Abstract
For several years, studies conducted for discovering tenderness biomarkers have proposed a list of 20 candidates. The aim of the present work was to develop an innovative methodology to select the most predictive among this list. The relative abundance of the proteins was evaluated on five muscles of 10 Holstein cows: gluteobiceps, semimembranosus, semitendinosus, Triceps brachii and Vastus lateralis. To select the most predictive biomarkers, a multi-block model was used: The Data-Driven Sparse Partial Least Square. Semimembranosus and Vastus lateralis muscles tenderness could be well predicted (R2 = 0.95 and 0.94 respectively) with a total of 7 out of the 5 times 20 biomarkers analyzed. An original result is that the predictive proteins were the same for these two muscles: µ-calpain, m-calpain, h2afx and Hsp40 measured in m. gluteobiceps and µ-calpain, m-calpain and Hsp70-8 measured in m. Triceps brachii. Thus, this method is well adapted to this set of data, making it possible to propose robust candidate biomarkers of tenderness that need to be validated on a larger population.
Highlights
As emphasized by many authors, tenderness is considered the most important qualitative characteristic of meat
If we focused in the present paper on the case L0 = 8 and R = 2, which makes it possible to minimize the mean of Mean Square Error in Prediction (MSEP), we studied cases where
It appears that the biomarkers selected for L0 = 4 are successively supplemented with 1, 2, 3 biomarkers when selecting a maximum of 5, 6, 7 biomarkers
Summary
As emphasized by many authors, tenderness is considered the most important qualitative characteristic of meat. Difficult to organize and time consuming [2]. These methods are invasive, and cannot be performed early enough to allow carcasses to be adapted to markets according to their level of tenderness. Previous works reviewed by Picard et al [5] made it possible to identify candidate biomarkers of tenderness. They belong to numerous biological pathways: heat shock proteins, oxidative and glycolytic metabolism, oxidative stress, muscle structure and contraction and proteolysis
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