Vol. 12, Issue 12 (2023)

Author(s):
Sanjyot Gaikwad, Dr. Ramesh Kunkerkar, Dr. SS Desai, Dr. RV Dhopavkar, Dr. JJ Kadam and Sanjay Misal

Abstract:
A fundamental statistical method that makes it simple to evaluate significant polygenic characters which are very important in plant breeding programme is multivariate analysis. In a compact family block design, the current experiment was carried out in Kharif 2022 using 33 finger millet germplasm accessions at the Education and Research farm, Department of Agriculture Botany, Dapoli, Dist. Ratnagiri. The purpose of the current study was to determine which genotypes produce the highest yield by evaluating the degree of genetic diversity analysis. In addition to recording observations for seventeen characters, a multivariate technique was used, and cluster analysis was performed. Based on Euclidean distance, the thirty-three genotypes were sorted into six different clusters. There was a significant amount of diversity in Cluster II, which had the greatest number of genotypes (Thirteen), followed by Cluster I (Nine), Cluster IV (six), Cluster III (Three), and Cluster V & VI (One each). The greatest grain yield inter-cluster distances were found between Cluster III and VI, then Cluster I and VI, Cluster V and VI, Cluster II and VI, and Cluster III and V. This suggests that there is significant diversity among these clusters, and that genotypes from these clusters could be used as possible parents for hybridization. The study found that among the thirty-three finger millet genotypes under investigation, there was a significant variation in grain yield per plant, which the major factor was contributing to genetic divergence. For the majority of the desirable characteristics, including the number of ear heads per plant, grain yield per plant, straw yield per plant, biological output per plant, and iron content, Cluster I had the highest maximum cluster means.