Literature DB >> 33633761

Modeling Illustrates That Genomic Selection Provides New Opportunities for Intercrop Breeding.

Jon Bančič1,2, Christian R Werner1, R Chris Gaynor1, Gregor Gorjanc1, Damaris A Odeny3, Henry F Ojulong3, Ian K Dawson2, Stephen P Hoad2, John M Hickey1.   

Abstract

Intercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimize farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in the early stages of a breeding program and to minimize the generation interval.
Copyright © 2021 Bančič, Werner, Gaynor, Gorjanc, Odeny, Ojulong, Dawson, Hoad and Hickey.

Entities:  

Keywords:  genomic selection; intercrop breeding program designs; intercropping ability; stochastic simulation; sustainable agriculture

Year:  2021        PMID: 33633761      PMCID: PMC7902002          DOI: 10.3389/fpls.2021.605172

Source DB:  PubMed          Journal:  Front Plant Sci        ISSN: 1664-462X            Impact factor:   5.753


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