199 related articles for article (PubMed ID: 36010536)
1. Prediction of Tea Polyphenols, Free Amino Acids and Caffeine Content in Tea Leaves during Wilting and Fermentation Using Hyperspectral Imaging.
Mao Y; Li H; Wang Y; Fan K; Song Y; Han X; Zhang J; Ding S; Song D; Wang H; Ding Z
Foods; 2022 Aug; 11(16):. PubMed ID: 36010536
[TBL] [Abstract][Full Text] [Related]
2. Prediction of Drought-Induced Components and Evaluation of Drought Damage of Tea Plants Based on Hyperspectral Imaging.
Chen S; Gao Y; Fan K; Shi Y; Luo D; Shen J; Ding Z; Wang Y
Front Plant Sci; 2021; 12():695102. PubMed ID: 34490000
[TBL] [Abstract][Full Text] [Related]
3. Low temperature response index for monitoring freezing injury of tea plant.
Mao Y; Li H; Wang Y; Fan K; Shen J; Zhang J; Han X; Song Y; Bi C; Sun L; Ding Z
Front Plant Sci; 2023; 14():1096490. PubMed ID: 36818866
[TBL] [Abstract][Full Text] [Related]
4. [Hyperspectral technology combined with CARS algorithm to quantitatively determine the SSC in Korla fragrant pear].
Zhan BS; Ni JH; Li J
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Oct; 34(10):2752-7. PubMed ID: 25739220
[TBL] [Abstract][Full Text] [Related]
5. pH indicator-based sensor array in combination with hyperspectral imaging for intelligent evaluation of withering degree during processing of black tea.
Wang Y; Ren Z; Li M; Yuan W; Zhang Z; Ning J
Spectrochim Acta A Mol Biomol Spectrosc; 2022 Apr; 271():120959. PubMed ID: 35121474
[TBL] [Abstract][Full Text] [Related]
6. Robustness and accuracy evaluation of moisture prediction model for black tea withering process using hyperspectral imaging.
An T; Yu S; Huang W; Li G; Tian X; Fan S; Dong C; Zhao C
Spectrochim Acta A Mol Biomol Spectrosc; 2022 Mar; 269():120791. PubMed ID: 34968835
[TBL] [Abstract][Full Text] [Related]
7. [Near-infrared hyperspectral imaging combined with CARS algorithm to quantitatively determine soluble solids content in "Ya" pear].
Li JB; Peng YK; Chen LP; Huang WQ
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 May; 34(5):1264-9. PubMed ID: 25095419
[TBL] [Abstract][Full Text] [Related]
8. Synchronously Predicting Tea Polyphenol and Epigallocatechin Gallate in Tea Leaves Using Fourier Transform-Near-Infrared Spectroscopy and Machine Learning.
Ye S; Weng H; Xiang L; Jia L; Xu J
Molecules; 2023 Jul; 28(14):. PubMed ID: 37513250
[TBL] [Abstract][Full Text] [Related]
9. Simultaneous quantification of chemical constituents in matcha with visible-near infrared hyperspectral imaging technology.
Ouyang Q; Wang L; Park B; Kang R; Chen Q
Food Chem; 2021 Jul; 350():129141. PubMed ID: 33618087
[TBL] [Abstract][Full Text] [Related]
10. Rapid determination by near infrared spectroscopy of theaflavins-to-thearubigins ratio during Congou black tea fermentation process.
Dong C; Li J; Wang J; Liang G; Jiang Y; Yuan H; Yang Y; Meng H
Spectrochim Acta A Mol Biomol Spectrosc; 2018 Dec; 205():227-234. PubMed ID: 30029185
[TBL] [Abstract][Full Text] [Related]
11. [Rapid and Dynamic Determination Models of Amino Acids and Catechins Concentrations during the Processing Procedures of Keemun Black Tea].
Ning JM; Yan L; Zhang ZZ; Wei LD; Li LQ; Fang JT; Huang CW
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Dec; 35(12):3422-6. PubMed ID: 26964222
[TBL] [Abstract][Full Text] [Related]
12. Color measurement of tea leaves at different drying periods using hyperspectral imaging technique.
Xie C; Li X; Shao Y; He Y
PLoS One; 2014; 9(12):e113422. PubMed ID: 25546335
[TBL] [Abstract][Full Text] [Related]
13. Evaluation of matcha tea quality index using portable NIR spectroscopy coupled with chemometric algorithms.
Wang J; Zareef M; He P; Sun H; Chen Q; Li H; Ouyang Q; Guo Z; Zhang Z; Xu D
J Sci Food Agric; 2019 Aug; 99(11):5019-5027. PubMed ID: 30977141
[TBL] [Abstract][Full Text] [Related]
14. [Measuring the Moisture Content in Maize Kernel Based on Hyperspctral Image of Embryo Region].
Tian X; Huang WQ; Li JB; Fan SX; Zhang BH
Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Oct; 36(10):3237-42. PubMed ID: 30246759
[TBL] [Abstract][Full Text] [Related]
15. Comparison of Si-GA-PLS and Si-CARS-PLS build algorithms for quantitation of total polyphenols in black tea using the spectral analytical system.
Zareef M; Arslan M; Hassan MM; Ahmad W; Chen Q
J Sci Food Agric; 2023 Dec; 103(15):7914-7920. PubMed ID: 37490702
[TBL] [Abstract][Full Text] [Related]
16. Early warning and diagnostic visualization of Sclerotinia infected tomato based on hyperspectral imaging.
Zhou Y; Chen J; Ma J; Han X; Chen B; Li G; Xiong Z; Huang F
Sci Rep; 2022 Dec; 12(1):21140. PubMed ID: 36477460
[TBL] [Abstract][Full Text] [Related]
17. Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.
Liang G; Dong C; Hu B; Zhu H; Yuan H; Jiang Y; Hao G
Sci Rep; 2018 May; 8(1):7854. PubMed ID: 29777147
[TBL] [Abstract][Full Text] [Related]
18. Rapid monitoring of black tea fermentation quality based on a solution-phase sensor array combined with UV-visible spectroscopy.
Li L; Li M; Cui Q; Liu Y; Chen Y; Wang Y; Zhang Z; Chen Q; Ning J
Food Chem; 2022 May; 377():131974. PubMed ID: 34979395
[TBL] [Abstract][Full Text] [Related]
19. Hyperspectral Imaging Detection of Total Viable Count from Vacuum Packing Cooling Mutton Based on GA and CARS Algorithms.
Duan HW; Zhu RG; Xu WD; Qiu YY; Yao XD; Xu CJ
Guang Pu Xue Yu Guang Pu Fen Xi; 2017 Mar; 37(3):847-52. PubMed ID: 30160397
[TBL] [Abstract][Full Text] [Related]
20. Moisture content monitoring in withering leaves during black tea processing based on electronic eye and near infrared spectroscopy.
Chen J; Yang C; Yuan C; Li Y; An T; Dong C
Sci Rep; 2022 Dec; 12(1):20721. PubMed ID: 36456868
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
