Abstract:

Food quality and safety are issues of concern to the government, food industry, and consumers; hence, it is imperative to detect harmful substances in foodstuff. Traditional techniques for this purpose include biochemical methods and instrumental analysis methods such as chromatography and chromatography-mass spectrometry. These methods, however, are time-consuming and unable to obtain the spatial distribution of the analytes. Therefore, the development of rapid, non-destructive, real-time, and visual detection technologies has emerged as a hotspot in the field of food research. In recent years, hyperspectral imaging, which combines imaging and spectral technology, is rapidly gaining ground. This technique allows one to determine the geometrical characteristics and chemical composition of samples. Compared with traditional spectral technologies, hyperspectral imaging has the advantages of wide detection ranges, in addition to being real-time and non-destructive. At present, hyperspectral imaging is widely used in meat quality evaluation, detection of adulteration, and meat classification. In addition, Raman imaging is mainly used for the detection of illegal additives in food and for adulteration detection. This technology is fast, non-destructive, and low cost; furthermore, spectral and spatial information of the targets can be simultaneously obtained. Mass spectrometry imaging allows for the visualization and high-throughput analysis of sample tissues, without the need for complex sample preparation steps such as labeling and staining. Compared with other imaging technologies, mass spectrum information of substances can be obtained by mass spectrometry imaging. As a molecular visualized technology, it helps obtain the spatial distribution of nutrients and harmful substances in food. Mass spectrometry imaging has unique advantages in food research, e. g., it is used for molecular-level detection and accurate positioning of substances, and hence, it has excellent application prospects in this field. In this paper, recent literature data about imaging technologies in the field of food research, including 72 reports published in professional local and overseas magazines, are collated. The principles of hyperspectral imaging, Raman imaging, and mass spectrometry imaging are introduced, along with the detailed applications of these methods in the quality detection, source identification, and microbial pollution of food. In addition, it also includes food physical damage, food adulteration and food chemical residues. Besides, the advantages and disadvantages of these imaging technologies are discussed. Finally, prospects for the development of imaging technologies in food research are presented. Future work related to hyperspectral imaging should focus on the development of high-sensitivity cameras and high-resolution systems. Improving the data processing efficiency and adding prediction models are also key points for the future. Future studies on Raman imaging can focus on the application of different chemometrics algorithms that would improve the evaluation of food quality and safety parameters. Expanding the scope of application of these methods in food research will also be the focus of future research. Regarding mass spectrometry imaging, attempts should be made to improve the ionization methods, detection sensitivity, spatial resolution, and data processing effectiveness. Additionally, the combination of spectral imaging and mass spectrometry imaging gives full play to their advantages, so that spectral and mass spectrometry information of the targets can be obtained. In short, the application of imaging technologies in food research is expected to be more promising.

Key words: hyperspectral imaging, Raman imaging, mass spectrometry imaging, food safety, quality control