Table 2.

Statistical error functions employed to identify the most suitable model for describing drying kinetics.

Error Function	Reference
$R^2=1-\left[{\displaystyle \frac{{\sum }_{i=1}^N{\left({MR}_{exp,i}-{MR}_{pre,i}\right)}^2}{{\sum }_{i=1}^N{\left({\overline{MR}}_{exp}-{MR}_{exp,i}\right)}^2}}\right]$	[28]
${\chi }^2={\displaystyle \sum _{i=1}^N}{\displaystyle \frac{{\left({MR}_{exp}-{MR}_{pre}\right)}^2}{{MR}_{pre}}}$	[13]
$MSE={\displaystyle \frac{1}{N}}{\displaystyle \sum _{i=1}^N}{\left({MR}_{exp,i}-{MR}_{pre,i}\right)}^2$	[13]
$SSE={\displaystyle \sum _{i=1}^N}{\left({MR}_{exp,i}-{MR}_{pre,i}\right)}^2$	[23]
$RMSE={\left({\displaystyle \frac{1}{N}}{\displaystyle \sum _{i=1}^N}{\left[{MR}_{exp,i}-{MR}_{pre,i}\right]}^2\right)}^{{\displaystyle \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$2$}\right.}}$	[29]
$AIC=N ln\left({\displaystyle \frac{SSE}{N}}\right)+2K$	[9]
${AIC}_c=AIC+{\displaystyle \frac{2K(K+1)}{N-K-1}}$	[9]

K represents the number of model parameters, and N indicates the total number of data points used. The terms MR_pre and MR_exp refer to the predicted and experimental moisture ratios, respectively. The statistical metrics include R² (coefficient of determination), χ² (chi-squared statistic), MSE (mean squared error), SSE (sum of square error), RMSE (root mean square error), AIC (Akaike information criterion), and AIC_c (adjusted Akaike information criterion).