Journal of Analytical Methods in Chemistry

1. Introduction

Natural antioxidants present in the diet have evidenced the increase of the resistance toward oxidative damages, and they may have a substantial impact on human health [1]. Furthermore, the use of natural extracts from plants as functional ingredients in food, beverage, and cosmetic applications is receiving a great deal of attention among scientists, as well as among consumers and food manufacturers [2]. Recently, there has been a renewed interest in natural product research due to the failure of alternative drug discovery methods to deliver many lead compounds in key therapeutic areas such as immune suppression, anti-infectives, and metabolic diseases [3]. Despite competition from other drug discovery methods, natural products are still providing their fair share of new clinical candidates and drugs [3]. We can find several natural products as sources of new drugs that have been recently reviewed in literature [4–7].

The olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product [8]. Considered as by-products of olive farming, olive tree leaves represent a significant material arriving to the olive mill [9]. They have been considered for centuries as an important herbal remedy in Mediterranean countries. Their positive effects on human health are multiple: antioxidant [10–16], hypoglycemic [17], antimicrobial [18], and anticancerous [19–22] among others. These properties are generally attributed to the presence of a range of compounds, such as secoiridoids, triterpenes, lignans, and flavonoids. It has been reported that by-products can have a similar or even higher proportion of bioactive compounds than the usable parts of produce [23]. For instance, the characterization and quantification of bioactive compounds is one of the first steps to be taken in any evaluation of the putative contribution of the olive and its derivatives to human health [24] since the chemical composition of olive tree leaves varies depending on several conditions such as origin, proportion of branches on the tree, storage conditions, climatic conditions, moisture content, and degree of contamination with soil and oils [25]. Recently, the effects of abiotic and biotic factors on the phenolic composition in olive tree leaves have been reviewed in literature [26]. Biotic factors such as genotype, load bearing, leaves age, and fungi and bacteria attacks as well as abiotic factors such as hydric deficiency, salinity, fertilization, sampling time, geographical zone, and climatic conditions influence the contents of phenolic compounds [26]. Recent researches revealed the impact of the geographical location on the total phenolic composition of olive leaves [27–30]. However, the data on the variation of the individual phenolic compounds in olive leaves are scarce. According to our knowledge, this is the first study on the phenolic compounds in olive tree leaves from Tunisian cultivars according to the geographical region.

Considering the importance of phenolic compounds in olive leaves, their determination and the scarce literature related to their behavior according to geographical origin, the aim of this study was to explore the phenolic composition of the leaves from the Tunisian olive cultivar “Chemlali” from different localities. This cultivar was chosen since it is widespread throughout Tunisia from the north to the south.

2. Materials and Methods

2.1. Sample Collection and Preparation of Extracts

Fresh olive leaves from the Tunisian “Chemlali” cultivar were obtained at the time of olive pruning from different regions from Tunisia (north, center, and south from coastal and mountainous areas) (available here). Leaves were dried at 25°C, ground, and then 1 g of the obtained homogenized powder was dissolved in 10 mL of methanol : water 80% (), and the mixture was allowed to stand in the dark for 24 h [31]. The extract was centrifuged at 5000 g for 10 min at room temperature, and the supernatants were then filtered using a 0.45 µm syringe filter to be analyzed by high-performance liquid chromatography (HPLC).

2.2. Chromatographic Separation of Phenolic Compounds

An Agilent 1200 HPLC system (Agilent Technologies, Waldbronn, Germany) equipped with a vacuum degasser, autosampler, a binary pump, and a DAD detector was used for the chromatographic determination. Phenolic compounds were separated by using an Agilent Eclipse Plus C18-column (4.6 × 150 mm, 1.8 mm particle size) operating at 25°C and a flow rate of 0.8 mL/min. The mobile phases used were water with acetic acid (0.5%) (phase A) and acetonitrile (phase B), and the solvent gradient changed according to the following conditions: 0 to 10 min, 5–30% B; 10 to 12 min, 30–33% B; 12 to 17 min, 33–38% B; 17 to 20 min, 38–50% B; and 20 to 23 min, 50–95% B. Finally, the B content was decreased to the initial conditions (5%) in 2 min, and the column reequilibrated for 10 min. A volume of 10 mL of the extracts was injected. The separated compounds were monitored in sequence first with a diode-array detector (DAD) at 240 and 280 nm and then with a mass spectrometry (MS) detector.

