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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 the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023507/ https://www.ncbi.nlm.nih.gov/pubmed/31963470 http://dx.doi.org/10.3390/foods9010098 |
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author | Basile, Teodora Marsico, Antonio Domenico Cardone, Maria Francesca Antonacci, Donato Perniola, Rocco |
author_facet | Basile, Teodora Marsico, Antonio Domenico Cardone, Maria Francesca Antonacci, Donato Perniola, Rocco |
author_sort | Basile, Teodora |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7023507 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70235072020-03-12 FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors Basile, Teodora Marsico, Antonio Domenico Cardone, Maria Francesca Antonacci, Donato Perniola, Rocco Foods Article 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. MDPI 2020-01-17 /pmc/articles/PMC7023507/ /pubmed/31963470 http://dx.doi.org/10.3390/foods9010098 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Basile, Teodora Marsico, Antonio Domenico Cardone, Maria Francesca Antonacci, Donato Perniola, Rocco FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title | FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title_full | FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title_fullStr | FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title_full_unstemmed | FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title_short | FT-NIR Analysis of Intact Table Grape Berries to Understand Consumer Preference Driving Factors |
title_sort | ft-nir analysis of intact table grape berries to understand consumer preference driving factors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023507/ https://www.ncbi.nlm.nih.gov/pubmed/31963470 http://dx.doi.org/10.3390/foods9010098 |
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