Colaço André F, Molin José P, Rosell-Polo Joan R, Escolà Alexandre
1Biosystems Engineering Department, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Av. Pádua Dias, 11, Piracicaba - SP 13418-900 Brazil.
3Present Address: CSIRO, Waite Campus, Locked Bag 2, Glen Osmond, SA 5064 Australia.
Hortic Res. 2018 Jul 1;5:35. doi: 10.1038/s41438-018-0043-0. eCollection 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.
超声波和光探测与测距(LiDAR)传感器一直是数字园艺领域中研究最为深入的传感技术之一。它们能够准确估计树冠的几何和结构参数,为高通量表型分析和精准园艺提供输入信息。本文进行了一项综述,以描述这些技术的发展历程,并确定园艺科学未来研究的主要主题、应用和关键点。大多数研究工作都集中在数据采集系统的开发、数据处理以及高分辨率三维建模上,以获取树冠体积和叶面积等树木结构参数。此类传感器在精准园艺中的应用报道仅限于实时变量率解决方案,其中测试了超声波或LiDAR传感器,以根据树木体积变化调整植物保护产品或肥料的剂量率。鼓励开展更多探索特定地点管理中其他应用的研究;例如,将树冠传感数据与在果园尺度上收集的其他信息源(如数字高程模型、土壤类型图、历史产量图等)相结合的研究。通过LiDAR扫描获得的高精度三维树木模型显示出其在树木表型分析方面的巨大潜力。然而,该技术尚未被研究人员广泛用于评估新植物品种的性能或不同管理措施的效果。针对整个果园、果园和苗圃进行树木扫描的商业解决方案将促进这种应用,并为植物表型分析和精准园艺的更多应用研究提供便利。