Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods

The red jujube quality is closely associated with its place of origin. In order to quickly and easily identify the geographical origin of red jujube, the classification of red jujube samples' near-infrared reflectance (NIR) spectra was performed using several fuzzy clustering methods in combina...

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Vydáno v:International journal of food properties Ročník 26; číslo 2; s. 3275 - 3290
Hlavní autoři: Hu, Caiping, Xu, Hongjia, Fu, Zhaoming, Wu, Bin, Zhang, Rui, Zhi, Chenhong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 15.12.2023
Taylor & Francis Ltd
Taylor & Francis Group
Témata:
Algorithms
China
Clustering
Discriminant analysis
fuzzy C-means
fuzzy clustering algorithm
Gustafson-kessel
Infrared spectroscopy
linear discriminant analysis
near-infrared spectroscopy
possibility fuzzy C-means clustering algorithm
principal component analysis
Principal components analysis
provenance
red jujube
reflectance
spectrometers
Spectrum analysis
Ziziphus
Ziziphus jujuba
China
ISSN:1094-2912, 1532-2386, 1532-2386
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Shrnutí:The red jujube quality is closely associated with its place of origin. In order to quickly and easily identify the geographical origin of red jujube, the classification of red jujube samples' near-infrared reflectance (NIR) spectra was performed using several fuzzy clustering methods in combination with principal component analysis (PCA) and linear discriminant analysis (LDA). Firstly, a NIR-M-R2 portable near-infrared spectrometer was used to collect four varieties of red jujube samples from four representative producing areas in four provinces: Gansu, Henan, Shanxi and Xinjiang in China. Each variety corresponded to a producing area, and it had 60 samples with a total of 240 samples. Near-infrared spectra of red jujube were acquired using a NIR-M-R2 portable near-infrared spectrometer, and the initial near-infrared spectra were preprocessed by Savitzky-Golay (SG) filtering. Secondly, PCA and LDA were used to further process the NIR data for dimension reduction and feature extraction, respectively. Finally, red jujube samples were classified by fuzzy C-means (FCM) clustering, Gustafson-Kessel (GK) clustering and possibility fuzzy C-means (PFCM) clustering. When GK served as the clustering algorithm, the clustering accuracy was the highest, as the value of 98.8%. Based on the experimental results, it was evident that the GK clustering algorithm played a significant role in identifying the place of origin of red jujube with near-infrared spectroscopy.
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ISSN:1094-2912
1532-2386
1532-2386
DOI:10.1080/10942912.2023.2281883