3D LiDAR point cloud dataset for moisture-level classification in broccoli and mushroom

Broccoli and mushroom samples (fresh and dried) were measured with light detection and ranging (LiDAR) sensor. The dual-wavelength LiDAR system for acquisition of 3D geometry and intensity data of samples, was configured with 1320 nm and 1450 nm. These two wavelengths were chosen to measure at one low sensitive wavelength and one wavelength, showing high sensitivity to the presence of water. Moisture content was measured after each LiDAR scan for the core and periphery segments of samples to capture spatial variability. Each sample was weighed directly after the scan and after oven drying until constant weight was reached, and the moisture content (MC) was calculated. Data are available as raw data with trajectories as well as data segmented on the individual samples and radiometrically calibrated by means of low and high reflecting standard materials. Data were augmented and moisture classification can be done with code provided with link below.