Assessment of genetic variability of quality, yield, and its attributing traits in sorghum (Sorghum bicolor (L.) Moench)

INDUCED GENETIC VARIABILITY, HERITABILITY AND TRAIT ASSOCIATIONS IN YELLOW-PERICARP SORGHUM [SORGHUM BICOLOR (L.) MOENCH] MUTANTS

Yellow-pericarp sorghum possesses nutritional and industrial value owing to its carotenoid content, low condensed-tannin concentration and high starch recovery. However, such landraces in peninsular India remain largely unimproved with limited genetic diversity available for conventional breeding. The present study explored genetic variability and trait associations in 60 M4 derived mutant lines from the yellow-pericarp sorghum landrace “Udgir Piwali” through gamma irradiation (100–500 Gy), ethyl methanesulphonate (EMS; 0.1–0.3%) and their combined treatments. Sixty-four entries, including three released checks and the parental control were evaluated for 19 morphological, yield and physiological traits in a randomized block design with two replications during post rainy season of 2024–25 at Parbhani, Maharashtra, India. Analysis of variance revealed significant differences among entries for all traits, with the greatest variation observed for fodder yield and panicle-related traits. Phenotypic coefficients of variation exceeded genotypic coefficients for all traits. Panicle weight and fodder yield showed high heritability (80 and 88%, respectively) coupled with high genetic advance as per cent of mean (37.72 and 37.27%), indicating substantial scope for selection. Grain yield per plant exhibited moderate heritability (55%) and genetic advance (15.59%). Genotypic correlation analysis showed strong positive associations of grain yield with panicle length (rg = 0.910), panicle weight (0.855), panicle width (0.687) and stem diameter (0.592). Path analysis identified positive direct effects of internodal length, panicle length and days to maturity, whereas flag leaf area and plant height exhibited negative direct effects. The study identified 400Gy 2, 400Gy-4, 500Gy-3, 300Gy-5 and 0.2% EMS-4 as promising mutant lines for further evaluation. These lines may serve as useful genetic resources for improving productivity in yellow-pericarp sorghum.

Assessment of Heritability and Correlation Analysis of Yield and Oil-Related Traits in Different Safflower (Carthamus tinctorius L.) Genotypes

Genetic variability and reliable heritability estimates are prerequisites for effective selection in plant breeding. This study assessed heritability and trait correlations for yield and yield-related characters in ten safflower (Carthamus tinctorius L.) genotypes. The experiment was carried out during the Rabi season of 2025–2026 at the Experimental Field, Botanical Garden, Department of Plant Breeding and Genetics, Sindh Agriculture University, Tandojam, Sindh, Pakistan. A Randomized Complete Block Design (RCBD) with three replications was used. Nine yield and yield-related traits were recorded and analyzed. Analysis of variance revealed highly significant (P ≤ 0.01) differences among the genotypes for all studied traits, indicating the presence of substantial genetic variability and considerable potential for genetic improvement through selection. Based on mean performance, genotypes PI-304093 and PI-306956 exhibited superior performance for most of the evaluated traits, suggesting their potential as valuable genetic resources for developing high-yielding safflower cultivars. Correlation analysis showed that most yield-related traits were positively and significantly associated with one another, indicating the possibility of simultaneous improvement through selection. High broad-sense heritability estimates were observed for days to 90% maturity (96.23%), plant height (97.99%), days to 75% flowering (95.09%), biomass per plant (79.97%), seed yield per plant (78.84%), oil content (67.69%), harvest index (62.25%), and capsules per plant (61.93%). These results indicate that direct phenotypic selection can be effective for most traits, and that harvest index may serve as a useful indirect selection criterion for improving seed yield. Genotypes PI-304093 and PI-306956 are recommended as promising parental material for safflower breeding, while multi-location, multi-season trials are suggested to confirm their stability before use in cultivar development.

Evaluation of Morphological Traits, Yield Performance and Genetic Variability of Soybean (Glycine max L.) Genotypes in the Madhupur Tract of Bangladesh

