Raman imaging for food quality and safety evaluation: Fundamentals and applications

Self Cite

134

Fourier transform infrared (FT-IR) and Raman and hyperspectral imaging (HSI) techniques have emerged as reliable analytical methods for effectively characterizing and quantifying quality attributes of different categories of powdery food products (such as milk powder, tea powder, cocoa powder, coffee powder, soybean flour, wheat flour, and chili powder). In addition to the ability for gaining rapid information about food chemical components (such as moisture, protein, and starch), and classifying food quality into different grades, such techniques have also been implemented to determine trace impurities in pure foods and other properties of particulate foods and ingredients with avoidance of extensive sample preparation. Developments of corresponding quality evaluation systems based on FT-IR, Raman, and HSI data that measure food quality parameters and ensure product authentication, would bring about technical and economic benefits to the food industry by enhancing consumer confidence in the quality of its products. Accordingly, a comprehensive review of the mushrooming spectroscopy-based FT-IR, Raman, and HSI literature is carried out in this article. The spectral data collected, the chemometric methods used, and the main findings of recent research studies on quality assessments of powdered materials are discussed and summarized. Providing a review in such a flourishing research field is relevant as a signpost for future study. The conclusion details the promise of how such noninvasive and powerful analytical techniques can be used for rapid and accurate determinations of powder quality attributes in both academical and industrial settings.

Section: Multivariate Analysesmentioning

confidence: 99%

Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review

Sun

2017

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134

“…Food matrixes commonly consist of inorganic components and organic components, varying from water and inorganic substances to proteins, amino acids, carbohydrates, lipids, vitamins, nucleic acids, and enzymes, etc (Sun, 2012) (He, Sun, Pu, Chen, & Lin, 2019;Yaseen, Sun, & Cheng, 2017). Due to complexity of food matrixes, the composition analysis of foods often requires high reliability and repeatability.…”

Section: Food Composition Analysismentioning

confidence: 99%

Development of Nanozymes for Food Quality and Safety Detection: Principles and Recent Applications

Huang

Sun

et al. 2019

Self Cite

141

The public concerns about agrifood safety call for innovative and reformative analytical techniques to meet the inspection requirements of high sensitivity, specificity, and reproducibility. Enzyme‐mimetic nanomaterials or nanozymes, which combine enzyme‐like properties with nanoscale features, emerge as an excellent tool for quality and safety detection in the agrifood sector, due to not only their robust capacity in detection but also their attraction in future‐oriented exploitations. However, in‐depth understanding about the fundamental principles of nanozymes for food quality and safety detection remains limited, which makes their applications largely empirical. This review provides a comprehensive overview of the principles, designs, and applications of nanozyme‐based detection technique in the agrifood industry. The discussion mainly involves three mimicking types, that is, peroxidase, oxidase, and catalase‐like nanozymes, capable of detecting major agrifood analytes. The current principles and strategies are classified and then discussed in details through discriminating the roles of nanozymes in diverse detection platforms. Thereafter, recent applications of nanozymes in detecting various endogenous ingredients and exogenous contaminants in foods are reviewed, and the outlook of profound developments are explained. Evidenced by the increasing publications, nanozyme‐based detection techniques are narrowing the gap to practical‐oriented food analytical methods, while some challenges in optimization of nanozymes, diversification of recognition‐to‐signal manners, and sustainability of methodology need to conquer in the future.

“…In addition, 2D‐median filter could be applied to remove high‐intensity spikes (Bocklitz, Guo, Ryabchykov, Vogler, & Popp, ). Additional information on preprocessing algorithms that can be applied to Raman imaging data can be found in Yaseen, Sun, and Cheng ().…”

Section: Chemometrics For Spice Authenticationmentioning

confidence: 99%

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Oliveira

Cruz-Tirado

Barbin

2019

108

Food fraud in herbs and spices is an important topic, which has led to new technologies being studied as potential tools for fraud identification. Nontargeted technologies have proven to be a useful tool for the authentication of herbs and spices. The present review focuses on the use of near‐infrared, hyperspectral imaging, Fourier‐transform infrared, Raman, nuclear magnetic resonance, and electron spin resonance spectroscopy for the authentication of spices, which includes the determination of origin and irradiated spices and the identification of adulterants. The methods developed based on vibrational spectroscopy combined with chemometric techniques seem to be promising tools for determining the presence of adulterants and contaminants in herbs and spices. On the other hand, nuclear magnetic resonance seems to be the most efficient technology to determine the origin of herbs and spices although, for some cases, studies with near‐infrared spectroscopy can be a viable substitute. Electron spin resonance spectroscopy is the technique par excellence used for the authentication of irradiated herbs and spices, so its use should be expanded to many more spices’ varieties. Portable devices are preferred by those involved in the food industry, due to its manageability and low cost. Data fusion and big data are shown as promising tools for spice fraud control. In conclusion, spectroscopic techniques show a great efficiency to authenticate spices, although their evaluation must be expanded to other spice varieties, to new strategies of data analysis (as data fusion and big data), and to the use of portable devices.