PMID- 36766027
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230213
IS  - 2304-8158 (Print)
IS  - 2304-8158 (Electronic)
IS  - 2304-8158 (Linking)
VI  - 12
IP  - 3
DP  - 2023 Jan 21
TI  - A Study on Origin Traceability of White Tea (White Peony) Based on Near-Infrared 
      Spectroscopy and Machine Learning Algorithms.
LID - 10.3390/foods12030499 [doi]
LID - 499
AB  - Identifying the geographical origins of white tea is of significance because the 
      quality and price of white tea from different production areas vary largely from 
      different growing environment and climatic conditions. In this study, we used 
      near-infrared spectroscopy (NIRS) with white tea (n = 579) to produce models to 
      discriminate these origins under different conditions. Continuous wavelet 
      transform (CWT), min-max normalization (Minmax), multiplicative scattering 
      correction (MSC) and standard normal variables (SNV) were used to preprocess the 
      original spectra (OS). The approaches of principal component analysis (PCA), 
      linear discriminant analysis (LDA) and successive projection algorithm (SPA) were 
      used for features extraction. Subsequently, identification models of white tea 
      from different provinces of China (DPC), different districts of Fujian Province 
      (DDFP) and authenticity of Fuding white tea (AFWT) were established by K-nearest 
      neighbors (KNN), random forest (RF) and support vector machine (SVM) algorithms. 
      Among the established models, DPC-CWT-LDA-KNN, DDFP-OS-LDA-KNN and 
      AFWT-OS-LDA-KNN have the best performances, with recognition accuracies of 
      88.97%, 93.88% and 97.96%, respectively; the area under curve (AUC) values were 
      0.85, 0.93 and 0.98, respectively. The research revealed that NIRS with machine 
      learning algorithms can be an effective tool for the geographical origin 
      traceability of white tea.
FAU - Zhang, Lingzhi
AU  - Zhang L
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
FAU - Dai, Haomin
AU  - Dai H
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
FAU - Zhang, Jialin
AU  - Zhang J
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
FAU - Zheng, Zhiqiang
AU  - Zheng Z
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
FAU - Song, Bo
AU  - Song B
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
FAU - Chen, Jiaya
AU  - Chen J
AD  - LiuMiao White Tea Corporation, Fuding 355200, China.
FAU - Lin, Gang
AU  - Lin G
AD  - Fujian Rongyuntong Ecological Technology Limited Company, Fuzhou 350025, China.
FAU - Chen, Linhai
AU  - Chen L
AD  - Fu'an Tea Industry Development Center, Fu'an 355000, China.
FAU - Sun, Weijiang
AU  - Sun W
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
AD  - Institute of China White Tea, Fuding 355200, China.
FAU - Huang, Yan
AU  - Huang Y
AUID- ORCID: 0000-0002-1368-2851
AD  - College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 
      350002, China.
AD  - Institute of China White Tea, Fuding 355200, China.
AD  - Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou 
      362400, China.
LA  - eng
GR  - K1520005A04/Fujian Agriculture and Forestry University Tea Industry Chain 
      Technology Innovation and Service System Construction Project/
GR  - KHCZ2101A/Institute of Chinese White Tea Open Subjects/
GR  - KHCZ2104A/Institute of Chinese White Tea Open Subjects/
GR  - FJZTF01/Fujian Zhangtianfu Tea Development Foundation Science and Technology 
      Innovation Fund/
PT  - Journal Article
DEP - 20230121
PL  - Switzerland
TA  - Foods
JT  - Foods (Basel, Switzerland)
JID - 101670569
PMC - PMC9914092
OTO - NOTNLM
OT  - geographic origin traceability
OT  - machine learning
OT  - near-infrared spectroscopy
OT  - white tea
COIS- Jiaya Chen from LiuMiao White Tea corporation (the author contributed to the 
      resources, the company provides a large number of experimental samples); Gang Lin 
      from Fujian Rongyuntong Ecological Technology Limited Company (the author 
      contributed to the resources, the company provides algorithmic support); Linhai 
      Chen from Fu'an Tea Industry Development Center (the author contributed to the 
      resources, the company provides a large number of experimental samples).
EDAT- 2023/02/12 06:00
MHDA- 2023/02/12 06:01
PMCR- 2023/01/21
CRDT- 2023/02/11 01:05
PHST- 2022/12/27 00:00 [received]
PHST- 2023/01/15 00:00 [revised]
PHST- 2023/01/18 00:00 [accepted]
PHST- 2023/02/11 01:05 [entrez]
PHST- 2023/02/12 06:00 [pubmed]
PHST- 2023/02/12 06:01 [medline]
PHST- 2023/01/21 00:00 [pmc-release]
AID - foods12030499 [pii]
AID - foods-12-00499 [pii]
AID - 10.3390/foods12030499 [doi]
PST - epublish
SO  - Foods. 2023 Jan 21;12(3):499. doi: 10.3390/foods12030499.