Testing the suitability of a terrestrial 2D LiDAR scanner for canopy characterization of greenhouse tomato crops

Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with elect...

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Bibliographic Details
Authors: Llop Casamada, Jordi|||0000-0001-9033-3770, Gil Moya, Emilio|||0000-0002-3929-5649, Llorens Calveras, Jordi|||0000-0003-4625-1860, Miranda Fuentes, Antonio, Gallart González-Palacio, Montserrat|||0000-0002-9347-2984
Format: article
Publication Date:2016
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/103143
Online Access:https://hdl.handle.net/2117/103143
https://dx.doi.org/10.3390/s16091435
Access Level:Open access
Keyword:Tomatoes--Yields
Greenhouse
Tomato crop
LiDAR sensor
Canopy characterization
Leaf Area Index (LAI)
Agrotech
Tomaquera -- Experimentació
Àrees temàtiques de la UPC::Enginyeria agroalimentària::Agricultura::Horticultura
Description
Summary:Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps.