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The area under the function: an index for selecting desirable genotypes.

C M Hernandez1, J Crossa, A Castillo

  • 1Universidad de Colima, Apdo. Postal 36, Tecomán, Colima, México.

TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik
|November 6, 2013
PubMed
Summary
This summary is machine-generated.

A new desirability index (D i) combines genotype mean yield and regression coefficient for plant breeding. This index aids in selecting superior genotypes by integrating yield potential and stability across diverse environments.

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Area of Science:

  • Agricultural Science
  • Plant Breeding
  • Genetics

Background:

  • Linear regression is common for selecting high-yielding, stable genotypes across environments.
  • Using mean yield and regression coefficient separately complicates genotype selection decisions.
  • High-yielding, less-stable genotypes often compete with low-yielding, stable ones.

Purpose of the Study:

  • To propose a unified desirability index (D i) integrating mean yield and regression coefficient.
  • To simplify the selection of superior genotypes in multi-environment trials.
  • To provide a more effective tool for plant breeders.

Main Methods:

  • Developed a desirability index (D i) defined as the area under the linear regression function.
  • Calculated D i using genotype mean yield and regression coefficient across environments.
  • Applied the D i to maize and wheat multi-environment yield trials.

Main Results:

  • The desirability index (D i) effectively integrates genotype mean yield and stability.
  • For symmetric trials, D i is influenced by mean yield; for asymmetric trials, the slope is influential.
  • In maize trials, three genotypes ranked higher with D i than with mean yield alone.
  • Wheat genotype rankings differed significantly between mean yield and D i.

Conclusions:

  • The desirability index (D i) offers a superior method for selecting high-yielding and stable genotypes.
  • D i aids breeders in making more informed decisions, especially when yield and stability conflict.
  • This unified index improves genotype evaluation in multi-environment breeding programs.