http://ir.lib.ruh.ac.lk/handle/iruor/7468 2026-04-26T16:25:39Z http://ir.lib.ruh.ac.lk/handle/iruor/20842 Root architectural traits and their contribution to yield in f₂ populations of selected rice crosses under contrasting soil catena conditions Millawithanachchi, M.C.; Dilshani, E.K.C.; Pinthujan, P.; Kumari, M.G.N.R. Rice yields in Sri Lanka’s Wet Zone are frequently constrained by soil and drainage limitations, yet root traits remain underutilized in breeding programs. This study evaluated four F₂ populations of rice crosses, their parents, and two check varieties at the Rice Research Station, Labuduwa, under upper and lower catena positions to evaluate genotype × environment effects under contrasting drainage conditions and to (i) compare root and shoot morphological traits and (ii) quantify associations between root traits and yield components. Plot-level means were analyzed using a two-way model with Cross and Catena effects, and significant Cross × Catena interactions were detected for several traits. Across environments, Crosses 2 and 4 exhibited superior root architecture, characterized by greater root zone width, number of roots, root strength, root volume, and root dry weight, along with competitive yield components. Moderate to high phenotypic and genotypic coefficients of variation for key root and yield traits indicated substantial scope for selection. False discovery rate–controlled correlation analysis revealed positive associations of root zone width, number of roots, root strength, and root volume with effective tiller number, shoot biomass, and total panicle weight. These findings demonstrate the value of targeted selection for root traits to enhance yield stability under contrasting drainage conditions in the Wet Zone of Sri Lanka. 2026-01-01T00:00:00Z http://ir.lib.ruh.ac.lk/handle/iruor/20841 Exploring morphological traits for enhanced yield potential in pakistani rice Farooq, Ayesha; Ali, Muhammad; Farah, Khan; Shaheen, Shabnum; Ratnasekera, Disna; Ahmad, Shahbaz; Xu, Zhiyong; Mubashar, Urooj; Ashfaq, Muhammad This study evaluated phenotypic variability among 14 selected rice (Oryza sativa L.) varieties using 16 quantitative morphological and physiological traits. Analysis of Variance (ANOVA) revealed significant differences (p < 0.05) across all traits, with coefficients of variation ranging from moderate to high, indicating substantial diversity. Physiological parameters measured at the reproductive stage, including photosynthetic and gas exchange traits, exhibited significant genotypic effects, while morphological descriptors reflected clear varietal differentiation despite potential environmental influences. Correlation analysis identified key trait associations relevant for yield improvement, highlighting their utility in breeding selection. Principal Component Analysis (PCA) revealed that the first five components (eigenvalues greater than 1) accounted for 81.8% of the total variance, with significant contributions from yield and phenological traits. Cluster analysis based on standardized data grouped the varieties into two major clusters, separating highly similar subgroups and identifying the most divergent pair—Basmati 2000 and Kisan Basmati. These findings demonstrate substantial phenotypic and genotypic divergence within the germplasm, providing valuable parental combinations for breeding programs that target yield potential and environmental adaptation. 2025-01-01T00:00:00Z http://ir.lib.ruh.ac.lk/handle/iruor/20840 Optimized genotyping-by-sequencing for high-resolution SNP discovery in rice (Oryza sativa L.) Farooq, Ayesha; Ali, Muhammad; Asrar, Muhammad; Chatham, Muhammad Bilal; Ahmad, Shahbaz; Shaheen, Shabnum; Ratnasekera, Disna; Xu, Zhiyong; Mahmood, Sammina; Ali, Qurban; Ashfaq, Muhammad; Khan, Farah Rice (Oryza sativa L.) is a staple crop vital to food security worldwide, particularly in South Asia. Enhancing its yield potential and disease resistance through genomic tools is a pressing necessity for sustainable agriculture. This study aimed to identify genome-wide Single Nucleotide Polymorphisms (SNPs) associated with key agronomic traits in Pakistani rice germplasm using Genotyping-By-Se quencing (GBS) and Genome-Wide Association Studies (GWAS). Fourteen diverse rice varieties were genotyped using ApeKI-based GBS, generating high-quality sequencing data. Following quality filtering and alignment to the MSU v6.0 Nipponbare reference genome, a total of 208 highly significant SNPs (-log₁₀P ≥ 4) were identified. GWAS was conducted using a mixed linear model incorporating pop ulation structure and kinship, while STRUCTURE analysis was employed to assess subpopulation stratification. Significant associations were identified for fifteen agronomic and yield-related traits, including days to flowering, plant height, grain weight, and disease resistance. Key pleiotropic loci such as OsGRb06041, OsGRg05186, and OsGRb22352 were linked with multiple traits. Population structure anal ysis revealed two main genetic clusters (K=2), reflecting the divergence between traditional basmati types and improved cultivars. This study delivers a robust genomic resource for Marker-Assisted Selection (MAS) and future functional studies in rice. It highlights specific genomic regions with potential utility in breeding programs aimed at enhancing productivity, resilience, and quality traits in Pakistani rice germplasm. 2025-01-01T00:00:00Z http://ir.lib.ruh.ac.lk/handle/iruor/20839 Regional projections and sampling strategies for the global germplasm resources collection of Oryza rufipogon Griff. Wang, Kai; Long, Jinhua; Lei, Jizhou; Liang, Yuntao; Ratnasekera, Disna; Qian, Qian; Zheng, Xiaoming Oryza rufipogon Griff., the wild progenitor of cultivated rice, contains essential genetic resources for rice improvement and global food security. Preserving the integrity of its germplasm has therefore become a critical conservation priority. In this study, we applied GIS based spatial analysis and the MaxEnt model, integrating global occurrence data of O. rufipogon with 20 environmental variables to predict suitable habitats during the Last Interglacial (LIG, 130 to 115 ka before present [BP]), the Last Glacial Maximum (LGM, 26–19 ka BP), and the present. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), and spatial clustering was conducted based on the contributions of Journal Pre-proof environmental factors. The results identified three current core ecological zones: the tropical monsoon region of Southeast and East Asia; the tropical grassland–monsoon region of South Asia; and the tropical rainforest region spanning northern Australia, the Philippines, and Indonesia. During the LGM, colder and drier climates led to a more fragmented distribution, whereas the LIG showed a clearer expansion into broader tropical and subtropical zones. Priority regions for O. rufipogon germplasm collection were identified across Southeast, East, and South Asia, as well as northern Australia. This study proposes a targeted sampling strategy that incorporates elevation, soil properties, and water availability, providing a solid scientific basis for global O. rufipogon surveys and the conservation of high-quality germplasm resources. 2025-01-01T00:00:00Z