Soil quality evaluation under different land management practices

Abstract

Sustainable agricultural production requires prudent management backed by reliable information that accurately elucidates the complex relationships between land management practices and soil quality trends. Therefore, this study investigates the influence of management on soil properties acquired at different depths, and yields, at five different field sites within Ohio, USA. The principal management systems considered were no till with or without manure and cover crops, natural vegetation (NV) or forest, and conventional tillage (CT) defined as farms with surface residue cover (<30 %). Analyses of variance (ANOVA), correlation analyses, stepwise regression, and the principal component analyses (PCA) were used to elucidate and model the link between four different management practices and the soil physical and chemical properties. The ANOVA results indicate that the available water capacity and electrical conductivity (EC) were the major variables affected by management. In contrast, soil pH, bulk density (ρ b), porosity, soil organic carbon (SOC), and total nitrogen (TN), were invariable with management, yet only pH and EC did not significantly vary with the interaction of soil type and management effects. In comparison, the PCA results suggest that SOC, TN, porosity, ρ b, and EC were the major determining factors controlling yield variability. Interestingly, the derived models revealed that the highest yields, notably 10 and 2.7 Mg ha−1 for corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) occurred in soils under CT management. Quantifying the nexus between soil properties and management choices as demonstrated in this study, can provide critical insight for sustainable agricultural production.