Abstract
ABSTRACT Various attributes are often required to build soil quality indicators. However, determining these attributes is time-consuming and requires several specific devices. Thus, it is desirable to develop indexes that express soil quality based on easily determined attributes. The objective of this study was to investigate the spatial variability of the S index and its correlation with other physical and chemical soil attributes to generate a pedotransfer function for estimating the S index. A georeferenced sampling mesh covering 1.4 ha and employing 71 points was installed. The soil samples were collected in 0.00–0.15 m and 0.15–0.30 m deep layers to determine the physical and chemical attributes. The results indicated that the S index was correlated with porosity, carbon stocks, cation exchange capacity, and particle size fractions. However, macroporosity, microporosity, and sand content were the most suitable attributes for the construction of pedotransfer functions. A principal component analysis indicated that the S index was representative of 9.4% and 11.5% of the total variability in the dataset in the respective soil layers. Spherical semivariogram models showed that the S index was spatially dependent and ranged between 84–188 m. The S index maps estimated by the pedotransfer function resemble the observed S values; therefore, the function can be applied in spatial variability studies.
Highlights
Evaluating soil management by farmers is difficult because obtaining physical attributes of soil is difficult; undisturbed soil samples must be collected and the laboratories used must be enabled in attributes determinations and have trained technicians to interpret the results
The scientific community has searched for soil quality indicators that can facilitate decision making by farmers
Higher levels of sand and silt were observed in the superficial layer, but the variation between layers were of smaller magnitude than were the granulometric variations found within the same layer
Summary
Evaluating soil management by farmers is difficult because obtaining physical attributes of soil is difficult; undisturbed soil samples must be collected and the laboratories used must be enabled in attributes determinations and have trained technicians to interpret the results. As proposed by Dexter (2004 a, b, c), the S index can be calculated from the adjustment coefficients of the soil water retention curve (SWRC). This index represents the slope of the line tangent to the inflection point of the SWRC. Several studies, such as Dexter (2004 a, b, c), Assis Júnior et al (2016), Magalhães et al (2018), Rossetti & Centurion (2018), have confirmed the accuracy of the S index using the soil compaction state, which is correlated with the microstructural porosity, bulk density, and soil organic matter content
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