计算机科学
抗氧化剂
协议(科学)
生化工程
荧光光谱法
鉴定(生物学)
生物技术
荧光
食品科学
化学
抗氧化能力
数据科学
作者
Alin Khaliduzzaman,Ken Abamba Omwange,Dimas Firmanda Al Riza,Keiji Konagaya,Mohammed Kamruzzaman,Siddik Alom,Tianqi Gao,Yoshito Saito,Naoshi Kondo
标识
DOI:10.1080/10408398.2021.1992747
摘要
The study of bioactive compounds like food antioxidants is getting huge attention and curiosity by researchers and other relevant stakeholders (e.g., food and pharmaceutical industries) due to their health benefits. However, the currently available protocols to estimate the antioxidant activity of foods are time-consuming, destructive, require complex procedures for sample preparation, need technical persons, and not possible for real-time application, which are very important for large-scale or industrial applications. On the other hand, fluorescence spectroscopy and imaging techniques are relatively new, fast, mostly nondestructive, and possible to apply real-time to detect the antioxidants of foods. However, there is no review article on fluorescence techniques for estimating antioxidants in agricultural produces. Therefore, the present review comprehensively summarizes the overview of fluorescence phenomena, techniques (i.e., spectroscopy and computer vision), and their potential to monitor antioxidants in fruits and vegetables. Finally, opportunities and challenges of fluorescence techniques are described toward developing next-generation protocols for antioxidants measurement. Fluorescence techniques (both spectroscopy and imaging) are simpler and faster than available traditional methods of antioxidants measurement. Moreover, the fluorescence imaging technique has the potential to apply in real-time antioxidant identification in agricultural produce such as fruits and vegetables. Therefore, this technique might be used as a next-generation protocol for qualitative and quantitative antioxidants measurement after improvements like new material technologies for sensor (detector) and light sources for higher sensitivity and reduce the cost of implementing real-world applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI