Effects of Different Factors on Concentration of Functional Components of Aronia and Saskatoon Berries

Antioxidant, Enzyme Inhibitory, and Protective Effect of Amelanchier lamarckii Extract

The present study aimed to investigate the chemical content of Romanian juneberries (Amelanchier lamarckii), their effect on antioxidant and enzyme inhibition activities, and their bioaccessibility after simulated in-vitro digestion. In Amelanchier lamarckii extract (AME), 16 polyphenolic compounds were identified by LC-ESI+-MS analysis. The most representative compounds found in the extract were cyanidin-galactoside, 3,4-dihydroxy-5-methoxybenzoic acid, feruloylquinic acid, and kaempferol, all belonging to the anthocyanins, phenolic acids, and flavonols subclasses. The polyphenols of AME exert quenching abilities of harmful reactive oxygen species, as the CUPRAC antioxidant assay value was 323.99 µmol Trolox/g fruit (FW), whereas the FRAP antioxidant value was 4.10 μmol Fe2+/g fruit (FW). Enzyme inhibition assays targeting tyrosinase (IC50 = 8.843 mg/mL), α-glucosidase (IC50 = 14.03 mg/mL), and acetylcholinesterase (IC50 = 49.55 mg/mL) were used for a screening of AME's inhibitory potential against these key enzymes as a common approach for the discovery of potential antidiabetic, skin pigmentation, and neurodegenerative effects. The screening for the potential antidiabetic effects due to the α-glucosidase inhibition was performed in glucose-induced disease conditions in a human retinal pigmented epithelial cell experimental model, proving that AME could have protective potential. In conclusion, AME is a valuable source of phenolic compounds with promising antioxidant potential and metabolic disease-protective effects, warranting further investigation for its use in the nutraceutical and health industries.

Differentiation of Medicinal Plants According to Solvents, Processing, Origin, and Season by Means of Multivariate Analysis of Spectroscopic and Liquid Chromatography Data

Effects of processing and extraction solvents on antioxidant properties and other characteristics were evaluated for ten medicinal plant species originating from two different localities and two production years. A combination of spectroscopic and liquid chromatography techniques possessed data for multivariate statistics. Water, 50% (v/v) ethanol, and dimethyl sulfoxide (DMSO) were compared to select the most suitable solvent for the isolation of functional components from the frozen/dried medicinal plants. DMSO and 50% (v/v) ethanol were evaluated as more efficient for phenolic compounds and colorants extraction, while water was more useful for element extraction. Drying and extraction of herbs with 50% (v/v) ethanol was the most appropriate treatment to ensure a high yield of most compounds. The satisfactory differentiation of herbs (61.8-100%) confirmed the significant effect of the processing, geographical, and seasonal factors on target functional component concentrations. Total phenolic and total flavonoid compounds content, total antioxidant activity expressed as TAA, yellowness, chroma, and browning index were identified as the most important markers for medicinal plant differentiation.

Influence of Profiles and Concentrations of Phenolic Compounds in the Coloration and Antioxidant Properties of Gaultheria poeppigii Fruits from Southern Chile

Chaura (Gaultheria poeppigii) is a plant species native from Southern Chile, which produces a berry fruit with potential beneficial health effects due to its content of phenolic compounds. The qualitative and quantitative determination of the phenolic compounds from fruits of different colored genotypes (white-, pink- and red-colored) collected from the Osorno volcano and the Conguillío National Park (CNP) in southern Chile were analyzed by mass spectrometry (HPLC-DAD-ESI-MS/MS) and HPLC-DAD, respectively. The total content of phenolic compounds was evaluated by the Folin-Ciocalteu method, and its antioxidant activity by the CUPRAC, TEAC and DPPH methods. Four anthocyanins were detected, with glycosylated derivatives of delphinidin and cyanidin being the most abundant. Fruits with more coloration had higher anthocyanin concentrations. Six flavonols were detected, with quercetin derivatives being the most abundant. The highest concentration of total flavonols reached 0.41 mg g^-1 in red colored fruits. The profiles of phenolic compounds showed differences between fruits depending on both the color and the area of collection. Finally, it would be interesting to evaluate the genetic profiles of chaura to determine whether this variation in phenolics and colorations is dependent on the geographical location or dependent on the genotype of the plant.

A Simplified Climate Change Model and Extreme Weather Model Based on a Machine Learning Method

The emergence of climate change (CC) is affecting and changing the development of the natural environment, biological species, and human society. In order to better understand the influence of climate change and provide convincing evidence, the need to quantify the impact of climate change is urgent. In this paper, a climate change model is constructed by using a radial basis function (RBF) neural network. To verify the relevance between climate change and extreme weather (EW), the EW model was built using a support vector machine. In the case study of Canada, its level of climate change was calculated as being 0.2241 (“normal”), and it was found that the factors of CO2 emission, average temperature, and sea surface temperature are significant to Canada’s climate change. In 2025, the climate level of Canada will become “a little bad” based on the prediction results. Then, the Pearson correlation value is calculated as being 0.571, which confirmed the moderate positive correlation between climate change and extreme weather. This paper provides a strong reference for comprehensively understanding the influences brought about by climate change.