Phenological models applied to grapevines are valuable tools to assist in the decision of cultural practices related to winegrowers and winemakers. The two-parameter sigmoid phenological model was used to estimate the three main phenological stages of the grapevine development, i.e., budburst, flowering, and veraison. This model was calibrated and validated with phenology data for 51 grapevine varieties distributed in four wine regions in Portugal (Lisboa, Douro, Dão, and Vinhos Verdes). Meteorological data for the selected sites were also used. Hence, 153 model calibrations (51 varieties × 3 phenological stages) and corresponding parameter estimations were carried out based on an unprecedented comprehensive and systematized dataset of phenology in Portugal. For each phenological stage, the centroid of the estimated parameters was subsequently used, and three generalized sigmoid models (GSM) were constructed (budburst: d = −0.6, e = 8.6; flowering: d = −0.6, e = 13.7; veraison: d = −0.5, e = 13.2). Centroid parameters show high performance for approximately 90% of the varieties and can thereby be used instead of variety-specific parameters. Overall, the RMSE (root-mean-squared-error) is < 7 days, while the EF (efficiency coefficient) is > 0.5. Additionally, according to other studies, the predictive capacity of the models for budburst remains lower than for flowering or veraison. Furthermore, the F-forcing parameter (thermal accumulation) was evaluated for the Lisboa wine region, where the sample size is larger, and for the varieties with model efficiency equal to or greater than 0.5. A ranking and categorization of the varieties in early, intermediate, and late varieties was subsequently undertaken on the basis of F values. These results can be used to more accurately monitor and predict grapevine phenology during a given season, thus supporting decision making in the Portuguese wine sector.

Reliable estimations of parameter values and associated uncertainties are crucial for crop model applications in agro-environmental research. However, estimating many parameters simultaneously for different types of response variables is difficult. This becomes more complicated for grapevines with different phenotypes between varieties and training systems. Our study aims to evaluate how a standard least square approach can be used to calibrate a complex grapevine model for simulating both the phenology (flowering and harvest date) and yield of four different variety–training systems in the Douro Demarcated Region, northern Portugal. An objective function is defined to search for the best-fit parameters that result in the minimum value of the unweighted sum of the normalized Root Mean Squared Error (nRMSE) of the studied variables. Parameter uncertainties are estimated as how a given parameter value can determine the total prediction variability caused by variations in the other parameter combinations. The results indicate that the best-estimated parameters show a satisfactory predictive performance, with a mean bias of −2 to 4 days for phenology and −232 to 159 kg/ha for yield. The corresponding variance in the observed data was generally well reproduced, except for one occasion. These parameters are a good trade-off to achieve results close to the best possible fit of each response variable. No parameter combinations can achieve minimum errors simultaneously for phenology and yield, where the best fit to one variable can lead to a poor fit to another. The proposed parameter uncertainty analysis is particularly useful to select the best-fit parameter values when several choices with equal performance occur. A global sensitivity analysis is applied where the fruit-setting parameters are identified as key determinants for yield simulations. Overall, the approach (including uncertainty analysis) is relatively simple and straightforward without specific pre-conditions (e.g., model continuity), which can be easily applied for other models and crops. However, a challenge has been identified, which is associated with the appropriate assumption of the model errors, where a combination of various calibration approaches might be essential to have a more robust parameter estimation.

The European grapevine moth (Lobesia botrana; Denis and Schiffermüller, 1775) is considered a key pest for grapevine (Vitis vinifera L.) in the Douro Region, Portugal. The phenology of both the grapevine and the pest has changed in the last decades due to the increase in temperature. Here, we assess the potential impact of climate change on the (a)synchrony of both species. The results show that the phenological stages (budburst, flowering and veraison) undergo an advancement throughout the region (at an ~1 km resolution) under a climate change scenario (Representative Concentration Pathways, RCP8.5) for the period 2051–2080, with respect to the historic period (1989–2015). For cv. Touriga Nacional and Touriga Franca, the budburst advances up to 14 days, whereas for flowering and veraison the advancements are up to 10 days (mainly at low elevations along the Douro River). For the phenology of Lobesia botrana, earliness was also verified in the three flights (consequently there may be more generations per year), covering the entire region. Furthermore, the third flight advances further compared to the others. For both varieties, the interaction between the third flight (beginning and peak) and the veraison date is the most relevant modification under the future climate change scenario (RCP8.5, 2051–2080). The aforementioned outcomes from the phenology models help to better understand the possible shifts of both trophic levels in the region under future climate, giving insights into their future interactions.

In the present study, we calibrated and validated thermal models to predict the DOY date at which the grape maturity index, potential alcohol/total acidity (PA/TA), reaches 0.75 (MS_0.75), 1.0 (MS₁), 1.5 (MS_1.5), and 2.0 (MS₂) for two grapevine Portuguese varieties, Touriga Nacional (TN) and Encruzado (EN), growing in the Dão wine region, Portugal. Daily rates of forcing calculated with the Sigmoid (SM) function and the Degree Day (DD) function were used. The outcomes show that the best performance of the models was obtained for the heat accumulation starting at flowering (t_x = EL23). The analysis of model sensitivity to changes in forcing rate coefficients (T₀, e, and d) enabled the selection of the same models for all maturity stage of each variety. The selected models revealed significant predictability, though dependent on the grape maturity stage and variety (EFF > 0.81 for TN and EFF > 0.75 for EN). The non-linear regression analyses of sugar concentration (SC) and total acidity (TA) with heat accumulation, calculated using the select models, demonstrated that a high fraction of SC and TA variance was explained by the variation of these temperature-based indices. Comparatively to SC and TA, the results highlight that the thermal conditions accumulated from flowering had a lower influence on pH juice variance.

The European grapevine moth, Lobesia botrana (Lepidoptera: Tortricidae) is considered to be the main pest in the vineyards of the Douro Demarcated Region (DDR) due to the economic losses it can cause. Damage is caused by the larvae of this pest feeding on grape clusters, rendering them susceptible to Botrytis cinerea in mid-season and leading to the development of primary and secondary rot at harvest. Understanding this pest´s behaviour in the region under future climate scenarios is an increasing challenge. Hence, the present study aims to assess the potential effects of two likely climate change scenarios (Representative Concentration Pathways, RCP4.5 and RCP8.5) on Lobesia botrana phenology, particularly at the beginning and at the peak of the three Lobesia botrana flights. Our findings show that the phenological events generally occur earlier in all locations and mostly during the long-term period of 2021–2080, being 7 to 12 days in advance in the RCP4.5 scenario, and 15 to 24 days in advance in RCP8.5, when compared to current values (2000–2019) and regardless of the flight number. These results suggest that a fourth complete flight is likely in the future, and that Lobesia botrana will become a tetravoltine species in the region. The flight (male catches) and infestation of Lobesia botrana over periods with daily temperatures above its upper limit of development (> 33 °C) were also analysed during the period 2000–2019 in the targeted sites. The upward trend in the number of days with maximum temperature above 33 °C tended to be accompanied by a decrease in the total number of male catches during the second and third flights, as well as a decrease in the percentage of attacked bunches by the second and third generations. Overall, climate change is expected to influence the phenology of this pest in the DDR.