Preeti Singh

and 6 more

Reclamation of mined soil improved soil quality and SOC sequestration. A chronosequence study consisting of 8 and 25years old reclaimed mine soils under Azadirachta indica, Gmelina arborea, Dalbergia sissoo and recently dumped soils in Gevra, Chhattisgarh, India was initiated to quantify the quality and quantity of carbon pools. MBC (microbial biomass carbon) showed highest value in case of Azadirachta indica (1468.45 ug C/g soil) followed by Dalbergia sissoo (1338.19 ug C/g soil) and Gmelina arborea (1160.61ug C/g soil) in surface soil after 25years of reclamation. Mean total soil C stock was estimated as 334.72,226.94 and 191.20 Mg C ha-1, under Azadirachta indicia, Dalbergia sissoo and Gmelina arborea plantation respectively. Carbon stock of the soil increased with an increase in year of reclamation. Among the four different pools of organic carbon, the carbon per cent was highest in the non-labile pool of carbon under Azadirachta indica (88.25%). Humic acid C content and C/N ratio had increased under Azadirachta indica, Dalbergia sissoo with an increase in the year of reclamation. FT-IR spectra in the case of Azadirachta indica, Dalbergia sissoo and Gmelina arborea indicated that relative proportions of aromatic groups along the chronosequence have increased. TOC (Total organic carbon) content was highest under Azardichta indica but aromaticity was highest under Gmelina arborea as obtained by E4/E6 and EET: EBZ ratio. These results indicated that different carbon pool and aromaticity of carbon improved with the increase in year of reclamation and significant relationships were present between spectroscopic indices and different soil carbon parameters.

Seema Chahar

and 6 more

Salts in the root zone have high spatial variability, changes rapidly and adversely affects soil quality and crop productivity. Rapid detection of electrical conductivity (EC) using visible-near infrared (Vis-NIR) and midinfrared (MIR) spectroscopy can alleviate the adverse effects on soil and plant, which through conventional method is time consuming. Soils were collected from the Indo-Gangetic plains and analyzed for EC using conventional, Vis-NIR, MIR spectroscopy and there was wide variation in EC measured by the conventional method. The spectral regions in 460-500 and 1890-1906 nm in the Vis-NIR region and 4200-4310, 5275-5280, 6660-6670, 7305-7310 and 8290-8300 nm in the MIR region were sensitive to detection of EC. Partial least square regression (PLSR) outperformed random forest regression (RF), support vector regression (SVR), and multivariate adaptive regression splines (MARS) both in Vis-NIR and MIR region during calibration. The ratio of performance deviation (RPD), coefficient of determination (R2) and root mean square error (RMSE) of the validation dataset were used to assess the prediction accuracy and the predictive performance of PLSR (2.44, 0.84, 0.21), RF (1.95, 0.81, 0.20), SVR (2.09, 0.78, 0.22) and MARS (1.81, 0.73, 0.27) models. PLSR model performed very well in the Vis-NIR range; however, in the MIR range, RF (1.43, 0.52, 0.20), followed by PLSR (1.40, 0.55, 0.35), performed better than SVR (1.39, 0.53, 0.35) and MARS (1.29, 0.44, 0.37). Vis-NIR spectroscopy with PLSR algorithm predicted EC better than MIR spectroscopy and would be the method of choice for rapid estimation and prediction of EC in the study region.