An Automated Field Phenotyping Pipeline for Application in Grapevine Research

• DOI: 10.3390/s150304823
• Publication Date: 2015-02-26T15:07:43Z
• Authors: Anna Kicherer; Katja Herzog; Michael Pflanz; Markus Wieland; Philipp Rüger; Steffen Kecke; Heiner Kuhlmann; Reinhard Töpfer
• Keywords: 0106 biological sciences; <i>Vitis vinifera</i>; Chemical technology; robot; TP1-1185; image acquisition; 01 natural sciences; Article; high-throughput analysis; plant phenotyping; Phenotype; Vitis vinifera; Fruit; grapevine breeding; Image Processing, Computer-Assisted; geoinformation; Vitis

Due to its perennial nature and size, the acquisition of phenotypic data in grapevine research is almost exclusively restricted to the field and done by visual estimation. This kind of evaluation procedure is limited by time, cost and the subjectivity of records. As a consequence, objectivity, automation and more precision of phenotypic data evaluation are needed to increase the number of samples, manage grapevine repositories, enable genetic research of new phenotypic traits and, therefore, increase the efficiency in plant research. In the present study, an automated field phenotyping pipeline was setup and applied in a plot of genetic resources. The application of the PHENObot allows image acquisition from at least 250 individual grapevines per hour directly in the field without user interaction. Data management is handled by a database (IMAGEdata). The automatic image analysis tool BIVcolor (Berries in Vineyards-color) permitted the collection of precise phenotypic data of two important fruit traits, berry size and color, within a large set of plants. The application of the PHENObot represents an automated tool for high-throughput sampling of image data in the field. The automated analysis of these images facilitates the generation of objective and precise phenotypic data on a larger scale.