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Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes
The intake of tomato glycoalkaloids can exert beneficial effects on human health. For this reason, methods for a rapid quantification of these compounds are required. Most of the methods for α-tomatine and dehydrotomatine quantification are based on chromatographic techniques. However, these techniq...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196588/ https://www.ncbi.nlm.nih.gov/pubmed/34063803 http://dx.doi.org/10.3390/molecules26113068 |
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author | Tamasi, Gabriella Pardini, Alessio Croce, Riccardo Consumi, Marco Leone, Gemma Bonechi, Claudia Rossi, Claudio Magnani, Agnese |
author_facet | Tamasi, Gabriella Pardini, Alessio Croce, Riccardo Consumi, Marco Leone, Gemma Bonechi, Claudia Rossi, Claudio Magnani, Agnese |
author_sort | Tamasi, Gabriella |
collection | PubMed |
description | The intake of tomato glycoalkaloids can exert beneficial effects on human health. For this reason, methods for a rapid quantification of these compounds are required. Most of the methods for α-tomatine and dehydrotomatine quantification are based on chromatographic techniques. However, these techniques require complex and time-consuming sample pre-treatments. In this work, HPLC-ESI-QqQ-MS/MS was used as reference method. Subsequently, multiple linear regression (MLR) and partial least squares regression (PLSR) were employed to create two calibration models for the prediction of the tomatine content from thermogravimetric (TGA) and attenuated total reflectance (ATR) infrared spectroscopy (IR) analyses. These two fast techniques were proven to be suitable and effective in alkaloid quantification (R(2) = 0.998 and 0.840, respectively), achieving low errors (0.11 and 0.27%, respectively) with the reference technique. |
format | Online Article Text |
id | pubmed-8196588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81965882021-06-13 Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes Tamasi, Gabriella Pardini, Alessio Croce, Riccardo Consumi, Marco Leone, Gemma Bonechi, Claudia Rossi, Claudio Magnani, Agnese Molecules Article The intake of tomato glycoalkaloids can exert beneficial effects on human health. For this reason, methods for a rapid quantification of these compounds are required. Most of the methods for α-tomatine and dehydrotomatine quantification are based on chromatographic techniques. However, these techniques require complex and time-consuming sample pre-treatments. In this work, HPLC-ESI-QqQ-MS/MS was used as reference method. Subsequently, multiple linear regression (MLR) and partial least squares regression (PLSR) were employed to create two calibration models for the prediction of the tomatine content from thermogravimetric (TGA) and attenuated total reflectance (ATR) infrared spectroscopy (IR) analyses. These two fast techniques were proven to be suitable and effective in alkaloid quantification (R(2) = 0.998 and 0.840, respectively), achieving low errors (0.11 and 0.27%, respectively) with the reference technique. MDPI 2021-05-21 /pmc/articles/PMC8196588/ /pubmed/34063803 http://dx.doi.org/10.3390/molecules26113068 Text en © 2021 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 Tamasi, Gabriella Pardini, Alessio Croce, Riccardo Consumi, Marco Leone, Gemma Bonechi, Claudia Rossi, Claudio Magnani, Agnese Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title | Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title_full | Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title_fullStr | Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title_full_unstemmed | Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title_short | Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes |
title_sort | combined experimental and multivariate model approaches for glycoalkaloid quantification in tomatoes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196588/ https://www.ncbi.nlm.nih.gov/pubmed/34063803 http://dx.doi.org/10.3390/molecules26113068 |
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