Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters

Abstract The food industry should have methods that allow identifying bioactive compounds quickly, efficiently and at low cost. The objective of this research was to obtain mathematical models for predicting the amount of total phenolics, anthocyanins and antioxidant capacity of blackberry, blueberry and jaboticaba skin, based on colorimetric parameters (L*, a*, b*, C* and h*). All analyses were done in the phenolic extracts obtained from these fruits. The mathematical models were obtained through multiple linear regression using the stepwise method. The significant correlation between the colorimetric parameters and chemical analyses resulted in models with a high predictive ability (high r2), such as in the determination of the contents of anthocyanins (r2 = 0.99), total phenolics (r2 = 0.86) and for the antioxidant capacity (r2 = 0.99). Thus, the prediction of levels of these bioactives compound, using colorimetric parameters, is very promising for cost and time savings.

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Main Authors: RIGOLON,Thaís Caroline Buttow, BARROS,Frederico Augusto Ribeiro de, VIEIRA,Érica Nascif Rufino, STRINGHETA,Paulo César
Format: Digital revista
Language:English
Published: Sociedade Brasileira de Ciência e Tecnologia de Alimentos 2020
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612020000600620
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spelling oai:scielo:S0101-206120200006006202020-11-23Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parametersRIGOLON,Thaís Caroline ButtowBARROS,Frederico Augusto Ribeiro deVIEIRA,Érica Nascif RufinoSTRINGHETA,Paulo César bioactive compounds polyphenols color pigments Abstract The food industry should have methods that allow identifying bioactive compounds quickly, efficiently and at low cost. The objective of this research was to obtain mathematical models for predicting the amount of total phenolics, anthocyanins and antioxidant capacity of blackberry, blueberry and jaboticaba skin, based on colorimetric parameters (L*, a*, b*, C* and h*). All analyses were done in the phenolic extracts obtained from these fruits. The mathematical models were obtained through multiple linear regression using the stepwise method. The significant correlation between the colorimetric parameters and chemical analyses resulted in models with a high predictive ability (high r2), such as in the determination of the contents of anthocyanins (r2 = 0.99), total phenolics (r2 = 0.86) and for the antioxidant capacity (r2 = 0.99). Thus, the prediction of levels of these bioactives compound, using colorimetric parameters, is very promising for cost and time savings.info:eu-repo/semantics/openAccessSociedade Brasileira de Ciência e Tecnologia de AlimentosFood Science and Technology v.40 suppl.2 20202020-12-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612020000600620en10.1590/fst.34219
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country Brasil
countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author RIGOLON,Thaís Caroline Buttow
BARROS,Frederico Augusto Ribeiro de
VIEIRA,Érica Nascif Rufino
STRINGHETA,Paulo César
spellingShingle RIGOLON,Thaís Caroline Buttow
BARROS,Frederico Augusto Ribeiro de
VIEIRA,Érica Nascif Rufino
STRINGHETA,Paulo César
Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
author_facet RIGOLON,Thaís Caroline Buttow
BARROS,Frederico Augusto Ribeiro de
VIEIRA,Érica Nascif Rufino
STRINGHETA,Paulo César
author_sort RIGOLON,Thaís Caroline Buttow
title Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
title_short Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
title_full Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
title_fullStr Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
title_full_unstemmed Prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (Rubus sp.), blueberry (Vaccinium sp.) and jaboticaba (Plinia cauliflora (Mart.) Kausel) skin using colorimetric parameters
title_sort prediction of total phenolics, anthocyanins and antioxidant capacity of blackberry (rubus sp.), blueberry (vaccinium sp.) and jaboticaba (plinia cauliflora (mart.) kausel) skin using colorimetric parameters
description Abstract The food industry should have methods that allow identifying bioactive compounds quickly, efficiently and at low cost. The objective of this research was to obtain mathematical models for predicting the amount of total phenolics, anthocyanins and antioxidant capacity of blackberry, blueberry and jaboticaba skin, based on colorimetric parameters (L*, a*, b*, C* and h*). All analyses were done in the phenolic extracts obtained from these fruits. The mathematical models were obtained through multiple linear regression using the stepwise method. The significant correlation between the colorimetric parameters and chemical analyses resulted in models with a high predictive ability (high r2), such as in the determination of the contents of anthocyanins (r2 = 0.99), total phenolics (r2 = 0.86) and for the antioxidant capacity (r2 = 0.99). Thus, the prediction of levels of these bioactives compound, using colorimetric parameters, is very promising for cost and time savings.
publisher Sociedade Brasileira de Ciência e Tecnologia de Alimentos
publishDate 2020
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612020000600620
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