Ham quality control by means of fuzzy decision trees: A case study

Lean muscle color strongly influences consumer impressions of quality. A bright-reddish pork is sought as an ideal; some variation of color is normal as can be observed if different pork muscles are considered. However, muscle color changes quite easily, and as a result can be indicative of meat quality. Assessment of meat quality is crucial both in cooked ham and raw ham processing plants. A good meat classification system should allow porks of uniform meat to be processed in a uniform way. This would result in a uniform parcel of ham (cooked or raw) and reduce cost and rejects. In this paper we present a classification methodology of fresh pork meat based on computer vision color analysis techniques and fuzzy decision trees. The discussed methodology has been tested on site and the obtained classifications have been compared with human experts' ratings giving interesting results.