## 5 Conclusions  
This model intercomparison evidenced the different performance of the phenological models in reproducing the budbreak date of eight grapevine varieties collected in different European regions. The reliability of two main phenological modeling approaches (CF and F) was evaluated considering different starting dates (1 st January/March or 1 st September/August) and the selection methodologies of the parameter set (HP and AV) for model application. The results showed, in general, higher performances of CF compared to F models where fixed starting dates were adopted, even if neither modeling approach highlighted a clear supremacy over the other. For this reason, CF and F models' behavior should be further investigated through ad hoc experiments for evaluating the role of dormancy on budbreak occurrence. Indeed, the findings of our model simulations evidenced distinct thermal requirements for grapevine varieties cultivated at different latitudes (i.e., Northern Europe vs. Southern Europe). The use of different starting dates highlighted that, unlike CF models, the accurate estimation of budbreak in F models is affected by the selection of a starting date for beginning of the eco-dormancy period. This implies that, if this phase is not accurately defined, F models may lead to over- or under-estimations of the budbreak date under different environmental conditions. In this context, comprehensive phenological datasets (e.g., grapevine phenological data collected at different latitudes) are needed to thoroughly investigate the effect of temperature variability on dormancy period and budbreak estimation. Finally, it is proposed the development and implementation of improved phenological models, which consider the effect of other climate (e.g., radiation) and soil (e.g., soil temperature) variables as well as some regulating factors of the endo-dormancy phase (e.g., day length). **Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2076-3417/10/11/3800/s1](http://www.mdpi.com/2076-3417/10/11/3800/s1)]([http://www.mdpi.com/2076-3417/10/11/3800/s1](http://www.mdpi.com/2076-3417/10/11/3800/s1)). Figure S1: R\({}^{2}\) and AIC values of the BRIN Daily model obtained for all fitted and average models, grapevine varieties and starting dates. The symbols (points and triangles) show the model results at two starting dates (in this example t\({}_{0}=-121\) and \(-152\) DOY), while the two colours represent fitting (red) and validation (blue) procedure, respectively. The filled symbols constitute the R\({}^{2}\) and AIC values of the models obtained by the selected HP parameter sets, while the dashed (fitting) and dotted (validation) lines depict the average R\({}^{2}\) and AIC values for both starting dates (in this example orange line \(=-121\) DOY and green line \(=-152\) DOY). The boxplots represent the R\({}^{2}\) and AIC values distribution for HP (orange and light blue: HP model application on all validation subsamples for t\({}_{0}=-121\) and t\({}_{0}=-152\) DOY, respectively) and AV (boxplot in the shaded area, orange and light blue: AV application on all validation subsamples for t\({}_{0}=-121\) and t\({}_{0}=-152\) DOY, respectively). The outliers represent all values out of the 1.5*InterQuartile Range (IQR) of the boxplot. Figure S2: R\({}^{2}\) and AIC values of the BRIN Hourly model obtained for all fitted and average models, grapevine varieties and starting dates. The symbols (points and triangles) show the model results at two starting dates (in this example t\({}_{0}=-121\) and \(-152\) DOY), while the two colours represent fitting (red) and validation (blue) procedure, respectively. The filled symbols constitute the R\({}^{2}\) and AIC values of the models obtained by the selected HP parameter sets, while the dashed (fitting) and dotted (validation) lines depict the average R\({}^{2}\) and AIC values for both starting dates (in this example orange line \(=\) -121 DOY and green line \(=\) -152 DOY).