Live lamb classification method based on fat, sex, and weight using ultrasound images to optimise slaughter decision-making

There are factors that affect the quality of the meat that we consume. Feeding, activity during growth, or even the stress suffered by the animal are examples of such factors that can affect the quality or even taste of the product. In the case of lamb, it has been observed that one of these factors is the amount of fat in the final product. The fat content of the meat affects the quality of the product both in terms of sale and consumption, and consequently the price of the product. Although ultrasound can estimate fat content in live animals, its routine commercial application for pre-slaughter classification remains limited due to cost, required expertise, and equipment availability. To solve this problem, this research article proposes a system to block the lamb in order to capture an image of the lamb’s fat using an ultrasound scanner. For this purpose, images of the fat in the lumbar region of 151 lambs have been analysed and compared with the actual measurement after slaughter. With the use of different image processing techniques it is possible to measure the fat of a live lamb and, in this way, to classify the lambs according to their level of fat into: Non-fat, Little covered, Covered, Fatty and Very fatty. This device is designed to be part of a lamb handling chute. Thus, in addition to sex and weight, a new classification variable is added to control meat quality and optimise the farmer profit without compromising animal welfare