Influência da sazonalidade nos parâmetros composicionais, por analisador infravermelho em amostras de leite

Abstract

Milk is an indispensable food in the Brazilian diet due to its nutritional value and is of great importance in the food industry. This food faces problems related to seasonality throughout the year, creating a problem in product standardization. Dairy companies are opting for various changes in the way they analyze their products, including the introduction of new laboratory instruments to promote faster and more reliable results. This study evaluates changes in the compositional parameters of raw milk according to seasonality. The methodology used was principal component analysis (PCA) applied to results obtained from near-infrared spectroscopy (NIR) analysis of milk from the Leopolis-PR region, provided by an industry located in the Londrina-PR region. The results showed that PCA applied to results obtained by NIR is a robust way to highlight seasonality. This approach was able to separate the four seasons in relation to the nutritional parameters of milk, namely: fat, protein, lactose, and total solids, thus identifying seasonal patterns in milk composition. The seasonality presented in this study can help companies and producers predict and adjust processes to reduce losses and increase productivity.