Soybean improvement depends on the identification of genetically diverse germplasm with superior agronomic performance. This study evaluated the phenotypic diversity, yield potential, and genetic variability of a large and diverse panel of 278 soybean genotypes under the agro-ecological conditions of the Madhupur Tract, Bangladesh, during November 2023 to April 2024. The experiment was conducted in a randomized complete block design with two replications. Morphological, phenological, physiological, and yield-related traits were recorded and analyzed using analysis of variance, correlation, principal component analysis (PCA), and genetic parameter estimation. Considerable variation was observed for all evaluated traits. Pointed ovate leaves (58.3%), white flowers (38.1%), indeterminate growth habit (97.8%), medium plant height (64.7%), medium maturity (85.3%), and medium seed size (54.3%) predominated among the genotypes. Grain yield per plant (GY) ranged from 0.46 to 20.06 g, with BS-53 recording the highest yield, while several other genotypes also exhibited comparatively superior yield and favorable agronomic characteristics. BS-260 matured earliest (88 days) and BS-18 exhibited the highest leaf chlorophyll content. GY showed strong positive correlations with seeds per plant (r = 0.906 ***) and pods per plant (r = 0.862 ***). PCA explained 67.4% of the total phenotypic variation in the first two principal components. High broad-sense heritability coupled with high genetic advance for most traits suggested substantial genetic variability and potential responsiveness to selection under the conditions of the present study. The comprehensive characterization of this diverse germplasm panel and the identification of high-yielding and agronomically favorable genotypes provide a valuable resource for soybean selection and breeding in Bangladesh, while the promising genotypes warrant further multi-location and multi-season validation.

Genetic Variability, Correlation and Path Coefficient Analysis for Grain Yield and its Component Traits in Rice (Oryza sativa L.)

The present investigation was undertaken to assess genetic variability among thirty rice (Oryza sativa L.) genotypes and to identify reliable indirect selection criteria for grain yield through correlation and path coefficient analysis. Thirty genotypes were evaluated in a randomised block design with three replications during Kharif 2025 at the Field Experimentation Centre, Naini Agricultural Institute, Prayagraj, Uttar Pradesh, for thirteen quantitative traits. Analysis of variance showed highly significant genotypic differences for twelve of the thirteen characters, confirming substantial genetic variability in the material. High heritability coupled with high genetic advance as a percentage of the mean was recorded for number of spikelets per panicle (98.4%; 41.1%), biological yield per plant (71.2%; 23.6%) and grain yield per plant (69.9%; 22.8%), indicating predominantly additive gene action and good scope for direct phenotypic selection for these traits. Grain yield showed a strong positive genotypic correlation with test weight (1.09), biological yield (0.871) and harvest index (0.715), and path analysis confirmed biological yield and harvest index as the traits with the largest positive direct effects on grain yield at both genotypic and phenotypic levels; test weight, despite its strong correlation with yield, acted mainly through indirect effects channelled via these two traits. The genotype DRRH2 combined the highest grain yield with high biological yield, harvest index and test weight and, together with 72-Dhan-59, 80-NLR-40024 and Vikramarya, is proposed as a promising donor for future hybridisation programmes aimed at raising grain yield in rice.

Multi-trait model-based assessment of selection efficiency and stability in soybean germplasm.

Genetic variability, heritability, and trait associations for yield and grain dimensions in diverse rice genotypes

Rice ( Oryza sativa L.) is a critical staple crop, necessitating continuous genetic improvement to enhance yield and quality traits to meet global food demands. This study aims to identify high‐yielding genotypes with desirable quality traits and elucidate the relationships among traits to inform breeding strategies. Twenty‐seven rice genotypes were evaluated for genetic variability, heritability, genetic advance, and trait associations. Nine agronomic traits were measured: grain yield, days to maturity, plant height, productive tiller number, 1000‐grain weight, grain length, grain width, grain shape, and awn length during the 2021–2023 cropping seasons. Analysis of variance revealed highly significant differences ( p  < 0.01) among genotypes for all traits, demonstrating pronounced phenotypic variations that suggest a diverse genetic background among the studied genotypes. Grain yield ranged from 4.38 t ha − 1 (Gerdeh) to 7.73 t ha − 1 (Shiroudi), with a mean of 6.052 t ha − 1 . Broad‐sense heritability ( H 2 ) was high (0.926–1.0) for all traits. Traits with both high heritability and high genetic advance as percentage of mean (GA% > 20%)—namely, grain shape, productive tiller number, grain yield, grain width, and grain length—are likely to respond effectively to direct phenotypic selection. Correlation analysis showed significant positive associations between grain yield and days to maturity ( r  = 0.532, p  < 0.01), 1000‐grain weight ( r  = 0.266, p  < 0.05), grain length ( r  = 0.269, p  < 0.05), and grain shape ( r  = 0.269, p  < 0.05), but a negative correlation with awn length ( r  = −0.406, p  < 0.01). Path analysis identified days to maturity (direct effect = 0.341, p  < 0.001) and grain shape (0.241) as key yield contributors. Hierarchical clustering grouped genotypes into four clusters, with Cluster 4 (including Shiroudi, Keshvari, and Neda) containing high‐yielding genotypes. These results provide clear guidance for designing efficient breeding programs through targeted selection of superior genotypes and trait‐based strategies. Shiroudi and Cluster 4 genotypes are promising candidates for breeding high‐yielding, quality rice varieties.