Meat and meat products are an important source of protein, vitamins and minerals in the human diet. Therefore, quality control is one of the essential stages in the processing of meat and meat products.
Conventional quality study methods are based on sensory and chemical analysis. However, they have drawbacks such as being subjective techniques (in the case of sensory analysis), being destructive, time-consuming or requiring extensive sample preparation. One of the techniques that has emerged as an alternative to these methods is spectroscopy, which stands out for its speed, simplicity and ability to detect internal attributes. This post will address the applications of spectroscopy for the study of quality parameters in meat.
The term near infrared (NIR) spectroscopy (which covers approximately from 780 to 2500 nm) is generally employed although sometimes the visible part of the spectrum (400-750 nm) is also used. The process consists of first developing a calibration model that is obtained from the spectra acquired from a large number of samples associated to the measurements of the quality parameters to be obtained. Subsequently, the model is validated quantitatively and qualitatively with new samples. Finally, the model is used as a reference, so that, once the spectrum of a new sample is known, its quality parameters can be precisely determined from the model.
The chemical composition of meat is studied because it is related to the general quality, taste and its impact on the consumer’s health. NIR spectroscopy studies include parameters, such as protein content, moisture/dry matter and intramuscular fat, which are related to the freshness of the meat. In particular, water can constitute up to 75% of fresh matter and the specific absorption of O-H bonds at 1450 and 1940 nm, which explains the reasons of using NIR spectroscopy to predict water content. However, the different studies show great variability about the reliability of the obtained calibration models. Normally, to achieve high precision, it is necessary to work with homogeneous samples (minced meat) and with a great variability in their chemical composition.
The fatty acid content of meat, a parameter that has acquired relevance due to the nutritional recommendations to reduce the intake of saturated fats and increase the consumption of polyunsaturated fatty acids, has also been studied with NIR spectroscopy. Good results are obtained in these cases with samples that are homogeneous and show great variability, but calibration models are still far from being able to be used in practical applications.
Other important parameters are color, pH and water holding capacity (WHC), since they are related to the sensory appreciation that consumers have of meat. Different studies show that NIR spectroscopy still has limitations when it comes to predicting these parameters, although it does have some capacity to classify meat based on these characteristics.
NIR spectroscopy has important application cases with meat products. For example, it has been employed to study the moisture, protein and fat content in pork sausages, achieving greater reliability in the case of moisture. Excellent results have also been obtained for the salt content and the percentage of salt in wet and dry matter for dry cured ham, or the moisture content during the drying process of fermented sausages.
Another important application of NIR spectroscopy with meat products includes classification based on the species, race or geographic origin of the animal to avoid fraud. For example, one study was able to identify beef, llama or horse meat in a homogeneous meat sample. Another study using NIR spectroscopy was able to distinguish whether the lamb meat came from agricultural or grazing regions.
The number of studies with NIR spectroscopy in meat has increased in recent years and has the advantage of being a fast, non-invasive and chemical-free method. NIR spectroscopy can predict the chemical composition in the case of ground meat, and although it still has limitations in the case of not processed meat, these measurements can serve as a reference for further developments. Here, the acquisition of a greater number of spectra for each sample, the scanning of larger areas or the determination of the wavelengths that contain the most significant information are important parameters that can contribute to improve the results obtained with NIR spectroscopy.
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Written by J.J. Imas
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 Peyvasteh, M.; Popov, A.; Bykov, A.; Meglinski, I. Meat freshness revealed by visible to near-infrared spectroscopy and principal component analysis. J. Phys. Commun. 2020, 4, 095011, doi:10.1088/2399-6528/ABB322.
 Prieto, N.; Roehe, R.; Lavín, P.; Batten, G.; Andrés, S. Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review. Meat Sci. 2009, 83, 175–186, doi:10.1016/J.MEATSCI.2009.04.016.