In this paper we describe the development of the first multiclass pesticide residue method applied to essential oils. A total of 70 pesticides covering a wide range of polarity and currently used on essential oil crops have been included in the method. The procedure consists of a 10-fold dilution of lavandin essential oil followed by a direct injection analysis by liquid chromatography/tandem mass spectrometry. The system used is an API 4000 QTrap equipped with an electrospray ionization interface and operating in scheduled selected reaction monitoring acquisition mode. Matrix effects were evaluated by comparing the slopes of matrix-matched and solvent-based calibration curves. Weak signal suppression or enhancement (<20%) was observed for most of the compounds. Method sensitivity was determined statistically by the injection of five matrix-matched calibration curves with the distribution's normality and the variance's homogeneity checked before establishment of a suitable regression model. Limits of detection (LODs) and quantification (LOQs) were then determined using the blank standard's deviation and the slope of the mean curve. The analytical method has been validated for 67 of the 70 pesticides and meets the following LOQs: ≤1 μg/L for 9 pesticides, ≤5 μg/L for 44, ≤10 μg/L for 9, and ≤20 μg/L for 5.

Metabolic profiling of Glycyrrhiza glabra using comprehensive two-dimensional liquid chromatography (LC × LC) coupled with photodiode array (PDA) and mass spectrometry (MS) detection is described. The separation was conducted under reversed-phase conditions, using a combination of first dimension ( D) 150 mm microbore cyano column utilising 2.7 μm diameter (d ) particles, and second dimension ( D) 50 mm superficially porous octadecylsilica column with 2.7 μm d particles. A multi-segmented shift gradient (MSG) for the D separation was developed, and the orthogonality achieved was compared with other modes of gradients, such as full in-fraction, and shift gradient systems. Results demonstrated a significant expansion of metabolic coverage using MSG in D, providing the highest measure of orthogonality compared to other gradient modes. Compound identifications were performed by employing complementary data from PDA and MS detection, with reference to structural group-type distribution in 2D space. A total of ca. 120 compounds were detected, and among them 37 were tentatively identified, distributed over the chemical families of glycosylated flavanones, triterpene saponins, and others. In comparison with one-dimensional LC, the total number of compounds detected was ca. 2-fold greater when LC × LC was employed. To the best of our knowledge, this is the first demonstration of the MSG mode in LC × LC, representing a powerful strategy to expand the metabolic coverage for analysis of plant-derived extracts, containing a multitude of different phytochemical classes.