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Fine-scale spatial information on soil properties is needed to successfully implement precision agriculture. Proximal gamma-ray spectroscopy has recently emerged as a promising tool to collect fine-scale soil information. The objective of this study was to evaluate a proximal gamma-ray spectrometer to predict several soil properties using energy-windows and full-spectrum analysis methods in two differently managed sandy loam fields: conventional and organic. In the conventional field, both methods predicted clay, pH and total nitrogen with a good accuracy (R² ≥ 0.56) in the top 0-15 cm soil depth, whereas in the organic field, only clay content was predicted with such accuracy. The highest prediction accuracy was found for total nitrogen (R² = 0.75) in the conventional field in the energy-windows method. Predictions were better in the top 0-15 cm soil depths than in the 15-30 cm soil depths for individual and combined fields. This implies that gamma-ray spectroscopy can generally benefit soil characterisation for annual crops where the condition of the seedbed is important. Small differences in soil structure (conventional vs. organic) cannot be determined. As for the methodology, we conclude that the energy-windows method can establish relations between radionuclide data and soil properties as accurate as the full-spectrum analysis method. [ABSTRACT FROM AUTHOR]

For robotic harvesting of sweet-pepper fruits in greenhouses a sensor system is required to detect and localize the fruits on the plants. Due to the complex structure of the plant, most fruits are (partially) occluded when an image is taken from one viewpoint only. In this research the effect of multiple camera positions and viewing angles on fruit visibility and detectability was investigated. A recording device was built which allowed to place the camera under different azimuth and zenith angles and to move the camera horizontally along the crop row. Fourteen camera positions were chosen and the fruit visibility in the recorded images was manually determined for each position. For images taken from one position only with the criterion of maximum 50% occlusion per fruit, the fruit detectability (FD) was in no case higher than 69%. The best single positions were the front views and looking with a zenith angle of 60° upwards. The FD increased when a combination was made of multiple viewpoint positions. With a combination of five favourite positions the maximum FD was 90%. [ABSTRACT FROM AUTHOR]