Studies of the relationship between rice stem composition and lodging resistance
Studies of the relationship between rice stem composition and lodging resistance
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水稻茎秆组成与抗倒伏关系的研究
DOI：
10.1017/s0021859618000369
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发表时间：
2018-04-01
影响因子：
2
通讯作者：
Li, J. Y.
中科院分区：
文献类型：
--
作者：
Gui, M. Y.;Wang, D.;Li, J. Y.
摘要株高和抗倒性对水稻产量有显著影响，但在作物栽培和育种中，这两个性状一直存在矛盾。旨在建立快速准确的株型评价机制，为选育高秆抗倒超级稻品种提供依据。采用植物解剖学和组织化学相结合的综合方法，研究了15份水稻品种在不同生长阶段的抗弯强度（一种材料特性，定义为材料在弯曲试验中屈服前的应力）和倒伏指数的变化，以了解这些参数的变化趋势及其潜在的影响因素。对水稻不同发育时期茎的解剖结构进行了观察，并测定了茎细胞壁中木质素含量。采用相关分析、多元回归和径向基函数（RBF）神经网络建立了3个水稻倒伏评价模型，并对模型结果进行了比较，以确定最适合预测水稻最佳株型的模型。在3种评价方法中，RBF网络的平均残差和相对预测误差最小，具有较高的精度和鲁棒性，可用于建立水稻形态性状和抗倒性的数学模型，以筛选最优品种。
Abstract Plant height and lodging resistance can affect rice yield significantly, but these traits have always conflicted in crop cultivation and breeding. The current study aimed to establish a rapid and accurate plant type evaluation mechanism to provide a basis for breeding tall but lodging-resistant super rice varieties. A comprehensive approach integrating plant anatomy and histochemistry was used to investigate variations in flexural strength (a material property, defined as the stress in a material just before it yields in a flexure test) of the rice stem and the lodging index of 15 rice accessions at different growth stages to understand trends in these parameters and the potential factors influencing them. Rice stem anatomical structure was observed and the lignin content the cell wall was determined at different developmental stages. Three rice lodging evaluation models were established using correlation analysis, multivariate regression and artificial radial basis function (RBF) neural network analysis, and the results were compared to identify the most suitable model for predicting optimal rice plant types. Among the three evaluation methods, the mean residual and relative prediction errors were lowest using the RBF network, indicating that it was highly accurate and robust and could be used to establish a mathematical model of the morphological characteristics and lodging resistance of rice to identify optimal varieties.