A three-dimensional statistical reconstruction model of grapevine (Vitis vinifera) simulating canopy structure variability within and between cultivar/training system pairs.

BACKGROUND AND AIMS In grapevine, canopy-structure-related variations in light interception and distribution affect productivity, yield and the quality of the harvested product. A simple statistical model for reconstructing three-dimensional (3D) canopy structures for various cultivar-training system (C x T) pairs has been implemented with special attention paid to balance the time required for model parameterization and accuracy of the representations from organ to stand scales. Such an approach particularly aims at overcoming the weak integration of interplant variability using the usual direct 3D measurement methods. MODEL This model is original in combining a turbid-medium-like envelope enclosing the volume occupied by vine shoots with the use of discrete geometric polygons representing leaves randomly located within this volume to represent plant structure. Reconstruction rules were adapted to capture the main determinants of grapevine shoot architecture and their variability. Using a simplified set of parameters, it was possible to describe (1) the 3D path of the main shoot, (2) the volume occupied by the foliage around this path and (3) the orientation of individual leaf surfaces. Model parameterization (estimation of the probability distribution for each parameter) was carried out for eight contrasting C x T pairs. KEY RESULTS AND CONCLUSIONS The parameter values obtained in each situation were consistent with our knowledge of grapevine architecture. Quantitative assessments for the generated virtual scenes were carried out at the canopy and plant scales. Light interception efficiency and local variations of light transmittance within and between experimental plots were correctly simulated for all canopies studied. The approach predicted these key ecophysiological variables significantly more accurately than the classical complete digitization method with a limited number of plants. In addition, this model accurately reproduced the characteristics of a wide range of individual digitized plants. Simulated leaf area density and the distribution of light interception among leaves were consistent with measurements. However, at the level of individual organs, the model tended to underestimate light interception.

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