Evaluation of fruit temperature on cherries by means of thermal point clouds

A LiDAR laser scanning and thermal imaging were employed to detect the temperature on sweet cherry surface $(\mathrm{T}_{\mathrm{Estimated}}$) by means of 3D point cloud. The LiDAR estimated temperature was temporally monitored in three varieties and compared with manually measured fruit temperature $(\mathrm{T}_{\mathrm{Measured}}$) and fruit fresh mass. The results showed correlation coefficients R
²
of 0.80 and 0.85 between estimated and measured temperatures of three different cultivars during the season. Related to fresh mass and the fruit quality data, $(\mathrm{T}_{\mathrm{Estimated}}$) showed no correlation during the growing stages.