The WG Precision Horticulture develops methods for acquiring in-situ sensor data of fruit or vegetables aimed at more precise process management in the production and postharvest.
The group works on
(i) gaining fruit and vegetables data from digital sensor signals, and
(ii) advancing agronomic models by means of the in-situ information on the fruit and veggies.
Our applications capture product data related to abiotic stress, e.g. due to changes in global radiation, temperature, ethylene exposure. Precisely adapting production processes to the needs of the crop reduces the consumption of resources, while continuing to enable high yields. For example, optimising thinning intensity in fruit production has been shown to reduce the use of chemicals while increasing the yield per hectare by 5 tonnes of apples. In sorting, storage, and shelf life, sensor data can help to keep product quality of the perishable, fresh produce. Consequently, digital product information can help to optimize processes along the supply chain.
Research equipment
- Thin-film sensor for mechanical load
- Texture Analyzer
- Dynamic load sensor to implant in fruits
- Temperature corrected refractometer
- Multi-spectral refractometer
- Electro-chemical gas sensors
- Oxygen micro sensor system
- GC
- U-HPLC
- Fluorescence spectroscopy
- Time-resolved fluorescence spectrometry
- Vis/NIR spectrophotometry (190 nm – 2500 nm) in various optical geometries
- Calibration stand (wavelength and intensity) for Vis/NIRS
- Optical bench
- Laser-induced spatially resolved spectroscopy (SRS)
- Tool for photometric fruit pigment analysis
- Terrestrial mobile LiDAR laser scanners
- Calibration stand (geometric and intensity) for LiDAR laser scanner
- Thermal cameras
- Hyperspectral cameras
- 3D time-of-flight camera
- Scholander bomb
- Sapflow meter
- dendrometer
- IRGA porometer
- Chlorophyll fluorescence kinetic
Free software tools developed by the group:
https://gitlab-extern.atb-potsdam.de/cracksense/3d_thermal_annotation
https://gitlab-extern.atb-potsdam.de/published/sheet
https://cran.r-project.org/package=MCBackscattering (R Code for Monte-Carlo Simulation on backscattering data)
https://github.com/ATB-Potsdam/Matlab_TVDI_cal (Matlab Code for calculating land surface temperature and vegetation indices from Landsat 8 satellite)
https://play.google.com/store/apps/details?id=com.cpinfo.fiorama (mobile App to record time series of fruit development)
https://play.google.com/store/apps/details?id=de.atb_potsdam.www.cherryharvest (mobile App for analyzing the cherry fruit growth)
Team of HORT
M.Sc. Nicolás Tapia Zapata
Dr. Helene Fotouo
Guest scientists, students:
M.Sc. Kowshik Kumar Saha (Bangladesh Agricultural Research Institute, Bangladesh)
M.Sc. Sven Jörissen (University Würzburg, Germany)
Prof. Dr. Harby Mostafa (Banha University, Egypt)
M.Sc. Yang Zhou (Zoe) (Massey University, New Zealand)
M.Sc. Ekaterine Burkadze (Agriculture University of Georgia)
Mr. Laurence Steffen