• Genetic gain for rice grain yield for International Rice Research Institute drought breeding program was estimated. • Positive trend of 0.68 %, 0.87 %, 1.9 % under irrigated control, moderate and severe drought achieved. • Superiority of new rice varieties over currently grown demonstrated on farmers’ fields. • International Rice Research Institute developed rice varieties can protect farmers from crop losses under drought conditions.

The underground reserve (root) has been an uncharted research territory with its untapped genetic variation yet to be exploited. Identifying ideal traits and breeding new rice varieties with efficient root system architecture (RSA) has great potential to increase resource-use efficiency and grain yield, especially under direct-seeded rice, by adapting to aerobic soil conditions. In this review, we tried to mine the available research information on the direct-seeded rice (DSR) root system to highlight the requirements of different root traits such as root architecture, length, number, density, thickness, diameter, and angle that play a pivotal role in determining the uptake of nutrients and moisture at different stages of plant growth. RSA also faces several stresses, due to excess or deficiency of moisture and nutrients, low or high temperature, or saline conditions. To counteract these hindrances, adaptation in response to stress becomes essential. Candidate genes such as early root growth enhancer PSTOL1, surface rooting QTL qSOR1, deep rooting gene DRO1, and numerous transporters for their respective nutrients and stress-responsive factors have been identified and validated under different circumstances. Identifying the desired QTLs and transporters underlying these traits and then designing an ideal root architecture can help in developing a suitable DSR cultivar and aid in further advancement in this direction.

The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha^-1), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to identify the genotypes that displayed the best performance according to the multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), and factor analysis and ideotype-design (FAI-BLUP) index. AMMI analysis demonstrated significant variation for environment (E), genotype (G), and genotype-by-environment interaction (GEI) (P < 0.01) for all the studied traits. The AMMI1 biplot showed that PC1 explained the majority of the variation for GY (77.6%), DTF (90.5%), Fe (73.5%), and Zn (86.8%), helping to identify stable and high-performing genotypes. AMMI2 biplot further resolved complex GEI patterns, highlighting genotypes with specific adaptability to individual environments. The GGE biplot revealed clear “which-won-where” patterns for GY, DTF, Fe, and Zn, explaining 94.37%, 99.71%, 83.49%, and 96.93% of GEI variation, respectively. BLUP analysis using a linear mixed model revealed significant GEI effects for GY, DTF, Fe, and Zn across 30 rice genotypes in three environments. Low heritability was observed for Fe (28.2%) and moderate for GY (54.4%) and Zn (56.4%), while DTF showed high heritability with strong genotypic accuracy. Genotype G7 was identified as stable, early, high-yielding, and rich in Fe based on HMGV, RPGV, and HMRPGV indices. The MTSI, MGIDI and FAI-BLUP analysis revealed that BHU-SKS-1 (G15) and IR105696 -1–2-3–1-1–1 -B (G9) were the most stable and best mean performer for high grain yield and high grain Fe & Zn content, while IR 108,195–3-1–1-2 (G7) was the most stable and best mean performer for high grain yield and high grain Fe content with early flowering.

Background: Rice plays a vital role in ensuring global food security, being a staple crop that feeds more than half of the global population. With rising food demand, improving its yield and quality is a prior demand that tends to meet the current changing scenarios and market demands. Unlocking its hidden genetic variability offers immense potential to breed superior varieties. Exploring heritability and genetic advance can accelerate the development of high-performing quality-rich rice cultivars to fulfill the need of future food demands and consumer preferences. Methods: A study aimed to evaluate twenty-eight rice genotypes during Kharif 2023 for genetic variability, heritability and genetic advance as per cent of mean for twenty-two yield and quality traits was conducted at Agricultural Research Farm, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi. Result: ANOVA showed highly significant differences in the twenty-eight genotypes suggesting that considerable variability exists at the genotype levels. Test weight displayed high genotypic coefficient of variability (GCV) and phenotypic coefficient of variability (PCV) followed by effective number of tillers per plant. For quality traits, alkali digestion value displayed the highest GCV and PCV, followed by gel consistency, elongation index and length-breadth ratio before cooking. The existence of considerable genetic variability in the genotypes studied for twenty-two traits was evident. All twenty-two traits exhibited higher heritability levels with varying degree of genetic advance. The traits PH, PL, SFP, TW, KLBC, KBBC, LBBC, ER, HRR, ADV, AC, GC and ADV showed high heritability values along with high genetic advance as per cent of mean. These traits have evidence of additive gene action and can be improved using direct selection methods.