Journal of Food Measurement and Characterization, Volume (17), No (2), Year (2023-4) , Pages (1962-1973)

Title : ( Predicting the rehydration process of mushroom powder by multiple linear regression (MLR) and artificial neural network (ANN) in different rehydration medium )

Authors: saeed nejatdarabi , Mohebbat Mohebbi ,

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Abstract

This study investigated mushroom powder rehydration using water, cornstarch, and potato starch as a rehydration medium. Wettability, dispersibility, and solubility were measured as the three main parameters of rehydration. Corn starch and potato starch were prepared at concentrations of 1, 2.5, and 5% and three temperatures of 30, 50, and 70 °C. Water was used as a control solution at three temperatures of 30, 50, and 70 °C. At a constant temperature, as starch concentration increased, it negatively affected wettability and solubility but positively affected dispersibility. The temperature of the rehydration medium also played a positive role in the rehydration of mushroom powder. According to our results, water, cornstarch, and potato starch were the best medium rehydration for mushroom powder, respectively. Multiple linear regression and an artificial neural network predicted rehydration process. Both models have a good ability to predict the rehydration of mushroom powder. However, the artificial neural network showed fewer RMSE than multiple linear regression. Moreover, Pearson correlation was used to determine the correlation between the rehydration process and different rehydration medium conditions. There were very high correlations between the rehydration parameter of mushroom powder by rehydration medium conditions in all rehydration mediums.

Keywords

Rehydration medium · Pearson correlation · Wettability · Dispersibility · Solubility
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@article{paperid:1094148,
author = {Nejatdarabi, Saeed and Mohebbi, Mohebbat},
title = {Predicting the rehydration process of mushroom powder by multiple linear regression (MLR) and artificial neural network (ANN) in different rehydration medium},
journal = {Journal of Food Measurement and Characterization},
year = {2023},
volume = {17},
number = {2},
month = {April},
issn = {2193-4126},
pages = {1962--1973},
numpages = {11},
keywords = {Rehydration medium · Pearson correlation · Wettability · Dispersibility · Solubility},
}

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%0 Journal Article
%T Predicting the rehydration process of mushroom powder by multiple linear regression (MLR) and artificial neural network (ANN) in different rehydration medium
%A Nejatdarabi, Saeed
%A Mohebbi, Mohebbat
%J Journal of Food Measurement and Characterization
%@ 2193-4126
%D 2023

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