Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications. (November 2017)

• Record Type: Journal Article
• Authors: Liu, Yuwei; Pu, Hongbin; Sun, Da-Wen
• Is Part Of: Trends in food science & technology. Volume 69:Part A(2017)
• Page Start: 25
• Page End: 35
• Publication Date: 2017-11
• Subjects: Imaging spectroscopy -- Cooking -- Drying -- Chilling -- Freezing -- Curing; Food industry and trade -- Periodicals; Food -- Biotechnology -- Periodicals; 664.005
• DOI: 10.1016/j.tifs.2017.08.013
• Languages: English
• ISSNs: 0924-2244

Abstract

Abstract: Background: The quality of products depends on their processing. Effective way of monitoring and controlling these processes will ensure the quality and safety of products. Since traditional measurement methods cannot achieve on-line monitoring, imaging spectroscopy, as a fast, accurate and non-destructive detection tool, has been widely used to evaluate quality and safety attributes of foods undergoing various processes. Scope and Approach: In the current review, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing. The study emphasized the ability of HSI technique to detect internal and external quality parameters in different food processes. Also, the advantages and disadvantages of HSI applications on these food processes are discussed. Key Findings and Conclusions: The literature presented in this review clearly demonstrate that HSI has the ability to inspect and monitor different food manufacturing processes and has the potential to control the quality and safety of the processed foods. Although still with some barriers, it can be expected the HSI systems will find more useful and valuable applications in the future evaluation of food processes. Highlights: Imaging spectroscopy is an on-line tool to detect quality attributes of food. Hyperspectral imaging (HSI) has been accepted to monitor various food processes. Chemical maps can show distribution of quality parameters during food processing. Several algorithms are used to build the model of food quality during processing.