Organic hempseed oil from the retail market: chemical profiling and multivariate analysis for label information assessment

Purpose Hempseed oil is a valuable emerging food product with recognized health positivity due to its composition. The paper aims to propose a multi-methodological chemical profiling of nine organic hempseed oil samples (different brands and prices) from the retail market, followed by multivariate data analysis. Design/methodology/approach Fatty acids, tocopherols, squalene, total carotenoids content, phenolic compounds, total phenolic content and anti-radical activity (DPPH center dot and ABTS center dot+ assays) were determined through chromatographic and spectrophotometric techniques. Multivariate (explorative and discriminant) analyses were applied to the profiling results to classify samples according to information claimed on the label, i.e. geographical origin (EU vs. non-EU), extraction procedure (cold-pressed vs. not cold-pressed) and price (lower or higher than 10 euro per 250 mL). Findings The chemical analysis confirmed the 3 to 1 ?-6:?-3 ratio and the excellent content in antioxidant species. However, no specific trend of results can be stressed. PCA (after variables selection) highlighted a natural grouping of samples, so three discriminant analyses were performed: kNN, Naive Bayes and LDA. The best classification efficiency was reached for the extraction procedure verification (93-100% correct classification), followed by geographical origin (83-94%) and prices (81.6-90%). Originality/value The integrated approach of chemical profiling coupled with multivariate analyses allowed the assessment of label information of the analyzed organic hempseed oil samples, despite the wide heterogeneity of the selected samples.

Automated summary

This paper proposes a multi-methodological chemical profiling and multivariate data analysis of organic hempseed oil samples from the retail market. The result of the analysis confirmed the ideal fatty acid ratio and excellent content of antioxidant species in the hempseed oil. The study also utilized discriminant analyses to classify samples according to label information, achieving high classification efficiency for extraction procedure verification, geographical origin, and prices.