## 4 Discussion
Indeed, the goodness of F models is shown to significantly increase when the starting date is optimized against observed experimental data [30; 45], demonstrating that the beginning of eco-dormancy period is dependent to the origin of the observed dataset and, thus, on the fulfilment of specific physiological requirements that change in relation to the climate conditions of the different environments. In fact, although no relevant differences were found for budbreak date estimation of grapevine varieties using CF models set on 1 st of September/August starting dates, the discrepancy of the F model simulations was evident when 1 st of January/March dates were used. Higher accuracy of F models to predict the budbreak date of grapevine varieties collected in Northern European countries was observed using the 1 st of March starting date as also confirmed by [27], while the 1 st January seems to be a more suitable starting date for representing budbreak date of the grapevine varieties from Southern Europe (Figures S5-S7). In this case, a compromise between both starting dates may be represented by the beginning of February [59]. However, the adoption of different starting dates in F models highlights the role of temperature on bud growth and the need to satisfy specific dormancy requirements for varieties cultivated at different latitudes before budbreak occurrence. These results were supported by the work of [PERSON] et al. [60] on the grapevine flowering stage. The authors pointed out that the selection of a priori value for the starting of thermal unit accumulation in F models may lead to an under- or over-estimation of the flowering phase, demonstrating the importance of a correct evaluation of the previous phenological stage in respect to the subsequent one. These findings were also observed in relation to the flowering stage of other species such as olive tree e.g., [61]). In this context, we infer that the dormancy period of grapevine may play a relevant role for predicting budbreak date especially under future scenarios. Indeed, more accurate estimations of budbreak date using CF models are provided when the endo-dormancy release is calibrated against observed data of perennial crops. This behavior is particularly evident under warmer temperatures (after 2050) where CF without endo-dormancy calibration and F models showed poor performances of phenology prediction [62]. The accurate identification of the endo-dormancy release avoids selecting a fixed a priori date, especially when this may have strong consequences on the estimation of budbreak date (as in F models). The impact of warmer temperatures after the endo-dormancy release showed higher effect on the budbreak phase compared to the influence of temperatures during chilling accumulation, as reported by [PERSON] et al. [63] in a two-year ad hoc experiment with different grapevine varieties and temperature regimes. However, the starting date for thermal unit accumulation depends on the physiological features of the grapevine variety and their interaction with the environment. Indeed, we found that the effect of temperature during the last part of winter and beginning of spring was also evident when models were tested on external sites (independent datasets, Figure 5). Although most of the models showed satisfactory results during application (R\({}^{2}\) and AIC), the average error (RMSE) between observed and simulated data was relatively high (from 4 to 19 days). This situation was exacerbated in F models where the reliability in simulating budbreak is dependent to the use of a specific starting date (1 st of January/1 st of March) and thus the original observed dataset. The discrepancy between the two starting dates raises the question of which initial date to choose for forcing unit accumulation when simulations are conducted on a European scale [31; 64]. The implications of this study are particularly relevant for growers especially when considering the impact of climate change.