Characterization of vine canopy through two dimensional imaging

In the last decade, reconstruction of plant dimensions and volume has gained a noticeable importance, in particular for the possibility of collecting data correlated to biomass, leaves area, etc. This is specifically of interest in the case of vineyards, where knowledge of variability can be not only a useful mean to evaluate the health condition of the vines and of the grapes, but also an important input to allow variable management practices. Different sensing technologies are available for shape reconstruction, as for instance ultrasonic sensors, laser scanners or depth cameras, however, their practical application is still limited by low quality information, high costs, or high speed data processing demand. For the present work two-dimensional imaging is proposed as a viable solution for shape reconstruction of canopies. The method takes advantage of low cost 2D commercial cameras, which can be installed on board the tractor allowing on the go collection of images of plants from the bottom. The paper describes the instrumentation set up and integration with a specific thresholding algorithm allowing segmentation of canopy profile. Tests were carried out on 20 different dates on a glera vineyard in an experimental farm in the North of Italy. The results were correlated with the number of leaves, leaf area index and canopy volume. High correlation was identified in the case of volume with coefficients of determination R² > 0.7 in most of the cases.