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Nondestructive Determination and Visualization of Quality Attributes in Fresh and Dry Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging

1
Zhejiang Academy of Traditional Chinese Medicine, Key Laboratory of Research and Development of Chinese Medicine of Zhejiang Province, Hangzhou 310007, China
2
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
3
Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
4
School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(9), 1959; https://doi.org/10.3390/app9091959
Received: 28 March 2019 / Revised: 5 May 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
(This article belongs to the Special Issue Applications of Hyperspectral Imaging for Food and Agriculture II)
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Abstract

Rapid and nondestructive determination of quality attributes in fresh and dry Chrysanthemum morifolium is of great importance for quality sorting and monitoring during harvest and trade. Near-infrared hyperspectral imaging covering the spectral range of 874–1734 nm was used to detect chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid content in Chrysanthemum morifolium. Fresh and dry Chrysanthemum morifolium flowers were studied for harvest and trade. Pixelwise spectra were preprocessed by wavelet transform (WT) and area normalization, and calculated as average spectrum. Successive projections algorithm (SPA) was used to select optimal wavelengths. Partial least squares (PLS), extreme learning machine (ELM), and least-squares support vector machine (LS-SVM) were used to build calibration models based on full spectra and optimal wavelengths. Calibration models of fresh and dry flowers obtained good results. Calibration models for chlorogenic acid in fresh flowers obtained best performances, with coefficient of determination (R2) over 0.85 and residual predictive deviation (RPD) over 2.50. Visualization maps of chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid in single fresh and dry flowers were obtained. The overall results showed that hyperspectral imaging was feasible to determine chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid. Much more work should be done in the future to improve the prediction performance. View Full-Text
Keywords: near-infrared hyperspectral imaging; chlorogenic acid; luteolin-7-O-glucoside; 3,5-O-dicaffeoylquinic acid; Chrysanthemum morifolium; prediction maps near-infrared hyperspectral imaging; chlorogenic acid; luteolin-7-O-glucoside; 3,5-O-dicaffeoylquinic acid; Chrysanthemum morifolium; prediction maps
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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He, J.; Zhu, S.; Chu, B.; Bai, X.; Xiao, Q.; Zhang, C.; Gong, J. Nondestructive Determination and Visualization of Quality Attributes in Fresh and Dry Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging. Appl. Sci. 2019, 9, 1959.

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