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Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly

The objective of the study is to develop a workflow to screen protein extracts and identify their nutritional potential as high quality nutritional culinary aids for recipes for the elderly. Twenty-seven protein extracts of animal, vegetable, and dairy origin were characterized. We studied their fat...

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Autores principales: Duval, Angéline, Sayd, Thierry, Aubry, Laurent, Ferreira, Claude De Oliviera, Ferraro, Vincenza, Sante-Lhoutellier, Véronique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589855/
https://www.ncbi.nlm.nih.gov/pubmed/33092127
http://dx.doi.org/10.3390/foods9101499
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author Duval, Angéline
Sayd, Thierry
Aubry, Laurent
Ferreira, Claude De Oliviera
Ferraro, Vincenza
Sante-Lhoutellier, Véronique
author_facet Duval, Angéline
Sayd, Thierry
Aubry, Laurent
Ferreira, Claude De Oliviera
Ferraro, Vincenza
Sante-Lhoutellier, Véronique
author_sort Duval, Angéline
collection PubMed
description The objective of the study is to develop a workflow to screen protein extracts and identify their nutritional potential as high quality nutritional culinary aids for recipes for the elderly. Twenty-seven protein extracts of animal, vegetable, and dairy origin were characterized. We studied their fate by monitoring static in vitro digestion, mimicking the physiological digestion conditions of the elderly. At the end of the gastric and intestinal phase, global measurements of digestibility and antioxidant bioactivities were performed. The statistical analysis workflow developed allowed: (i) synthesizing the compositional and nutritional information of each protein extract by creating latent variables, and (ii) comparing them. The links between variables and similarities between protein extracts were visualized using a heat map. A hierarchical cluster analysis allowed reducing the 48 quantitative variables into 15 qualitative latent variables (clusters). The application of the k-means method on each cluster enable to classify the protein extracts by level. This defined level was used as categorical value. Multiple correspondence analysis revealed groups of protein extracts with varied patterns. This workflow allowed the comparison/hierarchization between protein extracts and the creation of a tool to select the most interesting ones on the basis of their nutritional quality.
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spelling pubmed-75898552020-10-29 Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly Duval, Angéline Sayd, Thierry Aubry, Laurent Ferreira, Claude De Oliviera Ferraro, Vincenza Sante-Lhoutellier, Véronique Foods Article The objective of the study is to develop a workflow to screen protein extracts and identify their nutritional potential as high quality nutritional culinary aids for recipes for the elderly. Twenty-seven protein extracts of animal, vegetable, and dairy origin were characterized. We studied their fate by monitoring static in vitro digestion, mimicking the physiological digestion conditions of the elderly. At the end of the gastric and intestinal phase, global measurements of digestibility and antioxidant bioactivities were performed. The statistical analysis workflow developed allowed: (i) synthesizing the compositional and nutritional information of each protein extract by creating latent variables, and (ii) comparing them. The links between variables and similarities between protein extracts were visualized using a heat map. A hierarchical cluster analysis allowed reducing the 48 quantitative variables into 15 qualitative latent variables (clusters). The application of the k-means method on each cluster enable to classify the protein extracts by level. This defined level was used as categorical value. Multiple correspondence analysis revealed groups of protein extracts with varied patterns. This workflow allowed the comparison/hierarchization between protein extracts and the creation of a tool to select the most interesting ones on the basis of their nutritional quality. MDPI 2020-10-20 /pmc/articles/PMC7589855/ /pubmed/33092127 http://dx.doi.org/10.3390/foods9101499 Text en © 2020 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
Duval, Angéline
Sayd, Thierry
Aubry, Laurent
Ferreira, Claude De Oliviera
Ferraro, Vincenza
Sante-Lhoutellier, Véronique
Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title_full Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title_fullStr Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title_full_unstemmed Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title_short Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly
title_sort development of a statistical workflow for screening protein extracts based on their nutritional composition and digestibility: application to elderly
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589855/
https://www.ncbi.nlm.nih.gov/pubmed/33092127
http://dx.doi.org/10.3390/foods9101499
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