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.

An innovative smart label for naked-eye protein food freshness evaluation, based on polymeric sensing films, is presented. The proposed device consists of six miniaturized sensors, obtained by covalently binding six pH indicators, namely, mcresol purple (1), o-cresol red (2), bromothymol blue (3), thymol blue (4), chlorophenol red (5), and bromophenol blue (6), to an ethylene vinyl alcohol (EVOH) copolymer. All of the synthetic procedures for the functionalized polymers and their application as smart labels are thoroughly described and discussed. The innovative sensors are characterized using several instrumental techniques (DSC, FT-IR, EDX, SEM, and UV−vis). The application of the array of sensors to poultry meat and cod fillet spoilage monitoring by naked-eye evaluation and modeling by PCA is presented. Eventually, the composition of the food and the food's headspace in the selling tray is investigated and qualitatively characterized to validate the attributes of the array of sensors. The polymeric devices seem to be very promising for industrial scale-up, with the starting EVOH copolymer being extrudable and already employed in food packaging, as well as for large-scale application, being clear, efficient, and easy to read, even by untrained people.

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 review illustrates various types of polymer and nanocomposite polymeric based sensors used in a wide variety of devices. Moreover, it provides an overview of the trends and challenges in sensor research. As fundamental components of new devices, polymers play an important role in sensing applications. Indeed, polymers offer many advantages for sensor technologies: their manufacturing methods are pretty simple, they are relatively low-cost materials, and they can be functionalized and placed on different substrates. Polymers can participate in sensing mechanisms or act as supports for the sensing units. Another good quality of polymer-based materials is that their chemical structure can be modified to enhance their reactivity, biocompatibility, resistance to degradation, and flexibility.

The rationale behind the material and dye selection and the investigation of the properties of a solid-phase sensor array designed for following chicken meat spoilage is presented, having in mind that the final target must be the naked eye identification of the degradation steps. The device 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 commercial cellulose-based support. The dimensions of the sensor and the amount of dye sorbed on the solid are carefully studied. The preparation protocol to get reproducible sensing materials is established, based on the kinetic study and the color change investigation. The material stability and the capacity of changing color, according to the acid–base properties of the dyes, are tested. The sources of uncertainty, coming from the technique employed for signal data acquisition and treatment and from the intrinsic variability of the spots based on the commercial support, are established. The highest variability does not come from photo acquisition by a mobile phone, the effect of the illumination equipment, the partial least-squares (PLS) model employed to assess the amount of dye sorbed into the solid but from the variability of different spots and was found equal to 10%. The uncertainty is adequate for final employment since it is referred to as replicates under different conditions that are definitively judged almost always identical by naked eye evaluation, which is our last target for assessing a change of the colors associated with spoilage.

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.

No abstract

Gold and Silver nanoparticles (AuNPs and AgNPs) are perfect platforms for developing sensing colorimetric devices thanks to their high surface to volume ratio and distinctive optical properties, particularly sensitive to changes in the surrounding environment. These characteristics ensure high sensitivity in colorimetric devices. Au and Ag nanoparticles can be capped with suitable molecules that can act as specific analyte receptors, so highly selective sensors can be obtained. This review aims to highlight the principal strategies developed during the last decade concerning the preparation of Au and Ag nanoparticle-based colorimetric sensors, with particular attention to environmental and health monitoring applications.