Two statistical tools for assessing functionality and protein characteristics of different fava bean (Vicia faba l.) ingredients
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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 journal › Journal article › Research › peer-review
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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