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Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics

Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in “requeijão cremoso” (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial...

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Autores principales: de Oliveira Machado, G., Teixeira, Gustavo Galastri, Garcia, Rodrigo Henrique dos Santos, Moraes, Tiago Bueno, Bona, Evandro, Santos, Poliana M., Colnago, Luiz Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9318975/
https://www.ncbi.nlm.nih.gov/pubmed/35889306
http://dx.doi.org/10.3390/molecules27144434
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author de Oliveira Machado, G.
Teixeira, Gustavo Galastri
Garcia, Rodrigo Henrique dos Santos
Moraes, Tiago Bueno
Bona, Evandro
Santos, Poliana M.
Colnago, Luiz Alberto
author_facet de Oliveira Machado, G.
Teixeira, Gustavo Galastri
Garcia, Rodrigo Henrique dos Santos
Moraes, Tiago Bueno
Bona, Evandro
Santos, Poliana M.
Colnago, Luiz Alberto
author_sort de Oliveira Machado, G.
collection PubMed
description Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in “requeijão cremoso” (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T(1)) and transverse (T(2)) relaxation measurements in a wide bore Halbach magnet (0.23 T) with a 100 mm probe. The T(1) and T(2) analyses were performed using CWFP-T(1) (Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T(1) and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T(1) data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T(1) data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages.
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spelling pubmed-93189752022-07-27 Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics de Oliveira Machado, G. Teixeira, Gustavo Galastri Garcia, Rodrigo Henrique dos Santos Moraes, Tiago Bueno Bona, Evandro Santos, Poliana M. Colnago, Luiz Alberto Molecules Article Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in “requeijão cremoso” (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T(1)) and transverse (T(2)) relaxation measurements in a wide bore Halbach magnet (0.23 T) with a 100 mm probe. The T(1) and T(2) analyses were performed using CWFP-T(1) (Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T(1) and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T(1) data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T(1) data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages. MDPI 2022-07-11 /pmc/articles/PMC9318975/ /pubmed/35889306 http://dx.doi.org/10.3390/molecules27144434 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
de Oliveira Machado, G.
Teixeira, Gustavo Galastri
Garcia, Rodrigo Henrique dos Santos
Moraes, Tiago Bueno
Bona, Evandro
Santos, Poliana M.
Colnago, Luiz Alberto
Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title_full Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title_fullStr Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title_full_unstemmed Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title_short Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics
title_sort non-invasive method to predict the composition of requeijão cremoso directly in commercial packages using time domain nmr relaxometry and chemometrics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9318975/
https://www.ncbi.nlm.nih.gov/pubmed/35889306
http://dx.doi.org/10.3390/molecules27144434
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