Novel applications of infrared technologies in dairy industry

Abstract

Dairy industry is economically relevant in many countries, and milk and its derived products are important sources of nutrients both in developed and developing countries. Thus, the dairy industry is interested in the application of rapid and cost-effective technologies for raw product evaluation, processing control and labeling. One of the most widespread technologies for milk and dairy product analysis is the infrared spectroscopy, mainly in the mid-infrared (MIRS) and near-infrared (NIRS) spectra regions. Other than standard composition, the assessment of milk technological traits is of particular interest in Europe and, traditionally, milk coagulation traits and acidity, milk protein and mineral composition have been determined using time-consuming laboratory methods. Recently, the development of specific MIRS prediction models for such milk traits has allowed the collection of coagulation information at herd and population level for milk quality payment and genetic selection purposes, respectively. Therefore, MIRS technology offers the possibility to conduct largescale phenotypic, genetic and genomic studies, even through a posteriori prediction using historical milk spectra stored in the laboratories. Cheese provides essential nutrients such as fatty acids, minerals and vitamins, and its consumption in Europe has grown in the last decade. Nevertheless, due to the negative consequences of the Western diet on the cardiovascular system mainly related to the excessive intake of saturated fatty acids and sodium, the declaration of salt and saturated fatty acids contents in the product's label has become mandatory. In the last years, the dairy industry has successfully developed and implemented NIRS prediction models for at-line and inexpensive quantification of minerals and fatty acids of commercial cheeses in order to quickly incorporate this information on the label of dairy products. The development of MIRS and NIRS prediction models for milk and cheese traits has opened new opportunities in the field of dairy products, spanning from genetic selection to technological efficiency.

Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse

“…Firstly, spectral outliers were eliminated using the Mahalanobis distance (Global H > 3.0). Then, different scatter corrections such as detrending (D), standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied to the raw spectra as pretreatment to reduce noise effect and variability due to the scatter (De Marchi, Costa, Goi, Penasa, & Manuelian, 2019). Afterwards, each of these pre-processing techniques was combined with derivative mathematical treatments: 0,0,1,1; 1,4,4,1; 1,8,8,1; and 2,10,10,1.…”