International Journal of Science, Engineering and TechnologyAuthors: D. Ramesh, Assistant Professor
Abstract: Contemporary botanical research integrates genomic, phenotypic, and environmental data across unprecedented spatial and taxonomic scales. This paper synthesizes recent advances in biostatistical methods applied to plant science, emphasizing their interconnected use rather than isolated application. We systematically review four methodological domains: (1) phylogenetic comparative methods, including relaxed molecular clocks and network inference for divergence timing; (2) genome-wide association studies (GWAS) and quantitative trait locus (QTL) mapping, with innovations in population structure handling, meta-analysis, and machine learning; (3) adaptive evolution inference via genome-environment association (GEA) and quantitative genetic approaches; and (4) spatial statistics and species distribution modeling, including joint and deep-learning-based frameworks. Drawing on 30+ peer-reviewed studies from 2024–2026, we propose an integrative analysis pipeline that bridges these methods. This framework enables researchers to move from pattern description to causal inference in plant evolutionary ecology, biodiversity conservation, and crop breeding.
DOI: http://doi.org/10.5281/zenodo.20584468
