Prediction of Talc Content in Wheat Flour Based on a Near-Infrared Spectroscopy Technique

Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) as a Method of Identifying Contaminants in Sugar Beet Production Process-Case Studies

Food safety has received considerable attention in recent years. Methods for rapid identification of a variety contaminants in both the final product and the manufacturing process are constantly developing. This study used Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) spectroscopy to identify various contaminants endangering white sugar production. It was demonstrated that inorganic compounds (calcium carbonate-CaCO₃), plastic contaminants (polypropylene), and oily contaminants (compressor sealing and lubrication lubricant) can be identified with a high degree of precision. FT-MIR spectroscopy was proved to be a useful technique for detecting sugar contaminants rapidly and precisely even without the application of a sophisticated spectra analysis. Commercial databases of reference spectra usage significantly simplify and facilitate the application of this method.

Research Progress of Applying Infrared Spectroscopy Technology for Detection of Toxic and Harmful Substances in Food

In recent years, food safety incidents have been frequently reported. Food or raw materials themselves contain substances that may endanger human health and are called toxic and harmful substances in food, which can be divided into endogenous, exogenous toxic, and harmful substances and biological toxins. Therefore, realizing the rapid, efficient, and nondestructive testing of toxic and harmful substances in food is of great significance to ensure food safety and improve the ability of food safety supervision. Among the nondestructive detection methods, infrared spectroscopy technology has become a powerful solution for detecting toxic and harmful substances in food with its high efficiency, speed, easy operation, and low costs, while requiring less sample size and is nondestructive, and has been widely used in many fields. In this review, the concept and principle of IR spectroscopy in food are briefly introduced, including NIR and FTIR. Then, the main progress and contribution of IR spectroscopy are summarized, including the model’s establishment, technical application, and spectral optimization in grain, fruits, vegetables, and beverages. Moreover, the limitations and development prospects of detection are discussed. It is anticipated that infrared spectroscopy technology, in combination with other advanced technologies, will be widely used in the whole food safety field.

Application of near-infrared spectroscopy for the nondestructive analysis of wheat flour: A review

The quality and safety of wheat flour are of public concern since they are related to the quality of flour products and human health. Therefore, efficient and convenient analytical techniques are needed for the quality and safety controls of wheat flour. Near-infrared (NIR) spectroscopy has become an ideal technique for assessing the quality and safety of wheat flour, as it is a rapid, efficient and nondestructive method. The application of NIR spectroscopy in the quality and safety analysis of wheat flour is addressed in this review. First, we briefly summarize the basic knowledge of NIR spectroscopy and chemometrics. Then, recent advances in the application of NIR spectroscopy for chemical composition, technological parameters, and safety analysis are presented. Finally, the potential of NIR spectroscopy is discussed. Combined with chemometric methods, NIR spectroscopy has been used to detect chemical composition, technological parameters, deoxynivalenol, adulterants and additives of wheat flour. Furthermore, NIR spectroscopy has shown great potential for the rapid and online analysis of the quality and safety of wheat flour. It is anticipated that the current review will serve as a reference for the future analysis of wheat flour by NIR spectroscopy to ensure the quality and safety of flour products.

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NIR spectroscopy is an ideal technique for analysis of wheat flour due to its rapid and nondestructive nature.

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Use of NIR spectroscopy for chemical composition, technological parameters, and safety analysis.

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Online and handheld NIR spectrometers for wheat flour detection are the future trends.

Advances in infrared spectroscopy combined with artificial neural network for the authentication and traceability of food

The authentication and traceability of food attract more attention due to the increasing consumer awareness regarding nutrition and health, being a new hotspot of food science. Infrared spectroscopy (IRS) combined with shallow neural network has been widely proven to be an effective food analysis technology. As an advanced deep learning technology, deep neural network has also been explored to analyze and solve food-related IRS problems in recent years. The present review begins with brief introductions to IRS and artificial neural network (ANN), including shallow neural network and deep neural network. More notably, it emphasizes the comprehensive overview of the advances of the technology combined IRS with ANN for the authentication and traceability of food, based on relevant literature from 2014 to early 2020. In detail, the types of IRS and ANN, modeling processes, experimental results, and model comparisons in related studies are described to set forth the usage and performance of the combined technology for food analysis. The combined technology shows excellent ability to authenticate food quality and safety, involving chemical components, freshness, microorganisms, damages, toxic substances, and adulteration. As well, it shows excellent performance in the traceability of food variety and origin. The advantages, current limitations, and future trends of the combined technology are further discussed to provide a thoughtful viewpoint on the challenges and expectations of online applications for the authentication and traceability of food.