Opportunity, Challenges and Approaches of Multivariate Diversity Analysis for Quantitative Traits of Pulse Crops: A Review

Abstract

Plant breeding faces the significant challenge of feeding a growing global population on increasingly limited arable land. While advancements have been made in modern breeding practices, the narrow genetic base of many cultivated crops has created vulnerability in their genetic makeup. This underscores the necessity for a shift in plant breeding approaches, focusing on expanding the genetic resources utilized. Genetic diversity is widely recognized as a key factor in ensuring food and nutritional security. A deeper understanding of genetic variation will guide the conservation of essential resources. Multivariate techniques are particularly valuable in analyzing the relationships between variables, enabling researchers to explore these connections in a more expansive manner. By incorporating additional variables, methods like cross-tabulation, partial correlation, and multiple regression can clarify the nature of associations. D2 statistics and Principal Component Analysis (PCA) are commonly used to interpret morphological data due to their ease of interpretation. R software is a valuable tool in statistical analysis and data visualization, thanks to its adaptability. The findings from these analyses can inform various breeding strategies, including transgressive breeding, heterosis breeding, and the introduction of foreign genes to enhance specific traits.