Monitoring of chicken meat freshness by means of a colorimetric sensor array

TLDR

A new optoelectronic nose was developed to monitor chicken meat ageing. The system uses a 16‑pigment array incorporating diverse dyes into inorganic supports, with chromogenic data analyzed by PCA and PLS to build a predictive ageing model. Colour changes in the array reliably tracked chicken ageing, with PCA and PLS analyses achieving high predictive accuracy and demonstrating the system’s feasibility for monitoring food freshness.

Abstract

A new optoelectronic nose to monitor chicken meat ageing has been developed. It is based on 16 pigments prepared by the incorporation of different dyes (pH indicators, Lewis acids, hydrogen-bonding derivatives, selective probes and natural dyes) into inorganic materials (UVM-7, silica and alumina). The colour changes of the sensor array were characteristic of chicken ageing in a modified packaging atmosphere (30% CO2–70% N2). The chromogenic array data were processed with qualitative (PCA) and quantitative (PLS) tools. The PCA statistical analysis showed a high degree of dispersion, with nine dimensions required to explain 95% of variance. Despite this high dimensionality, a tridimensional representation of the three principal components was able to differentiate ageing with 2-day intervals. Moreover, the PLS statistical analysis allows the creation of a model to correlate the chromogenic data with chicken meat ageing. The model offers a PLS prediction model for ageing with values of 0.9937, 0.0389 and 0.994 for the slope, the intercept and the regression coefficient, respectively, and is in agreement with the perfect fit between the predicted and measured values observed. The results suggest the feasibility of this system to help develop optoelectronic noses that monitor food freshness.