Role of chemometric classification for future prediction: application on different geographical origins of Jordanian Guava

Abstract

In this study, the guava-origin fruits were collected from different cultivated regions in Jordan, then scanned using gas chromatography–mass spectrometry (GC-MS) to reveal the chemical constituents. The chemical contents were then used with the help of multivariate analysis to classify the regions. Guava fruit was collected from; Northern Shouneh-1, Northern Shouneh-2, Madaba, Saham Al-Kfarat, and Southern Shouneh. Hydrodistillation was implemented to extract the essential oils from guava fruits. Comprehensive chemical profiling of the extracted essential oils was achieved using (GC -MS). A total of thirty-eight chemical compounds have been detected and identified with variances from one region to another. Limonene, longifolene, β-copaene, and t-muurolo were found in high concentrations among the other detected compounds. The GC-MS data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to reveal the similarities/differences between guava fruit regions. The Northern Shouneh-1 and Madaba regions' fruits showed high similarity to each other due to the distinct contents of limonene and longifolene. On the other hand, cadinol was the main compound in Saham Kfarat and Southern Shouneh regions. Finally, Northern Shouneh-2 guava samples showed different content than other regions due to the distinguished levels of t-muurolol. Guava classification based on the GC-MS profile will meet the practical needs of its applications in food production and will contribute to the standardization of commercially available cultivars in Jordan.