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Modelling ... formula ... with historical weather information improves genomic prediction in new environments

机译:使用历史天气信息建模...可以改善新环境中的基因组预测

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摘要

MotivationInteraction between the genotype and the environment (G×E) has a strong impact on the yield of major crop plants. Although influential, taking G×E explicitly into account in plant breeding has remained difficult. Recently G×E has been predicted from environmental and genomic covariates, but existing works have not shown that generalization to new environments and years without access to in-season data is possible and practical applicability remains unclear. Using data from a Barley breeding programme in Finland, we construct an in silico experiment to study the viability of G×E prediction under practical constraints.
机译:基因型与环境之间的动机相互作用(<数学xmlns:mml =“ http://www.w3.org/1998/Math/MathML” id =“ IM2”> G × E )对主要农作物的产量有很大影响。尽管很有影响力,但使用 G × E 仍然很困难。最近 G × <已经从环境和基因组协变量预测了mi> E ,但是现有工作尚未表明无需获取季节数据即可将其推广到新环境和年份,并且仍具有实用性不清楚。利用来自芬兰大麦育种计划的数据,我们构建了计算机模拟实验来研究在实际约束下的 G × E 预测。

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