Microbes-mediated integrated nutrient management for improved rhizo-modulation, pigeonpea productivity, and soil bio-fertility in a semi-arid agro-ecology

Abstract

Excessive dependence on chemical fertilizers and ignorance to organic and microbial inputs under intensive cropping systems are the basic components of contemporary agriculture, which evolves several sustainability issues, such as degraded soil health and sub-optimal crop productivity. This scenario urges for integrated nutrient management approaches, such as microbes-mediated integrated plant nutrition for curtailing the high doses as chemical fertilizers. Rationally, experiment has been conducted in pigeonpea at ICAR-IARI, New Delhi, with the aim of identifying the appropriate nutrient management technique involving microbial and organic nutrient sources for improved rhizo-modulation, crop productivity, and soil bio-fertility. The randomized block-designed experiment consisted nine treatments viz. Control, Recommended dose of fertilizers (RDF), RDF+ Microbial inoculants (MI), Vermicompost (VC), Farm Yard Manure (FYM), Leaf Compost (LC), VC + MI, FYM + MI, and LC + MI. Rhizobium spp., Pseudomonas spp., Bacillus spp., and Frateuria aurantia were used as seed-inoculating microbes. The results indicated the significant response of integration following the trend VC + MI > FYM + MI > LC + MI > RDF + MI for various plant shoot-root growth attributes and soil microbial and enzymatic properties. FYM + MI significantly improved the water-stable aggregates (22%), mean weight diameter (1.13 mm), and geometric mean diameter (0.93 mm), soil organic carbon (SOC), SOC stock, and SOC sequestration. The chemical properties viz. available N, P, and K were significantly improved with VC + MI. The study summarizes that FYM + MI could result in better soil physico-chemical and biological properties and shoot-root development; however; VC + MI could improve available nutrients in the soil and may enhance the growth of pigeonpea more effectively. The outcomes of the study are postulated as a viable and alternative solution for excessive chemical fertilizer-based nutrient management and would also promote the microbial consortia and organic manures-based agro-industries. This would add to the goal of sustainable agricultural development by producing quality crop produce, maintaining agro-biodiversity and making the soils fertile and healthy that would be a “gift to the society.”

Effect of Potassic Fertilizer, FYM and Vermicompost on Growth Parameters, Yield Attributes and Yield of Pigeon Pea (Cajanus cajan) Crop in Chitrakoot Area

“…of branches plant -1 (32.8). These findings are further supported by Brar et al [16] Verma et al [17] and Gupta et al [18].…”

System of wheat intensification (SWI): Effects on lodging resistance, photosynthetic efficiency, soil biomes, and water productivity

“…These practices have been found to augment soil moisture availability, introduce additional nutrients, and enhance organic carbon levels through the decomposition of the organic residues. The existence of a readily decomposable carbon source in soil establishes a noteworthy association between microbial activity and enzyme activity [ 54 ], as well as enhanced soil water status [ 55 ], and exhibits a positive correlation with microbial biomass carbon [ 56 ]. The practice of hoeing in SWI serves as soil mulch, effectively reducing evaporation and improving soil moisture.…”

Occurrence and field evaluation of sugarcane genotypes for resistance to pokkah boeng disease in China

“…Therefore, resistance evaluations are necessary across multiple years or locations (Buerstmayr et al, 2008; Yan et al, 2022). Cluster analysis is a method for dividing a group of objects into classes so that similar objects are in the same class (Gupta et al, 2022; Kalogiouri et al, 2021), while discriminant analysis is a multivariate analysis used to find the linear combination of features that distinguish two or more classes (Huberty, 1975; Stella, 2019). Combining cluster analysis with discriminant analysis helps to improve the accuracy of classification.…”