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The present work aims to study the possibilities of developing silver nanoparticles using natural extracts of grape pomace wastes originating from the native variety of Fetească Neagră 6 Șt. This study focused on investigating the influence of grape pomace extract obtained by two different extraction methods (classical temperature extraction and microwave-assisted extraction) in the phytosynthesis process of metal nanoparticles. The total phenolic content of the extracts was assessed using the spectrophotometric method with the Folin–Ciocâlteu reagent, while the identification and quantification of specific components were conducted through high-performance liquid chromatography with a diode array detector (HPLC-DAD). The obtained nanoparticles were characterized by UV–Vis absorption spectroscopy, X-ray diffraction (XRD), and transmission electron microscopy (TEM), along with assessing their antioxidant and antimicrobial properties against Gram-positive bacteria. The data collected from the experiments indicated that the nanoparticles were formed in a relatively short period of time (96 h) and, for the experimental variant involving the use of a 1:1 ratio (v/v, grape pomace extract: silver nitrate) for the nanoparticle phytosynthesis, the smallest crystallite sizes (from X-ray diffraction—4.58 nm and 5.14 nm) as well as spherical or semispherical nanoparticles with the lowest average diameters were obtained (19.99–23 nm, from TEM analysis). The phytosynthesis process was shown to enhance the antioxidant properties (determined using the DPPH assay) and the antimicrobial potential (tested against Gram-positive strains) of the nanoparticles, as evidenced by comparing their properties with those of the parent extracts; at the same time, the nanoparticles exhibited a selectivity in action, being active against the Staphylococcus aureus strain while presenting no antimicrobial potential against the Enterococcus faecalis strain. [ABSTRACT FROM AUTHOR]

High performance liquid chromatography data related to the concentrations of 12 phenolic compounds in vegetative parts, measured at four sampling times were processed for developing prediction models, based on the cultivar, grapevine organ, growth stage, total flavonoid content (TFC), total reducing capacity (TRC), and total antioxidant activity (TAA). 12 Artificial neural network (ANN) models were developed with 79 input variables and different number of neurons in the hidden layer, for the prediction of 12 phenolics. The results confirmed that the developed ANN-models (R2 = 0.90 – 0.97) outperform the stepwise regression models (R2 = 0.05 – 0.78). Moreover, the sensitivity of the model outputs against each input variable was computed by using ANN and it was revealed that the key determinant of phenolic concentration was the source organ of the grapevine. The ANN prediction technique represents a promising approach to predict targeted phenolic levels in vegetative parts of the grapevine.

High performance liquid chromatography data related to the concentrations of 12 phenolic compounds in vegetative parts, measured at four sampling times were processed for developing prediction models, based on the cultivar, grapevine organ, growth stage, total flavonoid content (TFC), total reducing capacity (TRC), and total antioxidant activity (TAA). 12 Artificial neural network (ANN) models were developed with 79 input variables and different number of neurons in the hidden layer, for the prediction of 12 phenolics. The results confirmed that the developed ANN-models (R2 = 0.90 – 0.97) outperform the stepwise regression models (R2 = 0.05 – 0.78). Moreover, the sensitivity of the model outputs against each input variable was computed by using ANN and it was revealed that the key determinant of phenolic concentration was the source organ of the grapevine. The ANN prediction technique represents a promising approach to predict targeted phenolic levels in vegetative parts of the grapevine. [ABSTRACT FROM AUTHOR]

