Robust Soil Quality Index for Tropical Soils Influenced by Agricultural Activities

Abstract

The knowledge of the soil quality plays a vital role in the agricultural sector. Despite its importance, there is scarce scientific information concerning this regard. The objective of this research is to develop a methodology to identify and select the most appropriate indicators of Soil Quality Index (SQI) in a region with high agricultural activity. For its conformation, a descriptive statistical analysis and a Pearson correlation matrix were performed and the indicators that showed greater variation were identified using a Principal Components Analysis (PCA). A sensitivity analysis was carried out and the most sensible soil indicators of SQI were identified. This statistical procedure was also used to specify the weights of the indicators in SQI. The variables resulting from the multiparametric statistical analysis were pH, organic matter, sodium, calcium, iron, zinc, cation exchange capacity and electrical conductivity. The robustness of the SQI obtained in this study was demonstrated through simulations carried out by the numerical optimization through simplex method. The Soil Quality Index range obtained (0.54 -0.75) locates Culiacan Valley soils as moderate/high quality.

Development of a Soil Quality Index for Soils under Different Agricultural Management Conditions in the Central Lowlands of Mexico: Physicochemical, Biological and Ecophysiological Indicators

“…Once the principal components (PCs) were obtained, the eigenvalue selection criterion was used, which represents the variance of each one of the PCs, selecting those with an eigenvalue > 1 [56,57]. Once the PCs with an eigenvalue greater than 1 were established, the indicators that had a significant linear correlation with their principal component (PC) were selected r 2 ≥ 0.6 [17,18], with a commonality with the PC ≥ 0.6, which represents the proportion of the variation of the respective component. Subsequently, a process of redundancy reduction was carried out among the indicators, which results are significantly related to their respective PC, and appear under the following criteria and in order of importance: the number of significant interactions with other indicators > PC belonging (PC1 > PC2 > PC3 > ... > PCn) > correlation with its PC.…”

“…Then, the subsamples were air-dried and screened with a clean mesh with an opening diameter of 2 mm. Once dried and sieved, they were stored in plastic bags at 4 °C for further physicochemical analysis [16][17][18]. The sampling consisted of dividing each plot into three sub-plots of 600 m 2 each.…”

“…To perform the biological analyses, the soil samples were taken to the laboratory in sterile plastic bags and were refrigerated at 4 • C until their respective analyses [16][17][18]. For the physicochemical analyses, subsamples of the soils were mixed and transported at room temperature to the laboratory.…”

“…Another factor that affects the structure of the soil and therefore its quality is the OM content. It has been reported that soils with OM values above 3% are considered fertile soils [8,18,26], and soils with low OM values (<2%) present physical degradation. In the present study, the indicators related to soil nutritional quality were TOC, OM, TN, N-NH 4 + , N-NO 2 − , and N-NO 3 − .…”

“…The OM presented the same trend as the TOC indicator for the analyzed soils. The OM content is possibly related to the degree of physical degradation due to agricultural management and the use of nutrients by crops (Table 1) compared to soils under natural conditions (forest or grassland soils) [8,18,26]. Soils were classified regarding N, with the N-NO 3…”