Oleoresin samples collected directly from living-trees by three different tapping methods, and from four geographical origins were analyzed using two gas chromatography (GC) methods. The GC was coupled to a flame ionization detector (GC-FID) for quantification, and to a mass spectrometer (GC-MS) for identifying the chemical composition. Twenty-eight chemical components were detected and quantified. The proportions of each chemical component varied exceedingly between different samples, and other associated factors. The specific sample traits, including Pinus species, tapping method and geographical origin differentiated the sample batches. Notwithstanding, the main chemical components present in all the characterized samples are α-pinene and β-pinene. Statistical analysis demonstrated that the majority of molecules are of significant importance to sample traits. Moreover, the statistical analysis allows for the identification of the biomarkers associated with the sample traits. Additionally, Linear Discriminant Analysis models have shown very good performance in classifying samples based on the sample traits. Furthermore, the biomarkers allowing the establishment of differences between geographical origins are sativene, camphene, limonene, isopimaric acid and pimarinal, whereas the differentiation between tapping methods is established by sativene, pimaric acid, β-phellandrene, isopimaric acid, retinol and camphene, and lastly biomarkers allowing the differentiation between Pinus species are palustric acid, limonene, β-pinene and sativene.