Subjective measures are of limited value if you need to get objective answers. Labs involved in food safety or consumer acceptance, have to produce hard data; measuring the odour of meat by quantifying the concentrations of volatile freshness markers above the meat.
Although consumers provide the ultimate feedback on product quality, using suitable instrumentation, you can provide valid results, rapidly, objectively, and at a low costs per sample.
We recently undertook a study that showed that the freshness of beef can be measured by using SIFT-MS for instant, direct analysis of evolved volatile freshness marker compounds.
Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) is a fast, sensitive technique, used for checking the freshness of beef and other red meats. With detection limits equal to those of the best human noses. SIFT-MS is an effective technique for detecting spoilage of red meats, enabling wide-scale freshness screening.
Figures 1 and 2 show the results obtained for ground (minced) and sirloin steak cuts of New Zealand beef, respectively. Ground beef has a higher surface area per unit mass than steak, so is more susceptible to spoilage. Inorganic preservative is added to minced beef to prolong its shelf life. This appears to keep the dimethyl sulfide concentration constant for the duration of the reported study and also serves to moderate production of ethyl acetate. Ammonia and trimethylamine continue to be produced, however.
Figure 1. SIFT-MS headspace concentrations of various compounds above New Zealand ground (minced) beef at 37°C.
Figure 2. SIFT-MS headspace concentrations of various compounds above New Zealand sirloin steak at 37°C
This study demonstrates that SIFT-MS is ideally suited to early detection of beef degradation via the volatile compounds emitted by spoilage organisms – even for steak, which, due to its lower surface area, has a lower exposure to environmental microbes. The Syft Voice200ultra SIFT-MS instrument provides a robust, simple solution for sensitive, quantitative screening of large numbers of samples per day, both manually and automatically (via autosampler Integration).