Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients

Research output: Contribution to journalJournal articlepeer-review

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Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients. / Sharan, Siddharth; Zotzel, Jens; Stadtmüller, Johannes; Bonerz, Daniel; Aschoff, Julian; Saint-Eve, Anne; Maillard, Marie Noëlle; Olsen, Karsten; Rinnan, Åsmund; Orlien, Vibeke.

In: Foods, Vol. 10, No. 10, 2489, 2021.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Sharan, S, Zotzel, J, Stadtmüller, J, Bonerz, D, Aschoff, J, Saint-Eve, A, Maillard, MN, Olsen, K, Rinnan, Å & Orlien, V 2021, 'Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients', Foods, vol. 10, no. 10, 2489. https://doi.org/10.3390/foods10102489

APA

Sharan, S., Zotzel, J., Stadtmüller, J., Bonerz, D., Aschoff, J., Saint-Eve, A., Maillard, M. N., Olsen, K., Rinnan, Å., & Orlien, V. (2021). Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients. Foods, 10(10), [2489]. https://doi.org/10.3390/foods10102489

Vancouver

Sharan S, Zotzel J, Stadtmüller J, Bonerz D, Aschoff J, Saint-Eve A et al. Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients. Foods. 2021;10(10). 2489. https://doi.org/10.3390/foods10102489

Author

Sharan, Siddharth ; Zotzel, Jens ; Stadtmüller, Johannes ; Bonerz, Daniel ; Aschoff, Julian ; Saint-Eve, Anne ; Maillard, Marie Noëlle ; Olsen, Karsten ; Rinnan, Åsmund ; Orlien, Vibeke. / Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients. In: Foods. 2021 ; Vol. 10, No. 10.

Bibtex

@article{f9db279d72aa4e439ec671d7151b175c,
title = "Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients",
abstract = "Fava bean (Vicia faba L.) is a promising source of proteins that can be potentially used as nutritional and/or functional agents for industrial food applications. Fava ingredients are industrially produced, modified, and utilized for food applications. Their processing conditions influence physico-chemical protein properties that further impact ingredient functionality. To design a functionally suitable ingredient, an understanding of the interrelationships between different properties is essential. Hence, this work aimed to assess two statistical analytical tools, Pearson{\textquoteright}s correlation and Principal Component Analysis (PCA), for investigating the role of the process conditions of fava ingredients on their functional and protein properties. Fava concentrates were processed by pH (2, 4, 6.4 and 11), temperature (55, 75 and 95◦ C) and treatment duration (30 and 360 min) into different modified ingredients. These were utilized under two application conditions (pH 4 and 7), and their foam and emulsion properties as well as their ingredient characteristics (charge, solubility, and intrinsic fluorescence) were measured. The results show that foam and emulsion properties are not correlated to each other. They are associated with different protein and non-protein attributes as fava concentrate is a multi-component matrix. Importantly, it is found that the results from the two statistical tools are not fully comparable but do complement each other. This highlights that both statistical analytical tools are equally important for a comprehensive understanding of the impact of process conditions on different properties and the interrelationships between them. Therefore, it is recommended to use Pearson{\textquoteright}s correlation and principal component analysis in future investigations of new plant-based proteins.",
keywords = "Beverage application, Emulsion, Foam, PCA, Pearson{\textquoteright}s correlation, Processing",
author = "Siddharth Sharan and Jens Zotzel and Johannes Stadtm{\"u}ller and Daniel Bonerz and Julian Aschoff and Anne Saint-Eve and Maillard, {Marie No{\"e}lle} and Karsten Olsen and {\AA}smund Rinnan and Vibeke Orlien",
note = "Funding Information: This work was supported by the European Union?s Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie grant agreement no. 765415 (acronym FOODENGINE). Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2021",
doi = "10.3390/foods10102489",
language = "English",
volume = "10",
journal = "Foods",
issn = "2304-8158",
publisher = "MDPI AG",
number = "10",

}

RIS

TY - JOUR

T1 - Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients

AU - Sharan, Siddharth

AU - Zotzel, Jens

AU - Stadtmüller, Johannes

AU - Bonerz, Daniel

AU - Aschoff, Julian

AU - Saint-Eve, Anne

AU - Maillard, Marie Noëlle

AU - Olsen, Karsten

AU - Rinnan, Åsmund

AU - Orlien, Vibeke

N1 - Funding Information: This work was supported by the European Union?s Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie grant agreement no. 765415 (acronym FOODENGINE). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021

Y1 - 2021

N2 - Fava bean (Vicia faba L.) is a promising source of proteins that can be potentially used as nutritional and/or functional agents for industrial food applications. Fava ingredients are industrially produced, modified, and utilized for food applications. Their processing conditions influence physico-chemical protein properties that further impact ingredient functionality. To design a functionally suitable ingredient, an understanding of the interrelationships between different properties is essential. Hence, this work aimed to assess two statistical analytical tools, Pearson’s correlation and Principal Component Analysis (PCA), for investigating the role of the process conditions of fava ingredients on their functional and protein properties. Fava concentrates were processed by pH (2, 4, 6.4 and 11), temperature (55, 75 and 95◦ C) and treatment duration (30 and 360 min) into different modified ingredients. These were utilized under two application conditions (pH 4 and 7), and their foam and emulsion properties as well as their ingredient characteristics (charge, solubility, and intrinsic fluorescence) were measured. The results show that foam and emulsion properties are not correlated to each other. They are associated with different protein and non-protein attributes as fava concentrate is a multi-component matrix. Importantly, it is found that the results from the two statistical tools are not fully comparable but do complement each other. This highlights that both statistical analytical tools are equally important for a comprehensive understanding of the impact of process conditions on different properties and the interrelationships between them. Therefore, it is recommended to use Pearson’s correlation and principal component analysis in future investigations of new plant-based proteins.

AB - Fava bean (Vicia faba L.) is a promising source of proteins that can be potentially used as nutritional and/or functional agents for industrial food applications. Fava ingredients are industrially produced, modified, and utilized for food applications. Their processing conditions influence physico-chemical protein properties that further impact ingredient functionality. To design a functionally suitable ingredient, an understanding of the interrelationships between different properties is essential. Hence, this work aimed to assess two statistical analytical tools, Pearson’s correlation and Principal Component Analysis (PCA), for investigating the role of the process conditions of fava ingredients on their functional and protein properties. Fava concentrates were processed by pH (2, 4, 6.4 and 11), temperature (55, 75 and 95◦ C) and treatment duration (30 and 360 min) into different modified ingredients. These were utilized under two application conditions (pH 4 and 7), and their foam and emulsion properties as well as their ingredient characteristics (charge, solubility, and intrinsic fluorescence) were measured. The results show that foam and emulsion properties are not correlated to each other. They are associated with different protein and non-protein attributes as fava concentrate is a multi-component matrix. Importantly, it is found that the results from the two statistical tools are not fully comparable but do complement each other. This highlights that both statistical analytical tools are equally important for a comprehensive understanding of the impact of process conditions on different properties and the interrelationships between them. Therefore, it is recommended to use Pearson’s correlation and principal component analysis in future investigations of new plant-based proteins.

KW - Beverage application

KW - Emulsion

KW - Foam

KW - PCA

KW - Pearson’s correlation

KW - Processing

U2 - 10.3390/foods10102489

DO - 10.3390/foods10102489

M3 - Journal article

C2 - 34681537

AN - SCOPUS:85118167758

VL - 10

JO - Foods

JF - Foods

SN - 2304-8158

IS - 10

M1 - 2489

ER -

ID: 286421013