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On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard

Visible-Short Wave Near Infrared (VIS + SW − NIR) spectroscopy is a real alternative to break down the next barrier in precision viticulture allowing a reliable monitoring of grape composition within the vineyard to facilitate the decision-making process dealing with grape quality sorting and harves...

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Autores principales: Fernández-Novales, Juan, Tardáguila, Javier, Gutiérrez, Salvador, Diago, María Paz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695769/
https://www.ncbi.nlm.nih.gov/pubmed/31370313
http://dx.doi.org/10.3390/molecules24152795
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author Fernández-Novales, Juan
Tardáguila, Javier
Gutiérrez, Salvador
Diago, María Paz
author_facet Fernández-Novales, Juan
Tardáguila, Javier
Gutiérrez, Salvador
Diago, María Paz
author_sort Fernández-Novales, Juan
collection PubMed
description Visible-Short Wave Near Infrared (VIS + SW − NIR) spectroscopy is a real alternative to break down the next barrier in precision viticulture allowing a reliable monitoring of grape composition within the vineyard to facilitate the decision-making process dealing with grape quality sorting and harvest scheduling, for example. On-the-go spectral measurements of grape clusters were acquired in the field using a VIS + SW − NIR spectrometer, operating in the 570–990 nm spectral range, from a motorized platform moving at 5 km/h. Spectral measurements were acquired along four dates during grape ripening in 2017 on the east side of the canopy, which had been partially defoliated at cluster closure. Over the whole measuring season, a total of 144 experimental blocks were monitored, sampled and their fruit analyzed for total soluble solids (TSS), anthocyanin and total polyphenols concentrations using standard, wet chemistry reference methods. Partial Least Squares (PLS) regression was used as the algorithm for training the grape composition parameters’ prediction models. The best cross-validation and external validation (prediction) models yielded determination coefficients of cross-validation (R(2)(cv)) and prediction (R(2)(P)) of 0.92 and 0.95 for TSS, R(2)(cv) = 0.75, and R(2)(p) = 0.79 for anthocyanins, and R(2)(cv) = 0.42 and R(2)(p) = 0.43 for total polyphenols. The vineyard variability maps generated for the different dates using this technology illustrate the capability to monitor the spatiotemporal dynamics and distribution of total soluble solids, anthocyanins and total polyphenols along grape ripening in a commercial vineyard.
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spelling pubmed-66957692019-09-05 On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard Fernández-Novales, Juan Tardáguila, Javier Gutiérrez, Salvador Diago, María Paz Molecules Article Visible-Short Wave Near Infrared (VIS + SW − NIR) spectroscopy is a real alternative to break down the next barrier in precision viticulture allowing a reliable monitoring of grape composition within the vineyard to facilitate the decision-making process dealing with grape quality sorting and harvest scheduling, for example. On-the-go spectral measurements of grape clusters were acquired in the field using a VIS + SW − NIR spectrometer, operating in the 570–990 nm spectral range, from a motorized platform moving at 5 km/h. Spectral measurements were acquired along four dates during grape ripening in 2017 on the east side of the canopy, which had been partially defoliated at cluster closure. Over the whole measuring season, a total of 144 experimental blocks were monitored, sampled and their fruit analyzed for total soluble solids (TSS), anthocyanin and total polyphenols concentrations using standard, wet chemistry reference methods. Partial Least Squares (PLS) regression was used as the algorithm for training the grape composition parameters’ prediction models. The best cross-validation and external validation (prediction) models yielded determination coefficients of cross-validation (R(2)(cv)) and prediction (R(2)(P)) of 0.92 and 0.95 for TSS, R(2)(cv) = 0.75, and R(2)(p) = 0.79 for anthocyanins, and R(2)(cv) = 0.42 and R(2)(p) = 0.43 for total polyphenols. The vineyard variability maps generated for the different dates using this technology illustrate the capability to monitor the spatiotemporal dynamics and distribution of total soluble solids, anthocyanins and total polyphenols along grape ripening in a commercial vineyard. MDPI 2019-07-31 /pmc/articles/PMC6695769/ /pubmed/31370313 http://dx.doi.org/10.3390/molecules24152795 Text en © 2019 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
Fernández-Novales, Juan
Tardáguila, Javier
Gutiérrez, Salvador
Diago, María Paz
On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title_full On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title_fullStr On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title_full_unstemmed On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title_short On-The-Go VIS + SW − NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard
title_sort on-the-go vis + sw − nir spectroscopy as a reliable monitoring tool for grape composition within the vineyard
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695769/
https://www.ncbi.nlm.nih.gov/pubmed/31370313
http://dx.doi.org/10.3390/molecules24152795
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