Jul 2026· International Journal of Computational and Biological Sciences· 0 citations
TL;DR
A comprehensive analysis of the methodological, theoretical, and practical frameworks underlying molecular-marker applications in modern plant breeding is provided, offering a thorough perspective on how molecular biotechnology can be optimized to ensure future global food security.
Abstract
The integration of molecular markers into agricultural biotechnology has fundamentally transformed crop breeding paradigms, particularly concerning disease-resistance screening and the identification of complex agronomic traits. Global agricultural systems face unprecedented challenges from biotic stressors, shifting climatic patterns, and the continuous evolution of pathogenic microorganisms, thereby necessitating the rapid development of resilient crop varieties. This paper provides a comprehensive analysis of the methodological, theoretical, and practical frameworks underlying molecular-marker applications in modern plant breeding. By exploring the historical evolution from classical phenotypic selection to advanced genomics-assisted breeding, the discussion elucidates the mechanisms through which single nucleotide polymorphisms and simple sequence repeats facilitate the precise localization of quantitative trait loci. Furthermore, the paper details the analytical pipelines required for high-throughput genotyping, marker-assisted selection, and genome-wide association studies, highlighting their respective impacts on selection efficiency and cost reduction in crop improvement programs. An evaluation of contemporary empirical data reveals that integrating multi-omic approaches with established molecular markers significantly enhances the accuracy of predicting disease resistance across diverse agricultural panels. Ultimately, this research synthesizes current technological advancements and methodological constraints, offering a thorough perspective on how molecular biotechnology can be optimized to ensure future global food security.
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