Use of Artificial Neural Networks and NIR Spectroscopy for Non-Destructive Grape Texture Prediction.

In this article, a combination of non-destructive NIR spectroscopy and machine learning techniques was applied to predict the texture parameters and the total soluble solids content (TSS) in intact berries. The multivariate models obtained by building artificial neural networks (ANNs) and applying partial least squares (PLS) regressions showed a better prediction ability after the elimination of uninformative spectral ranges. A very good prediction was obtained for TSS and springiness (R2 0.82 and 0.72). Qualitative models were obtained for hardness and chewiness (R2 0.50 and 0.53). No satisfactory calibration model could be established between the NIR spectra and cohesiveness. Textural parameters of grape are strictly related to the berry size. Before any grape textural measurement, a time-consuming berry-sorting step is compulsory. This is the first time a complete textural analysis of intact grape berries has been performed by NIR spectroscopy without any a priori knowledge of the berry density class.

NIR Analysis of Intact Grape Berries: Chemical and Physical Properties Prediction Using Multivariate Analysis.

Texture characteristics are valuable parameters in the perceived quality and overall acceptability of fresh fruit. The characterization of grape texture attributes, such as firmness and crunchiness, is usually performed by sensory analysis or instrumental texture analysis. Both methodologies are destructive. Hence, it is not possible to test multiple times or perform any other analysis on the same sample. In this article, near-infrared (NIR) spectroscopy was applied to intact berries of table grape cv. Regal Seedless. NIR spectra were employed to predict both the physical parameter "hardness", which is correlated with the crunchiness of berry flesh and the sweetness, which is correlated with the total soluble solids content (TSS, as °Brix). The chemometric analysis was carried out exclusively based on an open-source software environment, producing results readily usable for any operator, besides the specific level of experience with NIR spectroscopy.

FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors.

Fourier-transform near infrared spectroscopy (FT-NIR) is a technique used in the compositional and sensory analysis of foodstuffs. In this work, we have measured the main maturity parameters for grape (sugars and acids) using hundreds of intact berry samples to build models for the prediction of these parameters from berries of two very different varieties: "Victoria" and "Autumn Royal". Together with the chemical composition in terms of sugar and acidic content, we have carried out a sensory analysis on single berries. Employing the models built for sugars and acids it was possible to learn the sweetness and acidity of each berry before the destructive sensory analysis. The direct correlation of sensory data with FT-NIR spectra is difficult; therefore, spectral data were exported from the spectrometer built-in software and analyzed with R software using a statistical analysis technique (Spearman correlation) which allowed the correlation of berry appreciation data with specific wavelengths that were then related to sugar and acidic content. In this article, we show how it is possible to carry out the analysis of single berries to obtain data on chemical composition parameters and consumer appreciation with a fast, simple, and non-destructive technique with a clear advantage for producers and consumers.

Optimized ultrasonic-assisted extraction of phenolic antioxidants from grape (Vitis vinifera L.) skin using response surface methodology.

Currently, the analysis of bioactive compounds is easily carried out by modern chromatographic and spectrometric techniques, but the success of the procedure still depends on the efficiency of the extraction methods. This work aimed at finding the optimal conditions for ultrasonic-assisted extraction (UAE) of phenolic antioxidants from grape skin using single-factor experimentation combined with response-surface methodology. Our extraction parameters were ethanol concentration, time and temperature. Total phenolic content (TPC and TPC-280), 2,2-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging activity and oxygen radical absorbance capacity (ORAC) were dependent variables. A second-order polynomial model satisfactorily described the experimental data. Optimized extraction conditions for UAE from grape skin were: 59.5% ethanol, 113.6 min and 66.8 °C for TPC extraction; 61.1% ethanol, 99.4 min and 66.1 °C for TPC-280 extraction; 57.1% ethanol, 99.5 min and 66.8 °C for DPPH radical-scavenging activity; 60.2% ethanol, 82.4 min and 66.8 °C for ORAC value. Our work provides detailed and useful information to optimize the extraction of grape skin phenols, which are widely used as dietary supplements and nutraceuticals.

Viticultural practice and winemaking effects on metabolic profile of Negroamaro.

Metabolic profiles of 32 Negroamaro red wines were analysed using (1)H NMR spectroscopy and multivariate statistical analyses (Principal Component Analysis, PCA, and Orthogonal Partial Least Square Discriminant Analysis, OPLS-DA). Among winemaking technologies three were compared: ultrasounds (U; 12 samples), cryomaceration using dry ice (C; 12 samples) and traditional (T; 8 samples). Moreover, each vinification technology was used for grapes grown by two different soil management practices, soil tillage (ST; 16 samples) and cover crop (CC; 16 samples), and by two different training systems, monolateral (M; 16 samples) and bilateral Guyot (B; 16 samples). All statistical models applied on NMR data revealed a good separation between ST (soil tillage) and CC (cover crop), showing a higher influence of the soil management practices compared to the winemaking technologies (ultrasound, cryomaceration and traditional). The differentiation among samples, due to soil management practices, was mainly caused by metabolites such as glycerol, 2,3-butanediol, malic acid, α/ß-glucose and phenolic compounds, such as tyrosine and caffeic acid.

Postharvest stilbenes and flavonoids enrichment of table grape cv Redglobe (Vitis vinifera L.) as affected by interactive UV-C exposure and storage conditions.

Flavonoids and stilbenes are secondary metabolites produced in plants that can play an important health-promoting role. The biosynthesis of these compounds generally increases as a response to biotic or abiotic stress; therefore, in order to achieve as high phenolic accumulation as possible, the interactive effects of storage conditions (temperature and time) and UV-C radiation on polyphenols content in postharvest Redglobe table grape variety were investigated. During a storage time longer than 48h, both cold storage (4°C) and UV-C exposure of almost 3min (2.4kJm(-2)) positively enhanced the content of cis- and trans-piceid (34 and 90µgg(-1) of skin, respectively) together with quercetin-3-O-galactoside and quercetin-3-O-glucoside (15 and 140µgg(-1) of skin, respectively) up to three fold respect to control grape samples. Conversely, catechin was not significantly affected by irradiation and storage treatments. With regard anthocyanins, the highest concentrations of cyanidin-3-O-glucoside and peonidin-3-Oglucoside were observed in Redglobe, stored at both room temperature and 4°C, after 5min (4.1kJm(-2)) of UV-C treatment and 24h of storage. Gathered findings showed that combined postharvest treatments can lead to possible "functional" grapes, within normal conditions of market commercialization, responding to the rising consumers demand to have foods that support and promote health.

Synthesis and biological evaluation of a water-soluble derivative of the potent V-ATPase inhibitor archazolid.

The water-solubility of the highly potent V-ATPase inhibitors archazolid A and the glucosylated derivative archazolid C was studied in the presence of a wide range of cosolvents, revealing very low solubilites. The first water-soluble analogue was then designed, synthesized, and evaluated for V-ATPase inhibitory activity in vitro.

Design, synthesis, and biological evaluation of glycine-based molecular tongs as inhibitors of Abeta1-40 aggregation in vitro.

A series of N-terminus benzamides of glycine-based symmetric peptides, linked to m-xylylenediamine and 3,4'-oxydianiline spacers, were prepared and tested as inhibitors of beta-amyloid peptide Abeta(1-40) aggregation in vitro. Compounds with good anti-aggregating activity were detected. Polyphenolic amides showed the highest anti-aggregating activity, with IC(50) values in the micromolar range. Structure-activity relationships suggested that pi-pi stacking and hydrogen-bonding interactions play a key role in the inhibition of Abeta(1-40) self-assembly leading to amyloid fibrils.