Analysis of Differences in Wheat Infected with Powdery Mildew Based on Fluorescence Imaging System - Computer and Computing Technologies in Agriculture IX - Part II
Conference Papers Year : 2016

Analysis of Differences in Wheat Infected with Powdery Mildew Based on Fluorescence Imaging System

Abstract

This study aimed to investigate the variation characteristics of rapid light-response curves of wheat leaves infected with powdery mildew. According to the heterogeneity between two selection patterns of area of interest (AOI), determination of fluorescence induction parameters and fitting of rapid light-response curves were conducted based on fluorescence imaging system in wheat powdery mildew experimental plots. The results showed that relative electron transport rate rETR was reduced with the increase of disease severity level; rETR of the rectangle selection pattern was relatively low. Specifically, the reduction in rETR is mainly influenced by the decrease of absorption coefficient Abs. Among fitting parameters of rapid light-response curves, the potential and the maximum relative electron transport rate, initial slope, light suppression parameter and semi-saturation intensity were reduced with the increase of disease severity level; the heterogeneity of fitting parameters between two selection patterns reflected the “critical state” of leaf fluorescence characteristics. Infected leaves at severe level (80 %) had relatively low light-harvesting capacity and tolerance to strong light, which easily caused light inhibition. According to the lateral heterogeneity analysis of photosynthesis of wheat leaves infected with powdery mildew, there was relatively high heterogeneity between fluorescence parameters of wheat infected leaves, especially in leaves with lesions on the surface.
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hal-01614215 , version 1 (10-10-2017)

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Shizhou Du, Qinhong Liao, Chengfu Cao, Yuqiang Qiao, Wei Li, et al.. Analysis of Differences in Wheat Infected with Powdery Mildew Based on Fluorescence Imaging System. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. pp.68-75, ⟨10.1007/978-3-319-48354-2_7⟩. ⟨hal-01614215⟩
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