The detection of chlorophyll content for salt stress of the wheat seedling by hyperspectral imaging

Qiong Wu; Dazhou Zhu; Cheng Wang; Zhihong Ma; Dongyan Zhang; Kun Chen; Jihua Wang

doi:10.1117/12.899759

8 September 2011 The detection of chlorophyll content for salt stress of the wheat seedling by hyperspectral imaging

Qiong Wu, Dazhou Zhu, Cheng Wang, Zhihong Ma, Dongyan Zhang, Kun Chen, Jihua Wang

Proceedings Volume 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications; 81931D (2011) https://doi.org/10.1117/12.899759
Event: International Symposium on Photoelectronic Detection and Imaging 2011, 2011, Beijing, China

Abstract

An auto-development pushbroom imaging spectrometer (PIS) with wavelength range of 400-1000 nm was applied to measure the chlorophyll content of wheat seedling. It showed that according to images of spectral imaging for leaves of Chinese Spring (Salt-sensitive), Zhouyuan 9369(common and high-yield) and Changwu 134(salt-tolerant) wheat seedling under salt stress, growth of salt-sensitive Chinese Spring wheat seedling was inhibited and it was feasible to carry out qualitative analysis. Images could intuitively reflect morphological information of growth status of wheat seedling and could show spectral differences of different leaves and different locations of one leave. Also, it was feasible to identify green and yellow locations of leaf and to carry out qualitative analysis. The tested sites of spectrum and the chlorophyll content measured sites were on the same area of single leaf. After measuring the hyperspectral image of leaf, the mean reflectance spectra of each leaf was calculated Totally, 126 samples were collected, which were then divided into a calibration set and a prediction set. Partial least square regression (PLSR) method was used to build the calibration model. Results showed that the extracted hyperspectral spectra had high correlation with chlorophyll content. The correlation coefficient of the calibration model is R=0.8138, the standard error of prediction is SEP=4.75. The results indicated that hyperspectral imaging were suitable for the non-invasive detection of chlorophyll content of wheat seedling.

Citation Download Citation

Qiong Wu, Dazhou Zhu, Cheng Wang, Zhihong Ma, Dongyan Zhang, Kun Chen, and Jihua Wang "The detection of chlorophyll content for salt stress of the wheat seedling by hyperspectral imaging", Proc. SPIE 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, 81931D (8 September 2011); https://doi.org/10.1117/12.899759

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