Geoclimatic, morphological, and temporal effects on Lebanese olive oils composition and classification: A ¹H NMR metabolomic study

Highlights

• Classification of olive oils based on morphological traits of olives was performed.

• Olive oils were discriminated at subregional level by following a sequential strategy.

• Harvest date and year effects on olive oils and their classifications were determined.

• Interferences between the factors affecting the olive oil matrix were described.

Abstract

Two hundred and thirty-four Lebanese olive samples were collected from different regions and the corresponding oils were analysed by ¹H NMR spectroscopy. The variables obtained, related to fatty acids and minor components, were used as inputs in univariate and multivariate analyses aiming to characterize and classify the oils according to geographical, morphological, and temporal factors. Samples were sorted according to the colour, size, and shape of olives, which allowed statistically significant classifications to be achieved. A sequential strategy was developed to discriminate among samples from different altitudes and latitudes. Following this strategy, obvious trends and classifications were obtained at subregional level. Furthermore, the shift in the harvest date within a range of three weeks was considered and its effect on the classification models was investigated. Likewise, the harvest year effect was evaluated; the precipitation level in April and May had a significant impact on the characteristics of the oils.

Introduction

Olive oil is a fundamental food ingredient recognized for its nutritional qualities and potential health benefits owed not only to its high oleic acid and antioxidant contents but also to its uniquely high level of squalene, which is known to have an anticancer activity (Waterman & Lockwood, 2007), as well as oleocanthal, a secoiridoid phenolic compound with potential therapeutic properties against inflammation, cancer, and neurodegenerative diseases (Parkinson & Russell, 2014). It is well established that the organoleptic properties of olive oil, which are strongly correlated to its geographical and varietal origins (Perri, Benincasa, & Muzzalupo, 2012, Chapter 13), are behind its wide commercialization and elevated market value. These features of olive oil are affected by several factors, such as variety of olives, geoclimatic conditions of the olive grove, and agricultural practices. In this context, the designation of olive oils according to their origin (e.g., “protected designation of origin” and “protected geographical indication”) has become primary in labelling information, prompting the need for affordable and accurate analytical methods for authentication (Perri et al., 2012). ¹H NMR spectroscopy can be used as a powerful tool for rapid quantification of fatty acids as well as minor components (e.g., squalene and phenolic compounds) without the need for any sample treatment (Dais & Hatzakis, 2013). Many studies using ¹H NMR spectroscopy in combination with statistical tools have been performed to characterize and classify olive oils according to the variety (Sacchi et al., 1996) and geographical origin of olives (Alonso-Salces et al., 2010, Alonso-Salces et al., 2015, D’Imperio et al., 2007, Longobardi et al., 2012, Mannina et al., 2010, Mannina et al., 2001, Petrakis et al., 2008, Sacchi et al., 1998, Sacco et al., 2000). However, varietal and geographical characteristics of Lebanese olive oils, based on composition profiles, have not been investigated. Lebanon has a moderate Mediterranean climate, creating ideal conditions for olive trees cultivation. The Lebanese olive groves are almost exclusively based on non-irrigated native varieties that cover approximately 56,300 ha, or 5.4% of the country land mass. The productivity ranges from 1.5 to 3 metric tons of olives per hectare, depending on the harvest year, and the oil content varies from 18 to 25% (Investment Development Authority of Lebanon, 2014, Lebanese Ministry of Agriculture, 2003). Olive production is spread across the country but can be grouped mainly into northern and southern regions, each generating around 40% of the total crop. These two main regions are not readily differentiated in terms of their geoclimatic conditions, which complicates the regional classification of oils. Furthermore, an additional complication may arise due to the interference from varietal factors since the oils to be discriminated, based on geographical considerations, cannot be accurately sorted according to varieties beforehand. In some cases, a given variety cannot be determined due to morphological changes in response to different geoclimatic conditions and agricultural practices (Hagidimitriou, Katsiotis, Menexes, Pontikis, & Loukas, 2005). In this study, olive samples from northern, southern, and central regions of Lebanon were collected at different altitudes. ¹H NMR metabolomic profiling of the oils was used to obtain characteristic variables related to saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), linoleic and linolenic acids, as well as minor components. This set of variables was then treated by means of multivariate statistical procedures, notably the principal component analysis (PCA) and linear discriminant analysis (LDA), to characterize the oil samples according to their geographical origin (altitude and latitude) as a function of olive morphology (colour, size, and shape), taking into account the effects of the harvest date and year.