## 3 Results and Discussion
### ANN Modeling
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \multicolumn{1}{c}{**Outputs**} & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **Bias** \\ \hline _E. coli_ & \(-1.975\) & \(2.184\) & \(0.238\) & \(-3.249\) & \(3.170\) & \(-0.966\) & \(-1.380\) & \(-0.038\) \\ \hline _L. monocytogenes_ & \(3.812\) & \(-0.721\) & \(3.187\) & \(-2.314\) & \(-0.781\) & \(3.672\) & \(0.430\) & \(-2.516\) \\ \hline _Salmonella_ spp. & \(-1.050\) & \(2.077\) & \(1.293\) & \(0.412\) & \(0.956\) & \(1.309\) & \(-0.427\) & \(-0.883\) \\ \hline Enterobacteriaceae & \(-2.312\) & \(2.685\) & \(0.499\) & \(-1.411\) & \(3.048\) & \(-0.823\) & \(-1.563\) & \(-0.213\) \\ \hline TPC & \(-0.844\) & \(1.456\) & \(0.758\) & \(-0.376\) & \(0.957\) & \(0.904\) & \(-0.157\) & \(-0.513\) \\ \hline \end{tabular}
\end{table} 
Table 7: The weight coefficients and biases: \(W_{2}\) and \(B_{2}\), respectively. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \multicolumn{1}{c}{**Parameter**} & \(\boldsymbol{\chi}^{2}\) & _RMSE_ & _MBE_ & _MPE_ & _SSE_ & _AARD_ & \(\boldsymbol{r}^{2}\) \\ \hline _E. coli_ & \(0.001\) & \(0.037\) & \(-2.5\times 10^{-5}\) & \(0.574\) & \(0.041\) & \(0.924\) & \(0.997\) \\ \hline _L. monocytogenes_ & \(0.007\) & \(0.085\) & \(0.000\) & \(2.553\) & \(0.217\) & \(1.859\) & \(0.994\) \\ \hline _Salmonella_ spp. & \(0.000\) & \(0.010\) & \(-3.7\times 10^{-5}\) & \(0.197\) & \(0.003\) & \(0.568\) & \(0.998\) \\ \hline Enterobacteriaceae & \(9.14\times 10^{-5}\) & \(0.009\) & \(-0.000\) & \(0.145\) & \(0.003\) & \(0.351\) & \(0.999\) \\ \hline TPC & \(0.000\) & \(0.012\) & \(-1.5\times 10^{-5}\) & \(0.196\) & \(0.005\) & \(0.541\) & \(0.999\) \\ \hline \end{tabular}
\end{table} 
Table 8: The goodness-of-fit tests for the developed ANN model. The developed ANN model had a minor lack of observed fit tests (Tables 8 and 9), implying that the ANN model satisfactorily predicted all the responses of the microorganisms' viability in molasses. In the past decade, ANN models have been successfully used to model osmotic pretreatment in sugar beet molasses of various food materials, including pork [47], fish [48], celery [11], cabbage [10], and appels [49]. To our knowledge, the present study is the first report on the ANN modeling of microorganisms' viability in sugar beet molasses depending on the levels of osmolality and different exposure times. Figure 4: Comparison between experimentally obtained and ANN model–predicted values of (**a**) _E. coli_, (**b**) _L. monocytogenes_, (**c**) _Salmonella_ spp., (**d**) Enterobacteriaceae, and (**e**) TPC. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameter** & **Skew** & **Kurt** & **Mean** & **StDev** & **Var** \\ \hline _E. coli_ & 2.294 & 9.468 & \(-2.5\times 10^{-5}\) & 0.037 & 0.001 \\ \hline _L. monocytogenes_ & \(-1.509\) & 5.684 & 0.000 & 0.086 & 0.007 \\ \hline _Salmonella_ spp. & \(-0.278\) & \(-0.906\) & \(-3.7\times 10^{-5}\) & 0.010 & 0.000 \\ \hline Enterobacteriaceae & 0.356 & 2.228 & 0.000 & 0.009 & \(9.14\times 10^{-5}\) \\ \hline TPC & 0.036 & 0.861 & \(-1.5\times 10^{-5}\) & 0.012 & 0.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: The residual analysis for the developed ANN model. Experimental validation for developed models in empiric systems of the osmotic dehydration of different food materials is not covered in the paper, so this research will be continued in another study, with an elaborated experimental plan of the models' validation.