Exploring the volatile metabolome of conventional and organic walnut oils by solid-phase microextraction and analysis by GC-MS combined with chemometrics. (30th November 2021)

• Record Type: Journal Article
• Authors: Kalogiouri, Natasa P.; Manousi, Natalia; Rosenberg, Erwin; Zachariadis, George A.; Paraskevopoulou, Adamantini; Samanidou, Victoria
• Is Part Of: Food chemistry. Volume 363(2021)
• Publication Date: 2021-11-30
• Subjects: Walnut oils -- SPME -- GC-MS -- Organic farming -- sPLS-DA, authenticity; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.130331
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Optimization of a HS-SPME-GC-MS methodology to investigate walnut oils' volatile profile. Discrimination between organic and conventional walnut oils. Development of a sPLS-DA model with high prediction accuracy. Establishment of characteristic volatile markers. Abstract: It is challenging to establish a correlation between the agronomical practices and the volatile profile of high-value agricultural products. In this study, the volatile metabolome of walnut oils from conventional and organic farming type was explored by HS-SPME-GC-MS. The SPME protocol was optimized after evaluating the effects of extraction time, extraction temperature, and sample mass. The optimum parameters involved the extraction of 0.500 g walnut oil at 40 °C within 60 min. Twenty Greek walnut oils produced with conventional and organic farming were analyzed and 41 volatile compounds were identified. The determined compounds were semi-quantified, and further processed with chemometrics. Agglomerative hierarchical clustering (AHC) and principal component analysis (PCA) were used. A robust classification model was developed using sparse partial least squares–discriminant analysis (sPLS-DA) for the discrimination of walnut oils into conventional and organic, establishing volatile markers that could be used to guarantee the type of farming.