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@article{197253,
        author = {Shubham Kumar and Varun Bansal and Shivani},
        title = {Creation of an Integrated Evaluation Algorithm to Genetic Divergence Analysis in Rice (Oryza sativa L.)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {9358-9363},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197253},
        abstract = {Appropriate crop development programs depend on accurate evaluation of genetic differentiation. Although more conventional statistical techniques, such as the principal component test and Mahalanobis D² test, are widely used, there has not been much work done to incorporate them into systematic computing programs in the subject of agriculture. In this work, a sophisticated algorithm for evaluating multivariate genetic divergence of rice (Oryza sativa L.) is presented and justified. Twenty-six rice genotypes were examined for morphological, yield, and quality characteristics in the field. The approach computes the objective genotype ranking and estimates the divergence by combining principal component extraction, cluster analysis, and path coefficient modelling into a single procedural chain. The results showed a considerable degree of variance among genotypes, and the harvest index, days to flowering, and spikelets per panicle all contributed significantly to overall divergence. The proposed evaluation approach enhances reproducibility, lessens the impact of computation, and helps with data-driven parent selection in breeding projects.},
        keywords = {Genetic divergence; Evaluation algorithm; Rice; Principal component analysis; Cluster analysis; Yield traits.},
        month = {April},
        }