Desenvolvimento de narizes optoeletrônicos utilizando dispositivos analíticos para controle de qualidade em alimentos e óleos essenciais

Abstract

Optoelectronic noses are composed of multiple sensor elements that change color upon interaction with volatile species present in a mixture and are used to produce specific digital fingerprints for various types of samples. Their main application is the discrimination of complex samples, which depends on the appropriate choice of sensor elements, substrate, and image acquisition method. In this work, optoelectronic noses were developed and applied in two distinct scenarios: (i) discrimination of different essential oils and essences, including identification of adulterated samples; and (ii) monitoring the early stages of decomposition of bovine, swine, and chicken meats at room temperature. In the first application, the sensor array containing nine colorimetric reagents chosen for their different chemical properties was used to generate specific digital fingerprints of the volatile samples. Separation occurred rapidly, with only 5 minutes of exposure, and clusters based on chemical similarity between essential oils and essences were observed through hierarchical cluster analysis (HCA). Principal component analysis (PCA) revealed two well-defined groups, allowing identification of adulterated and non-adulterated samples. In the second application, the array consisted of ten pH indicators incorporated into a starch-based film, exposed to foods stored in closed jars for 48 hours. Perceptible changes in color patterns became evident after 21 hours, indicating the first signs of decomposition in the three types of meat. Chemometric analysis allowed discrimination not only of the meat type but also of different stages of deterioration, demonstrating the system’s potential for monitoring and quality control applications. In both cases, digital images before and after exposure to volatile compounds were obtained using a smartphone. RGB values were extracted using appropriate software, and the recorded color changes provided a unique digital color map fingerprint for each evaluated condition. The results demonstrate that the developed optoelectronic noses represent a promising tool for quality control, combining colorimetric sensors with digital analysis and multivariate statistics to differentiate complex samples and contribute to rapid monitoring of authenticity in essential oils and freshness in meat products.