Predicting inbred parent synchrony at flowering for maize hybrid seed production by integrating crop growth model with whole genome prediction

Abstract

One of the challenges of maize hybrid seed production is to ensure synchrony at flowering of the two inbred parents of a hybrid, which depends on the specific parental combination and environmental conditions of the production field. Maize flowering can be simulated using a mechanistic crop growth model that converts thermal time accumulation to leaf numbers based on inbred specific physiological parameter values. Heretofore, these inbred specific physiological parameters need to be measured or assigned based on prior knowledge. Here, we leverage genetic, environmental and management data to predict physiological parameters and simulate flowering phenotypes by using whole genome prediction methodology combined with a crop growth model (CGM-WGP) as part of in-field in-season inbred growth development. We use two estimation sets that differ in terms of management and weather information to test the robustness of our approach. As part of our findings, we demonstrate the importance of defining informative priors to generate biologically meaningful predictions of unobserved physiological parameters. Our CGM-WGP infrastructure is efficient at simulating flowering phenotypes. An important practical application of our method is the ability to recommend differential planting intervals for male and female maize inbreds used in commercial seed production fields to synchronize male and female flowering. Core ideas Synchrony at flowering of maize inbred parents is crucial for optimal pollination and consequently seed yield. Integrating WGP with CGM can accurately predict physiological parameters and simulate maize flowering phenotypes. CGM-WGP infrastructure can be used to optimize field operations for large scale maize hybrid seed production.

Plant phenotyping relevance

CGMと全ゲノム予測を統合し、トウモロコシの開花表現型をシミュレーション・予測する計算手法が研究の中心であり、植物形質推定法として該当する。

Code and data availability

The supplied blocks describe proprietary Corteva field phenotyping (flowering dates, leaf counts, SNP genotypes) and a C++ CGM-WGP implementation, but contain no public dataset, image, code deposit, model checkpoint, or availability statement with an authors' public URL. Supplemental materials are mentioned but not as含

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