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Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy

The determination of internal maturity parameters of table grape is usually done destructively using manual methods that are time-consuming. The possibility was investigated to determine whether key fruit attributes, namely, total soluble solids (TSS); titratable acidity (TA), TSS/TA, pH, and BrimA...

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Autores principales: Daniels, Andries J., Poblete-Echeverría, Carlos, Opara, Umezuruike L., Nieuwoudt, Hélène H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896837/
https://www.ncbi.nlm.nih.gov/pubmed/31850021
http://dx.doi.org/10.3389/fpls.2019.01517
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author Daniels, Andries J.
Poblete-Echeverría, Carlos
Opara, Umezuruike L.
Nieuwoudt, Hélène H.
author_facet Daniels, Andries J.
Poblete-Echeverría, Carlos
Opara, Umezuruike L.
Nieuwoudt, Hélène H.
author_sort Daniels, Andries J.
collection PubMed
description The determination of internal maturity parameters of table grape is usually done destructively using manual methods that are time-consuming. The possibility was investigated to determine whether key fruit attributes, namely, total soluble solids (TSS); titratable acidity (TA), TSS/TA, pH, and BrimA (TSS – k x TA) could be determined on intact table grape bunches using Fourier transform near-infrared (FT-NIR) spectroscopy and a contactless measurement mode. Partial Least Squares (PLS) regression models were developed for the maturity and sensory quality parameters using grapes obtained from two consecutive harvest seasons. Statistical indicators used to evaluate the models were the number of latent variables (LVs) used to build the model, the prediction correlation coefficient (R(2)p) and root mean square error of prediction (RMSEP). For the respective parameters TSS, TA, TSS/TA, pH, and BrimA, the LVs were 21, 23, 5, 7, and 24, the R(2)p = 0.71, 0.33, 0.57, 0.28, and 0.77, and the RMSEP = 1.52, 1.09, 7.83, 0.14, and 1.80. TSS performed best when moving smoothing windows (MSW) + multiplicative scatter correction (MSC) was used as spectral pre-processing technique, TA with standard normal variate (SNV), TSS/TA with Savitzky-Golay first derivative (SG1d), pH with SG1d, and BrimA with MSC. This study provides the first steps towards a completely nondestructive and contactless determination of internal maturity parameters of intact table grape bunches.
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spelling pubmed-68968372019-12-17 Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy Daniels, Andries J. Poblete-Echeverría, Carlos Opara, Umezuruike L. Nieuwoudt, Hélène H. Front Plant Sci Plant Science The determination of internal maturity parameters of table grape is usually done destructively using manual methods that are time-consuming. The possibility was investigated to determine whether key fruit attributes, namely, total soluble solids (TSS); titratable acidity (TA), TSS/TA, pH, and BrimA (TSS – k x TA) could be determined on intact table grape bunches using Fourier transform near-infrared (FT-NIR) spectroscopy and a contactless measurement mode. Partial Least Squares (PLS) regression models were developed for the maturity and sensory quality parameters using grapes obtained from two consecutive harvest seasons. Statistical indicators used to evaluate the models were the number of latent variables (LVs) used to build the model, the prediction correlation coefficient (R(2)p) and root mean square error of prediction (RMSEP). For the respective parameters TSS, TA, TSS/TA, pH, and BrimA, the LVs were 21, 23, 5, 7, and 24, the R(2)p = 0.71, 0.33, 0.57, 0.28, and 0.77, and the RMSEP = 1.52, 1.09, 7.83, 0.14, and 1.80. TSS performed best when moving smoothing windows (MSW) + multiplicative scatter correction (MSC) was used as spectral pre-processing technique, TA with standard normal variate (SNV), TSS/TA with Savitzky-Golay first derivative (SG1d), pH with SG1d, and BrimA with MSC. This study provides the first steps towards a completely nondestructive and contactless determination of internal maturity parameters of intact table grape bunches. Frontiers Media S.A. 2019-11-28 /pmc/articles/PMC6896837/ /pubmed/31850021 http://dx.doi.org/10.3389/fpls.2019.01517 Text en Copyright © 2019 Daniels, Poblete-Echeverría, Opara and Nieuwoudt http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Daniels, Andries J.
Poblete-Echeverría, Carlos
Opara, Umezuruike L.
Nieuwoudt, Hélène H.
Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title_full Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title_fullStr Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title_full_unstemmed Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title_short Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy
title_sort measuring internal maturity parameters contactless on intact table grape bunches using nir spectroscopy
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896837/
https://www.ncbi.nlm.nih.gov/pubmed/31850021
http://dx.doi.org/10.3389/fpls.2019.01517
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