Measurements were carried out at Leibniz Universität Hannover, using terrestrial orchard monitoring measurement yaw (TOMMY) developed by Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB), in 2023.

Seven sweet cherry (Prunus avium) trees were allowed to acclimate to ambient temperature and then placed in cold conditions. Tree temperature was measured with a handheld IR thermometer and analysis based on fused data from terrestrial mobile 2D LiDAR sensor analysis and thermal camera to gain tree point clouds with temperature labels. Tree temperature acclimation data are provided here as an preliminary example file showing forced wetness appearance on the fruit surface, capturing fruit temperature and wetness reference data as well as T-annotated point clouds.

Files:

*.xlsx file contain

- several clusters of fruit or single fruit during acclimation, representing geometric x, y, z data; return signal strength intensity, temperature
- remaining point clouds
- reference readings capturing manual temperature and wetness ground truth as well as temperature estimated by TOMMY

Python code to read files.

A total of 549 RGB images of cherry fruit, usable for identifying the fruit, where visual reference for wetness classes was recorded. Images are available per tree (T1-7) in zip files.

Manually measured fruit surface temperature and visually classed wetness level are provided in CrackSense_ReferenceMeasurementTOMMY_Hannover.xlsx file.