Fast and non-invasive estimation of Meat Microbiological Quality
A new research paper, authored by a team from the Agricultural University of Athens, Greece, and the University of Hertfordshire, UK, highlights the potential of combining spectral image features from VideometerLab, FTIR spectroscopy features, and machine learning methodology for assessing the microbiological quality of minced pork meat. This approach offers a rapid, non-invasive, and promising technique for assessing the microbiological quality of meat.
Food safety is a critical concern, and ensuring the microbiological quality of meat is an essential aspect of food safety. However, traditional microbiological methods for assessing the quality of meat can be time-consuming, laborious, and often not reproducible.
The study demonstrated that using the combination of VideometerLab spectral imaging, FTIR spectroscopy, and machine learning techniques provided an accurate and rapid method for assessing the microbiological quality of minced pork meat. The authors note that this technique could have significant potential for the food industry, allowing for faster and more efficient assessments of meat quality and improving food safety. The study highlights the capabilities of VideometerLab and its potential applications in the food industry.
Learn more about Videometer’s capabilities in the Meat application area.
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