Deep learning in food authenticity: Recent advances and future trends

Zhuowen Deng, Tao Wang, Yun Zheng, Wanli Zhang and Yong-Huan Yun

Trends in Food Science & Technology, 2024, 144, 104344
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Nondestructive detection of multiple qualities of dried jujube in different storage periods based on hyperspectral imaging combined with deep learning

Fei Tan, Weixin Ye, Shiwei Ruan, Hao Cang, Yuan Zhang, Peng Xing, Jingkun Yan, Mingrui Zhao, Ruoyu Di, Pan Gao and Wei Xu

Infrared Physics & Technology, 2024, 143, 105595
DOI: 10.1016/j.infrared.2024.105595

Detection of Pesticide Residue Level in Grape Using Hyperspectral Imaging with Machine Learning

Weixin Ye, Tianying Yan, Chu Zhang, Long Duan, Wei Chen, Hao Song, Yifan Zhang, Wei Xu and Pan Gao

Foods, 2022, 11, 1609
DOI: 10.3390/foods11111609

Identification of geographical origins of Radix Paeoniae Alba using hyperspectral imaging with deep learning-based fusion approaches

Zeyi Cai, Zihong Huang, Mengyu He, Cheng Li, Hengnian Qi, Jiyu Peng, Fei Zhou and Chu Zhang

Food Chemistry, 2023, 422, 136169
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Corn variety identification based on improved EfficientNet lightweight neural network

Jinpu Xu, Jinhao Lan, Guangjie Lv and Dexin Ma

Front. Plant Sci., 2025, 16
DOI: 10.3389/fpls.2025.1603073

AI‐Powered Advancements in Food Analysis and Safety: Ensuring Quality, Protection, and Precision in Modern Food Systems: A Review

Ammar B. Altemimi, Farhang Hameed Awlqadr, Raqad R. Al‐Hatim, Syamand Ahmed Qadir, Mohammed N. Saeed, Aryan Mahmood Faraj, Tablo H. Salih, Hala S. Mahmood, Mohammad Ali Hesarinejad and Francesco Cacciola

eFood, 2025, 6
DOI: 10.1002/efd2.70076

End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses

Chu Zhang, Lei Zhou, Qinlin Xiao, Xiulin Bai, Baohua Wu, Na Wu, Yiying Zhao, Junmin Wang and Lei Feng

Plant Phenomics, 2022, 2022, 9851096
DOI: 10.34133/2022/9851096

Determination of quality and maturity of processing tomatoes using near-infrared hyperspectral imaging with interpretable machine learning methods

Mingrui Zhao, Hao Cang, Huixin Chen, Chu Zhang, Tianying Yan, Yifan Zhang, Pan Gao and Wei Xu

LWT, 2023, 183, 114861
DOI: 10.1016/j.lwt.2023.114861

Non-Destructive Geographical Traceability and Quality Control of Glycyrrhiza uralensis Using Near-Infrared Spectroscopy Combined with Support Vector Machine Model

Anqi Liu, Zibo Meng, Jiayi Ma, Jinfeng Liu, Haonan Wang, Yingbo Li, Yu Yang, Na Liu, Ming Hui, Dandan Zhai and Peng Li

Foods, 2026, 15, 411
DOI: 10.3390/foods15030411

Discrimination model of geographical area from coconut milk by near-infrared spectroscopy: Exploration in tandem with classical chemometrics, machine learning, and deep learning

Agustami Sitorus and Ravipat Lapcharoensuk

Microchemical Journal, 2024, 206, 111538
DOI: 10.1016/j.microc.2024.111538

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example

Hongxin Xie, Chaojie Wei, Wei Wang, Rui Chen, Liwei Cui, Liming Wang, Dongliang Chen, Yong-Liang Yu, Bai Li and Yu-Feng Li

Journal of Hazardous Materials, 2024, 463, 132886
DOI: 10.1016/j.jhazmat.2023.132886

Selection of Specimen Orientations for Hyperspectral Identification of Wild and Cultivated Ophiocordyceps sinensis

