Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.

中文翻译：

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水分供应变化下小麦产量和根系发育的基因组预测。

更深的根有助于植物在深层土壤中吸收可用资源，确保在干旱条件下更好的生长和更高的产量。开发了一个大规模的半田间根表型分析设备，以允许水分有效性梯度并通过水分有效性梯度检测基因型的潜在相互作用。基因分型的冬小麦品系在该设施的四个床中成行种植，其中来自邻居的间接遗传效应可能对性状变异很重要。目的是探索基因组预测谷物相关性状和深根性状的可能性，这些性状是通过在测量的每行冬小麦下的微型根管中拍摄的图像收集的。分析包括四个谷物相关性状：谷物产量、千粒重、蛋白质浓度、和在单独收获的每半行上​​测量的总氮含量。还分析了两个根性状，即每个管上 1.2 和 2 m 深度之间的总根长和四个间隔的根长。应用了两组模型，有或没有来自每行两侧的邻居的影响。对于任何性状，均未检测到基因型与不断变化的水可用性之间的相互作用。谷物相关性状的估计基因组遗传力范围为 0.263 至 0.680，根性状的估计基因组遗传力范围为 0.030 至 0.055。籽粒相关性状和根性状的遗传变异系数相似。籽粒相关性状的育种值预测准确度为 0.440 至 0.598，根系性状的预测准确度为 0.264 至 0.334。在模型中包括邻居效应通常会增加估计的基因组遗传力和预测的谷物产量和氮含量育种值的准确性。产量性状和根性状的加性遗传变异相对量相似，但未检测到基因型与水分利用率之间的相互作用。使用来自半田间设施的记录，可以获得谷物相关性状育种值的准确基因组预测和深根性状的合理准确预测育种值。包括邻居效应增加了谷物相关性状的估计加性遗传方差和预测育种值的准确性。尽管遗传力低，但可以获得高预测精度。产量性状和根性状的加性遗传变异相对量相似，但未检测到基因型与水分利用率之间的相互作用。使用来自半田间设施的记录，可以获得谷物相关性状育种值的准确基因组预测和深根性状的合理准确预测育种值。包括邻居效应增加了谷物相关性状的估计加性遗传方差和预测育种值的准确性。尽管遗传力低，但可以获得高预测精度。产量性状和根性状的加性遗传变异相对量相似，但未检测到基因型与水分利用率之间的相互作用。使用来自半田间设施的记录，可以获得谷物相关性状育种值的准确基因组预测和深根性状的合理准确预测育种值。包括邻居效应增加了谷物相关性状的估计加性遗传方差和预测育种值的准确性。尽管遗传力低，但可以获得高预测精度。使用来自半田间设施的记录，可以获得谷物相关性状育种值的准确基因组预测和深根性状的合理准确预测育种值。包括邻居效应增加了谷物相关性状的估计加性遗传方差和预测育种值的准确性。尽管遗传力低，但可以获得高预测精度。使用来自半田间设施的记录，可以获得谷物相关性状育种值的准确基因组预测和深根性状的合理准确预测育种值。包括邻居效应增加了谷物相关性状的估计加性遗传方差和预测育种值的准确性。尽管遗传力低，但可以获得高预测精度。