MEAT QUALITY PREDICTION

Wenyang Jia's PhD Project

Meat products are particularly plagued by safety problems because of their complicated structure and various production processes and complex supply chains. Conventional meat testing methods include sensory evaluation, chemical methods, and microbiological analysis. Sensory evaluation is evaluated by consumers or professional food staff, and the results are highly subjective and cannot be quantitatively analysed. The chemical analysis method has certain objectivity and the results are usually reliable, but it requires accurate sample preparation and professional analysis. In addition, the testing process needs to destroy the sample, and the corresponding instruments and equipment are relatively expensive, which is not suitable for rapid online testing. These instrument methods can meet the requirements of accurate detection, the sample preparation is more complicated, costly, and time-consuming, which cannot meet the rapid screening requirements of high-throughput samples on-line and the needs of dynamically monitoring the meat supply chain from the producer to the consumer.

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Rapid and non-invasive analytical methods to evaluate meat quality have become a priority for the industry over the conventional chemical methods. To achieve rapid analysis of safety and quality parameters of meat products, hyperspectral imaging (HSI) is now widely applied in research studies for detecting the various components of different meat products, but its application in meat production and supply chain integrity as a quality control (QC) solution is still ambiguous. Hyperspectral imaging sets up many continuous spectral bands in a numbers of images, and each pixel of the image has continuous spectral information. The chemical and physical information of meat products can be monitored with HSI technique in a rapid and non-destructive manner because of the spectral and the spatial information HSI acquired. HSI combined with chemometric algorithms has a superior advantage because of its ability to provide rich spectral and spatial information from its hypercubes (3-dimentional data set), with which the intrinsic quality and safety attributes of meat products are predicted with numerical information and distribution map.

With the rapid development of hyperspectral detection technology, HSI technology has expanded its different development directions in addition to its extensive practicality. For the whole chain of meat product, fast, reliable, and robust methods are needed to allow the safety and quality of meat and meat products. HSI can indicate the specific component and this technology can be used as a more effective selectable tool to conventional detection methods. With the introduction of Food Industry 4.0, HSI advances can change the meat industry to become from reactive to predictive when facing meat safety issues.