2022
DOI: 10.1002/jsfa.12153
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Determining the heat of desorption for cassava products based on data measured by an automated gravimetric moisture sorption system

Abstract: This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as

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Cited by 5 publications
(5 citation statements)
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“…This difference supports the enthalpy–entropy compensation theory. Therefore, data, presented in this study, showed that (T hm ) is higher than (T β ), suggesting that the adsorption process of dried fig samples is entropy-driven ( 35 , 38 , 82 , 83 ).…”
Section: Resultsmentioning
confidence: 59%
“…This difference supports the enthalpy–entropy compensation theory. Therefore, data, presented in this study, showed that (T hm ) is higher than (T β ), suggesting that the adsorption process of dried fig samples is entropy-driven ( 35 , 38 , 82 , 83 ).…”
Section: Resultsmentioning
confidence: 59%
“…As consequence, the interaction energy between the water molecules and the material surface increases (Djendoubi Mrad et al, 2012). Although the sorption heat is usually considered to be approximately independent of temperature, there are many systems where the effect of temperature on ΔHs,0 is not negligible (Hyla et al, 2019; Sarnavi et al, 2023). In food systems, this effect was observed in formulations containing cocoa (Collazos‐Escobar et al, 2020) and fats (Sun et al, 2023).…”
Section: Resultsmentioning
confidence: 99%
“…Symbols are mean values of three replicates and bars are standard deviations. temperature on ΔH s,0 is not negligible (Hyla et al, 2019;Sarnavi et al, 2023). In food systems, this effect was observed in formulations containing cocoa (Collazos-Escobar et al, 2020) and fats (Sun et al, 2023).…”
Section: Sorption Heat and Entropymentioning
confidence: 92%
“…The graph of observations and predictions of the results of the training and testing of the MLR model and the ANN model shown has a shaded area in the range of ±3.71% return. This is based on the standard error of estimation in the acceptable range of 2.36-3.71% based on research of cassava (Sarnavi et al, 2022). In graphs 4, 5, 6, and 7 it is found that the prediction results at the beginning have a higher error rate and have been shrinking lately.…”
Section: Model Comparisonmentioning
confidence: 99%