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Soil inorganic carbon (SIC) is important carbon reservoirs in desert ecosystems. However, little attention was paid to estimate carbon stock in these regions. In the present study, the distribution of SIC stock was investigated using digital soil mapping in Bikaner district, Rajasthan, India. A total of 187 soil profiles were used for SIC estimation by Quantile regression forest model. Landsat data, terrain attributes and bioclimatic variables were used as environmental variables. Ten-fold cross-validation was used to evaluate model. Equal-area quadratic splines were fitted to soil profile datasets to estimate SIC at six standard soil depths (0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm). The SIC in the study area ranged from 0.27 to 27.85 g kg−1 in 0–5 cm and 0.31 to 27.84 g kg−1 in 5–15 cm, respectively. The model could capture reasonable variability (R2 = 11–21%) while predicting SIC for different depths. The Lin's concordance correlation coefficient values ranged from 0.20 to 0.32, indicating poor relationship between the predicted and observed values. The values of prediction interval coverage probability (PICP) recorded 86.4–91.1% for SIC at different depths. Annual precipitation and precipitation seasonality were the most important covariates in soil below the 30 cm depth. The predicted SIC stocks were 10.3 ± 0.01, 81.6 ± 0.07 and 186.7 ± 0.13 Mg ha−1 at 0–15, 0–100 and 0–200 cm, depth, respectively. The uncertainty analysis suggests that there is room to improve the current spatial predictions of SIC. It is anticipated that this digital mapping of SIC will be useful for assessment of carbon cycle in arid regions. [ABSTRACT FROM AUTHOR]

The present study assessed the visible and short wave infrared (VNIR-SWIR) laboratory spectroscopy coupled random forest regression (RF) technique for predicting soil properties in the southern Karnataka Plateau, India. The spectral data acquired for about 228 profile samples were used to predict key soil properties. The RF model fits well for the spectral prediction of clay (R2 = 0.65), sand (R2 = 0.60), cation exchange capacity (R2 = 0.74), field capacity (R2 = 0.65) and permanent wilting point (R2 = 0.72). Wherein soil organic carbon was poorly predicted with an R2 of 0.22 and RPD of 1.2 due to its lower content and narrow range (0.8 to 20 g kg−1). The spectral assessment by PCA showed that the first (50%) and third (34%) components had high spectral variation and significantly correlated with soil properties such as pH, CEC, clay, FC, and PWP related to wavelengths indicating clay minerals and iron oxides. However, the second component had less spectral variation (13%) that is related to wavelengths indicating various organic components and correlated well with SOC. Thus, the VNIR-SWIR spectroscopy could be a suitable supplementary method for rapidly predicting soil properties related to clay minerals and iron oxides. [ABSTRACT FROM AUTHOR]

Classification of fields into management units based on soil variability and fertility is important for spatial crop planning. The present study was conducted in Chukanagallu subwatershed (97 km2), Koppal district of Northern Karnataka Plateau, India to map the soil fertility management units and to analyse the suitability of soil for different crops. Random forest regression and classification algorithms were used to map the differentiating characteristics of soil series (soil depth, coarse fragments and soil colour), physicochemical properties (pH, EC and OC) and fertility parameters (P2O5, K2O, S, Fe, Mn, Zn, Cu, B). Random forest model performed well for the prediction of fertility parameters (R2 = 44–73%) and physicochemical properties (R2 = 39–83%) compared to soil depth and coarse fragments (R2 = 17–18%). Predicted soil fertility parameters and physicochemical properties were used for the delineation of different homogenous fertility management units. Soil series characteristics and fertility parameters were also evaluated using a multi-criteria approach for suitability of soil for cotton, groundnut and rice cultivation and the results showed that major area of subwatershed is moderately suitable for the cultivation of cotton, rice and groundnut. The management units derived from DSM approach were symmetrical in production potential and requires similar management aspects which are useful for appropriate planning of management strategies such as crop selections and nutrient management to achieve sustainable production. [ABSTRACT FROM AUTHOR]

This study was conducted in Chinchura-Mogra and Polba-Dapur Blocks of Hugli District, West Bengal to determine the changes in cropping systems on water-retention characteristics (WRC) and available water capacity (AWC) and their relations with other soil properties. In the present study, three sites contained adjacent cropping systems of banana and mango orchard, paddy–paddy, and paddy–potato–vegetables were selected. Soil samples were collected from depths of 0–30 and 30–60 cm in three representative sites of each cropping system with three replications guided by land use and soil map of study area. Analysis of variance was performed to compare the impact of cropping systems on available water content and water-retention characteristics. The mean clay content was greater both on the surface (61.70%) and in the subsurface (55.06%) in the soils under the paddy–paddy cropping system than banana and mango orchard and paddy–potato–vegetable cropping systems. Paddy–potato–vegetables cropping system (0.55%) has lower soil organic carbon compared to the banana and mango orchard (0.63 %) and paddy–paddy cropping system (0.65%) at 0–30 cm deep, whereas no significant difference in soil organic carbon was recorded in 30–60 cm deep. The results of available water capacity indicated that paddy–paddy cropping system recorded lower available water capacity at both ranges of depth. Available water capacity is significantly positively correlated with silt and organic carbon. The results of water-retention studies indicated that 75 and 85% of available water was removed from the soil of paddy–potato–vegetable cropping system by 0.5 M Pa at 0–30 and 30–60 cm deep, respectively, whereas only 56–62% of available water was removed by 0.5 M Pa in the other two systems. The results show that the paddy–potato–vegetable cropping system is more vulnerable to moisture stress during drought periods. [ABSTRACT FROM PUBLISHER]