Nutritional Components of Beverage Granules by Near-Infrared Spectroscopy Based on PLS Model

Abstract

The nutritional content of instant beverages sold in the market is uneven. The existing standards and regulatory system are not sound enough, and the phenomenon of the unknown nutritional content of ingredients frequently occurs, which makes the beverage lose its nutritional characteristics, and long-term drinking may cause harm to consumers’ health. Therefore, it is necessary to strengthen the quality and safety supervision of beverage granules and carry out quality and authenticity inspections and evaluations. The purpose of this study is to collect samples of milk tea powder and to detect its protein, total sugar, ash, fat, and moisture content. By analyzing its near-infrared spectral characteristics, the paper establishes the NIR (near-infrared spectrum) rapid detection model and the PLS (partial least square) model of protein and fat in milk powder. The study uses external inspection and cross-validation to judge the reliability of the model. The results showed that the relative error of protein was less than 1.9%, and the relative error of fat was less than 1.5%, which indicated that the model had good predictability. It provides a new strategy for the quality evaluation and formula process identification of milk tea powder. It also provides a strong reference for the improvement of local standards and the formulation of national standards for milk tea powder. The study provides strong data support for illegal businesses to take effective actions to abuse consumer sentiment and take advantage of the regulatory vacuum period.