Jul 2026· Indian Journal of Agricultural Research· 0 citations· 28 references
Abstract
Background: Rice (Oryza sativa L.) productivity is increasingly constrained by climate variability, biotic stresses and limited natural resources, necessitating the effective utilisation of genetically diverse germplasm. Traditional rice landraces possess valuable adaptive, stress-tolerant and yield-related traits; however, their potential remains largely underutilized in breeding programmes. Methods: The present investigation was conducted during the zaid season of 2025 under field conditions using 130 rice (Oryza sativa L.) landraces evaluated in an augmented experimental design. A total of 21 agronomic, physiological and reproductive traits were assessed. Genetic divergence and trait relationships were analysed using principal component analysis (PCA) and hierarchical cluster analysis to identify the major traits contributing to phenotypic variability and yield performance. Result: Eight principal components with eigenvalues greater than one explained a substantial proportion of the total phenotypic variation. The first two components contributed most of the variability and were primarily associated with plant vigour, reproductive efficiency, biomass accumulation and yield-related traits. Plant height (X3), flag leaf length (X4), internode length (X7), grains per panicle (X9), 1000-seed weight (X10) and pollen fertility (X19) were the major contributors to genotype differentiation. Cluster analysis grouped the 130 genotypes into four distinct clusters. Groups I, II and IV exhibited high pollen fertility and superior yield performance, whereas Group III showed lower pollen fertility and poor yield traits. PCA biplot analysis further revealed a close association of high-yielding genotypes with pollen fertility, biomass traits and physiological efficiency. pollen fertility emerged as a key trait influencing genetic divergence and yield performance. The genetically diverse and superior-performing genotypes identified in this study represent valuable resources for rice improvement programmes aimed at enhancing productivity and adaptability.
Sodic soils, characterised by excessive sodium ion accumulation, significantly hamper rice productivity in major cultivation zones. This study aimed to assess genetic variability, divergence and inheritance parameters among 89 rice (Oryza sativa L.) genotypes under sodic soil conditions to identify promising lines donor lines for breeding programs. The experiment was conducted during kharif 2021 at a single site (ANDUAT, Ayodhya, Uttar Pradesh) using an augmented block design (ABD) with 5 blocks and 13 quantitative traits were recorded. Principal component analysis (PCA) and Mahalanobis D² cluster analysis used to determine genetic divergence and trait contributions to variability. Significant differences were observed among genotypes for all traits, indicating substantial genetic variability. Eight clusters were formed among which cluster II comprised the highest number of genotypes was 16, while Cluster III exhibited the highest inter-cluster distance (3.15), revealing its potential for identifying genetically diverse parental lines. The first 5 principal components showed 62.06 % of the total phenotypic variance, with PC1 (19.36 %) and PC2 (13.18 %) contributing most to total variation. Key traits contributing to this variation included grain yield per plant (GYP), biological yield (BY), plant height (PH), flag leaf area (FLA) and spikelet fertility (SF). The PC1 was primarily associated with the GYP (-0.5721) and biological yield per plant (-0.5187), whereas PC2 was influenced mainly by spikelet fertility (0.4130) and days to maturity (0.4241). Broad-sense heritability was ranged from 3.20 % to 96.63 % across different traits. Biological yield per plant exhibited the highest heritability (96.63 %), followed by grain yield and flag leaf area, which also showed high heritability coupled with high genetic advance as percent of mean, indicating predominant additive gene action and high selection efficiency. Promising genotypes such as WHM-1024 (25.96 g) and WHM-1016 (25.63 g) demonstrated high grain yield, whereas TCN-2080 (84.00), TCN-2066 (90.00) RAU-3074 (90.00), and NDR-2065 (119.00) showed early flowering and maturity. The integration of multivariate and genetic parameter analyses provides a robust basis for selection of genetically diverse parents and key yield-contributing traits for sodicity-tolerant rice breeding programs.
S. Poonam, C. Subhash, B. Uma et al.· Plant Science Today· 0 citations
Rice (Oryza sativa L.) is a major staple crop possesses extensive genetic variability, particularly among traditional landraces that serve as valuable resources for yield improvement, stress tolerance and nutritional enhancement. The present study evaluated 130 rice genotypes for 21 agro-morphological traits and physiological traits under field conditions using an augmented design during kharif 2024. Genetic divergence was estimated using Mahalanobis D² statistics and genotypes were grouped using Tocher’s clustering method. The analysis classified genotypes into 33 clusters, with Cluster 1 comprising the highest number of entries (22), while Clusters 12–33 were represented by highly divergent singleton genotypes. Large clusters were characterised by early flowering, moderate maturity and optimal plant height, whereas medium and singleton clusters exhibited distinct trait combinations such as higher grain yield, longer flag leaf, increased tiller number, elevated chlorophyll content (SPAD) and greater 1000-seed weight. The presence of substantial inter-cluster divergence suggests wide genetic variability among the studied genotypes. Selection of genetically distant parents, particularly from singleton and medium clusters, may enhance heterosis and recombination for yield and adaptive traits. These findings provide insights into the genetic diversity of rice germplasm and support strategic parent selection for developing high-yielding, climate-resilient and nutritionally improved rice varieties.
