Clonal Evaluation and Genetic Divergence Studies in Mulberry Genotypes
Manickavasagam Mithilasri, K. T. Parthiban, R. Kalpana, Shankar S.M.
Asian Research Journal of Agriculture · pp. 147–159 · Published 5 Apr 2024
10.9734/arja/2024/v17i2433Abstract
Aims: This study aims to evaluate the wood quality and leaf quality traits of selected mulberry clones and assess the genetic divergence among them, providing valuable insights for the development of superior genotypes with enhanced economic value for the sericulture and agroforestry sectors. Study design: Twenty-one genetic resources of mulberry were collected from various regions in India and evaluated through clonal test in a Row Column Design to assess growth attributes and genetic divergence. Place and Duration of Study: The study was conducted in India, and the systematic progeny test and clonal evaluation were carried out in Forest College and Research Institute, Mettupalayam during 2018-2022. Methodology: The selected clones were evaluated for growth attributes such as plant height, diameter at breast height (DBH), volume, number of branches, leaf length, leaf width, petiole length, number of leaves, and leaf area. Genetic divergence was estimated using D2 statistics, and clustering of clones was performed using the 'GENRES' statistical package. Results: The study identified several clones with significantly higher growth attributes, highlighting their potential for selection in breeding and cultivation programs. Variability and heritability studies indicated that volume exhibited the highest heritability, suggesting strong genetic control and potential for improvement. Conclusion: Clones MI-0718, MI-0807, and MI-0845 showed superior growth performance and genetic divergence, indicating their suitability for further breeding and improvement programs. The study provides insights into the genetic variability of mulberry clones and emphasizes selecting superior clones for enhancing wood volume and overall productivity.
Cited by 1
K. T. Parthiban, M. V. Jawahar Vishnu, S. Revathi · Wood and Fiber Science · 2025
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