Modelling illustrates that genomic selection provides new opportunities for intercrop breeding

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 optimise 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 early stages of a breeding program and to minimize the generation interval.

Can we harness digital technologies and physiology to hasten genetic gain in U.S. maize breeding?

“…Continued integration of gap analysis methodologies with CGM-WGP could thus provide insight into specific targets for improvement of yield and yield stability across environmental gradients in the TPE. Considering the farming system context can provide a productive next methodological step to realize crop improvement gains through changes in root systems (Thorup-Kristensen and Kirkegaard, 2016; Bančič et al, 2021), which so far have been elusive in maize (Reyes et al, 2015; Messina et al, 2020a).…”

Simulation‐based decision‐making and implementation of tools in hybrid crop breeding pipelines

“…Modern breeding programs require efficient breeding approaches that utilize the advancements in breeding to achieve higher performance in terms of genetic gains. The evaluation of breeding schemes through simulation has opened a new window of possibilities to examine these advancements and inferences to be made about the right strategy to implement (Allier et al, 2019a;Bančič et al, 2021;Lara et al, 2022;Silva et al, 2021). For instance, our results demonstrate that scenarios that incorporate genomic selection are superior for dealing with situations where the G×E interaction is a factor that introduces noise in the selection process.…”

Genomic and phenotypic characterization of finger millet indicates a complex diversification history

“…S2). The traits we measured included features of morphology, physiology and yield that are important for crop production and the integration of finger millet in mixed crop farming systems (Dawson et al, 2019), including in intercrop systems (Brooker et al, 2015), that are of particular interest in breeding research (Bančič et al, 2021).…”

“…Diversifying crop production is an important global objective to address human and environmental health concerns, such as malnutrition and the use of intensive unsustainable monoculture production systems (Bančič et al, 2021;von Grebmer et al, 2014). To achieve diversification, we need to increase focus on under-researched crops, also known as orphan crops.…”