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Article|01 Jul 2018|OPEN
Application of light detection and ranging and ultrasonic sensors to high-throughput phenotyping and precision horticulture: current status and challenges
André F. Colaço1,2, José P. Molin2, Joan R. Rosell-Polo3 & Alexandre Escolà3
1Present address: CSIRO, Waite Campus, Locked Bag 2, Glen Osmond, SA 5064, Australia
2Biosystems Engineering Department, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Av. Pádua Dias, 11, Piracicaba - SP 13418-900, Brazil
3Research Group on AgroICT and Precision Agriculture, Department of Agricultural and Forest Engineering, School of Agrifood and Forestry Science and Engineering, University of Lleida – Agrotecnio Center, Av. Rovira Roure, 191, 25198 Lleida, Catalonia, Spain

Horticulture Research 5,
Article number: 35 (2018)
doi: 10.1038/hortres.2018.35
Views: 503

Received: 09 Nov 2017
Revised: 14 Feb 2018
Accepted: 10 Apr 2018
Published online: 01 Jul 2018


Ultrasonic and light detection and ranging (LiDAR) sensors have been some of the most deeply investigated sensing technologies within the scope of digital horticulture. They can accurately estimate geometrical and structural parameters of the tree canopies providing input information for high-throughput phenotyping and precision horticulture. A review was conducted in order to describe how these technologies evolved and identify the main investigated topics, applications, and key points for future investigations in horticulture science. Most research efforts have been focused on the development of data acquisition systems, data processing, and high-resolution 3D modeling to derive structural tree parameters such as canopy volume and leaf area. Reported applications of such sensors for precision horticulture were restricted to real-time variable-rate solutions where ultrasonic or LiDAR sensors were tested to adjust plant protection product or fertilizer dose rates according to the tree volume variability. More studies exploring other applications in site-specific management are encouraged; some that integrates canopy sensing data with other sources of information collected at the within-grove scale (e.g., digital elevation models, soil type maps, historical yield maps, etc.). Highly accurate 3D tree models derived from LiDAR scanning demonstrate their great potential for tree phenotyping. However, the technology has not been widely adopted by researchers to evaluate the performance of new plant varieties or the outcomes from different management practices. Commercial solutions for tree scanning of whole groves, orchards, and nurseries would promote such adoption and facilitate more applied research in plant phenotyping and precision horticulture.