Valorization of hemp seed meal, a byproduct of hemp oil processing, was performed by measuring the distribution of nutritional and antinutritional compounds in different hemp seed meal fractions. According to chemical composition, two cotyledon-containing fractions (>180 and <180 μm) were significantly richer in protein (p < 0.05) (41.2% ± 0.04% and 44.4% ± 0.02%, respectively), lipid (15.1% ± 0.02% and 18.6% ± 0.04%, respectively), and sugar content (4.96% ± 0.11% and 3.46% ± 0.08%, respectively) in comparison to the hull-containing fractions (>350 and >250 μm), which were significantly richer in crude fiber content (29.5% ± 0.04% and 21.3% ± 0.03%, respectively). The free radical scavenging capacity (IC50) of fraction extracts increased (p < 0.05) with increasing mean particle size (from 17.18 ± 0.59 to 5.29 ± 0.30 mg/mL). Cannabisin B and N-trans-caffeoyltyramine were the most abundant phenolic compounds in the hull fractions (from 267 ± 15.9 to 287 ± 23.1 mg/kg), while cotyledon fractions had higher content of catechin (from 313 ± 12.4 to 744 ± 22.2 mg/kg) and p-hydroxybenzoic acid (from 124 ± 6.47 to 129 ± 8.56 mg/kg (P < 0.05). Well-balanced ω-6 to ω-3 fatty acid ratio (3:1) was determined in all fractions. Antinutrients (trypsin inhibitors, phytic acid, glucosinolates, and condensed tannins) were mostly located in the cotyledon fractions. These findings indicate that the separation of hemp seed meal into different fractions could be used to concentrate valuable target compounds and consequently facilitate their recovery.

Abstract:© Versita Sp. z o.o. Keywords: Plant phenolics • Rapid Resolution HPLC • Medicinal plantRapid Resolution HPLC/DAD method, on a 1.8 μm, 4.6×50 mm column, was developed to enable a rapid separation of a mixture of 17 compounds, which consisted of hydroxybenzoic acids, hydroxycinnamic acids, flavones, flavonols, flavanone, flavonol-glycoside and antraquinone, in a single run, within 22 minutes. The developed method is precise, accurate and sensitive enough for simultaneous quantitative evaluation of major compounds in crude and hydrolyzed extracts of parsley, buckthorn, mint, caraway and birch. In order to overcome the inability to quantify all the phenolic compounds present in the samples caused by lack of external standards, HPLC approaches for the total phenolic content estimation based on sum of all integrated peak areas were made. These results were compared with the total phenolic content determined by Folin-Cioacalteu method. Although the correlation between the series of data was not significant (p<0.05), the difference between the results of total phenolic content obtained spectrophotometrically and by HPLC was not high in the case of parsley, buckthorn and mint extract. Regarding the obtained results, the HPLC approach could serve as an excellent tool for total phenolic content estimation, without the need for complete identification of the individual compounds.

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Microalgal biomass can be used in creating various functional food and feed products, but certain species of microalgae and cyanobacteria are known to produce various compounds causing off-flavour. In this work, we investigated selected cyanobacterial strains ofSpirulina,Anabaena, andNostocgenera originating from Serbia, with the aim of determining the chemical profile of volatile organic compounds produced by these organisms. Additionally, the influence of nitrogen level during growth on the production of volatile compounds was investigated forNostocandAnabaenastrains. In addition, multivariate techniques, namely, principal component analysis (PCA) and hierarchical cluster analysis (HCA), were used for making distinction among different microalgal strains. The results show that the main volatile compounds in these species are medium chain length alkanes, but other odorous compounds such as 2-methylisoborneol (0.51–4.48%), 2-pentylfuran (0.72–8.98%),β-cyclocitral (0.00–1.17%), andβ-ionone (1.15–2.72%) were also detected in the samples. Addition of nitrogen to growth medium was shown to negatively affect the production of 2-methylisoborneol, while geosmin was not detected in any of the analyzed samples, which indicates that the manipulation of growth conditions may be useful in reducing levels of some unwanted odor-causing components.

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Abstract-In this paper, we present an efficient Artificial Neural Network (ANN)-based model to estimate both azimuth and elevation arrival angles of a signal source. To achieve this goal, the ANN model is constructed using measurement data obtained by a rectangular antenna array in the space-frequency domain. Unlike classical superresolution algorithms such as 2D MUSIC, the proposed model is capable to account for imperfections of measurement equipment as well as mutual couplings between array elements. The neural model has been verified for several angular positions and frequencies. It is shown that the use of ANN model to estimate angular positions of a signal source yields more accurate results when compared to 2D MUSIC. Moreover, the neural model significantly outperforms 2D MUSIC in terms of speed of computation.

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