Aug 2026· Jagannath University Journal of Science· Vol 12· 0 citations· 72 references
TL;DR
This review comprehensively discusses the applications of plant bioinformatics in crop improvement and stress tolerance, highlighting major computational approaches, databases, tools, and emerging trends.
Abstract
Plant bioinformatics has emerged as a cornerstone of modern plant science by enabling the large-scale analysis and interpretation of genomic and post-genomic data for crop improvement. The rapid advancement of high-throughput sequencing technologies, coupled with powerful computational tools, has transformed traditional breeding approaches into data-driven strategies. Bioinformatics facilitates the identification of genes, quantitative trait loci (QTLs), regulatory networks, and molecular markers associated with agronomically important traits, particularly stress tolerance. Abiotic stresses such as drought, salinity, heat, and cold, as well as biotic stresses caused by pathogens and pests, significantly limit crop productivity worldwide. Integrating bioinformatics with genomics, transcriptomics, proteomics, metabolomics, and phenomics has enabled a deeper understanding of plant stress responses and accelerated the development of resilient crop varieties. This review comprehensively discusses the applications of plant bioinformatics in crop improvement and stress tolerance, highlighting major computational approaches, databases, tools, and emerging trends. The challenges and prospects of bioinformatics-driven plant breeding are also critically examined.
Jagannath University Journal of Science, Volume 12, Number 1, Jun. 2025, pp. 177−187
By combining genomic data with precision breeding techniques, researchers are developing crops that are better adapted to a growing population and a changing climate, positioning the integration of molecular breeding and bioinformatics as a central pillar of future global food security.
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This review critically synthesizes current knowledge of plant stress biology with recent advances in genomics‐assisted breeding, phenomics, genome editing, predictive breeding, and climate‐smart agronomic management within a unified framework for climate‐resilient crop improvement.
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