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Early yield prediction in pear based on canopy LIDAR scanning

机译:基于冠层激光雷达扫描的梨早期产量预测

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The agricultural industry faces the challenge of increase yield and improve the food quality. This paper presents a study on the prediction of fruit production and also intends to detect other information that can be obtained based on the scans of fruit trees using a LIDAR sensor. We worked on a Williams pear orchard using a semi-automatic procedure in order to estimates tree volume. We compute the canopy area with a simple method based on the Gauss's formula at harvest and during tree dormancy. We correlates volume vs. weight of harvested fruits from each plant. Regression coefficients were obtained for individual and grouped data. At harvest time, we obtain a good relationship between the volume of the canopy and the production (r = 67). The information obtained is very valuable in terms of the general state of the crop, the evolution and distribution of production within the orchard, and to make adequate decisions about its management.
机译:农业行业面临着增加产量和改善食品质量的挑战。本文提出了一项关于水果产量预测的研究,并且还打算检测使用LIDAR传感器基于果树扫描而获得的其他信息。我们使用半自动程序对威廉姆斯梨园进行了研究,以便估算树木的体积。我们根据收获时和树木休眠期间的高斯公式,采用一种简单的方法来计算树冠面积。我们将每种植物收获的果实的体积与重量关联起来。获得了个体和分组数据的回归系数。在收获时,我们在树冠的体积和产量之间获得了良好的关系(r = 67)。获得的信息对于农作物的总体状态,果园内生产的演变和分布以及对果园的管理做出充分的决定都是非常有价值的。

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