Estimation of genetic variability and gene action for grain yield in finger millet

Assessment of Genetic Variability for Morphological and Nutritional Traits in Finger Millet (Eleusine coracana (L.) Gaertn.)

Aims: To evaluate genetic variability parameters for twelve morphological and four nutraceutical traits in forty-five finger millet genotypes to identify traits with potential for crop improvement. Study Design: Randomised Complete Block Design (RCBD). Place and Duration of Study: Hill Millet Research Station, NAU, Waghai, The Dangs, and Cotton Research Sub-Station, NAU, Achhalia, during summer 2024 and summer 2025. Methodology: Forty-five diverse finger millet genotypes were evaluated with three replications. Days to 50% flowering and days to maturity were recorded on a plot basis, while plant height, productive tillers per plant, ear head length, fingers per panicle, finger width, weight of matured panicle per plant, 1000-seed weight, harvest index, fodder yield per plant and grain yield per plant were recorded from five randomly selected plants. Quality traits (protein, calcium, iron and crude fibre) were analysed using standard chemical and spectrophotometric methods. Analysis of variance and genetic parameters such as GCV, PCV, ECV, broad-sense heritability and genetic advance as a percentage of the mean were estimated. Results: The study revealed significant genetic variability among the 45 finger millet genotypes for all sixteen traits. Environmental effects and genotype × environment interactions significantly influenced most agronomic traits, whereas nutritional traits remained relatively stable across environments. High heritability coupled with high genetic advance (as a percentage of the mean) was observed for ear head length (cm), finger width (cm), 1000-seed weight (g), protein content (%), calcium content (mg/100 g), iron content (mg/100 g) and crude fibre (%), indicating the predominance of additive gene action and the effectiveness of phenotypic selection for improving these traits. Moderate heritability along with high genetic advance as a percentage of the mean was recorded for grain yield per plant (g), harvest index (%) and weight of matured panicle per plant (g), suggesting good scope for improvement through selection. Conclusion: The study revealed substantial genetic variability among the finger millet genotypes. Traits such as ear head length, finger width, 1000-seed weight, grain yield, protein, calcium, iron and crude fibre exhibited high potential for improvement through direct selection. These traits can be effectively utilised in developing high-yielding and nutritionally superior finger millet varieties.

Genetic Variability and Correlation Analysis among Guar Genotypes for Fodder Yield and Quality Related Traits

Limited genetic variability remains a major constraint to genetic improvement in guar (Cyamopsis tetragonoloba L.) restricting both its productivity and cultivation in Pakistan. As a drought adapted legume with significant value as fodder, green manure, and a soil-enhancing nitrogen fixer, guar holds considerable untapped potential for sustainable agriculture. Enhancing its genetic base is therefore essential for developing high-yielding, nutritionally superior varieties suited to arid and semi-arid environments. To address this need, a field experiment was conducted in October 2022 at the University of Agriculture, Faisalabad, using a Randomized Complete Block Design (RCBD) with three replications to assess genetic variability and trait associations among 24 guar genotypes. Five plants per genotype were evaluated for agronomic traits (plant height, branches, tillers, leaves, leaf area, clusters plant⁻¹, pods cluster⁻¹, pods plant⁻¹, fresh and dry biomass) and forage quality attributes (crude protein, crude fiber, ash, moisture, NDF, and ADF), with quality traits quantified via Near Infrared Spectroscopy (NIRS). Significant phenotypic variability was recorded among genotypes. Plant height ranged from 78–141.2 cm, branches 2.16–10.06, leaves 44.87–330.33, fresh biomass 200–700 g, dry biomass 70–244 g, and crude protein 15.16–23.37%. Plant height showed strong positive correlations with fresh biomass, leaf area, and crude protein, whereas branches and clusters exhibited negative associations. Tillers were positively correlated with several yield components but not with leaf area or protein. Crude protein was positively associated with NDF, ash, and crude fiber. Superior genotypes identified included Guar-401 (plant height), Guar-303 and Guar-701 (number of branches), Guar-102 and Guar-701 (number of leaves), and Guar-103 and Guar-803 (protein). These high performing genotypes provide valuable genetic resources for developing improved guar cultivars with enhanced fodder yield and nutritional quality.

Phenotypic Diversity and Correlation Analysis of Morphological Traits in Rice (Oryza sativa L.)

Sixty rice genotypes were evaluated during the Kharif season of 2023 at the Norman E. Borlaug Crop Research Centre (NEBCRC), G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, using an alpha-lattice design with two replications to quantify phenotypic diversity and examine associations among 15 morphological and yield-related traits. The traits comprised plant height, flag-leaf length, flag-leaf breadth, leaf area, days to 50% flowering, number of panicles per plant, panicle length, number of grains per panicle, grain yield, biological yield, harvest index, grain length, grain breadth, grain length/breadth ratio and test weight. Pearson correlation analysis revealed that grain yield was strongly and positively associated with harvest index (r = 0.81, P < 0.01) but negatively associated with biological yield (r = -0.35, P < 0.01). Biological yield was positively associated with days to 50% flowering (r = 0.79, P < 0.01), flag-leaf length (r = 0.69, P < 0.01), leaf area (r = 0.68, P < 0.01), grains per panicle (r = 0.36, P < 0.01), plant height (r = 0.27, P < 0.05) and panicle length (r = 0.27, P < 0.05). Standardised Euclidean-distance-based hierarchical analysis partitioned the genotypes into five clusters containing 19, 8, 14, 10 and 9 entries, respectively. The greatest inter-cluster distance occurred between Clusters II and IV (6.885), while the smallest occurred between Clusters I and II (4.826). Cluster V showed the largest within-cluster distance (4.713), indicating comparatively high heterogeneity. Genotypes belonging to the widely separated Clusters II and IV constitute useful parental pools, provided their trait means and agronomic performance are also complementary. The results demonstrate appreciable morphological differentiation and identify trait relationships relevant to selection for rice improvement.

Genetic Mechanisms Associated with Physiological, Nutritional Traits and Grain Yield in Pearl Millet (Pennisetum glaucum L.)

One hundred genotypes of pearl millet including three checks were tested during kharif 2024 in an Alpha Lattice design to understand the genetic mechanisms associated in governing the inheritance of grain yield, nutritional (iron, zinc, and protein content in seeds), and physiological traits (harvest index, relative water content, and SPAD chlorophyll meter reading). Higher variability for iron and zinc; moderate variability for grain yield, harvest index, and protein; and low variability for relative water content and SPAD chlorophyll meter reading were recorded. High heritability and high genetic advance as percent of mean were noted for iron content, zinc content, grain yield per plant, protein content, and harvest index, indicating predominance of additive gene action, and an early and simple selection would be advisable. High heritability coupled with moderate genetic advance over percent mean registered for relative water content indicated the operation of additive gene actions and might consistently manifest in future generations, resulting in increased effectiveness of the breeding program. Moderate heritability along with low genetic advance for SPAD chlorophyll meter reading revealed governance of non-additive genes and can be improved by heterosis breeding as simple selection might not be effective.

Developing and validating a mini core set of global durum wheat panel using multivariate analysis

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.