Suppr超能文献

化学计量学助力的光谱技术用于食品中源自食物的酚类和维生素的测定:综述

Chemometrics-powered spectroscopic techniques for the measurement of food-derived phenolics and vitamins in foods: A review.

作者信息

Hassan Md Mehedi, Xu Yi, Sayada Jannatul, Zareef Muhammad, Shoaib Muhammad, Chen Xiaomei, Li Huanhuan, Chen Quansheng

机构信息

College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, PR China.

School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.

出版信息

Food Chem. 2025 May 1;473:142722. doi: 10.1016/j.foodchem.2024.142722. Epub 2025 Jan 3.

Abstract

Foods are rich in various bioactive compounds, like phenolics, and vitamins, which play important physiological roles in the human body. The analysis of phenolics and vitamins in plant and animal-based foods is a topic of growing interest. Compared with conventional methods, the chemometrics-powered infrared, Fourier transform-near infrared and mid-infrared, ultraviolet-visible, fluorescence, and Raman spectroscopy offer a reliable, low-cost, and nondestructive means to determine phenolics and vitamins. This study briefly presents the physical properties of phenolics and vitamins and their physiological benefits, features of commonly used spectroscopic techniques, sample preparation for spectroscopic data analysis, and the progress of chemometrics methods for model calibration using spectroscopic data and their primary challenges in predicting phenolics and vitamins in real samples for the last five years. The spectral preprocessing method combined feature extraction quantitative chemometric model comparatively showed the best results for simultaneous and single detection. Finally, this study put forward future directions.

摘要

食物富含各种生物活性化合物,如酚类物质和维生素,它们在人体中发挥着重要的生理作用。对植物性和动物性食物中的酚类物质和维生素进行分析是一个越来越受关注的话题。与传统方法相比,化学计量学驱动的红外、傅里叶变换近红外和中红外、紫外可见、荧光和拉曼光谱提供了一种可靠、低成本且无损的方法来测定酚类物质和维生素。本研究简要介绍了酚类物质和维生素的物理性质及其生理益处、常用光谱技术的特点、光谱数据分析的样品制备,以及过去五年中使用光谱数据进行模型校准的化学计量学方法的进展及其在预测实际样品中的酚类物质和维生素时面临的主要挑战。光谱预处理方法结合特征提取定量化学计量模型在同时检测和单一检测方面相对显示出最佳结果。最后,本研究提出了未来的发展方向。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验