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<p>The current study evaluated the genetic divergence and molecular diversity among 50 finger millet (<i>Eleusine coracana</i> (L.) Gaertn.) genotypes to identify potential candidates for crop improvement. Using Mahalanobis’ D<sup>2</sup> statistics, significant variability was observed across 19 traits, with Tocher's method grouping the genotypes into nine clusters. Cluster I was the largest, while four clusters comprised single genotypes, indicating high genetic uniqueness. Intra- and inter-cluster distances revealed substantial diversity, with the greatest inter-cluster distance between Clusters VIII and V, suggesting potential for heterosis in hybridization programs. Cluster V showed superior performance in traits such as grain yield, days to maturity, and total phenol content, making it a valuable candidate for breeding. Phenol content (36.24%), iron content (23.84%), and antioxidant activity (16.16%) were key contributors to genetic divergence. Genotypic correlation analysis revealed significant positive associations of grain yield with number of fingers per ear-head and harvest index. Path coefficient analysis identified harvest index and straw yield per plant as the major contributors to grain yield, exhibiting the highest positive direct effects, indicating their importance as selection criteria. Using SSR and SRAP markers, molecular diversity analysis&#xa0;revealed a 93.75% polymorphism rate for SSR markers and an 86.58% rate for SRAP markers, with SSR markers showing higher genetic variability (PIC 0.434). The largest genetic distance (0.74) between PCGF-13 and FMA-45 highlighted their potential for bi-parental mapping populations. Overall, this combined analysis offers valuable insights for finger millet breeding programs by emphasizing the importance of selecting diverse parental lines to enhance complex traits like yield and nutritional content. This article aligns with SDG 2 (Zero Hunger) of the UN Agenda for Sustainable Development.</p>

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Integrating path analysis and molecular markers to understand genetic diversity in finger millet, Eleusine coracana (L.) Gaertn.

  • 期刊论文

  • 发表日期：

    2026年5月5日

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  • Mihir A. Hansalia,
  • Vikas Pali,
  • Amar A. Sakure,
  • Sushil Kumar,
  • Dinesh J. Parmar,
  • Mihir M. Pandya,
  • Dinesh Joshi

摘要

The current study evaluated the genetic divergence and molecular diversity among 50 finger millet (Eleusine coracana (L.) Gaertn.) genotypes to identify potential candidates for crop improvement. Using Mahalanobis’ D2 statistics, significant variability was observed across 19 traits, with Tocher's method grouping the genotypes into nine clusters. Cluster I was the largest, while four clusters comprised single genotypes, indicating high genetic uniqueness. Intra- and inter-cluster distances revealed substantial diversity, with the greatest inter-cluster distance between Clusters VIII and V, suggesting potential for heterosis in hybridization programs. Cluster V showed superior performance in traits such as grain yield, days to maturity, and total phenol content, making it a valuable candidate for breeding. Phenol content (36.24%), iron content (23.84%), and antioxidant activity (16.16%) were key contributors to genetic divergence. Genotypic correlation analysis revealed significant positive associations of grain yield with number of fingers per ear-head and harvest index. Path coefficient analysis identified harvest index and straw yield per plant as the major contributors to grain yield, exhibiting the highest positive direct effects, indicating their importance as selection criteria. Using SSR and SRAP markers, molecular diversity analysis revealed a 93.75% polymorphism rate for SSR markers and an 86.58% rate for SRAP markers, with SSR markers showing higher genetic variability (PIC 0.434). The largest genetic distance (0.74) between PCGF-13 and FMA-45 highlighted their potential for bi-parental mapping populations. Overall, this combined analysis offers valuable insights for finger millet breeding programs by emphasizing the importance of selecting diverse parental lines to enhance complex traits like yield and nutritional content. This article aligns with SDG 2 (Zero Hunger) of the UN Agenda for Sustainable Development.