Hariharan, R. Mahendran, K. Satheeskumar et al.· Plant Science Today· 0 citations
Rice (Oryza sativa L.) improvement depends on the effective utilisation of diverse germplasm and the identification of key yield-contributing traits. The present study evaluated 25 genetically diverse rice germplasm accessions during Kharif 2025 using multivariate genetic diversity, DUS-based morphological characterisation, correlation, and path coefficient analyses. The experiment was conducted in a CRBD with three replications, and observations were recorded for 10 qualitative and 11 quantitative traits. Analysis of variance revealed highly significant differences among the genotypes for all quantitative traits, indicating substantial genetic variability. Grain yield per plant exhibited a strong positive association with biological yield per plant (r = 0.99) at both the genotypic and phenotypic levels. Path coefficient analysis identified biological yield per plant (0.92) as the most influential trait, with the highest positive direct effect on grain yield. Mahalanobis D² analysis grouped the genotypes into six distinct clusters, with the maximum inter-cluster distance observed between Clusters II and VI (44.21), indicating their potential value in hybridisation programmes. DUS characterisation revealed considerable qualitative variation that facilitated varietal identification and germplasm differentiation. The findings identified promising and genetically diverse germplasm accessions that may provide useful parental material for yield improvement and the broadening of the genetic base of future rice-breeding populations.
Dhamarasingu Gayathri, A. Pandey, Madduri Usha Sri et al.· International Journal of Pla...· 0 citations
Background: Yield improvement in hybrid rice depends on identifying component traits that are reliably associated with productivity.
Aims: This study aimed to determine the nature and magnitude of genotypic associations and to assess the direct and indirect effects of yield-attributing traits on single-plant yield in rice.
Study Design: The experimental material comprised 39 F₁ hybrids, three CMS lines (evaluated through their respective maintainer lines), 13 restorer lines, and four checks. The hybrids were developed during Kharif 2025 using a Line × Tester mating design and evaluated in a Randomised Block Design with three replications.
Place and Duration of Study: The hybrids were developed during Kharif 2025 and evaluated during Rabi 2025–2026 at the experimental farm of ICAR–Indian Institute of Rice Research, Hyderabad.
Methodology: Observations were recorded for eight traits: days to 50% flowering, plant height (cm), number of productive tillers, panicle length (cm), number of filled grains per panicle, spikelet fertility (%), thousand-grain weight (g), and single-plant yield (g).
Results: Among the traits studied, the number of productive tillers exhibited the highest positive correlation with single-plant yield (r = 0.72, P < 0.01), followed by plant height (r = 0.45, P < 0.01), panicle length (r = 0.34, P < 0.01), and days to 50% flowering (r = 0.29, P < 0.05). Path coefficient analysis revealed positive direct effects on single-plant yield through the number of productive tillers (0.66987), panicle length (0.14114), number of filled grains per panicle (0.13347), and plant height (0.09584), indicating their contribution to yield improvement.
Conclusion: Therefore, prioritising the number of productive tillers, panicle length, and number of filled grains per panicle as key selection criteria could facilitate the development of high-yielding hybrid rice cultivars and contribute to sustainable improvements in rice productivity.
C. Sankaran, Ch. Damodar Raju, K. Sruthi et al.· Journal of Advances in Biolo...· 0 citations
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.
Anwesha Dey, G. M. Lal, Shashank Mishra· International Journal of Pla...· 0 citations
Maize (Zea mays L.) is one of the most economically and nutritionally significant cereal crops globally, yet its productivity in India remains considerably below the world average, necessitating systematic genetic improvement through the exploitation of available germplasm diversity. The present study was undertaken to morphologically characterise and assess the phenotypic diversity of 184 maize inbred lines derived from three distinct germplasm sources (176 inbred lines and 8 local checks) evaluated during the rabi season of 2024–25 at the Experimental Research Farm, Central Agricultural University, Manipur, India, using an Augmented Block Design. Data were recorded for 23 morphological and agronomic traits encompassing phenological, vegetative, yield component and grain quality characteristics. Analysis of variance revealed highly significant genotypic differences for most traits. Phenotypic coefficient of variation (PCV) exceeded genotypic coefficient of variation (GCV) for all traits, with high heritability estimates recorded for most traits, indicating the predominance of additive genetic effects and the effectiveness of direct selection. Phenotypic correlation analysis identified cob weight, kernels per row, rows per cob and test weight as the most strongly associated traits with grain yield per plant. Principal Component Analysis extracted eight significant components with eigenvalues greater than 1.0, cumulatively explaining 76.57 % of the total phenotypic variation, with shelling percentage, kernel traits, plant architectural traits and leaf morphology emerging as the primary contributors across successive components. Hierarchical cluster analysis using grouped the 176 inbred lines into two distinct clusters comprising 66 and 118 genotypes respectively, with germplasm distributed across both clusters. Genotypes V2225-36, V2189-226 and V2225-44 were identified as top-yielding selections, while 118955, LMC-11 and 118449 emerged as promising early maturing donors. The identified superior and genetically divergent genotypes are recommended as elite parents for future hybrid breeding programmes targeting the agro-climatic conditions of northeastern India.
C. A. Himasira, K. Pramesh, S. Dayananda et al.· Plant Science Today· 0 citations
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