Impact of Long-term Application of Organic and Inorganic Nutrient Through Inductive cum Targeted Yield Model on Soil Physical Properties under Pearl Millet [Pennisetum glaucum (L.)] –Wheat [Triticum aestivum (L.)] Cropping System of Semi-arid North-West India. Issue 20 (13th November 2021) - Kumar, Vikas; Goyal, V.; Dahiya, Rita; Dey, P.
ABSTRACT: Sustainability of cereal-based cropping system is important for the livelihood and food security in semi-arid regions. The present study explores the impact of long-term organic and inorganic nutrients and integrated fertilization practices of soil test crop response (STCR) approach of inductive-cum-targeted yield model on soil physical properties and its correlation with soil organic carbon (OC) under pearl millet–wheat in sandy-loam soils of semiarid north-west regions of India. Results showed that OC in the soils significantly increased in farm yard manure (FYM) and integrated treatments up to a maximum of 135% and 148%, respectively, in a period of 8 years over the control in surface soils (0–15 cm). The increase in OC significantly increased the infiltration rate (IR), hydraulic conductivity (HC), soil water retention at all suctions, water stable aggregates (WSA) (> 0.25 mm) and mean weight diameter of the soil aggregates, while decreased the bulk density (BD) and penetration resistance (PR) both at surface and subsurface soil layers. Soil OC also showed a negative correlation with BD (r = −0.955) and PR (r = −0.820). The hydraulic properties of the soil, viz., soil water retention, showed a high positive correlation with field capacity (r = 0.973), 0.922 for permanent wilting point (r = 0.922), HC (r = 0.938), IR (r = 0.973), and WSA (r = 0.979) with OC. Thus, long-term application of organic material in conjunction with NP improved soil physical health, provided better environment to grow crops through improved nutrient concentration and its translocation that ultimately helps to achieve yield target through STCR (Soil Test Crop Response) approach of inductive-cum-targeted yield model.