Redefining modern food analysis: Significance of omics analytical techniques integration, chemometrics and bioinformatics
文献类型： 外文期刊
第一作者： Okoye, Charles Obinwanne
作者： Okoye, Charles Obinwanne;Jiang, Huifang;Jiang, Jianxiong;Okoye, Charles Obinwanne;Tan, Xiaoli;Okoye, Charles Obinwanne;Nazar, Mudasir
作者机构： Jiangsu Univ, Sch Environm & Safety Engn, Biofuels Inst, Zhenjiang 212013, Peoples R China;Jiangsu Univ, Sch Life Sci, Zhenjiang 212013, Peoples R China;Univ Nigeria, Dept Zool & Environm Biol, Nsukka 410001, Nigeria;Jiangsu Acad Agr Sci, Inst Anim Sci, Nanjing 210014, Peoples R China
关键词： Modern biotechnology; Food analysis; Omics; Multi-omics; Foodomics; Food safety; Analytical techniques
期刊名称：TRAC-TRENDS IN ANALYTICAL CHEMISTRY （ 2022影响因子：13.1； 五年影响因子：13.1 ）
ISSN： 0165-9936
年卷期： 2024 年 175 卷
收录情况： SCI
摘要： Food analysis is a scientific discipline that has evolved from traditional methods into sophisticated approaches due to advances in analytical chemistry and modern biotechnology. With the global demand for safe, nutritious, and sustainable food, omics techniques have become pivotal in ensuring food authenticity and safety. These analytical techniques encompass genomics, metagenomics, transcriptomics, proteomics, and metabolomics, offering comprehensive insights into food composition and functionality. Besides, omics analytical techniques offer multidisciplinary insights into food science and analysis. Despite their diverse potential, these techniques remain underutilized in food analysis due to knowledge, technical, and cost barriers, necessitating further action for improvement. This review explored the contributions of omics analytical techniques, chemometrics, and bioinformatics in revolutionizing modern food analysis, highlighting their significance and potential breakthroughs through multi-omics integration and sophisticated data platforms. However, the abundance and complexity of omics data necessitate efficient handling and analysis, where bioinformatics and chemometrics play crucial roles. Integrating varied omics data, which coincide with standardizing processes and quality control, and developing prediction models are anticipated for sustainable food analysis.
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