Multiple soil quality assessment methods for evaluating effects of organic fertilization in wheat-maize rotation system

Abstract

Soil degradation is a common phenomenon in smallholder farmlands in Asia and Africa. To mitigate soil degradation and the subsequent elevation in agricultural productivity, it is crucial to improve soil quality using a low-cost and time-saving organic fertilization technique. Although the soil quality index (SQI) has been widely used to assess and monitor soil quality in degenerative farmlands, studies comparing SQI calculation methods are rare. The specific objectives of this study were to (1) compare the differences in SQIs calculated using principal component analysis, factor analysis, discriminant analysis, partial least squares discriminant analysis (PLS-DA), and hierarchical clustering; (2) analyze the effects of organic fertilization on soil quality in smallholdings; and (3) determine the correlations among organic fertilizer rate, soil quality, and crop yield. We analyzed 37 soil physical, chemical, and biological properties under three organic fertilization groups [high organic fertilizer group (HOF), low organic fertilizer group (LOF), and no organic fertilizer group (NOF)] as potential soil quality indicators by using multiple assessment methods in the wheat-maize rotation system in Quzhou County, North China Plain, China. SQIs calculated using PLS-DA and the nonlinear scoring method had the best discrimination ability. Compared with the NOF group, the HOF and LOF groups exhibited an increase in SQIs by 6.93–36.99% and 3.98–26.76%, respectively. The high rate of application of organic fertilizers improved soil quality and enhanced crop yield. Moreover, soil quality was positively correlated with crop yield. These results confirmed the feasibility of using organic fertilizers for soil quality improvement and implied PLS-DA to be an effective method for selecting the minimum dataset for soil quality assessment.