Background: Soil quality (SQ) assessment is affected by methods that convert data sets into indices, and such analyses are expensive and time-consuming. Qualitative SQ assessments are faster and cheaper than quantitative methods and they can be repeated to monitor SQ in crop and pasture systems. We evaluated SQ using qualitative and quantitative SQ indicators of two grazing systems under Voisin rational grazing (VRG) with trees (WT) or without trees (NT). We took an adjacent native forest as a reference and we used principal component analysis (PCA) to compare the accuracy of the assessment methods.
Results: According to the set of indicators used for quantitative assessment, the WT system and the Forest had higher SQ than other systems as a result of higher values of soil physical and chemical indicators. This the reflected better performance of soil in functions related to structural support, nutrient cycling and biological productivity. According to the set of indicators used for qualitative assessment, the WT system showed better SQ than the NT areas because of the higher scores of all indicators and better performance of the soil functions, and those values were close to the Forest in the indicators. PCA applied to integrate the data of qualitative and quantitative indicators indicated that SQ in WT was similar to Forest.
Conclusion: The qualitative evaluation was as efficient as the quantitative evaluation for SQ assessment in VRG areas with and without trees. Its use can promote farmers' autonomy and the development of skills to identify environmental factors that help to evaluate their practices. © 2023 Society of Chemical Industry.
Keywords: fertility attributes; organic matter; physical attributes; qualitative analysis.
© 2023 Society of Chemical Industry.