AI Article Synopsis

  • Grapevine research typically relies on visual scoring methods in the field due to the plants' size and perennial nature, limiting phenotypic data acquisition.
  • New sensor technologies are emerging, allowing for non-invasive evaluation of phenotypic traits with various field phenotyping platforms.
  • The study introduces the Phenoliner, an innovative and robust field phenotyping platform that utilizes a grape harvester design, incorporating advanced sensors and an artificial light source to standardize high-quality data collection regardless of external light conditions.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539483PMC
http://dx.doi.org/10.3390/s17071625DOI Listing

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