高光谱影像的苹果花叶病叶片花青素定量反演

doi:10.3964/j.issn.1000-0593(2017)10-3187-06

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Abstract Anthocyanin has the antioxidant effect, which is helpful to the recover of leaf injury. The dynamic change of anthocyanin concentration can be considered as a sensitive indicator to reflect plant physiological conditions affected by external environmental stresses, consequently the anthocyanin content of mosaic virus infecting apple leaves can be used as an important criterion for assessing the degree of disease. In this research, hyperspectral images of apple leaves with mosaic disease were acquired by imaging spectrometer. By the combination of each two bands, spectral reflectance was used to establish the optimal spectral indexes which were highly correlated to the anthocyanin content in infected leaves. Further more, a accurate anthocyanin concentration estimation model was established taking these spectral indexes as parameters. The results were as follows: (1) The damage of mesophyll cells in mosaic virus infecting apple leaves would cause the increase of anthocyanin content. As a result, the spectral reflectance of infected area increased significantly in visible region, while in near infrared region the reflectance was lower than the normal. In addition, the red-edge position shifted to the shorter wavelength and both the red-edge area and the first derivative spectral reflectance at red-edge position decreased. (2) The correlation between leaf anthocyanin content and spectral reflectance was extremely significant at most of the wavebands and reached the peak at 581 nm. The normalised deviation spectral index combined with spectral reflectance at 770 and 722 nm, the simple ratio spectral index combined with spectral reflectance at 717 and 770 nm and the deviation spectral index correlated with spectral reflectance at 581 and 520 nm were all significantly related to leaf anthocyanin content, with the correlation coefficent of 0.838, 0.865 and 0.875, respectively. (3) Anth-PLSR was the optimal model to estimate apple leaf anthocyanin content, of which the determination coefficient was 0.823 and RMSE was 0.056. The anthocyanin content distribution diagram of leaves were made by solving the hyperspectral images pixel using Anth-PLSR model, thus the anthocyanin content of an integral leaf was calculated. On the other hand, by extracting the average spectral reflectance from the the hyperspectral image of a whole leaf, the anthocyanin content of the integral leaf can be obtained using Anth-PLSR model. The results of these two different methods showed a high consistence by fitting analysis, which demonstrated that the latter method could be used to rapidly detect the anthocyanin content of apple leaves.

Key words：Hyperspectral imaging; Mosaic disease; Apple leaves; Anthocyanin value; Band selection; Pigment spectral indices

Received: 2016-11-16 Accepted: 2017-03-26

ZTFLH:

TP79

Corresponding Authors: CHANG Qing-rui E-mail: changqr@nwsuaf.edu.cn

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http://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2017)10-3187-06 OR http://www.gpxygpfx.com/EN/Y2017/V37/I10/3187