Geographical Origin Identification of Chinese Tomatoes Using Long-Wave Fourier-Transform Near-Infrared Spectroscopy Combined with Deep Learning Methods-Reference-Cited by-同舟云学术

Geographical Origin Identification of Chinese Tomatoes Using Long-Wave Fourier-Transform Near-Infrared Spectroscopy Combined with Deep Learning Methods

Published:2023-01-17 Issue:4 Volume:16 Page:664-676
ISSN:1936-9751
Container-title:Food Analytical Methods
language:en
Short-container-title:Food Anal. Methods

Author:

Yuan Weidong,Jiang Hongzhe,Sun Mengmeng,Zhou Yu,Zhang Cong,Zhou Hongping

Funder

National Natural Science Foundation of China

the Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Publisher

Springer Science and Business Media LLC

Subject

Safety Research,Safety, Risk, Reliability and Quality,Applied Microbiology and Biotechnology,Food Science,Analytical Chemistry

Link

https://link.springer.com/content/pdf/10.1007/s12161-023-02444-1.pdf

Reference48 articles.

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3. Castro TA, Leite BS, Assunção LS et al (2021) Red tomato products as an alternative to reduce synthetic dyes in the food industry: a review. Molecules 26(23):7125. https://doi.org/10.3390/molecules26237125

4. Chen Q, Zhao J, Fang CH et al (2007) Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM). Spectrochim Acta Part A Mol Biomol Spectrosc 66(3):568–574. https://doi.org/10.1016/j.saa.2006.03.038

5. Chen Y, Lin Z, Zhao X et al (2014) Deep learning-based classification of hyperspectral data. IEEE J Sel Topics Appl Earth Obs Remote Sens 7(6):2094–2107. https://doi.org/10.1109/JSTARS.2014.2329330

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