scoring function for different locations, studies and management. The thirteen variables of MDS that exhibited sensitivity to management between organic and conventional soil were selected by meta-analysis. The indicator weight was assigned by a combination of experts scoring, AHP and meta-analysis. To test the applicability and sensitivity of the soil health assessment by Meta-AHP, a sixteen-year long-term test was assessed by the conventional SHI method (cSHI) and Meta-AHP. The results showed that similar evaluation results and significant positive correlations (**P < 0.01, n = 9) between the two evaluated methods were observed, and the results calculated using Meta-AHP had the best discrimination under different plant systems due to the higher F values when compared with the cSHI. This study developed a sensitive and consistent SH assessment framework that can be used applied to a variety of location, study, and soil management systems.