2.3. Time of Flight and Ion Trap Mass Spectrometry Detection

The HPLC system was firstly coupled to a Bruker Daltonics micrOTOF mass spectrometer (Bruker Daltonics, Bremen, Germany) using an orthogonal electrospray interface. The mass spectrometer was operated in the negative ionization mode and acquired data in the mass range from m/z 50 to 1000 with a spectra rate of 1 Hz. The capillary was set at +4 kV, the end plate offset at −500 V, the nebulizer gas at 2 bar, and the dry gas at 9 L/min at 250°C. The accurate mass data of the molecular ions were processed through the software data analysis and target analysis 4.0 (Bruker Daltonics). External mass spectrometer calibration was performed using a Cole-Parmer syringe pump (Vernon Hills, Illinois, USA) directly connected to the interface, equipped with a Hamilton syringe (Reno, Nevada, USA). The standard solution was injected at the beginning of the run, and all the spectra were calibrated prior to phenolic compounds’ identification. Then, the same HPLC system was coupled to a Bruker Daltonics Esquire 2000 ion trap mass spectrometer (Bruker Daltonics, Bremen, Germany) equipped with an electrospray interface (Agilent Technologies, CA, USA) operating in the negative ionization mode. The ion trap scanned at the 50–1000 m/z range at 13000 µ/s during the separation and detection. The maximum accumulation time for the ion trap was set at 200 ms, the target count at 20000, and compound stability was set at 50%. The optimum values of the ESI-MS parameters were as follows: capillary voltage, +3.0 kV; drying gas temperature, 300°C; drying gas flow, 7.0 L/min; and nebulizing gas pressure, 21.7 psi. The instrument was controlled by Esquire NT software from Bruker Daltonics. Peak identification was performed on the basis of their relative retention time values, TOF-MS and IT-MS/MS data, comparison with authentic standard solutions, and using the information previously reported in the literature [32]. Limits of detection (LOD) and quantification (LOQ) were respectively as follow: 0.09 and 0.3 ppm for hydroxytyrosol, 0.31 and 1.03 ppm for tyrosol, 0.02 and 0.06 ppm for luteolin, and 0.02 and 0.06 ppm for apigenin.

2.4. Radical-Scavenging Capacity (RSC)

The olive leaf samples were analyzed for their capacity to scavenge the stable DPPH^• radical [33]. A volume of 3 mL of a freshly prepared DPPH solution (10⁻⁴ M in methanol) was added to 0.5 mL of the polar extract. The reaction mixture was shaken vigorously for 10 s in a vortex apparatus and then maintained in the dark for 20 min, after which a steady state was reached. The absorbance of the mixture was measured at 515 nm against a blank solution (without radical). A control sample (without olive leaf extract) was prepared and measured. The RSC toward DPPH^• was expressed as the % reduction in DPPH^• concentration by the constituents of the oils: % [DPPH^•] red = 100∗(1 – [DPPH^•]₂₀/[DPPH^•]₀) where [DPPH^•]₀ and [DPPH^•]₂₀ were the concentrations of DPPH^• in the control sample () and in the test mixture after the 20-minute reaction, respectively.

2.5. Statistical Analysis

Statistical analysis was performed by means of XLSTAT for Windows. Data are given as means of triplicates. Hierarchical cluster analysis (HCA) was performed using Ward’s method based on Euclidean distance.

3. Results and Discussion

3.1. HPLC-MS Analysis of the Olive Leaf Extract

The base peak chromatogram (BPC) of “Chemlali” olive leaf extract and the compounds characterized in the negative ion mode are shown in Figure 1. Peak identification was carried out using Target Analysis software (Bruker Daltonics), by comparing both migration time and accurate MS and MS/MS spectral data obtained from olive leaf samples and commercial standards, together with the information previously reported in the literature.