Value Adding to Red Grape Pomace Exploiting Eco-friendly FT-NIR Spectroscopy Technique

Páscoa, Ricardo N.M.J.; Machado, Sandia; Magalhães, Luís M.; Lopes, João A.

doi:10.1007/s11947-014-1454-z

Cited by 16 publications

(6 citation statements)

References 39 publications

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“…FT-NIR spectroscopy combined with chemometrics has been used as a tool for geographical origin discrimination [7] and quality control [8,9] since this technique allows the development of calibration models that can be used for both the quantitative and qualitative determination of various parameters (e.g., pH, sugars, etc. ), including minor components (e.g., polyphenols) [10,11] in various food matrices and beverages. Since FT-NIR spectroscopy can capture variations of both chemical and sensory properties, this technique seems ideal to investigate the influence of sugars and acidic composition on consumer acceptance.…”

Section: Introductionmentioning

confidence: 99%

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

Basile

Marsico

Cardone

et al. 2020

Foods

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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.

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Section: Introductionmentioning

confidence: 99%

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

Basile

Marsico

Cardone

et al. 2020

Foods

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“…To quantify the performance of the model, we calculated the RMSE and bias between the measured and estimated LAI from the testing dataset. The correlation coefficient (r) and range error ratio (RER) were also used to assess the practical efficiency of the model [56,57]. Essentially, empirical thresholds have been defined based on RER, because models with an RER of less than 3 have little practical utility, while values between 3 and 10 indicate a limited practical utility, and values above 10 show that the model has a high utility value:…”

Section: Evaluation Of Our Methodsmentioning

confidence: 99%

A Prior Knowledge-Based Method to Derivate High-Resolution Leaf Area Index Maps with Limited Field Measurements

Shi

Wang

et al. 2016

Remote Sensing

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High-resolution leaf area index (LAI) maps from remote sensing data largely depend on empirical models, which link field LAI measurements to the vegetation index. The existing empirical methods often require the field measurements to be sufficient for constructing a reliable model. However, in many regions of the world, there are limited field measurements available. This paper presents a prior knowledge-based (PKB) method to derivate LAI with limited field measurements, in an effort to improve the accuracy of empirical model. Based on the assumption that the experimental sites with the same vegetation type can be represented by similar models, a priori knowledge for crops was extracted from the published models in various cropland sites. The knowledge, composed of an initial guess of each model parameter with the associated uncertainty, was then combined with the local field measurements to determine a semi-empirical model using the Bayesian inversion method. The proposed method was evaluated at a cropland site in the Huailai region of Hebei Province, China. Compared with the regression method, the proposed PKB method can effectively improve the accuracy of empirical model and LAI estimation, when the field measurements were limited. The results demonstrate that a priori knowledge extracted from the universal sites can provide important auxiliary information to improve the representativeness of the empirical model in a given study area.

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“…Additionally, between the two distinct IR intervals used, assessed with resort to different instruments, NIR is the one that has gained more attention, due to its reliability and easiness of use, nowadays existing portable spectrophotometers for this specific interval, which are suitable for the winery industry, both for industrial and vineyard contexts [ 81 , 86 ]. Actually, NIR spectroscopy has been already successfully applied to winemaking residues, namely grape pomace, to estimate total phenolics content and total antioxidant capacity ( R 2 higher than 0.95), representing a non-destructive technique to assess the value of these residues [ 87 ]. The NIR hyperspectral imaging (900 and 1700 nm), resorting to portable cameras, has also been explored in the characterization of grape seeds, skins, and stems [ 79 ], besides being also used to discern grape varieties [ 86 ], resorting to ANN approaches in the latter case.…”

Section: Use Of Chemometrics For the Traceability Of Winery By-promentioning

confidence: 99%

Addressing Facts and Gaps in the Phenolics Chemistry of Winery By-Products

Machado

Domínguez‐Perles

2017

Molecules

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Grape and wine phenolics display a noticeable structural diversity, encompassing distinct compounds ranging from simple molecules to oligomers, as well as polymers usually designated as tannins. Since these compounds contribute critically to the organoleptic properties of wines, their analysis and quantification are of primordial importance for winery industry operators. Besides, the occurrence of these compounds has been also extensively described in winery residues, which have been pointed as a valuable source of bioactive phytochemicals presenting potential for the development of new added value products that could fit the current market demands. Therefore, the cumulative knowledge generated during the last decades has allowed the identification of the most promising compounds displaying interesting biological functions, as well as the chemical features responsible for the observed bioactivities. In this regard, the present review explores the scope of the existing knowledge, concerning the compounds found in these winery by-products, as well as the chemical features presumably responsible for the biological functions already identified. Moreover, the present work will hopefully pave the way for further actions to develop new powerful applications to these materials, thus, contributing to more sustainable valorization procedures and the development of newly obtained compounds with enhanced biological properties.

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Value Adding to Red Grape Pomace Exploiting Eco-friendly FT-NIR Spectroscopy Technique

Cited by 16 publications

References 39 publications

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

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

A Prior Knowledge-Based Method to Derivate High-Resolution Leaf Area Index Maps with Limited Field Measurements

Addressing Facts and Gaps in the Phenolics Chemistry of Winery By-Products

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