Fabricating a novel colorimetric-bionic sensor coupled multivariate calibration for simultaneous determination of myoglobin proportions in pork

The quality of pork meat is of considerable importance as one of the principal sources of proteins. The study proposed the quantification of myoglobin proportions (deoxymyoglobin, oxymyoglobin and metmyoglobin) in pork meat by exploring the feasibility of colorimetric-bionic sensor array combined with efficient variable selection algorithms. Specifically, a novel colorimetric-bionic sensor array consists of nine chemically responsive dyes was fabricated. Subsequently, multivariate calibration algorithms such as partial least square (PLS), uninformative variable elimination-PLS (UVE-PLS), bootstrapping soft shrinkage-PLS (BOSS-PLS) and random frogPLS (RF-PLS) were applied and appraised. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) were used for the performance appraisal of the models. Optimum results were noticed with RF-PLS for myoglobin proportions (0.8412 < Rp<0.9484, 1.69 < RMSEP<3.79, and 1.68 < RPD<3.14). Therefore, this study proved that the colorimetric-bionic sensors array combined with RF-PLS could be used for rapid, simple, and non-destructive detection of quality in pork meat.

Automated summary

This study quantified myoglobin proportions in pork meat by combining a colorimetric-bionic sensor array with the RF-PLS algorithm, demonstrating its potential for rapid and non-destructive quality detection in pork meat.