Jiménez-Brenes F M, López-Granados F, de Castro A I, Torres-Sánchez J, Serrano N, Peña J M
Institute for Sustainable Agriculture, CSIC, 14004 Córdoba, Spain.
Institute of Agricultural Research and Training (IFAPA), 14004 Córdoba, Spain.
Plant Methods. 2017 Jul 6;13:55. doi: 10.1186/s13007-017-0205-3. eCollection 2017.
Tree pruning is a costly practice with important implications for crop harvest and nutrition, pest and disease control, soil protection and irrigation strategies. Investigations on tree pruning usually involve tedious on-ground measurements of the primary tree crown dimensions, which also might generate inconsistent results due to the irregular geometry of the trees. As an alternative to intensive field-work, this study shows a innovative procedure based on combining unmanned aerial vehicle (UAV) technology and advanced object-based image analysis (OBIA) methodology for multi-temporal three-dimensional (3D) monitoring of hundreds of olive trees that were pruned with three different strategies (traditional, adapted and mechanical pruning). The UAV images were collected before pruning, after pruning and a year after pruning, and the impacts of each pruning treatment on the projected canopy area, tree height and crown volume of every tree were quantified and analyzed over time.
The full procedure described here automatically identified every olive tree on the orchard and computed their primary 3D dimensions on the three study dates with high accuracy in the most cases. Adapted pruning was generally the most aggressive treatment in terms of the area and volume (the trees decreased by 38.95 and 42.05% on average, respectively), followed by trees under traditional pruning (33.02 and 35.72% on average, respectively). Regarding the tree heights, mechanical pruning produced a greater decrease (12.15%), and these values were minimal for the other two treatments. The tree growth over one year was affected by the pruning severity and by the type of pruning treatment, i.e., the adapted-pruning trees experienced higher growth than the trees from the other two treatments when pruning intensity was low (<10%), similar to the traditionally pruned trees at moderate intensity (10-30%), and lower than the other trees when the pruning intensity was higher than 30% of the crown volume.
Combining UAV-based images and an OBIA procedure allowed measuring tree dimensions and quantifying the impacts of three different pruning treatments on hundreds of trees with minimal field work. Tree foliage losses and annual canopy growth showed different trends as affected by the type and severity of the pruning treatments. Additionally, this technology offers valuable geo-spatial information for designing site-specific crop management strategies in the context of precision agriculture, with the consequent economic and environmental benefits.
树木修剪是一项成本高昂的作业，对作物收获、营养、病虫害防治、土壤保护和灌溉策略具有重要影响。对树木修剪的研究通常涉及对树冠主要尺寸进行繁琐的实地测量，而且由于树木几何形状不规则，测量结果可能也不一致。作为密集田间工作的替代方法，本研究展示了一种创新程序，该程序基于将无人机（UAV）技术与先进的基于对象的图像分析（OBIA）方法相结合，用于对数百棵采用三种不同策略（传统、改良和机械修剪）进行修剪的橄榄树进行多时间三维（3D）监测。在修剪前、修剪后和修剪后一年收集无人机图像，并随时间量化和分析每种修剪处理对每棵树的投影树冠面积、树高和树冠体积的影响。
此处描述的完整程序在大多数情况下能自动识别果园中的每棵橄榄树，并在三个研究日期高精度地计算其主要3D尺寸。就面积和体积而言，改良修剪通常是最激进的处理方式（树木平均分别减少38.95%和42.05%），其次是传统修剪的树木（平均分别减少33.02%和35.72%）。关于树高，机械修剪导致的树高降低幅度更大（12.15%），而其他两种处理方式下的树高降低值最小。树木一年的生长受到修剪强度和修剪处理类型的影响，即当修剪强度较低（<10%）时，改良修剪的树木生长高于其他两种处理方式的树木；在中等强度（10 - 30%）时，与传统修剪的树木生长相似；当修剪强度高于树冠体积的30%时，其生长低于其他树木。
结合基于无人机的图像和OBIA程序，只需最少的田间工作就能测量树木尺寸并量化三种不同修剪处理对数百棵树的影响。受修剪处理类型和强度的影响，树木叶片损失和年度树冠生长呈现不同趋势。此外，该技术为在精准农业背景下设计特定地点的作物管理策略提供了有价值的地理空间信息，从而带来经济和环境效益。
