A proper understanding of soil parameters under different production systems of the world is necessary for efficient soil management. We, therefore, carried out the present study to assess the status of some selected soil properties (soil pH and electrical conductivity (EC)), phyto-available nutrients (available nitrogen (AN), available potassium (AK), exchangeable calcium (Ex. Ca), exchangeable magnesium (Ex. Mg), available sulfur (AS), and soil organic carbon (SOC) pools (SOC, total organic carbon (TOC), very labile C, labile C, less labile C, and non-labile C) and to establish relationships among the measured soil parameters at different depths of Vertisols of India under various land uses. A total of 150 composite soil samples (from 25 plots including nine from agricultural land, nine from horticultural land, three from forest land, and four from grassland) were collected from 6 soil depths viz, 0-10, 10-20, 20-40, 40-60, 60-80, and 80-100 cm under agriculture, horticulture, forest, and grassland land uses present in Central India and analyzed. The values of soil pH, EC, AN, AK, Ex. Ca, Ex. Mg, and AS in various soil depths under different land uses varied widely. The values of SOC (0.19 to 1.00%), TOC (0.58 to 2.42%), very labile C (0.14 to 0.83%), labile C (0.05 to 0.25%), less labile C (0.05 to 0.26%) and non-labile C (0.23 to 1.42%) in various soil depths under different land uses also varied significantly. Forest and grassland land uses had higher levels of SOC, TOC, very labile, and non-labile C content in all the soil depths in comparison to SOC, TOC, very labile, and non-labile C content in different soil depths under agriculture and horticulture land use. The levels of SOC, TOC, very labile, and non-labile C content under all the land uses decreased with increasing soil depths. SOC was positively and significantly correlated with AN, AK, AS, and estimated SOC pools in surface soil layers. Principal component analysis (PCA) of soil parameters in different soil depths resulted in 5 principal components (PCs) with > 1 eigenvalue and accounting for > 75% variability. This information could be used for managing SOC status and phyto-available nutrients in Vertisols under different land uses.
Read full abstract