Showing papers by "Francisco J. Heredia published in 2021"

Optimization of Protein Extraction of Oenological Interest from Grape Seed Meal Using Design of Experiments and Response Surface Methodology

Abstract: After grape processing, large amounts of seeds are produced as a side product. Grape seeds are rich in proteins that could be extracted and revalorized by the wine industry due to their high techno-functional value for modulating quality features of red wines or as an alternative to the use of other stabilizers, which are also proteins but submitted to legal restrictions. Box–Behnken design and response surface methodology were used to optimize the protein extraction from defatted grape seed meal to maximize the protein purity of the isolate under practical operating conditions of pH, temperature, meal/water ratio and extraction time. The most significant factor was pH, both in the linear and quadratic forms. Additionally, the interaction between pH and temperature exhibited a significant effect on protein content. The removal of phenolic compounds from grapeseed meal, before optimizing protein extraction, led to a significant increase of 7.70% in the protein purity of grape seed protein concentrate. Therefore, grape seeds can be used as a sustainable way for protein production in the oenological sector due to the availability of grape seeds, their low cost as a grape-processing by-product, and the protein purity reached thanks to the described procedure for optimization of protein extraction.

Assessment of Total Fat and Fatty Acids in Walnuts Using Near-Infrared Hyperspectral Imaging.

Abstract: "Persian" walnut (Juglans Regia L.) is one of the most consumed tree nuts in the world. It is rich in several bioactive compounds, with polyunsaturated and monounsaturated fatty acids (PUFA and MUFA) appearing at high concentrations. Walnut consumption protects against cardiovascular, carcinogenic, and neurological disorders. The fatty acid profile has usually been determined by gas chromatography, a reliable and robust tool, but also complex, polluting, and time consuming. In this study, near infrared hyperspectral imaging has been used for the screening of total fat, MUFA, PUFA, saturated, and individual fatty acids in walnuts. Five different walnuts varieties have been considered and modified partial least square (MPLS) regressions have been performed. The SEs of prediction (SEP) in external validation (ranged from 2.12% for PUFA to 13.08% for MUFA) suggest that hyperspectral imaging can be a reliable tool for controlling these parameters in a simple, non-destructive and environmentally friendly way.

Assessment of Sensory and Texture Profiles of Grape Seeds at Real Maturity Stages Using Image Analysis.

Abstract: The usefulness of digital image analysis in estimating sensory attributes of grape seeds in relation to maturation level was evaluated for the first time. Seeds from Syrah grapes harvested throughout the ripening period were grouped according to maturity using the DigiEye® system. The discriminant ability, homogeneity, repeatability, and uniformity of a sensory panel were assessed after training on grape seeds. The aim was to evaluate the use of digital image techniques in order to accurately establish the maturity level of grape seeds, based on sensory and textural features. All sensory attributes (color, hardness, cracking, vegetal, bitterness and astringency) showed significant (p < 0.05) correlations with the chemical maturity stage. Color and vegetal (sensory attributes), together with deformation energy (instrumental texture parameter) (De), allowed for the classification of the seeds into four real maturity stages, hence their usefulness as grape seed ripening indicators. Significant (p < 0.05) and high-correlation factors were also found between instrumental and sensory attributes. Therefore, digital analysis can be a useful tool to better define the maturity stage in the vineyard, and to dispose of grape seeds with well-defined sensory profiles for specific oenological applications. This could help to determine the optimal harvest date to manage winemaking, in order to produce high quality wines in warm climates.

Reduction of the Number of Samples for Cost-Effective Hyperspectral Grape Quality Predictive Models

Abstract: Developing chemometric models from near-infrared (NIR) spectra requires the use of a representative calibration set of the entire population. Therefore, generally, the calibration procedure requires a large number of resources. For that reason, there is a great interest in identifying the most spectrally representative samples within a large population set. In this study, principal component and hierarchical clustering analyses have been compared for their ability to provide different representative calibration sets. The calibration sets generated have been used to control the technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars. Finally, the accuracy and precision of the models obtained with these calibration sets resulted from the application of the selection algorithms studied have been compared with each other and with the whole set of samples using an external validation set. Most of the standard errors of prediction (SEP) in external validation obtained from the reduced data sets were not significantly different from those obtained using the whole data set. Moreover, sample subsets resulting from hierarchical clustering analysis appear to produce slightly better results.

A Study of Overripe Seed Byproducts from Sun-Dried Grapes by Dispersive Raman Spectroscopy.

Abstract: Overripe seeds from sun-dried grapes submitted to postharvest dehydration constitute a scarcely investigated class of vinification byproduct with limited reports on their phenolic composition and industrial applications. In this study, Raman spectroscopy was applied to characterize a selection of overripe seed byproducts from different white grapes (cv. Moscatel, cv. Pedro Ximenez and cv. Zalema) submitted to postharvest sun drying. The Raman measurements were taken using a 1064 nm excitation laser in order to mitigate the fluorescent effect and the dispersive detection scheme allowed a compactness of the optical system. Spectroscopic data were processed by a principal component analysis to reduce the dimensionality and partner recognition. The evolution of the Raman spectrum during the overripening process was compared with the phenolic composition of grape seeds, which was determined by rapid resolution liquid chromatography/mass spectrometry (RRLC/MS). A multivariate processing of the spectroscopic data allowed the classification of overripe seeds according to the grape variety and the monitoring of stages of the postharvest sun drying process.