Studies of the relationship between rice stem composition and lodging resistance. (25th May 2018)

• Record Type: Journal Article
• Authors: Gui, M. Y.; Wang, D.; Xiao, H. H.; Tu, M.; Li, F. L.; Li, W. C.; Ji, S. D.; Wang, T. X.; Li, J. Y.
• Is Part Of: Journal of agricultural science. Volume 156:Number 3(2018)
• Page Start: 387
• Page End: 395
• Publication Date: 2018-05-25
• Subjects: Multivariate analysis, -- neural network, -- stem anatomy, -- stem flexural strength; Agriculture -- Periodicals; 630.5
• DOI: 10.1017/S0021859618000369
• Languages: English
• ISSNs: 0021-8596

Abstract

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.