Rice Genomics and Genetics 2024, Vol.15, No.3, 142-152 http://cropscipublisher.com/index.php/rgg 151 Guo L., and Ye G., 2014, Use of major quantitative trait loci to improve grain yield of rice, Rice Science, 21(2): 65-82. https://doi.org/10.1016/S1672-6308(13)60174-2 Huang X., Qian Q., Liu Z., Sun H., He S., Luo D., Xia G., Chu C., Li J., and Fu X., 2009, Natural variation at the DEP1 locus enhances grain yield in rice, Nature Genetics, 41(4): 494-497. https://doi.org/10.1038/ng.352 Inthapanya P., Sihavong P., Sihathep V., Chanphengsay M., Fukai S., and Basnayake J., 2000, Genotype differences in nutrient uptake and utilisation for grain yield production of rainfed lowland rice under fertilised and non-fertilised conditions, Field Crops Research, 65(1): 57-68. https://doi.org/10.1016/S0378-4290(99)00070-2 Jayaprakash T., Reddy T., Babu V., and Bhave M., 2017, Association analysis of protein and yield related traits in f3 population of rice (Oryza sativa L.) crosses, International Journal of Current Microbiology and Applied Sciences, 6: 2476-2485. https://doi.org/10.20546/IJCMAS.2017.608.293 Jewel Z., Ali J., Mahender A., Hernandez, J., Pang Y., and Li Z., 2019, Identification of quantitative trait loci associated with nutrient use efficiency traits, using SNP markers in an early backcross population of rice (Oryza sativaL.), International Journal of Molecular Sciences, 20(4): 900. https://doi.org/10.3390/ijms20040900 Li B., Liu H., Zhang Y., Kang T., Zhang L., Tong J., Xiao L., and Zhang H., 2013, Constitutive expression of cell wall invertase genes increases grain yield and starch content in maize, Plant Biotechnology Journal, 11(9): 1080-1091. https://doi.org/10.1111/pbi.12102 Li R., Li M., Ashraf U., Liu S., and Zhang J., 2019, Exploring the relationships between yield and yield-related traits for rice varieties released in China from 1978 to 2017, Frontiers in Plant Science, 10: 543. https://doi.org/10.3389/fpls.2019.00543 Li S.L., Zheng H.Y., and Wang L., 2020, Application and prospect of gene editing technology in crop breeding, Biotechnology Bulletin, 36(11): 209-221. Mamata K., Rajanna M., and Savita S., 2018, Assessment of genetic parameters for yield and its related traits in f2 populations involving traditional varieties of rice (Oryza sativa L.), International Journal of Current Microbiology and Applied Sciences, 7(1): 2210-2217. https://doi.org/10.20546/IJCMAS.2018.701.266 Matsubara K., Yamamoto E., Kobayashi N., Ishii T., Tanaka J., Tsunematsu H., Yoshinaga S., Matsumura O., Yonemaru J., Mizobuchi R., Yamamoto T., Kato H., and Yano M., 2016, Improvement of rice biomass yield through QTL-based selection, PLoS One, 11(3): e0151830. https://doi.org/10.1371/journal.pone.0151830 Meena D., Kumar M.S., and Soni R., 2023, Assessment of genetic diversity for grain yield in rice (Oryza sativa L.) genotypes under humid south eastern plain of Rajasthan, India, International Journal of Plant and Soil Science, 35(18): 971-977. https://doi.org/10.9734/ijpss/2023/v35i183361 Munns R., Tester M., 2008, Mechanisms of salinity tolerance, Annu Rev. Plant Biol., 59(1): 651-681. Naik S., Raman A., Nagamallika M., Venkateshwarlu C., Singh S., Kumar S., Singh S., Ahmed H., Das S., Prasad K., Izhar T., Mandal N., Singh N., Yadav S., Reinke R., Swamy B., Virk P., and Kumar A., 2020, Genotype×Environment interactions for grain iron and zinc content in rice, Journal of the Science of Food and Agriculture, 100(11): 4150-4164. https://doi.org/10.1002/jsfa.10454 Perween S., Kumar A., Singh S., Endra S., Kumar M., and Kumar R., 2020, Genetic variability parameters for yield and yield related traits in rice (Oryza sativa L.) under irrigated and drought stress condition, International Journal of Current Microbiology and Applied Sciences, 9(2): 1137-1143. https://doi.org/10.20546/ijcmas.2020.902.133 Pujar M., Pujar M., Govindaraj M., Gangaprasad S., Kanatti A., and Shivade H., 2020, Genetic variation and diversity for grain iron, zinc, protein and agronomic traits in advanced breeding lines of pearl millet (Pennisetum glaucumL.) for biofortification breeding, Genetic Resources and Crop Evolution, 67: 2009-2022. https://doi.org/10.1007/s10722-020-00956-x Rana N., Rahim M., Kaur G., Bansal R., Kumawat S., Roy J., Deshmukh R., Sonah H., and Sharma T., 2019, Applications and challenges for efficient exploration of omics interventions for the enhancement of nutritional quality in rice (Oryza sativa L.), Critical Reviews in Food Science and Nutrition, 60(19): 3304-3320. https://doi.org/10.1080/10408398.2019.1685454 Sakamoto T., and Matsuoka M., 2008, Identifying and exploiting grain yield genes in rice, Current Opinion in Plant Biology, 11(2): 209-214. https://doi.org/10.1016/j.pbi.2008.01.009 Samonte S., Wilson L., Medley J., Pinson S., McClung A., and Lales J., 2006, Nitrogen utilization efficiency: relationships with grain yield, grain protein, and yield-related traits in rice, Agronomy Journal, 98(1): 168-176. https://doi.org/10.2134/AGRONJ2005.0180 Sanjeeva Rao D., Neeraja C.N., Madhu Babu P., Nirmala B., Suman K., Rao L.V.S., Surekha K., Raghu P., Longvah T., Surendra P., Kumar R., Babu V.R., and Voleti S.R., 2020, Zinc biofortified rice varieties: challenges, possibilities, and progress in India, Front Nutr., 7: 26. Singh U., Dixit S., Alam S., Yadav S., Prasanth V., Singh A., Venkateshwarlu C., Abbai R., Vipparla A., Badri J., Ram T., Prasad M., Laha G., Singh V., and Kumar A., 2021, Marker assisted forward breeding to develop a drought, bacterial leaf blight, and blast-resistant rice cultivar, The Plant Genome, 15(1): e20170. https://doi.org/10.1002/tpg2.20170
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