Development of a soil quality index to evaluate agricultural cropping systems in southern Brazil

Abstract

Soil quality indexes (SQIs) are tools that can help farmers and decision-makers to adopt management protocols that preserve or even improve soil characteristics. In this context, this research aimed to compare six strategies for calculating a soil quality index with different degrees of complexity, to define the simplest, most effective, and low-cost technological tool for soil quality (SQ) assessment, aiming to contribute to soil sustainability management in agricultural production in Southern Brazil. Sample collection points (CPs) were established at three locations (CP1, CP2, and CP3) under three different land-use systems: native forest (NF), a tillage system (TS), and a no-till system (NTS). Characterization of the SQ was performed based on three datasets: a total dataset (TDS) with 30 indicators, a reduced dataset using multivariate Principal Component Analysis (RDS-PCA), with seven indicators, and a dataset based on Literature and Expert Opinions (LEO-DS) with five indicators, as well as two additional systems, including simple addition (SQI-1, SQI-3, and SQI-5) and weighted addition (SQI-2, SQI-4, and SQI-6). The results indicated that all SQIs efficiently detected soil quality changes in the different systems. Dataset reduction approaches to determine SQI values between different land uses confirmed that the simplest QS integration method (SQI-6) is just as effective as the more complex methods (SQI-1, SQI- 2, SQI-3, SQI-4, and SQI-5). The results indicated that all SQIs efficiently detected soil quality changes in the different systems. Therefore, using SQI weighted with a reduced number of soil indicators (LEO-DS), such as pH, phosphorus (P), Rapid Diagnosis of Soil Structure (RDSS), Relative Soil Density (RD), and Total Organic Carbon (TOC), may be a potential protocol to support the implementation of an effective and low-cost technological tool for soil management in southern Brazil.