Principal Component and Cluster Analysis on Eating and Cooking Quality Parameters in Rice (Oryza sativa L.) Germplasm

Author: Hari Prasanth P., Agalya Jasmin S., Ramchander Selvaraj, Dinesh Kumar P., Devasena N., Sharmili K. and Wilson D.

Download PDF

Abstract

Eating and cooking quality traits in rice are complex traits such as grain size, shape, and texture of the cooked kernels parameters. These traits are influenced by various factors including genetic makeup, amylose content, gelatinization temperature, and processing techniques. Improving the grain quality parameters, especially the eating and cooking quality of rice has wide-ranging implications, including enhancing market competitiveness, increasing consumer satisfaction, and addressing nutritional needs. It also contributes to sustainable agriculture practices by optimizing resource utilization and reducing food waste. The present study was conducted to assess the divergence of fifty-five rice genotypes based on eight-grain quality traits. The results of principal component analysis (PCA) revealed that the four principal components (PC) accounted for approximately 82% of the total variability observed among the fifty-five rice genotypes. By employing Mahalanobis D2 analysis, all fifty-five genotypes were categorized into nine clusters. The largest inter-cluster distance was observed between Cluster VII and Cluster VIII (36.67), followed by Cluster V and Cluster IX (34.75), and Cluster V and Cluster VI (32.78), indicating the presence of significant genetic diversity among the genotypes. The genotypes belonging to Cluster VII to Cluster VIII, Cluster V and Cluster IX, and Cluster V and Cluster VI can be considered for hybridization purposes, as they exhibit higher mean values for quality traits and greater inter-cluster distance, indicating increased diversity.

Keywords

Quality traits, Principal Component, Cluster and Genotypes

Conclusion

In this study, fifty-five rice genotypes were analysed for their cooking quality traits and were grouped into nine clusters based on their percent contribution to the traits. GT and AC were found to be the major contributors to genetic diversity. High inter-cluster distances between some clusters indicated higher genetic diversity and potential for future breeding programs. Cluster VIII was found to be the best-performing cluster, and three genotypes (KRG49, KRG55, and KRG56) were identified as promising candidates for improving amylose content. Varieties with intermediate amylose contents are typically favored in Indian circumstances because they appear dry and fluffy and maintain their soft feel even after cooling. In conclusion, these findings have practical implications for rice breeding programs aimed at developing high-quality rice varieties.

References

-

How to cite this article

Hari Prasanth P., Agalya Jasmin S., Ramchander Selvaraj, Dinesh Kumar P., Devasena N., Sharmili K. and Wilson D. (2023). Principal Component and Cluster Analysis on Eating and Cooking Quality Parameters in Rice (Oryza sativa L.) Germplasm. Biological Forum – An International Journal, 15(5): 382-388.