Maize ( Zea mays L.) is the third most important cereal crop after rice ( Oryza sativa ) and wheat ( Triticum aestivum ). Salinity stress significantly affects vegetative biomass and grain yield and, therefore, reduces the food and silage productivity of maize. Selecting salt‐tolerant genotypes is a cumbersome and time‐consuming process that requires meticulous phenotyping. To predict salt tolerance in maize, we estimated breeding values for four biomass‐related traits, including shoot length, shoot weight, root length, and root weight under salt‐stressed and controlled conditions. A five‐fold cross‐validation method was used to select the best model among genomic best linear unbiased prediction (GBLUP), ridge‐regression BLUP (rrBLUP), extended GBLUP, Bayesian Lasso, Bayesian ridge regression, BayesA, BayesB, and BayesC. Examination of the effect of different marker densities on prediction accuracy revealed that a set of low‐density single nucleotide polymorphisms obtained through filtering based on a combination of analysis of variance and linkage disequilibrium provided the best prediction accuracy for all the traits. The average prediction accuracy in cross‐validations ranged from 0.46 to 0.77 across the four derived traits. The GBLUP, rrBLUP, and all Bayesian models except BayesB demonstrated comparable levels of prediction accuracy that were superior to the other modeling approaches. These findings provide a roadmap for the deployment and optimization of genomic selection in breeding for salt tolerance in maize.

The experiment was conducted at SIF of Chandra Shekhar Azad University of Agriculture & Technology, Kanpur during Rabi season of 2017-18. It was experiment consisted eight treatments of different nutritional doses of micro nutrient, organic manure, and micro-organisms, along with major nutrient with the objective to find out the effect of vermicompost, FYM, Azotobacter, PSB with chemical fertilizer on growth, treatment combination for wheat and assess the economics of the treatments. Due to balance nutrition in wheat variety Shekhar (K-1006). The experiment was organized under RBD with three replications. It was the soil of the field Analyzed medium fertility status concerning available NPK, S and Zn status of micronutrients. The treatment T₅ (RDF + Azotobacter + PSB + vermicompost @ 5 t ha^-1) found superior in terms of maximum root and shoot growth, yield attributes and yield the maximum grain yield (58.75 q/ha.), under recorded in T₅ (RDF + Azotobacter + PSB + vermicompost @ 5 t ha^-1) treatment compared to control treatment.