## 3 Results and Discussion
### Drying Characteristics
This can be ascribed to the higher water-holding capacity of air at low \(RH\), which causes the speeding-up of the moisture transfer over the same drying time. Precisely, the increment of \(RH\) from 20 to 60%, decreases the absolute humidity of drying air from 5.270 \(\times\) 10\({}^{-3}\) to 1.608 \(\times\) 10\({}^{-2}\) and saturation deficit from 5.800 \(\times\) 10\({}^{-3}\) to 2.550 \(\times\) 10\({}^{-4}\). In this regard, a shorter \(t\) of about 28.1% is required to reach a target \(X^{*}\) = 0.350 when decreasing the \(RH\) from 60 to 20% at the same \(T\) and \(v\). Nevertheless, the influence of the \(RH\) was noticeably smaller compared to the \(T\) effect. A high prediction was observed by the Page model (\(R^{2}\) = 0.997-0.999, \(RMSE\) = 5.510 \(\times\) 10\({}^{-3}\)-1.119 \(\times\) 10\({}^{-2}\), \(MAPE\) = 2.6-4.6%). The \(k\) values comprised between 7.901 \(\times\) 10\({}^{-3}\) and 9.502 \(\times\) 10\({}^{-3}\), whereas \(n\) values were falling between 0.764 and 0.819. Moreover, the effect of \(v\) on \(X^{*}\) is illustrated in Figure 3c. The \(v\) varied from 0.15 to 1.00 ms\({}^{-1}\), while \(RH\) = 40% and \(T\) = 30 \({}^{\circ}\)C. The results indicated that the increase of \(v\) exhibited a faster reduction of \(X^{*}\), which may be attributed to the faster heat transfer between the drying air and kernels, hence favored a more rapid drying process. The air velocity acted as an agent for supplying heat to kernels via convection and enabled the acceleration of moisture evaporation. At \(v\) =1.00 ms\({}^{-1}\), the time required to reach a target \(X^{*}\)= 0.350 was 348 min compared to 420 min needed for \(v\) = 0.15 ms\({}^{-1}\), which resulted in a reduction of 17.1%. However, it remains evident, that \(v\) had the least effect on the drying behavior compared to \(T\) and \(RH\). Alike findings were reported by [PERSON] and [PERSON] [34] and [PERSON] and [PERSON] [39] who agreed that \(v\) has a minor impact on the drying behavior of wheat. The statistical indicators revealed that the fitting model accurately anticipated the drying data at different \(v\). Particularly, the \(R^{2}\) \(\geq\) 0.996, \(RMSE\) \(\leq\) 1.418 \(\times\) 10\({}^{-2}\) and \(MAPE\) \(\leq\) 5.6%. The values of \(k\) and \(n\) ranged from 9.502 \(\times\) 10\({}^{-3}\) to 1.237 \(\times\) 10\({}^{-2}\) and from 0.740 to 0.774. Figure 4a presents the distribution of the residuals in a histogram chart computed as the difference between observed \(X^{*}\)obs and predicted \(X^{*}\)_pmd_ by Page model. The distribution of the residuals was soundly symmetric and unimodal around the abundant value 0 and suggesting a fairly normal distribution, which supported the validity of the selected model. The residuals were randomly scattered between \(-\)0.045 and 0.025. However, the majority of residuals (frequency from 31.86 to 34.13%) fell between 1.667 \(\times\) 10\({}^{-3}\) and 7.50 \(\times\) 10\({}^{-3}\). The observed versus predicted plot in Figure 4b displays a closely straight-line distribution of data which signposts a high accuracy prediction with \(R^{2}\) = 0.998, \(RMSE\) = 1.110 \(\times\) 10\({}^{-2}\) and \(MAPE\) = 5.8%. Moreover, the variation of the drying rate \(dXdt^{-1}\) over drying time \(t\) for the selected drying conditions is shown graphically in Figure 5. Overall, the highest changes of \(dXdt^{-1}\) were observed within the time-period (\(t\) < 400 min), where the migration of a large amount of moisture occurred. Afterwards, a progressive decrease over a more extended period was  
Figure 4: (**a**) Frequency distribution of residuals; (**b**) observed moisture ratio \(X^{*}\)obs vs. predicted \(X^{*}\)_pmd_ for all sets of drying conditions. observed which can be ascribed to the greater internal resistance for water removal.