Diversified cropping modules designed for soil restoration, CO2 sequestration, and generating carbon credits

This study aimed to know the potential of different cropping modules (CMs) that started on the degraded land representing 4450 km2 of the Vindhyan region of India. The objective of the study was to know (i) the higher carbon dioxide (CO2) biosequestration, (ii) enhance soil organic carbon (SOC) fractions, and (iii) generate carbon (C) credit to the additional income as a climate currency to the farmers. The experiment was carried out on 4–13 years (2010–2022) old practiced CMs viz; (1) Eucalyptus (Eucalyptus sp.) + bajra (Pennisetum glaucum), 13‐year; (2) Guava (Psidium guajava) + phalsa (Grewia asiatica), 4‐year; (3) Teak (Tectona grandis) + wheat (Triticum aestivum), 10‐year; (4) Tomato (Solanum lycopersicum), 13‐year; (5) Pasture land, 13‐year, and (6) Rice (Oryza sativa),13‐year. Soil samples were collected from two depths (0–0.15 and 0.15–0.30 m) under 82.7 and 83.33 East longitude and 23.52 and 25.32 North latitudes. Results showed that the mean data of depths pH and electrical conductivity (EC) ranged from 4.4–8.1 and 0.10–0.77 dS m−1, respectively. Furthermore, the mean data of both depths' bulk density (ρb) varied between 1.3 and 1.5 Megagram (Mg) m−3. The mean data of both depths available soil organic C (ASOC) (7.25 g kg−1) and SOC stock (14.43 Mg ha−1) in the pasture land‐based CMs found 137.7% and 111.0% more over rice‐based CMs (3.05 g kg−1 and 6.84 Mg ha−1), respectively. The maximum permanganate oxidizable carbon (POX‐C), microbial biomass C in soil (MBCS), and total organic C (TOC) stock based on mean data of both depths were 798.2 mg kg−1, 92.6 μg g−1, and 46.3 Mg ha−1 found in pasture land‐based CMs. Regarding mean data of both depths, the recalcitrant index (RI) and lability index (LI) ranged about 0.4–0.9 and 1.7–2.0, respectively. Moreover, the highest total CO2 biosequestration (124.7 Mg ha−1), C credit (US$ 6233 ha−1), and the social cost (US$ 10,720 ha−1) were observed in eucalyptus + bajra‐based CMs. Based on the principal component analysis (PCA) study, the principal component 1 (PC1) and PC2 explained 74.6 and 16.6% variability on various parameters, respectively. Furthermore, the correlation coefficient between ASOC and MBCS was 0.74. The hypothesis of this study was to create agricultural CMs that would restore degraded land levels of SOC fraction, enhance the CO2 biosequestration, and generate C‐credit for farmers as a climate currency for additional income. Furthermore, it will fulfil the net zero emission goal and bring dow