Initial steps for high-throughput phenotyping in vineyards. Vitis 2014

The evaluation of phenotypic characters of grape-vines is required directly in vineyards and is strongly limited by time, costs and the subjectivity of person in charge. Sensor-based techniques are prerequisite in order to allow non-invasive phenotyping of individual plant traits, to increase the quantity of object records and to reduce error variation. Thus, a Prototype-Image-Acquisition-System (PIAS) was developed for semi-au-tomated capture of geo-referenced images in an experi-mental vineyard. Different strategies were tested for image interpretation using MATLAB®. The interpreta-tion of images from the vineyard with real background is more practice-oriented but requires the calculation of depth maps. Different image analysis tools were veri-fied in order to enable contactless and non-invasive de-tection of bud burst and quantification of shoots at an early developmental stage (BBCH 10) and enable fast and accurate determination of the grapevine berry size at BBCH 89. Depending on the time of image acquisi-tion at BBCH 10 up to 94 % of green shoots were visible in images. The mean berry size (BBCH 89) was record-ed non-invasively with a precision of 1 mm. K e y w o r d s: image-based phenotyping, grapevine breeding, image analysis, depth maps, BBCH, bud burst, berry size, non-invasive