Near-infrared spectroscopy and imaging in food quality and safety

Abstract

Over the last two decades, near-infrared spectroscopy (NIRS) has established itself as a non-destructive analytical technique in a variety of disciplines. However, recent technological advancements in hardware design and data mining techniques have unleashed the potential of NIRS to become a tool of choice for routine analyses of agricultural products. The current paper synthesizes the status of NIRS in the agri-food industry in terms of hardware and software development as well as the direction in which the NIRS research is headed. An extensive review of literature reveals that the emphasis on hardware development is focused on developing compact, robust, and portable spectrometers and hyperspectral imaging (HSI) systems. The software development on the other hand is geared towards developing better preprocessing, analyses, and modeling techniques using chemometrics, support vector machines, and artificial neural networks. The four main agri-food sectors identified to be the beneficiaries of this research revolution are grain quality monitoring; postharvest handling of fruits and vegetables; identification of contaminants in animal produce and feed; and food safety and authenticity. Apart from discussing the aforementioned topics, the paper also provides food scientists some working knowledge on parameters crucial to the performance of spectral and imaging systems. It is expected that further development of NIRS will help agricultural and food scientists to enhance the quality and safety of our food.

Rapid Identification of Pork Adulterated in the Beef and Mutton by Infrared Spectroscopy

“…However, the PLS-DA model showed less prediction error than the SVM model. This might be due to the SVM model which is good for less variant nonlinear spectral model [50,51]. The spectral data contained many linear variants which caused the higher prediction error in the SVM model, which was identical with the previous report [52].…”

Use of spectroscopic data for automation in food processing industry

“…NIR spectroscopy can be used in either reflectance mode for obtaining information from solid or granular samples or transmittance mode for obtaining information from liquid samples or from solid samples within the 700-1,100 nm range. Basic instrumentation of NIR spectroscopy and details of hardware advancements tailored to specific application in food industry are available elsewhere [4,5]. The NIR spectral region corresponds mainly to overtone and combination bands [6] since all other fundamental vibrational modes are in the MIR region.…”

Using hyperspectral imaging to characterize consistency of coffee brands and their respective roasting classes

“…Thus, it is important to develop quality control tools and measures, so that companies and consumers can monitor whether a given food product or beverage meets certain quality expectations. The use of hyperspectral imaging technologies in the food industry provides opportunities for improving food safety and quality control (Feng and Sun, 2012;Gowen et al, 2007;Huang et al, 2014;Van Loo et al, 2012;Wang and Paliwal, 2007). However, there has been much less research into how the same technology can be used to characterize and quantify the consistency of commercial food and beverage brands.…”