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为给果园精细管理中果树修枝整形、果实品质评价以及果实产量估算等提供科学的理论依据和技术指导,以果园自然开心形苹果树为研究对象,基于果树三维点云结构,进行果树冠层空间光照分布建模研究。用三维点云重构技术和点云分割技术获取果树不同高度的点云分层,分别使用像素占比和Graham扫描算法计算各高度点云分层垂直投影的有效投影面积和占地面积及有效叶面积指数。以果树冠层不同高度层的有效叶面积指数为自变量,对不同高度层平均相对光照强度进行线性回归,获得果树冠层光照分布模型,并对模型进行验证。结果表明:所建果树冠层光照分布模型的校正决定系数R2c为0.924,校正均方根误差RMSEC为0.05,验证决定系数R2v为0.955,验证均方根误差RMSEP为0.04,相对分析误差RPD为4.91。该模型具有较高的预测精度和较强的预测能力。
In order to provide scientific theoretical basis and technical guidance for fruit tree pruning, fruit quality evaluation and fruit yield estimation in orchard fine management, taking apple orchard natural happy apple tree as research object, based on fruit tree three-dimensional point cloud structure, Research on Spatial Light Distribution Modeling. Using 3D point cloud reconstruction technology and point cloud segmentation technology to get the point clouds at different heights of fruit trees, pixel projection and Graham scanning algorithm were used to calculate the effective projection area, area and effective area of the vertical projection of each point cloud Leaf area index. Taking the effective leaf area index of different height layers of fruit tree canopy as the independent variable, the average relative illumination intensity of different height layers was linearly regressed, and the light distribution model of fruit canopy was obtained, and the model was verified. The results showed that the calibration coefficient R2c was 0.924, the root mean square error of calibration RMSEC was 0.05, the validation coefficient R2v was 0.955, the root mean square error of validation RMSEP was 0.04, and the relative analytical error RPD was 4.91 . The model has high prediction accuracy and strong prediction ability.