Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves

For two growing seasons (2005 and 2006), leaves of grapevine cv. Cabernet-Sauvignon were collected at three growth stages (bunch closure, veraison, and ripeness) from 10-year-old vines grafted on 1103 Paulsen and SO4 rootstocks and subjected to three watering regimes in a commercial vineyard in central Greece. Leaf shape parameters (leaf area-LA, perimeter-Per, maximum midvein length-L, maximum width-W, and average radial-AR) were determined using an image analysis system. Leaf morphology was affected by sampling time but not by year, rootstock, or irrigation treatment. The rootstock×irrigation×sampling time interaction was significant for all the leaf shape parameters (LA, Per, L, W, and AR) and the means of the interaction were used to establish relationships between them. A highly significant linear function between L and LA could be used as a non-destructive LA prediction model for Cabernet-Sauvignon. Eleven models proposed for the non-destructive LA estimation in various grapevine cultivars were evaluated for their accuracy in predicting LA in this cultivar. For all the models, highly significant linear functions were found between calculated and measured LA. Based on r ² and the mean square deviation (MSD), the model proposed for LA estimation in cv. Cencibel LA = 0.587(L×W)] was the most appropriate.