Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data

The world production of chestnuts has significantly grown in recent decades. Consumer attitudes, increasingly turned towards healthy foods, show a greater interest in chestnuts due to their health benefits. Consequently, it is important to develop reliable methods for the selection of high-quality p...

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Autores principales:	Piermaria Corona, Maria Teresa Frangipane, Roberto Moscetti, Gabriella Lo Feudo, Tatiana Castellotti, Riccardo Massantini
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	food quality assessment non-destructive analysis near-infrared spectrum visible spectrum sensory panel Italy Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/35ae8d9e0a6f426c989c1b51de8e7d4d
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id	oai:doaj.org-article:35ae8d9e0a6f426c989c1b51de8e7d4d
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spelling	oai:doaj.org-article:35ae8d9e0a6f426c989c1b51de8e7d4d2021-11-25T17:32:48ZChestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data10.3390/foods101125752304-8158https://doaj.org/article/35ae8d9e0a6f426c989c1b51de8e7d4d2021-10-01T00:00:00Zhttps://www.mdpi.com/2304-8158/10/11/2575https://doaj.org/toc/2304-8158The world production of chestnuts has significantly grown in recent decades. Consumer attitudes, increasingly turned towards healthy foods, show a greater interest in chestnuts due to their health benefits. Consequently, it is important to develop reliable methods for the selection of high-quality products, both from a qualitative and sensory point of view. In this study, Castanea spp. fruits from Italy, namely Sweet chestnut cultivar and the Marrone cultivar, were evaluated by an official panel, and the responses for sensory attributes were used to verify the correlation to the near-infrared spectra. Data fusion strategies have been applied to take advantage of the synergistic effect of the information obtained from NIR and sensory analysis. Large nuts, easy pellicle removal, chestnut aroma, and aromatic intensity render Marrone cv fruits suitable for both the fresh market and candying, i.e., marron glacé. Whereas, sweet chestnut samples, due to their characteristics, have the potential to be used for secondary food products, such as jam, mash chestnut, and flour. The research lays the foundations for a superior data fusion approach for chestnut identification in terms of classification sensitivity and specificity, in which sensory and spectral approaches compensate each other’s drawbacks, synergistically contributing to an excellent result.Piermaria CoronaMaria Teresa FrangipaneRoberto MoscettiGabriella Lo FeudoTatiana CastellottiRiccardo MassantiniMDPI AGarticlefood quality assessmentnon-destructive analysisnear-infrared spectrumvisible spectrumsensory panelItalyChemical technologyTP1-1185ENFoods, Vol 10, Iss 2575, p 2575 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	food quality assessment non-destructive analysis near-infrared spectrum visible spectrum sensory panel Italy Chemical technology TP1-1185
spellingShingle	food quality assessment non-destructive analysis near-infrared spectrum visible spectrum sensory panel Italy Chemical technology TP1-1185 Piermaria Corona Maria Teresa Frangipane Roberto Moscetti Gabriella Lo Feudo Tatiana Castellotti Riccardo Massantini Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
description	The world production of chestnuts has significantly grown in recent decades. Consumer attitudes, increasingly turned towards healthy foods, show a greater interest in chestnuts due to their health benefits. Consequently, it is important to develop reliable methods for the selection of high-quality products, both from a qualitative and sensory point of view. In this study, Castanea spp. fruits from Italy, namely Sweet chestnut cultivar and the Marrone cultivar, were evaluated by an official panel, and the responses for sensory attributes were used to verify the correlation to the near-infrared spectra. Data fusion strategies have been applied to take advantage of the synergistic effect of the information obtained from NIR and sensory analysis. Large nuts, easy pellicle removal, chestnut aroma, and aromatic intensity render Marrone cv fruits suitable for both the fresh market and candying, i.e., marron glacé. Whereas, sweet chestnut samples, due to their characteristics, have the potential to be used for secondary food products, such as jam, mash chestnut, and flour. The research lays the foundations for a superior data fusion approach for chestnut identification in terms of classification sensitivity and specificity, in which sensory and spectral approaches compensate each other’s drawbacks, synergistically contributing to an excellent result.
format	article
author	Piermaria Corona Maria Teresa Frangipane Roberto Moscetti Gabriella Lo Feudo Tatiana Castellotti Riccardo Massantini
author_facet	Piermaria Corona Maria Teresa Frangipane Roberto Moscetti Gabriella Lo Feudo Tatiana Castellotti Riccardo Massantini
author_sort	Piermaria Corona
title	Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
title_short	Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
title_full	Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
title_fullStr	Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
title_full_unstemmed	Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data
title_sort	chestnut cultivar identification through the data fusion of sensory quality and ft-nir spectral data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/35ae8d9e0a6f426c989c1b51de8e7d4d
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Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data

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