Genetic divergence and cluster analysis of finger millet (Eleusine coracana L. Gaertn) genotypes based on multivariate traits

The present study assessed genetic divergence among 84 finger millet (Eleusine coracana L. Gaertn) genotypes using Mahalanobis’ D² statistics, pooled over two years at Jagdalpur. The genotypes were grouped into six distinct clusters, indicating substantial genetic variability. Cluster IV had the highest number of genotypes (21), followed by Cluster II (19) and Cluster I and VI (12 each), suggesting a wide genetic base. The highest intra-cluster distance was observed in Cluster II (15.38), while the maximum inter-cluster divergence was between Cluster II and Cluster VI (40.87), highlighting their potential as parents for hybridization to exploit heterosis.Cluster mean analysis revealed that Cluster VI exhibited the highest grain yield (4.40 g/plant), along with superior performance in ear weight, biological yield, grain diameter, and harvest index, making it a promising group for yield improvement. Cluster II also recorded high grain yield (4.00 g), finger number, and harvest index. Cluster III showed the earliest maturity (100.47 days), indicating its suitability for breeding early-maturing varieties. Cluster IV stood out for tallest plants and longest fingers, while Cluster V had the highest number of fingers per ear and grain diameter. The observed inter-and intra-cluster diversity provides valuable insights for selecting genetically divergent parents to develop high-yielding, early-maturing, and nutritionally rich finger millet cultivars.

Authors

Publication Details

Journal
International Journal of Advanced Biochemistry Research
Published
2025-01-01
DOI
https://doi.org/10.33545/26174693.2025.v9.i8sh.5195
Primary Topic
Leaf Properties and Growth Measurement
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic divergence and cluster analysis of finger millet (Eleusine coracana L. Gaertn) genotypes based on multivariate traits

Nanden Mehta, JL Salam, Ritu Saxena, Raja Ram Kanwer
International Journal of Advanced Biochemistry Research
Leaf Properties and Growth Measurement
article

Genetic divergence and cluster analysis of finger millet (Eleusine coracana L. Gaertn) genotypes based on multivariate traits

Nanden Mehta, JL Salam, Ritu Saxena, Raja Ram Kanwer
article en

Abstract

The present study assessed genetic divergence among 84 finger millet (Eleusine coracana L. Gaertn) genotypes using Mahalanobis’ D² statistics, pooled over two years at Jagdalpur. The genotypes were grouped into six distinct clusters, indicating substantial genetic variability. Cluster IV had the highest number of genotypes (21), followed by Cluster II (19) and Cluster I and VI (12 each), suggesting a wide genetic base. The highest intra-cluster distance was observed in Cluster II (15.38), while the maximum inter-cluster divergence was between Cluster II and Cluster VI (40.87), highlighting their potential as parents for hybridization to exploit heterosis.Cluster mean analysis revealed that Cluster VI exhibited the highest grain yield (4.40 g/plant), along with superior performance in ear weight, biological yield, grain diameter, and harvest index, making it a promising group for yield improvement. Cluster II also recorded high grain yield (4.00 g), finger number, and harvest index. Cluster III showed the earliest maturity (100.47 days), indicating its suitability for breeding early-maturing varieties. Cluster IV stood out for tallest plants and longest fingers, while Cluster V had the highest number of fingers per ear and grain diameter. The observed inter-and intra-cluster diversity provides valuable insights for selecting genetically divergent parents to develop high-yielding, early-maturing, and nutritionally rich finger millet cultivars.

International Journal of Advanced Biochemistry ResearchVol. 9(8S)
Zero hunger
Openalex Percentile: Top 85%
Leaf Properties and Growth Measurement
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.