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P K Bhaumik1, M K Sinha, S P Banerjee

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Researchers screened 10 rice strains using the D(2) statistic, identifying strain D as superior. The number of grains per panicle significantly influenced strain grouping and relatedness, aiding in selecting high-yielding varieties.

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Area of Science:

  • Agricultural Science
  • Genetics and Plant Breeding
  • Biometrics

Background:

  • Selecting superior crop varieties is crucial for agricultural productivity.
  • Mahalanobis D(2) statistic is a valuable tool for multivariate analysis in crop improvement.
  • Understanding genetic diversity and relationships among strains aids breeding programs.

Purpose of the Study:

  • To screen and identify superior rice (Oryza sativa) strains from ten diverse types.
  • To analyze genetic divergence and relationships among the selected rice strains using the D(2) statistic.
  • To group strains based on their genetic distance and identify potential breeding crosses.

Main Methods:

  • Experiment conducted in a randomized block design with three replications.
  • Observations recorded on plant height, heading duration, tillers, grain number per panicle, yield per plant, and 100-grain weight.
  • Mahalanobis D(2) statistic employed for multivariate analysis and strain clustering.

Main Results:

  • All recorded observations were significant at the 1% level.
  • The number of grains per panicle contributed most significantly to the D(2) values.
  • Ten strains were grouped into four clusters (A, B, C, D), with Cluster B containing six strains.
  • Strain D was identified as the best performer, followed by strains in clusters B, C, and A.

Conclusions:

  • The D(2) statistic effectively differentiated and grouped rice strains based on agronomic traits.
  • Strain D demonstrated superior performance, indicating its potential for cultivation or further breeding.
  • The study identified potential crosses and highlighted the importance of grain number per panicle in strain evaluation.