# Some Aspects of the Modelling of Dried Red Beets Rehydration Process
## 3 Results and Discussion  
Table 4 presents the results of the statistical analysis on the modelling of mass, volume, dry matter, and moisture content changes during the rehydration of dried red beets. As far as mass gain during the rehydration of dried red beets is concerned, it can be stated that all models described the mass gain in a quite acceptable way. The values of used statistical test criteria for the five considered models varied between 0.9069 and 0.9967 for R\({}^{2}\), 0.9020 and 0.9964 for adjusted R\({}^{2}\), and 0.0179 and 0.2388 for RMSE. The lowest values of R\({}^{2}\) and adjusted R\({}^{2}\) were present in the [PERSON] (Newton) model and [PERSON] and Pabis model (0.9069-0.9852 and 0.9020-0.9845, respectively), but the mentioned models showed better values regarding the root mean square error (0.0383-0.1075) than the [PERSON] model (0.1078-0.2388) for which the values of R\({}^{2}\) and adjusted R\({}^{2}\) ranged from 0.9659 to 0.9950 and from 0.9642 to 0.9948, respectively. The Page and the modified Page models described the kinetics of dried red beet's mass gain during rehydration in the best way. The values of the used statistical test methods were as follows: R\({}^{2}\) = 0.9687-0.9967, adjusted R\({}^{2}\) = 0.9671-0.9964, and RMSE = 0.0179-0.0528. The conclusions drawn from the statistical analyses on the modelling of volume increase were similar to the question of mass gain. It can be accepted that all models fitted quite well to the experimental data for volume increase. The results for the statistical analyses for all considered models were the following: R\({}^{2}\) = 0.8885-0.9950, adjusted R\({}^{2}\) = 0.8826-0.9947, and RMSE = 0.0210-0.4080. The Page model and the modified Page model showed, however, the best values of the considered statistical criteria, namely, 0.9444-0.9950 for the coefficient of determination, 0.9414-0.9947 for the adjusted coefficient of determination, and 0.0210-0.0877 for the root mean square error. Therefore, both modelscan be recommended as the most suitable for the modelling of the course of volume increase during the rehydration process for dried red beets. As far as dry matter loss during the rehydration of dried red beets is concerned, it can be noticed that all models described the kinetics of dry matter changes during the considered process satisfactorily. The R\({}^{2}\) fell within the range of 0.9321 to 0.9965, the adjusted R\({}^{2}\) changed from 0.9285 to 0.9963, and the RMSE varied between 0.0135 and 0.986. Comparing the results of the statistical analyses for the five considered models, the Peleg model can be treated as the best among them (R\({}^{2}\) = 0.9400-0.9947, adjusted R\({}^{2}\) = 0.9368-0.9944, and RMSE = 0.0135-0.0362). Taking into account the values of the determination coefficient (0.9380-0.9934) and the values of the adjusted determination coefficient (0.9347-0.9931), it can be assumed that all considered models performed well regarding the moisture content increase during the rehydration process for dried red beets. The values of the RMSE for the Page model (2.5976-5.6206) were, however, much higher than for the remaining models (0.267-0.0746). Comparing the results of the statistical analyses, it can be stated that the most acceptable values of the considered test methods were obtained from the modified Page model (R\({}^{2}\) = 0.9643-0.9931, adjusted R\({}^{2}\) = 0.9625-0.9928, RMSE = 0.0267-0.0603). Our results for the rehydration process modelling have been similar to those previously presented [45; 46; 47; 50; 74; 75]. The results of examining the impact of \(T_{d}\), \(v_{d}\), \(L\), and \(T_{r}\) on the constants of the investigated models are presented in Table 5 for the models adopted to predict the mass gain during the rehydration of dried red beets, in Table 6 for the models adopted to volume increase, in Table 7 for the models adopted to dry matter loss, and in Table 8 for the models adopted to moisture content increase.