Ecophysiological modeling of yield and yield components in winter wheat using hierarchical Bayesian analysis
Ecophysiological modeling of yield and yield components in winter wheat using hierarchical Bayesian analysis
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使用分层贝叶斯分析建立冬小麦产量和产量组成部分的生态生理模型
DOI：
10.1002/csc2.20652
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发表时间：
2022
期刊：
影响因子：
2.3
通讯作者：
Alderman, Phillip D.
中科院分区：
文献类型：
--
作者：
Poudel, Pratishtha;Bello, Nora M.;Marburger, David A.;Carver, Brett F.;Liang, Ye;Alderman, Phillip D.
产量构成因素被广泛认为是小麦(Triticum aestivumL.)不同环境和不同类型的产量。在这项研究中，我们使用分层贝叶斯方法，以产量构成性状千粒重(TKW)和非产量生物量(NYB)为基础，对俄克拉荷马州小麦产量进行了生态生理模拟。贝叶斯方法使我们能够量化参数值周围的不确定性，而不是获得参数的单个值估计。这项研究的主要目的是(A)解释小麦产量作为组成性状TKW和NYB的函数，从而研究其对源-库平衡的影响；以及(B)评估它们与小麦发育关键阶段的天气条件的关系。第二个目标是将贝叶斯估计引入生态生理建模。在俄克拉荷马州的三个地点(Altus、Chickasha和Lahoma)种植的15个小麦基因型在三个收获年(2017至2019年)进行了评估，其中地点和年份的组合定义了一个环境。结果表明，环境对产量变异的解释比基因或基因×环境(G×E)互作解释的比例更大，但G×E的证据是充分的。产量预计会随着TKW和NYB的增加而增加，这意味着实现潜在产量的来源限制。然而，生殖前期天气变量对产量和NYB之间关系的贡献指向了库强度被折衷的方向。综上所述，我们的方法为硬红冬小麦品种的籽粒产量源库共同限制提供了证据。
Yield components are widely recognized as drivers of wheat (Triticum aestivumL.) yield across environments and genotypes. In this study, we used a hierarchical Bayesian approach to model wheat grain yield in Oklahoma on an eco‐physiological basis using yield component traits thousand kernel weight (TKW) and nonyield biomass (NYB). The Bayesian approach allowed us to quantify uncertainties around the parameter values rather than obtaining a single value estimate for a parameter. The main objectives of this study were to (a) explain wheat yield as a function of component traits TKW and NYB, and thereby examine the implications for source‐sink balance; and (b) assess their association with weather conditions during key stages of wheat development. A secondary objective was to introduce Bayesian estimation for eco‐physiological modeling. Fifteen wheat genotypes planted in three locations in Oklahoma (Altus, Chickasha, and Lahoma) were evaluated across three harvest years (2017 to 2019), whereby the combination of location and year defined an environment. Results indicate that the environment explained a greater proportion of the variability in yield than genotypes or than genotype × environment (G × E) interaction; however, evidence for G × E was substantial. Yield was expected to increase with increasing TKW and NYB, which would suggest a source limitation to achieve potential yield. Yet, the contribution of early reproductive stage weather variables to the relationship between yield and NYB pointed in the direction of sink strength being compromised. In summary, our approach provides evidence for source‐sink co‐limitation in grain yield of this sample of hard red winter wheat genotypes.