Herzog, Katja

Kicherer, Anna

Kuhlmann, Heiner

Roscher, Ribana

Rüger, Philipp

Schwarz, Hans-Peter

Töpfer, Reinhard

Wieland, Markus

English

JKI Open Journal Systems (Julius Kühn-Institut)

Nachwuchswissenschaftlerforum / Young Scientists Meeting 2013 Kicherer et al.     High-Throughput Phenotyping of yield parameters in the vineyard – first steps  Anna Kicherer1, Katja Herzog1, Ribana Roscher2, Markus Wieland³, Philipp Rüger4, Heiner Kuhlmann³, Hans-Peter Schwarz4 and Reinhard Töpfer1  1Julius Kühn-Institut, Institute for Grapevine Breeding, Siebeldingen  2Bonn University, Institute of Geodesy and Geoinformation, Department of Photogrammetry  3Bonn University, Institute of Geodesy and Geoinformation, Department of Geodesy  4Geisenheim University, Department of Viticultural Engineering Email of corresponding author: anna.kicherer@jki.bund.de  Complementary to genotyping tech-niques like Marker-Assisted-Selection (MAS), faster methods for plant phenol-typing need to be established permit-ting high quality, objectivity, and preci-sion in phenotypic data recording. Fur-thermore, for a woody crop plant like grapevine high throughput-(HT)-pheno-typing needs to be developed for appli-cations in vineyards rather than in the lab or greenhouses. Adaptable image based phenotyping techniques will be one way to receive plant features non-invasive and with high-throughput.   Quantifying yield parameters is chal-lenging, particularly when measure-ments need to be done on large sam-ples. Complex shapes and slight varia-tions between genotypes make it diffi-cult and very time-consuming. Objec-tive manual screenings can be done on small samples but this method is rather vague especially when done by multiple persons or varying descriptive stand-ards.   Therefore, as an intermediate step two high-throughput image interpretation tools for the lab (CAT-Cluster Analysing Tool; BAT-Berry Analysing Tool) were developed.   Building up on a Prototype-Image-Acquisition (PIA) system developed in CROP.SENSe.net, PHENOvines aims at the implementation of a HT-phenotyping platform for field applica-tion to be used within a breeding pro-gram. Including an improved Image-Acquisition-System which consists of five cameras, RTK-GPS (GPS position accuracy around 2 cm), and an adjusted prototype software to take geo-referenced RGB images.   These phenotyping platform facilitate a non-invasive and contactless detection of phenotypic traits of grapevines. As a first step to detected yield parameters directly in the field a high-throughput image interpretation which enables a fast acquisition of grape berry size from RGB images was tested.  It is anticipated that in future the phenotyping platform will be based on an autonomous robot that drives through experimental and production vine-yards. In its final version pictures shall be taken automatically depending on the GPS position.  Berichte aus dem Julius Kühn-Institut 171 7

High-Throughput Phenotyping of yield parameters in the vineyard – first steps

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High-Throughput Phenotyping of yield parameters in the vineyard – first steps

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