Exploring the volatile metabolome of conventional and organic walnut oils by solid-phase microextraction and analysis by GC-MS combined with chemometrics

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 degrees 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.

Automated summary

The volatile metabolome of walnut oils from conventional and organic farming type was explored using HS-SPME-GC-MS, with 41 volatile compounds identified and processed using chemometrics. A robust classification model was developed to distinguish walnut oils into conventional and organic farming types.