Fruit surface temperature data at different ripeness stages and ambient temperature provided as temperature-annotated 3D point clouds of apple trees.

Abstract

By means of a unique, low vibration circular conveyor system, plant sensors capturing light detection and ranging (LiDAR) unit and thermal camera were moved on the same route, around blocks of apple trees, with seven Malus x domestica Borkh. 'Gala' apple trees in each block. Measurements took place four times during the season. Additionally at harvest, diurnal courses were recorded with 18 readings during three days. The data are provided as [i] raw data (3D point clouds of 3 blocks of trees scanned from right and left sides and thermal images), [ii] processed 3D point clouds of canopies annotated with temperature data from the thermal camera, and [iii] manually segmented 3D point clouds of fruit, representing the spatially-resolved fruit surface temperature (FST). Manual FST readings are provided on each measuring date and during diurnal courses. The fruit data are capturing 1236 FST, providing temperature distribution as 3D point cloud and one manually recorded reference FST per fruit. Additionally, fruit size and colour were measured for each fruit, despite for the first date, when fruit were too small for colour readings. Weather data are provided from a station located in the orchard. Usage of data could be (a) in developing methodology for 3D point cloud processing based on raw data, accomplished with reference FST data. Furthermore, (b) the pre-processed point clouds of fruit surface temperature can be reused in ecophysiological studies related to global warming, optimizing fruit production systems, and other. Because the sensors and trees were measured from the same angle and distance, time series analysis of the canopies would be possible.

Plant phenotyping relevance

LiDARと熱画像を統合し、果実表面温度を3D点群として取得・注釈化した再利用可能なデータセットであり、植物表現型取得手法とデータ提供が中心です。

Code and data availability

The paper is a Data in Brief article describing a public Zenodo deposit containing the paper's own phenotyping measurements: raw LiDAR point clouds, thermal images, temperature-annotated 3D point clouds of apple canopies, 1236 manually segmented fruit point clouds with FST reference readings, fruit size/colour data, an