A study of the polyphenols content and antioxidant capacity of grapevine waste and hazelnut skins (roasted material) from post-harvest products that originate from Piedmont (Italy) has been carried out and the results herein presented. Ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) were used to achieve process intensification in shorter extraction times, with lower environmental impact and higher selectivity compared to classic maceration. Besides classic solvents, the aqueous β-cyclodextrin solution (1.5%) showed to be an excellent extraction medium for grapevine waste. Total phenolic content (TP) from grapevine waste ranged from 18.23±2.4 to 198±3mg gallic acid equivalents (GAE)/g dry weight, while total antioxidant capacity (TAC) expressed as EC50 ranged from 0.0902±0.08mg/mL to 0.0041±0.02mg/mL. For hazelnut skins, TP ranged from 61.68±0.8 to 200.79±3.0mg GAE/g dry weight, while TAC ranged from 0.0021±0.0004 to 0.0002±0.0001mg/mL extract. We have shown that, compared to maceration, the use of UAE and MAE methods can enhance polyphenols recovery and antioxidant capacity. [ABSTRACT FROM AUTHOR]

Abstract: Secondary phenolic metabolites play an important role in plant defense mechanisms and most of them are known to be valuable in human health. There are only few studies related to the significant role of various mycorrhizal fungi on changes taking place in their host secondary metabolites. Furthermore, grapevine pruning wastes were known as a potential source of high-value phytochemicals with respect to medicinal and antimicrobial properties. Total phenols and quercetin content of four Iranian grape (Vitis vinifera L.) varieties (Asgari, Khalili, Keshmeshi and Shahroodi) were investigated following inoculation with four arbuscular mycorrhizal fungi (AMF) strains (Glomus mosseae, Glomus fasciculatum and Glomus intraradices and a mixture of three species). Moreover, quercetin content of vegetative parts (leaf and stem tissues) was studied using a simple extraction and isocratic HPLC method. Additionally the effect of a common postharvest processing treatment (oven-drying) on the quercetin content of these grape varieties were also investigated. Higher levels of quercetin were consistently found in Keshmeshi (70.8μg/g FW) and Shahroodi (100.6μg/g FW) varieties following inoculation with G. mosseae. The non inoculated plants of the same varieties were found to produce only 35.7 and 16.3μg/g FW quercetin, respectively. Oven-drying did not affect the leaf quercetin content in none of samples except in Keshmeshi variety in which drying resulted to higher quercetin yield in comparison with fresh leaf tissues (72.4 vs. 37.0μg/g FW, respectively). The present study suggests that grapevine wastes are valuable sources for extraction of flavonoid quercetin which can also be further increased following inoculation with arbuscular mycorrhizal fungi. [Copyright &y& Elsevier]

High performance liquid chromatography data related to the concentrations of 12 phenolic compounds in vegetative parts, measured at four sampling times were processed for developing prediction models, based on the cultivar, grapevine organ, growth stage, total flavonoid content (TFC), total reducing capacity (TRC), and total antioxidant activity (TAA). 12 Artificial neural network (ANN) models were developed with 79 input variables and different number of neurons in the hidden layer, for the prediction of 12 phenolics. The results confirmed that the developed ANN-models ( R 2 = 0.90 - 0.97) outperform the stepwise regression models ( R 2 = 0.05 - 0.78). Moreover, the sensitivity of the model outputs against each input variable was computed by using ANN and it was revealed that the key determinant of phenolic concentration was the source organ of the grapevine. The ANN prediction technique represents a promising approach to predict targeted phenolic levels in vegetative parts of the grapevine.

Stilbene-enriched extracts from Vitis vinifera waste (cane, wood, and root) were characterized by UHPLC-MS. Eleven stilbenes were identified and quantified as follows: ampelopsin A, (E)-piceatannol, pallidol, (E)-resveratrol, hopeaphenol, isohopeaphenol, (E)-ε-viniferin, (E)-miyabenol C, (E)-ω-viniferin, r2-viniferin, and r-viniferin. The fungicide concentration inhibiting 50% of growth of Plasmopara viticola sporulation (IC 50 ) was determined for the extracts and also for the main compounds isolated. r-Viniferin followed by hopeaphenol and r2-viniferin showed low IC 50 and thus high efficacy against Plasmopara viticola. Regarding stilbene extracts, wood extract followed by root extract showed the highest antifungal activities. These data suggest that stilbene complex mixtures from Vitis vinifera waste could be used as a cheap source of bioactive stilbenes for the development of natural fungicides.