Image-based phenomic prediction can provide valuable decision support in wheat breeding

Abstract

Traditionally, breeders' selection decisions in early generations are largely based on visual observations in the field. With the advent of affordable genome sequencing and high-throughput phenotyping technologies, enhancing breeders' ratings with such information became attractive. In this research, it is hypothesized that GxE interactions of secondary traits (i.e., growth dynamics' traits) are less complex than those of related target traits (e.g., yield). Thus, phenomic selection (PS) may allow selecting for genotypes with beneficial response-pattern in a defined population of environments. A set of 45 winter wheat varieties was grown at five year-sites and analyzed with linear and factor-analytic (FA) mixed models to estimate GxE interactions of secondary and target traits. The dynamic development of drone-derived plant height, leaf area and tiller density estimations was used to estimate the timing of key stages, quantities at defined time points, and temperature dose-response curve parameters. Most of these secondary traits and grain protein content showed little GxE interactions. In contrast, the modeling of GxE for yield required a FA model with two factors. A trained PS model predicted overall yield performance, yield stability and grain protein content with correlations of 0.41, 0.22 and 0.34. While these accuracies are modest and do not outperform well-trained GS models, PS additionally provided insights into the physiological basis of target traits. An ideotype was identified that potentially avoids the negative pleiotropic effects between yield and protein content.

High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase

“…Hence, temperature dose-response parameters represent robust basic physiological traits if monitored in multi-year trials. Roth et al (2022a) could show that such basic physiological traits allow the phenomic prediction of yield, yield stability and protein content for a Swiss elite winter wheat set. The reported heritabilities and genetic correlations of this study of phenology and temperature response traits are in accordance with the ones reported in Roth et al (2022a), raising hope that similar methods will also work on less diverse genotype sets.…”

Mixing things up! Identifying early diversity benefits and facilitating the development of improved variety mixtures with high throughput field phenotyping

“…Furthermore, in order to gain representative data, plot size could be varied according to the respective trait (Rebetzke et al., 2014). Estimation of yield is usually done in relatively large plots (1.25 × 6 m) while other traits such as canopy cover, plant height or plant indices can be readily measured in micro‐plots (e.g., 1.25 × 1.75 m) or even single rows (Anderegg et al., 2020, 2021; Kronenberg et al., 2021; Roth et al., 2023). Using micro‐plots or single rows, the number of evaluation units on a specific area can be a multiple (e.g., 3–4x) compared to a situation where yield plots are the measurement units.…”