Variety, temperature and viticulture practices (e.g. pruning, trimming, cluster thinning, irrigation etc.) all have an influence on grapevine (Vitis vinifera L.) phenology and berry maturation. Process-based phenological modelling which assumes temperature as the driving factor can be used to predict differences in development among varieties. Management practices including those that alter the Leaf Area to Fruit Weight (LA:FW) ratio may also influence the timing of key phenological stages and berry maturation. Regression modelling the relationship between LA:FW ratio and phenology or maturation parameters will enable a better understanding of these responses for different varieties. The aims of this work were 1) to characterise the differences between varieties for three key phases of development: flowering, veraison and the time to reach a target sugar concentration set at 200g/L using process-based phenological models; 2) to investigate different methods of characterising veraison as a phenological event to define the value of alternate objective measures; 3) to investigate the influence of altering the LA:FW ratio via trimming shoots (reducing leaf area) or removing crop (reducing the fruit weight) on two occasions (shortly after fruit set or at veraison) on the time of veraison and berry maturation parameters (soluble solids, titratable acidity, pH and berry weight). 2) and 3) were considered for two different varieties, Pinot noir and Sauvignon blanc. Linear and non-linear regression modelling was used to explore the relationships in 2) and 3). For the first aim, the Grapevine Flowering Veraison (GFV) model that uses a linear thermal summation of average daily temperatures from the 60th day of the year (in the Northern hemisphere) and a base temperature of 0°C was used to classify 95 varieties for the parameter F* (the accumulation of forcing units) for the time of 50% flowering and 105 varieties for 50% veraison. For maturity, data corresponding to a threshold sugar concentration of 200g/L were calibrated for seven different process-based models and calibrations calculated from either daily mean, daily maximum, average or hourly temperatures. The best fit model was the Sigmoid model in terms of efficiency and parsimony - assessed by the lowest Akaike Information Criterion (AIC), model efficiency, (EF), and Root Mean Squared Error (RMSE) - and the GFV model in terms of parsimony using daily mean temperatures. 35 varieties were parameterised and classified using both models for the day of the year to reach a sugar concentration of 200g/L. Seven different ways of assessing veraison were used to determine the relationship between soluble solids concentration and the measurement considered. Soluble solids ranged from 7 to 9 °Brix for the different methods. 8 °Brix was found to be a simple robust measure that allows comparison between different varieties, seasons and sites and was used in subsequent modelling to investigate the influence of LA:FW ratio on phenology and berry composition. Altering the LA:FW ratios of two varieties (Pinot noir and Sauvignon blanc) by trimming main shoots (leaf removal) delayed veraison, and both leaf removal and crop thinning influenced the dynamics of soluble solids accumulation; leaf removal slowed rates of soluble solids accumulation and resulted in lower concentrations of soluble solids at harvest whereas crop removal had the opposite effect. Titratable acidity, berry weight and pH were unaffected by the LA:FW ratio changes. The method of removing crop (removing all bunches on alternate shoots versus removing alternating bunches-apical then basal- from each shoot) did not influence the response but the presence of laterals advanced soluble solids accumulation. Non-linear exponential regression models across a wide range of LA:FW ratios best described the following different parameters for both varieties: Day of year to 8 °Brix, duration from 8 to 14 °Brix and soluble solids at harvest. The classification of flowering, veraison and the day to reach a sugar concentration of 200g/L are the most extensive to date within the literature. The methodology developed for these classifications and to assess the quality of prediction could also be applied to other crops. LA:FW ratio manipulations can shift the timing of keys events, such as veraison and soluble solids accumulation; the regression results indicated that it is possible to delay timing by the same magnitude of time as observed for between varietal differences in timing. This represents a potential tool to manipulate changes in development under future climate scenarios.