Metabolomic Analysis of Cannabinoid and Essential Oil Profiles in Different Hemp (Cannabis sativa L.) Phenotypes.

Hemp (Cannabis sativa L.) cannabinoids and terpenoids have therapeutic effects on human and animal health. Cannabis plants can often have a relatively high heterogeneity, which leads to different phenotypes that have different chemical profiles despite being from the same variety. Little information exists about cannabinoid and terpenoid profiles in different hemp phenotypes within the same variety. For this study, 11 phenotypes from three different varieties ("Carmagnola" selected (CS), "Tiborszallasi" (TS), and "Finola" selection (FS)) were analyzed. The components of essential oil (29) were analyzed using gas chromatography with flame ionization detection (GC/FID), and 10 different cannabinoids of each phenotype were determined using high-performance liquid chromatography (HPLC). Principal component analysis (PCA) and analysis of variance (ANOVA) showed that according to the components of essential oil, FS and TS plants were more uniform than CS plants, where there were great differences between CI and CII phenotypes. The content of cannabinoid CBD-A was the highest in all four FS phenotypes. By comparing cannabinoid profiles, FS was clearly separated from TS and CS, while these two varieties were not clearly distinguishable. Phenotypes TV and CI had the highest total content of Δ-9-THC, while all phenotypes of FS had the highest total content of CBD. The highest total content of CBG was determined in phenotype CI. Obtained results are useful for the development of new supplementary ingredients, for different pharmacy treatments, and for further breeding purposes.

Comparison of sensory and chemical evaluation of lager beer aroma by gas chromatography and gas chromatography/mass spectrometry.

BACKGROUND: Although the evaluation of beer is conducted by sensory experts, we cannot neglect the influence of human factors and subjectivity. This problem could be solved by the chemical analysis of the volatile part of beer aroma and, from this, we can build a database for the construction of a model that classifies samples in a comparable manner to sensory assessment. RESULTS: Twenty-two batches of the same beer brand were assessed by sensory evaluation and described chemically in terms of the contents of alcohols and esters (n = 9), hop essential oil compounds (n = 15) using gas chromatography (GC) and other aroma volatiles (n = 33) as analysed by head space solid-phase microextraction (SPME)-GC/mass spectrometry. The best match of 91% with respect to sample classification on the basis of chemical analyses to sensory scores was achieved with a dataset of results from headspace-SPME and analyses of higher alcohols and esters by regularized discriminant analysis. CONCLUSION: The results of the present study show that deviations in beer aroma are not a consequence of a permanent repeatable error in brewing process, nor are they influenced by raw materials, but, instead, they are a consequence of alcoholic fermentation. Sensory analysis could be replaced with chemical/statistical analysis on an appropriate data set and for a distinct beer brand. The good results achieved confirm our approach; however, for different beer brands or types, this method should be optimised. © 2017 Society of Chemical Industry.

Application of total reflection X-ray spectrometry in combination with chemometric methods for determination of the botanical origin of Slovenian honey.

This work on the botanical origin of various types of honey produced in Slovenia and based on the mineral content analyses by the total reflection X-ray spectrometry (TXRF) is a continuation of this group's preliminary work (Golob, T.; Dobersek, U.; Kump, P.; Necemer, M. Food Chem. 2005, 91, 593-600), which introduced the analytical methodology and employed only a simple statistical evaluation and which examined the possibility to determine the botanical origin of honey samples via elemental content. A much more comprehensive study on a total of 264 major types of honey samples harvested in 2004, 2005, and 2006 and interpreting the results with up to date chemometric methods was performed in this work. Slovenia is a small country by surface area, but it is pedologically and climatically diverse, therefore offering interesting possibilities for studying the influence of these diversities on the elemental content of natural products. By employing principal component analysis (PCA) and regularized discriminant analysis (RDA) it was established that from all of the measured elements only the four characteristic key elements Cl, K, Mn, and Rb could be used to best discriminate the types of honey. It was established that the employed combination of a simple, fast, and inexpensive multielement TXRF analytical approach and the evaluation of data by chemometric methods has the potential to discriminate the botanical origins of various types of honey.

Density functional calculation of the 2D potential surface and deuterium isotope effect on 13C chemical shifts in picolinic acid N-oxide. Comparison with experiment.

2D free energy surfaces V = V(rOH, rO...O) for the intramolecular H-bond in the title compound were calculated by the DFT method and used in the calculation of primary and secondary chemical shifts of the compound dissolved in chloroform and acetonitrile. Solvent effects were accounted for by the SCRF/PCM method. The corresponding two-dimensional chemical shift surfaces with included solvent reaction field were obtained using the Continuous Set of Gauge Transformations approach at the B3LYP/6-311+G(2d,2p) level of theory. The chemical shifts were estimated as quantum averages along the two internal coordinates in the hydrogen bond and along several vibrational levels according to the Boltzmann distribution at room temperature. Fairly good agreement between the experimental and calculated isotope effects was obtained. 1D and 2D NMR spectra of solutions of picolinic acid N-oxide and its deuterated analogue were recorded and assigned.

Chemometric classification of Apulian and Slovenian wines using 1H NMR and ICP-OES together with HPICE data.

High-performance ion chromatography exclusion, inductively coupled plasma emission spectroscopy, and nuclear magnetic resonance (NMR) measurements were carried out in combination with chemometrics on 33 wine samples coming from three Slovenian wine-growing regions and from Apulia (southern Italy). The chemometric classification of wines according to their geographical origin was obtained with a nearly 100% degree of achievement. The discriminating potential of the (1)H NMR and of the other analytical determinations has been estimated separately. The best prediction of wines has been obtained with NMR data.