| Effect of green tea powder on the quality attributes and antioxidant activity of whole-wheat flour pan bread J Ning, GG Hou, J Sun, X Wan, A Dubat LWT-Food Science and Technology 79, 342-348, 2017 | 159 | 2017 |
| Quantitative analysis and geographical traceability of black tea using Fourier transform near-infrared spectroscopy (FT-NIRS) G Ren, S Wang, J Ning, R Xu, Y Wang, Z Xing, X Wan, Z Zhang Food Research International 53 (2), 822-826, 2013 | 129 | 2013 |
| Metabolomics based on UHPLC-Orbitrap-MS and global natural product social molecular networking reveals effects of time scale and environment of storage on the metabolites and … S Xu, JJ Wang, Y Wei, WW Deng, X Wan, GH Bao, Z Xie, TJ Ling, J Ning Journal of Agricultural and Food Chemistry 67 (43), 12084-12093, 2019 | 117 | 2019 |
| Sensomics analysis of the effect of the withering method on the aroma components of Keemun black tea W Huang, S Fang, J Wang, C Zhuo, Y Luo, Y Yu, L Li, Y Wang, WW Deng, ... Food Chemistry 395, 133549, 2022 | 110 | 2022 |
| Evaluating green tea quality based on multisensor data fusion combining hyperspectral imaging and olfactory visualization systems L Li, S Xie, J Ning, Q Chen, Z Zhang Journal of the Science of Food and Agriculture 99 (4), 1787-1794, 2019 | 107 | 2019 |
| Revelation of volatile contributions in green teas with different aroma types by GC–MS and GC–IMS N Liu, S Shen, L Huang, G Deng, Y Wei, J Ning, Y Wang Food Research International 169, 112845, 2023 | 86 | 2023 |
| Green analytical assay for the quality assessment of tea by using pocket-sized NIR spectrometer Y Wang, M Li, L Li, J Ning, Z Zhang Food Chemistry 345, 128816, 2021 | 84 | 2021 |
| Intelligent evaluation of black tea fermentation degree by FT-NIR and computer vision based on data fusion strategy G Jin, Y Wang, L Li, S Shen, WW Deng, Z Zhang, J Ning Lwt 125, 109216, 2020 | 80 | 2020 |
| Chemical constituents analysis of white tea of different qualities and different storage times JM Ning, D Ding, YS Song, ZZ Zhang, X Luo, XC Wan European Food Research and Technology 242, 2093-2104, 2016 | 80 | 2016 |
| Rapid prediction of chlorophylls and carotenoids content in tea leaves under different levels of nitrogen application based on hyperspectral imaging Y Wang, X Hu, G Jin, Z Hou, J Ning, Z Zhang Journal of the Science of Food and Agriculture 99 (4), 1997-2004, 2019 | 79 | 2019 |
| Evaluating taste-related attributes of black tea by micro-NIRS YJ Wang, TH Li, LQ Li, JM Ning, ZZ Zhang Journal of Food Engineering 290, 110181, 2021 | 78 | 2021 |
| Using near-infrared hyperspectral imaging with multiple decision tree methods to delineate black tea quality G Ren, Y Wang, J Ning, Z Zhang Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 237, 118407, 2020 | 78 | 2020 |
| Effects of dynamic and static withering technology on volatile and nonvolatile components of Keemun black tea using GC-MS and HPLC combined with chemometrics ZW Hou, YJ Wang, SS Xu, YM Wei, GH Bao, QY Dai, WW Deng, JM Ning Lwt 130, 109547, 2020 | 78 | 2020 |
| Safety and anti-hyperglycemic efficacy of various tea types in mice M Han, G Zhao, Y Wang, D Wang, F Sun, J Ning, X Wan, J Zhang Scientific reports 6 (1), 31703, 2016 | 74 | 2016 |
| Stepwise Identification of Six Tea (Camellia sinensis (L.)) Categories Based on Catechins, Caffeine, and Theanine Contents Combined with Fisher Discriminant … J Ning, D Li, X Luo, D Ding, Y Song, Z Zhang, X Wan Food Analytical Methods 9, 3242-3250, 2016 | 71 | 2016 |
| Highly identification of keemun black tea rank based on cognitive spectroscopy: Near infrared spectroscopy combined with feature variable selection G Ren, Y Wang, J Ning, Z Zhang Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 230, 118079, 2020 | 69 | 2020 |
| NIR hyperspectral imaging coupled with chemometrics for nondestructive assessment of phosphorus and potassium contents in tea leaves YJ Wang, G Jin, LQ Li, Y Liu, YK Kalkhajeh, JM Ning, ZZ Zhang Infrared Physics & Technology 108, 103365, 2020 | 68 | 2020 |
| Enhanced quality monitoring during black tea processing by the fusion of NIRS and computer vision Y Wang, L Li, Y Liu, Q Cui, J Ning, Z Zhang Journal of Food Engineering 304, 110599, 2021 | 67 | 2021 |
| Classification of five Chinese tea categories with different fermentation degrees using visible and near-infrared hyperspectral imaging J Ning, J Sun, S Li, M Sheng, Z Zhang International journal of food properties 20 (sup2), 1515-1522, 2017 | 67 | 2017 |
| Rapid and real-time detection of black tea fermentation quality by using an inexpensive data fusion system G Jin, Y Wang, M Li, T Li, W Huang, L Li, WW Deng, J Ning Food Chemistry 358, 129815, 2021 | 63 | 2021 |
