Big data analytics in food industry: a state-of-the-art literature review

被引：0
作者：
Siddique, Aftab [1 ]
Gupta, Ashish [2 ]
Sawyer, Jason T. [3 ]
Huang, Tung-Shi [1 ]
Morey, Amit [1 ]
机构：
[1] Auburn Univ, Dept Poultry Sci, Auburn, AL 36849 USA
[2] Auburn Univ, Dept Business Analyt & Informat, Auburn, AL USA
[3] Auburn Univ, Dept Anim Sci, Auburn, AL USA
来源：
NPJ SCIENCE OF FOOD | 2025年 / 9卷 / 01期
关键词：
TRANSFORM INFRARED-SPECTROSCOPY; COMPUTER VISION SYSTEM; RESPONSE-SURFACE METHODOLOGY; SUPPLY CHAIN MANAGEMENT; SOCIAL MEDIA; ANTIMICROBIAL RESISTANCE; ARTIFICIAL-INTELLIGENCE; HYPERSPECTRAL IMAGES; PATHOGENIC BACTERIA; EXTRUSION PROCESS;
D O I：
10.1038/s41538-025-00394-y
中图分类号：
TS2 [食品工业];
学科分类号：
0832 ;
摘要：
The food industry has experienced rapid growth over the past two decades, driven by technological advancements that have generated vast quantities of complex data. However, the industry's ability to effectively analyze and leverage this data remains limited due to the lack of control over diverse variables. This review addresses a critical gap by exploring how AI-ML-based approaches can be applied to solve key challenges in the food sector.
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页数：26
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