Assessing Soil Quality in Oasis Ecosystems Using a Minimum Dataset

Abstract

【Objective】 Ensuring and enhancing soil quality is of paramount importance for developing sustainable agriculture, and soil quality assessment has gained significant attention globally. This paper aims to propose an appropriate method for evaluating soil quality in the Mosuowan irrigation region of Xinjiang, in northwestern China. 【Method】 Fifty soil samples were taken from random locations determined with the help of GPS. For each sample, we measured organic matter, available phosphorus and potassium, alkali-hydrolyzed nitrogen, pH, EC, K+, Ca2+, Na+, Mg2+, Cl-, NO3- and SO42-. Principal component analysis and cluster analysis were used to find the minimum dataset required to evaluate soil quality, and the soil quality was calculated using the comprehensive quality index method. 【Result】 Soil organic matter content and alkali-hydrolyzable nitrogen were low in the studied region. Available phosphorus and available potassium were abundant but distributed unevenly. The salt content showed significant spatial variation. Soil quality varied substantially in the region, but was below moderate level in most areas. Results obtained from the principal component analysis were more accurate and aligned with ground-true data. 【Conclusion】 The overall soil quality in the Mosuowan irrigation region is poor, and the principal component analysis is more accurate than the cluster analysis for evaluating soil quality.

Keywords

• soil quality assessment
• minimum data set
• principal component analysis
• cluster analysis
• mosuowan irrigation