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Studies of the relationship between rice stem composition and lodging resistance

Part of: AGS Millet Collection

Published online by Cambridge University Press:  25 May 2018

M. Y. Gui ,
D. Wang ,
H. H. Xiao ,
M. Tu ,
F. L. Li ,
W. C. Li ,
S. D. Ji ,
T. X. Wang  and
J. Y. Li
M. Y. Gui
Affiliation:
State Key Laboratory Cultivation Base for Cell Differentiation Regulation, Xinxiang, Henan 453007, China
D. Wang
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
H. H. Xiao
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
M. Tu
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
F. L. Li
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
W. C. Li
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
S. D. Ji
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
T. X. Wang*
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China Engineering Laboratory of Green Medicinal Material Biotechnology, Xinxiang, Henan 453007, China
J. Y. Li*
Affiliation:
College of Life Science, Henan Normal University, Xinxang, Henan 453007, China
*
Author for correspondence: T. X. Wang, E-mail: [email protected] and J. Y. Li, E-mail: [email protected]
Author for correspondence: T. X. Wang, E-mail: [email protected] and J. Y. Li, E-mail: [email protected]
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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.

Keywords

Multivariate analysisneural networkstem anatomystem flexural strength
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 3 , April 2018 , pp. 387 - 395
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Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

*

These authors contributed equally to this work.

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