Abstract
In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data.
Highlights
With new developments in electronics, software and sensor techniques, plant phenotyping has become a key technology in the agriculture sector
In the present study we developed a new, very robust field phenotyping platform, the Phenoliner, for applications in grapevine research and breeding
Field tests were conducted in October 2016 in an experimental vineyard plot at the JKI Geilweilerhof located in Siebeldingen, Germany (49◦ 21.7470 N, 8◦ 04.6780 E)
Summary
With new developments in electronics, software and sensor techniques, plant phenotyping has become a key technology in the agriculture sector. Platforms for the assessment of phenotypic data under controlled conditions are widespread [1,2,3,4]. These systems allow a very detailed assessment of plants under a controlled environment, genotype-environment interaction not taken into consideration. These systems are not applicable for perennial crops, e.g., cultivated in trellis systems. The application of non-invasive, sensor-to-plant methods facilitates the record of objective and repeatable phenotypic
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