6533b7d8fe1ef96bd126b38f

RESEARCH PRODUCT

L'imagerie multispectrale embarquée pour caractériser la croissance et l'état sanitaire du feuillage de la vigne

subject

description

Multispectral imaging systems are widely used in remote sensing and applied to viticulture context for the canopy characterization. This technique is not used in proximal sensing, to characterize vineyard foliage. Yet the results of field tests led in fixed position have revealed its capacity to estimate the leaf area. The aim of this project is to assess the suitable of a multispectral imaging system as an embedded sensor for vine foliage characterization. To this end, a multispectral camera acquiring visible and near-infrared images and a Greenseeker RT-100 apparatus providing an NDVI (Normalized Difference Vegetation Index), were installed on a track laying tractor. It was equipped with a centimetric GPS device for data georeferencing. Image acquisition was realized outdoor (using natural sunlight) in the trellis plan. The experimental field was composed of three grape varieties (Pinot Noir, Chardonnay and Meunier) that were planted according to the latin square pattern. Several datasets were collected in 2013, which corresponded to different phenological stages of the vine, from the berry formation to a stage close to harvest date. This work will present the advantage of imagery technique to focus the characterization of vegetation in the berry area. We will present the evolution of the vegetation in this area and compared it to ones considered in the general trellis high. Three grapevine varieties are observed and two modalities of pruning methods are tested : Chablis pruned and Cordon (or Simple- Guyot) pruned. Further analysis of the data revealed that multispectral imaging is an accurate and versatile technique to characterise vine foliage especially with NDVI applications.