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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Detalhes bibliográficos
Autores: Llop, Jordi, Gil Moya, Emilio, Llorens Calveras, Jordi, Miranda-Fuentes, Antonio, Gallart, Montserrat
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/59551
Acesso em linha:https://doi.org/10.3390/s16091435
http://hdl.handle.net/10459.1/59551
Access Level:acceso abierto
Palavra-chave:Greenhouse
Tomato crop
lidar
canopy characterization
LAI
Descrição
Resumo: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.