Application of PTR-MS to the Analysis of Volatile Organic Compounds from Cranberries as a Useful Tool for Sustainable Development

Volatile organic compounds (VOCs) emitted by cranberries from three locations were studied using a proton transfer reaction mass spectrometer (PTR-MS). Cranberries were collected from natural wetlands in a protected landscape (Łętowskie Lake and the Kępice area, northern Poland), from an allotment garden near Słupsk (northern Poland), and from a cranberry plantation (Poland). The collected samples showed statistically significant differences between the three studied cranberry sources, with samples from the garden differing significantly from those from plantations and wetlands. The results of multivariate analyses, such as cluster analysis, also indicated differences in the composition of VOCs responsible for cranberry aroma from different sources. Multivariate PCA revealed similarities between the volatile organic compound (VOC) emissions of cranberries from natural wetlands and plantations. Additionally, machine learning was used to classify cranberries collected from different sites. The classification accuracy of the MLP model for a limited number of variables was approximately 97% at the testing and validation level. This paper presents the potential application of PTR-MS to VOC emission studies, along with statistical analysis and machine learning, as an example of a potential tool for sustainable development in the study of edible fruit aromas.