. 2023 Oct 7;100:106633. doi: 10.1016/j.ultsonch.2023.106633

Table 1.

The predicted values, constants and statistical analysis of the models fitted to the drying data for thin-layer guar gum-coated sour cherry.

Model name	Model equation	Model constants	SSE	r	RMSE	Predicted moisture ratio
Midilli	MR = aexp(-ktⁿ) + bt	a = 0.9999 k = 0.0944 n = 0.5083 b = -0.0023	0.0002	0.9998	0.0082	1.000	0.653	0.518	0.417	0.331	0.256	0.188
Page	MR = exp(-ktⁿ)	k = 0.0504 n = 0.761	0.0015	0.9983	0.0177	1.000	0.673	0.511	0.401	0.321	0.260	0.213
Wang and Singh	MR = 1 + at + bt²	a = -0.0184 b = 0.0001	0.0141	0.9846	0.0531	1.000	0.747	0.538	0.375	0.256	0.183	0.154
Newton	MR = exp(-kt)	k = 0.0198	0.0114	0.9876	0.0435	1.000	0.743	0.552	0.410	0.305	0.227	0.168
Henderson and Pabis	MR = aexp(-kt)	a = 0.9533 k = 0.0187	0.0085	0.9908	0.0412	0.953	0.720	0.544	0.411	0.310	0.234	0.177
Logarithmic	MR = aexp(-kt) + c	a = 0.8362 k = 0.0269 c = 0.1435	0.0048	0.9948	0.0346	0.980	0.702	0.517	0.393	0.310	0.255	0.218
Experimental moisture ratio						1.000	0.646	0.525	0.408	0.329	0.258	0.192

* where, SSE is sum of squared errors; r is correlation coefficient; RMSE is root mean squared error; MR is moisture ratio (dimensionless); t is time (min); a, k, n, b, and c are coefficients of the models (dimensionless).