A novel selection model based on multivariate methods and arbitrary genetic parameters: a case study on tomato...

Area of Science:

• Plant breeding
• Quantitative genetics
• Biometrical genetics

Background:

• Selection is crucial for breeders to reduce population size and enhance success.
• Various selection methods exist, assessing superior genotypes based on traits like univariate, multivariate, phenotypic, and genotypic data.
• Mathematical calculations of trait importance rely on genetic makeup and parameters.

Purpose of the Study:

• To present a general model for multivariate selection.
• To enable selection for multiple traits, complex inheritance, large populations, segregating generations, and stress tolerance.
• To provide a tool for identifying suitable genotypes based on breeding objectives.

Main Methods:

• Developed a general model for multivariate selection based on biometrical concepts in four steps.
• Incorporated mathematical calculations of trait importance based on genetic makeup (degree of dominance/additive gene action) and genetic parameters.
• Provided a MATLAB script for practical application.

Main Results:

• The model allows simultaneous selection for multiple traits, including those with complex inheritance.
• It facilitates the identification of superior genotypes in large populations and segregating generations.
• The model aids in finding genotypes tolerant to environmental stresses.

Conclusions:

• The presented multivariate selection model is simple, precise, repeatable, and fast.
• It enables simultaneous improvement of several traits, enhancing breeding efficiency.
• The model, with its step-by-step case study and MATLAB script, is readily applicable by breeders.