Raman spectroscopy can be used for analysis of important quality indicators in meat, feasibly leading to on-line applications of the technique in the future.
Overall meat eating quality is very important for consumer confidence, willingness to pay and repeat purchase of fresh meat. Intramuscular fat (IMF) content, pH, water-holding capacity (WHC) and color are the best indicators of the eating quality of fresh pork. However, these quality indicators are difficult to measure before the meat is sent from processors. Raman spectroscopy is a vibrational spectroscopic technique with the potential to analyze IMF, pH and WHC, all in one analysis. The following study aimed to use Raman spectroscopy to estimate IMF in pork loins by recording spectra from intact samples at the slaughter house.
In general, the quality consumers prefer in pork is characterized by moderate IMF content, an ultimate pH of 5.6-6.0, high WHC and a reddish-pink color. In contrast, most of the pigs reared in Norway are lean, resulting in low levels of IMF. Lower levels of IMF are often associated with undesirable deviations in pH and WHC. This leads to a significant share of the pork being sold having an unknown and inconsistent quality. Consumers will then have to, in most cases, rely on their own knowledge of meat quality when deciding what to buy.
In international surveys it has been shown that consumers are willing to pay over twice as much for meat of premium quality compared to passable quality. Pricing meat according to its quality is currently an untapped resource in the Norwegian meat industry, and it could increase earnings substantially if systems were put in place for quality differentiation. Objective methods for assessing meat quality should be a cornerstone in this work.
Using a Raman instrument equipped with a wide area illumination probe, IMF could be estimated successfully both for intact and homogenized pork loins. IMF of the samples ranged from 1.4% to 8.6%, which was considered representative for Norwegian pigs. The PLSR model for intact samples had cross validated r2 of 0.84 and an error of 0.78%, while the model for homogenized samples had r2 of 0.94 and an error of 0.47%, only using one factor. These results are clearly good enough to classify meat to different quality grades.
Results from this study introduced a new application for Raman spectroscopy in meat quality analysis, namely estimation of IMF, and should encourage further research and development to make Raman spectroscopy a useful technique for the food industry.
Before Raman spectroscopy can be implemented in the meat industry, more research is needed to refine calibration models for IMF and other quality indicators (e.g. WHC and pH). Another important aspect is the need for instrumentation developed to endure the conditions and requirements of the meat industry.
By: Jens Petter Wold