Analytical Capabilities and Future Perspectives of Chemometrics in Omics for Food Microbial Investigation

化学计量学 生化工程 组学 计算生物学 环境化学 生物技术 数据科学 化学 计算机科学 生物 工程类 色谱法 生物信息学
作者
Feifei Sun,Yu Zhang,Chin Ping Tan,Ying Gu,Yuanfa Liu,Yong‐Jiang Xu
出处
期刊:Critical Reviews in Analytical Chemistry [Taylor & Francis]
卷期号:: 1-14 被引量:1
标识
DOI:10.1080/10408347.2025.2463430
摘要

Microbiomes significantly impact food flavor, food quality and human health. The development of omics technologies has revolutionized our understanding of the microbiome, the generated complex datasets, as well as their processing and interpretation need to be taken seriously. Currently, chemometrics has shown huge potential in omics data analysis, which is crucial to reveal the functional attributes and mechanisms of microbiomes in food nutrition and safety. However, various chemometric tools have their own characteristics, selecting appropriate technologies and performing multiomics data fusion analysis to improve the precision and reliability of food microbial investigations is still a huge challenge. In this review, we summarized the omics technologies used in food microbiome studies, overviewed the principle and applicability of chemometrics in omics, and discussed the challenges and prospects of chemometrics. The urgent need for chemometrics is to integrate deep learning (DL) and artificial intelligence algorithms to enhance its analytical capabilities and prediction accuracy. We hope this review will provide valuable insights of the integration of multiomics and bioinformatics combined with various chemometric techniques in data analysis for food microbial investigation. In the future, chemometrics combined with modern technologies for multiomics data analysis will further deepen our understanding of food microbiology and improve food safety.
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