Onogi Akio
Department of Plant Life Science, Faculty of Agriculture, Ryukoku University, Otsu, Shiga, Japan.
Methods Mol Biol. 2022;2467:359-396. doi: 10.1007/978-1-0716-2205-6_13.
Crop growth models (CGMs) consist of multiple equations that represent physiological processes of plants and simulate crop growth dynamically given environmental inputs. Because parameters of CGMs are often genotype-specific, gene effects can be related to environmental inputs through CGMs. Thus, CGMs are attractive tools for predicting genotype by environment (G×E) interactions. This chapter reviews CGMs, genetic analyses using these models, and the status of studies that integrate genomic prediction with CGMs. Examples of CGM analyses are also provided.
作物生长模型(CGMs)由多个方程组成,这些方程代表了植物的生理过程,并根据环境输入动态模拟作物生长。由于作物生长模型的参数通常是基因型特异性的,基因效应可以通过作物生长模型与环境输入相关联。因此,作物生长模型是预测基因型与环境(G×E)相互作用的有吸引力的工具。本章回顾了作物生长模型、使用这些模型的遗传分析,以及将基因组预测与作物生长模型相结合的研究现状。还提供了作物生长模型分析的示例。