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Non-destructive estimation of plant parameters is prerequisite for fast and precise management of crops on commercial farm level. The aim of this study was to estimate leaf area (LA) in mature tomato plants using a linear conveyor mounted LiDAR laser scanner. High density 3-dimentional (3D) point cloud model of whole plant was reconstructed from LiDAR data. Plant parameters such as plant height, plant volume, canopy area and point per plant (PPT) were extracted by analyzing the 3D point clouds. Destructive method was utilized in laboratory for reference data collection capturing LA, fresh mass, dry mass. Linear regression models were developed to estimate LA using different LIDAR estimated parameters and reference LA and models were cross validated using leave-one-out method. Among the models, plant height showed strong correlation (R2 = 0.90, RMSE = 4.6 %) and followed by PPT (R2 = 0.83, RMSE = 8.3 %). This result indicates that mobile LiDAR laser scanning could be a reliable non-destructive LA estimation tool for tomato.
Kowshik Kumar Saha
Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Germany
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Download from Proceedings of IEEE 2021 International Workshop on Metrology for Agriculture and Forestry