Timely way to assess lamb quality

With the improvement of living standards, people are increasingly demanding higher meat quality.

Research shows that intramuscular fat (IMF) has a strong correlation with meat quality. However, measuring intramuscular fat is usually conducted by laboratories, which is currently impractical for individuals to do. 

Conventionally, meat quality appraisal is assessed by visual inspection and chemical analysis, which has the disadvantages of being subjective and time‐consuming. We want to make it easier to determine IMF. The goal of our project is to develop a supervised learning method for estimating lamb IMF using deep learning. We expect our model to achieve an 85% accuracy on the basis of our test dataset.

Transforming technologies


Computer Science

Yinhao Deng

vote for this project: TT70

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