Hejuan Du, Xinyue Cui, Xingfeng Chen, Dawa Drolma, Shihao Xie, Jiaguo Li, Limin Zhao, Jun Liu and Tingting Shi

Processes, 2026, 14, 412
DOI: 10.3390/pr14030412

Rapid identification of medicinal plants via visual feature-based deep learning

Chaoqun Tan, Long Tian, Chunjie Wu and Ke Li

Plant Methods, 2024, 20
DOI: 10.1186/s13007-024-01202-6

Hyperspectral Imaging with Machine Learning Approaches for Assessing Soluble Solids Content of Tribute Citru

Cheng Li, Mengyu He, Zeyi Cai, Hengnian Qi, Jianhong Zhang and Chu Zhang

Foods, 2023, 12, 247
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Synergistic spectral-spatial fusion in hyperspectral Imaging: Dual attention-based rice seed varieties identification

Shuqi Tang, Nan Zhong, Yuhao Zhou, Shaobin Chen, Zhibao Dong, Long Qi and Xiao Feng

Food Control, 2025, 176, 111411
DOI: 10.1016/j.foodcont.2025.111411

Rapidly detecting fennel origin of the near-infrared spectroscopy based on extreme learning machine

Enguang Zuo, Lei Sun, Junyi Yan, Cheng Chen, Chen Chen and Xiaoyi Lv

Sci Rep, 2022, 12
DOI: 10.1038/s41598-022-17810-y

Prediction performance and reliability evaluation of three ginsenosides in Panax ginseng using hyperspectral imaging combined with a novel ensemble chemometric model

Youyou Wang, Siman Wang, Ruibin Bai, Xiaoyong Li, Yuwei Yuan, Tiegui Nan, Chuanzhi Kang, Jian Yang and Luqi Huang

Food Chemistry, 2024, 430, 136917
DOI: 10.1016/j.foodchem.2023.136917

Identification of Turtle-Shell Growth Year Using Hyperspectral Imaging Combined with an Enhanced Spatial–Spectral Attention 3DCNN and a Transformer

Tingting Wang, Zhenyu Xu, Huiqiang Hu, Huaxing Xu, Yuping Zhao and Xiaobo Mao

Molecules, 2023, 28, 6427
DOI: 10.3390/molecules28176427

The impact of high-quality data on the assessment results of visible/near-infrared hyperspectral imaging and development direction in the food fields: a review

Hongyu Xu, Jie Ren, Jidong Lin, Shijie Mao, Zijin Xu, Ziwei Chen, Jiajing Zhao, Yangyang Wu, Ning Xu and Ping Wang

Food Measure, 2023
DOI: 10.1007/s11694-023-01822-x

Hyperspectral discrimination of ginseng variety and age from Changbai Mountain area

Ruiyang Cheng, Xueyuan Bai, Jianying Guo, Luqi Huang, Daqing Zhao, Zhaojian Liu and Wei Zhang

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2024, 307, 123613
DOI: 10.1016/j.saa.2023.123613

A review of analytical techniques coupled with chemometric methods for tobacco origin traceability

Xiaoyue Yuan, Lili Cui, Shulei Han, Yaning Fu, Hongjuan Wang, Yushan Tian, Xiao Li, Huan Chen, Hongwei Hou and Yuwei Yuan

Industrial Crops and Products, 2025, 236, 122004
DOI: 10.1016/j.indcrop.2025.122004

Principles and applications of convolutional neural network for spectral analysis in food quality evaluation: A review

Na Luo, Daming Xu, Bin Xing, Xinting Yang and Chuanheng Sun

Journal of Food Composition and Analysis, 2024, 128, 105996
DOI: 10.1016/j.jfca.2024.105996

Portable near-infrared hyperspectral technology fused with machine learning enables simultaneous prediction and classification of protein solubility in peas

Jingwen Zhu, Xuchun Zhu, Bingyu Chen, Koris András, Feiyue Ren, Zhaowei Han, Xinmiao Yao, Ye Zhou and Hongzhi Liu

Food Chemistry, 2026, 503, 147805
DOI: 10.1016/j.foodchem.2025.147805