206 related articles for article (PubMed ID: 30221355)
1. Non-destructive classification of apple bruising time based on visible and near-infrared hyperspectral imaging.
Pan X; Sun L; Li Y; Che W; Ji Y; Li J; Li J; Xie X; Xu Y
J Sci Food Agric; 2019 Mar; 99(4):1709-1718. PubMed ID: 30221355
[TBL] [Abstract][Full Text] [Related]
2. Detection of early bruises on apples using hyperspectral reflectance imaging coupled with optimal wavelengths selection and improved watershed segmentation algorithm.
Tian X; Liu X; He X; Zhang C; Li J; Huang W
J Sci Food Agric; 2023 Oct; 103(13):6689-6705. PubMed ID: 37267465
[TBL] [Abstract][Full Text] [Related]
3. Nondestructive Detection and Quantification of Blueberry Bruising using Near-infrared (NIR) Hyperspectral Reflectance Imaging.
Jiang Y; Li C; Takeda F
Sci Rep; 2016 Oct; 6():35679. PubMed ID: 27767050
[TBL] [Abstract][Full Text] [Related]
4. Comparing visible and near infrared 'point' spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness.
Wang Z; Ding F; Ge Y; Wang M; Zuo C; Song J; Tu K; Lan W; Pan L
Spectrochim Acta A Mol Biomol Spectrosc; 2024 Aug; 316():124344. PubMed ID: 38688212
[TBL] [Abstract][Full Text] [Related]
5. A sampling approach for predicting the eating quality of apples using visible-near infrared spectroscopy.
Martínez Vega MV; Sharifzadeh S; Wulfsohn D; Skov T; Clemmensen LH; Toldam-Andersen TB
J Sci Food Agric; 2013 Dec; 93(15):3710-9. PubMed ID: 23633436
[TBL] [Abstract][Full Text] [Related]
6. [Detection of slight bruises on apples based on hyperspectral imaging and MNF transform].
Zhang BH; Huang WQ; Li JB; Zhao CJ; Liu CL; Huang DF; Gong L
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 May; 34(5):1367-72. PubMed ID: 25095440
[TBL] [Abstract][Full Text] [Related]
7. A Hyperspectral Imaging Approach for Classifying Geographical Origins of Rhizoma Atractylodis Macrocephalae Using the Fusion of Spectrum-Image in VNIR and SWIR Ranges (VNIR-SWIR-FuSI).
Ru C; Li Z; Tang R
Sensors (Basel); 2019 May; 19(9):. PubMed ID: 31052476
[TBL] [Abstract][Full Text] [Related]
8. Identification of Apple Varieties Using a Multichannel Hyperspectral Imaging System.
Huang Y; Yang Y; Sun Y; Zhou H; Chen K
Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32911790
[TBL] [Abstract][Full Text] [Related]
9. [Feature extraction of hyperspectral scattering image for apple mealiness based on singular value decomposition].
Huang M; Zhu QB
Guang Pu Xue Yu Guang Pu Fen Xi; 2011 Mar; 31(3):767-70. PubMed ID: 21595236
[TBL] [Abstract][Full Text] [Related]
10. The application of FT-NIRS for the detection of bruises and the prediction of rot susceptibility of 'Hass' avocado fruit.
Wedding BB; Wright C; Grauf S; Gadek P; White RD
J Sci Food Agric; 2019 Mar; 99(4):1880-1887. PubMed ID: 30264542
[TBL] [Abstract][Full Text] [Related]
11. Classification Learning of Latent Bruise Damage to Apples Using Shortwave Infrared Hyperspectral Imaging.
Nturambirwe JFI; Perold WJ; Opara UL
Sensors (Basel); 2021 Jul; 21(15):. PubMed ID: 34372227
[TBL] [Abstract][Full Text] [Related]
12. [Discrimination of brownheart and watercore of apples based on energy spectrum of visible/near infrared transmittance].
Wang JH; Sun XD; Pan L; Sun Q; Han DH
Guang Pu Xue Yu Guang Pu Fen Xi; 2008 Sep; 28(9):2098-102. PubMed ID: 19093569
[TBL] [Abstract][Full Text] [Related]
13. Determination of spectral resolutions for multispectral detection of apple bruises using visible/near-infrared hyperspectral reflectance imaging.
Baek I; Mo C; Eggleton C; Gadsden SA; Cho BK; Qin J; Chan DE; Kim MS
Front Plant Sci; 2022; 13():963591. PubMed ID: 36105710
[TBL] [Abstract][Full Text] [Related]
14. Study on Qualitative Impact Damage of Loquats Using Hyperspectral Technology Coupled with Texture Features.
Li B; Han Z; Wang Q; Sun Z; Liu Y
Foods; 2022 Aug; 11(16):. PubMed ID: 36010443
[TBL] [Abstract][Full Text] [Related]
15. Hyperspectral Imaging and Spectrometry-Derived Spectral Features for Bitter Pit Detection in Storage Apples.
Jarolmasjed S; Khot LR; Sankaran S
Sensors (Basel); 2018 May; 18(5):. PubMed ID: 29762463
[TBL] [Abstract][Full Text] [Related]
16. Accurate and nondestructive detection of apple brix and acidity based on visible and near-infrared spectroscopy.
Zhang Y; Chen Y; Wu Y; Cui C
Appl Opt; 2021 May; 60(13):4021-4028. PubMed ID: 33983342
[TBL] [Abstract][Full Text] [Related]
17. A new application of NIR spectroscopy to describe and predict purees quality from the non-destructive apple measurements.
Lan W; Jaillais B; Leca A; Renard CMGC; Bureau S
Food Chem; 2020 Apr; 310():125944. PubMed ID: 31835215
[TBL] [Abstract][Full Text] [Related]
18. Geographical origin of Chinese apples based on multiple element analysis.
Zhang J; Nie J; Kuang L; Shen Y; Zheng H; Zhang H; Farooq S; Asim S
J Sci Food Agric; 2019 Nov; 99(14):6182-6190. PubMed ID: 31250438
[TBL] [Abstract][Full Text] [Related]
19. Fruit variability impacts puree quality: Assessment on individually processed apples using the visible and near infrared spectroscopy.
Lan W; Jaillais B; Chen S; Renard CMGC; Leca A; Bureau S
Food Chem; 2022 Oct; 390():133088. PubMed ID: 35537239
[TBL] [Abstract][Full Text] [Related]
20. Multielement authentication of apples from the cold highlands in southwest China.
Zhang J; Nie J; Zhang L; Xu G; Zheng H; Shen Y; Kuang L; Gao X; Zhang H
J Sci Food Agric; 2022 Jan; 102(1):241-249. PubMed ID: 34081336
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]