Study on advancement in bioinformatics for crop improvement: integrating genomics, phenomics, and machine learning

Abstract

Bioinformatics has emerged as a vital tool in agriculture, performing an important role in crop improvement and precision agriculture. This review study explores the applications of bioinformatics in these areas, highlighting the importance of next-generation sequencing (NGS) and third-generation sequencing technologies like PacBio and ONT. The integration of bioinformatics and genomics has revolutionized crop improvement strategies, facilitating the creation of crop varieties that are more suitable for evolving climates. The review emphasizes the creation of integrated crop databases for managing large-scale genotype and phenotype data and discusses the role of bioinformatics in precision agriculture for optimizing resource usage and minimizing environmental impact. Multiomics technologies are highlighted for gaining insights into plant biology and facilitating informed decisions in crop improvement. Machine learning algorithms play a prominent role in interpreting diverse and complex datasets generated by imaging or sequencing, aiding in efficient plant phenotyping and the identification of associations between DNA sequences and traits. The review concludes by emphasizing the importance of collaboration, data integration, and the potential of bioinformatics in advancing agriculture.