Technology Garden

Welcome to the FST-TOMMY CrackSense open access database, capturing the fruit surface temperature (FST) of various crops and different climates. In recent years, due to increase in population and climate change, increasing efforts have been made on developing resilient approaches to minimize food waste along the supply chain. The impact of climatic changes, hereof, increasing temperature, are prone to be among the main triggers of physiological disorders and abiotic stresses, generating losses in pre and post-harvest scenarios of horticultural produce.

Previously, monitoring temperature at the fruit level in orchards has been enabled with stationary thermocouples on few fruit and simulations based on weather data with low spatial resolution. More recently, data at canopy and fruit level have been achieved, employing close range remote sensing approaches and sensor data fusion based on a Terrestrial Orchard Monitoring and Measuring arraY (TOMMY) that has been used to scan canopies in various climates.

Each entry of the database represents a dataset of an individual fruit. The entry captures the mean temperature of individual fruit, considering several temperature points per fruit, and the range of temperature variation found on the surface of this fruit. Supplementary data for each entry capture meta data on the plot, weather data from local weather station, and raw data for the FST calculation (temperature-annotated pointclouds of entire canopies and individual fruit).

Data contributions are from CrackSense partners: INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT (INRAe); LEHR- UND VERSUCHSANSTALT FÜR GARTENBAU UND ARBORISTIK E.V. (LVGA); THE AGRICULTURAL RESEARCH ORGANISATION OF ISRAEL - THE VOLCANI CENTRE (ARO); LEIBNIZ-INSTITUT FUR AGRARTECHNIK UND BIOOKONOMIE EV (ATB); AGROTIKOS SYNETAIRISMOS POLISEOS XIRON KAI NOPON STAFYLION KIATOY KORINTHIAS PIGASOS (PEGASUS).

This research was funded by European Horizon2020 RIA program, project “CrackSense“, grant number 101086300.

The data may become valuable in ecophysiological and data science questions. The data are, therefore according to the FAIR guidelines of European Union available for reuse under the license cc-by-4.0. The data use requests citation of this database with the following information:

ATB, 2025. FST TOMMY database on fruit surface temperature with spatial resolution within the canopy, recorded in different climatic conditions. D2.4 CrackSense, url: https://technologygarden.atb-potsdam.de/cracksense, access [date]

Each dataset uses the following nomenclature:

ID	Running specific number
Image	Photo of the measuring scene
DateTime	Date and time of the measurement in the field
UTC	Difference of Date/Time compared to coordinated universal time
Plot	Country code and place of the measurement
	GPS from Google Maps
Crop	Species
Cultivar	Variety or cultivar
Tree label	Any additional label according to nomenclature of the data provider
Fruit label	Any additional label according to nomenclature of the data provider
Free text	Remarks from the data provider
x [m]	Position of fruit considering the x axis in the local canopy scan
y [m]	Position of fruit considering the y axis in the local canopy scan
z [m]	Position of fruit considering the z axis in the local canopy scan
r [m]	Euclidean distance between LiDAR origin and fruit centroid
(rad)	Angular coordinate with respect to the LiDAR position
Fruit size [mm]	Estimated fruit size (based on LiDAR data)
	Mean fruit surface temperature (based on T-annotated LiDAR data)
	Difference of fruit surface temperature within the fruit or fruit cluster, considering the interquartile temperature range (iqr) (based on T-annotated LiDAR data).
	Mean canopy surface temperature (based on T-annotated LiDAR data)
	Difference of canopy surface temperature, considering the interquartile temperature range (iqr) (based on T-annotated LiDAR data)
Tair [°C]	Air temperature at 1 m by local weather station, or indicated otherwise in the free text comments
Wind speed [m/s]	Wind speed measured above the canopies by local weather station
Relative humidity [%]	Relative humidity measured at 1 m by local weather station
Global radiation [W/m²]	Global radiation measured above the canopies by local weather station
Precipitation [mm]	Rainfall measured above the canopies by local weather station
Pointcloud	Raw data: T-annotated 3D LiDAR pointcloud of the canopy in which the fruit is located. The 3D pointcloud provides the geometric information of the canopy in Cartesian coordinates and the return signal strength intensity (RSSI) of each point. The RSSI values can be transformed to reflectivity using a calibration file, which is available on request.
Image	High resolution image of the canopy, in which the fruit is located
Upload TimeDate	Time and date, when the entry was uploaded to this database

Additional columns in the csv download	Name of the T-annotated 3D LiDAR point cloud of the canopy or zip file with canopy and individual fruit pointclouds Name of the high resolution image of the canopy, in which the fruit is located