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 (MS0.75), 1.0 (MS1), 1.5 (MS1.5), 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 function (SM) and the Degree Day function (DD) were used. The outcomes show that the best performance of the models was obtained for the heat accumulation starting at flowering (tx = 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.

Background and Aims The evaluation of genotype‐by‐environment interaction and the genotypic correlations between important economic traits are two relevant issues of the methodology of grapevine selection that remain insufficiently explored. The aim of this study is to provide methodological tools to: (i) assess the genotype‐by‐environment interaction and (ii) evaluate the genetic correlations between traits and their practical impacts on genetic selection. Methods and Results A multi‐environment analysis for each trait and multi‐trait analyses were applied for the evaluation of genotype‐by‐environment interaction and genetic correlation between pairs of traits, respectively. The presence of genotype‐by‐environment interaction for all traits was detected. Genetic correlation between traits varied from non‐existent to strong. Conclusions This study supports and recommends the applicability of multi‐environment and multi‐trait analyses to grapevine clonal selection data. The detection of genotype‐by‐environment interaction in grapevine clones was successfully assessed. When multi‐trait models were applied they provided greater accuracy and precision in selection. Significance of the Study This study shows the importance of the mixed multivariate models for the development of the grapevine clonal selection. They should be implemented in a grapevine selection program.

The grapevine vegetative cycle, which is morphologically described by its phenological stages, is strongly determined by weather conditions. Phenological models are widely applied in viticulture and are based on the assumption that air temperature is the preponderant environmental factor which determines vine development. In this study, phenological development models (PDMs) were calibrated and validated to simulate several intermediate stages between budbreak and veraison for cv. Touriga Nacional (TN) and cv. Encruzado (EN) winegrape varieties, which are widely grown in the Dao Wine Region, Portugal. These are thermal models, with which the daily sum of the rate of forcing (R) was calculated using a sigmoid function. For this purpose, a high-quality and comprehensive dataset was used which combines phenology data and weather station data in several vineyard sites spread over the region. The model showed an overall high performance (global RMSE of 5.4 days for EN and 5.0 days for TN), although it depended on the phenological stage and variety. The RMSE ranged from 3.2 to 6.2 for TN, and from 3.9 to 6.8 for EN. For both varieties and in all phenological stages, the RMSE was significantly lower than the standard deviation of the phenological observations. For TN, the model efficiency was greater than 0.71 for all phenological stages. In future studies, these models will be combined with specific models that simulate the evolution of winegrape berry quality indicators commonly used for harvest decision support. The relatively low complexity of the selected PDMs enables their use as a crop management and decision support tool. To our knowledge, no previous studies have been carried out on either of these two varieties and their intermediate phenological timings. The present study is an illustration of conceivable model development under diverse environmental conditions, thus allowing similar approaches to be adopted in other wine regions on a worldwide scale.

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In this study, the influence of soil and atmosphere conditions on noon and basal leaf water potential of vines ''Touriga Nacional'' in the Dão region submitted to different irrigation treatments is analysed. Both indicators showed to be dependent on environmental conditions at the time of measurement. Leaf water potential at noon of fully watered plants was linearly related with atmospheric conditions, with values registered when vapour pressure deficit (VPD) was higher than approximately 3 kPa being no different from the values registered in stressed plants. Therefore, this indicator cannot be reliably used to distinguish different plant water stress levels when atmospheric conditions induce high evaporative demands. The basal leaf water potential (w b) was also influenced by VPD at the time of measurement for all soil water conditions. In well irrigated plants, it was even possible to establish a baseline that can therefore be used to identify nonwater stressed conditions (w b (MPa) =-0.062-0.0972 VPD (kPa), r 2 = 0.78). A good correlation was found between soil humidity and w b. However, more than the average value of the whole thickness of soil monitored, the w b values were dependent on the distribution of soil humidity, with the plants responding to the presence of wet layers. Communicated by V. Sadras.