Meat spoilage is a very complex combination of processes related to bacterial activities. Numerous efforts are underway to develop automated techniques for monitoring this process. We selected a panel of pH indicators and a colourimetric dye, selective for thiols. Embedding these dyes into an anion exchange cellulose sheets, i.e., the commercial paper sheet known as “Colour Catcher®” commonly used in the washing machine to prevent colour run problems, we obtained an array made of six coloured spots (here named Dye name-CC@). The array, placed over the tray containing a sample of meat or fish (not enriched at any extend with spoilage products), progressively shows a colour change in the six spots. Photos of the array were acquired as a function of time, RGB indices were used to follow the spoilage, Principal Component Analysis to model the data set. We demonstrate that the array allows for the monitoring the overall spoilage process of chicken, beef, pork and fish, obtaining different models that mimic the degradation pathway. The spoilage processes for each kind of food, followed by the array colour evolution, were eventually compared using three-way PCA, which clearly shows same degradation pattern of protein foods, altered only according to the different substrates.

This work presents a colorimetric dye-based array for naked-eye detection of chicken meat spoilage. The array is obtained by fixing five acid−base indicators, m-cresol purple (1), o-cresol red (2), bromothymol blue (3), thymol blue (4), and chlorophenol red (5), and a sensing molecule specific for thiols, 5,5′-dithiobis(2-nitrodibenzoic acid), called Ellman's reagent (6), on a cellulose-based support. The dyes, being permanently charged, are fixed on the support via ion-exchange. The entire degradation process of beast poultry meat, at ambient temperature and in a domestic fridge, is followed by the change of the color of the array, placed in the headspace over the meat samples. The device is set after selection of the most suitable starting form, which could be the acidic or the basic color of indicators, being the proper dye concentration and the dimension of the spots already established. Basing on sensors colors, we identified three levels of the degradation process of chicken meat, named SAFE, WARNING, and HAZARD. By instrumental analysis, we demonstrated that sensors response was correlated to volatile organic compounds (VOCs) composition in the headspace and, thus, to meat spoilage progress. We demonstrated that biogenic amines (BAs), commonly considered a critical spoilage marker, are indeed produced into the samples but never present in the headspace, even in traces, during the investigated time-lapse. The VOC evolution nevertheless allows one to assign the sample as WARNING and further HAZARD. Some indicators turned out to be more informative than others, and the best candidates for a future industrial application resulted in a bromothymol blue (3)-, chlorophenol red (5)-, and Ellman's reagent (6)-based array.

This work aims to develop an efficient sensing device to detect milk freshness when stored at typical home conditions. The synthesis of the pH-sensitive optode array, the experimental setup for milk freshness monitoring, and the optode array images acquisition procedure are presented. The employment of various chemometric tools on optode array RGB triplets to visualize, compare, and predict the spoilage of commercial types of milk is discussed. The conclusions drawn from multivariate analyses on optode colors were confirmed using different independent methods. Despite the apparent simplicity, the here proposed sensing device fulfills the requirements for both consumer-friendly naked-eye analysis and chemometrics-assisted prediction of milk freshness. Furthermore, the application of the sensing device on real milk samples during spoilage at home conditions represents a major step forward in the panorama of freshness indicators for dairy products.