Artificial intelligence-enabled analysis methods and their applications in food chemistry

被引：0

作者：

Gu, Chunyan ^{[1
]}

Wang, Gang ^{[1
]}

Zhuang, Weihua ^{[1
]}

Hu, Jie ^{[1
]}

He, Xun ^{[2
]}

Zhang, Liang ^{[3
]}

Du, Zhao ^{[1
]}

Xu, Xuemei ^{[4
]}

Yin, Minggang ^{[4
]}

Yao, Yongchao ^{[1
]}

Sun, Xuping ^{[2
]}

Hu, Wenchuang ^{[1
,3
]}

机构：

[1] Sichuan Univ, West China Hosp, Precis Med Translat Res Ctr, Frontiers Sci Ctr Dis Related Mol Network,Dept Lab, Chengdu, Peoples R China

[2] Sichuan Univ, West China Hosp, Ctr High Altitude Med, Chengdu, Peoples R China

[3] One Chip Biotechnol Co LTD, Chengdu, Peoples R China

[4] Zigong First Peoples Hosp, Dept Blood Transfus, Zigong, Peoples R China

来源：

CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION | 2025年

关键词：

Food chemistry; artificial intelligence; machine learning; food safety; food quality control; CLASSIFICATION; QUALITY;

D O I：

10.1080/10408398.2025.2521648

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

Food chemistry is a science that studies the composition, properties, and changes of food at the chemical and molecular levels, as well as their relationships to human health. With the rapid advancement of artificial intelligence (AI) technology, the field of food chemistry has undergone significant transformation, and new development opportunities have emerged. AI provides efficient, precise, and intelligent solutions for food analysis. This review examines the integration of AI technologies with conventional analytical methodologies in food chemistry, focusing on recent advancements in their applications. It elaborates on AI-driven approaches in spectroscopic analysis, chromatography, mass spectrometry, and sensor technology, highlighting their transformative potential in food quality control, identification of bioactive constituents, contaminant detection, nutritional analysis, and novel ingredient design. Through specific case studies, the review demonstrates how AI enhances analytical efficiency and accuracy, providing innovative solutions for future research and practical applications in food chemistry.

引用

页数：22

共 103 条

[91] Application of Molecular Transformer approach for predicting the potential reactions to generate advanced glycation end products in infant formula [J].

Yang, Huihui ;

Bai, Xiaosen ;

Feng, Baolong ;

Wang, Qinghua ;

Meng, Li ;

Wang, Fengzhong ;

Wang, Yutang .

FOOD CHEMISTRY, 2023, 407

[92] Yum-Me: A Personalized Nutrient-Based Meal Recommender System [J].

Yang, Longqi ;

Hsieh, Cheng-Kang ;

Yang, Hongjian ;

Pollak, John P. ;

Dell, Nicola ;

Belongie, Serge ;

Cole, Curtis ;

Estrin, Deborah .

ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2017, 36 (01)

[93] Heterocyclic aromatic amines in roasted chicken: Formation and prediction based on heating temperature and time [J].

Yao, Guangming ;

Zhou, Yajun ;

Li, Zongping ;

Ma, Qingshu .

FOOD CHEMISTRY, 2023, 405

[94] Coupled Gold Nanoparticles with Aptamers Colorimetry for Detection of Amoxicillin in Human Breast Milk Based on Image Preprocessing and BP-ANN [J].

Ye, Ziqian ;

Du, Jinglong ;

Li, Keyu ;

Zhang, Zhilun ;

Xiao, Peng ;

Yan, Taocui ;

Han, Baoru ;

Zuo, Guowei .

FOODS, 2022, 11 (24)

[95] Combining stable isotope, multielement and untargeted metabolomics with chemometrics to discriminate the geographical origins of ginger (Zingiber officinale Roscoe) [J].

Yu, Dai-xin ;

Guo, Sheng ;

Zhang, Xia ;

Yan, Hui ;

Mao, Su-wan ;

Wang, Jie-mei ;

Zhou, Jia-qi ;

Yang, Jian ;

Yuan, Yu-wei ;

Duan, Jin-ao .

FOOD CHEMISTRY, 2023, 426

[96] Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe) [J].

Yu, Dai-xin ;

Zhang, Xia ;

Guo, Sheng ;

Yan, Hui ;

Wang, Jie-mei ;

Zhou, Jia-qi ;

Yang, Jian ;

Duan, Jin-Ao .

FOOD CHEMISTRY, 2022, 396

[97] Integrating Image Analysis and Machine Learning for Moisture Prediction and Appearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment [J].

Yu, Shuai ;

Zheng, Haoran ;

Wilson, David I. ;

Yu, Wei ;

Young, Brent R. .

FOODS, 2024, 13 (12)

[98] E-eye, flash GC E-nose and HS-GC-MS combined with chemometrics to identify the adulterants and geographical origins of Ziziphi Spinosae Semen [J].

Zhang, Jiu-ba ;

Li, Ming-xuan ;

Zhang, Yun-fei ;

Qin, Yu-wen ;

Li, Yu ;

Su, Lian-lin ;

Li, Lin ;

Bian, Zhen-hua ;

Lu, Tu -lin .

FOOD CHEMISTRY, 2023, 424

[99] Near-infrared hyperspectral imaging technology combined with deep convolutional generative adversarial network to predict oil content of single maize kernel [J].

Zhang, Liu ;

Wang, Yaqian ;

Wei, Yaoguang ;

An, Dong .

FOOD CHEMISTRY, 2022, 370

[100] The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants [J].

Zhang, Longlong ;

Yang, Qiuping ;

Zhu, Zhiyuan .

FOODS, 2024, 13 (12)

← 2 3 4 5 6 7 8 9 10 11 →