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Biomass estimation from canopy measurements for leafy vegetables based on ultrasonic and laser sensors

机译:基于超声波和激光传感器的叶片蔬菜冠层测量的生物量估计

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This paper reports on the evaluation of a prototype sensor system embedded in a low-cost portable instrument for leaf vegetable production. The system involves circular scanning of crop canopies to identify crop biomass yield using distance sensors. The results of these scans are height profiles along an angular position from 0 to 360 degrees, which are the input for the biomass estimation. Two experiments were developed to test the performance of the system's prototype. The first experiment was conducted in a greenhouse with lettuce and kale. Biomass was estimated from the sensor system's measurements resulting in the coefficient of determination (R-2) for regression between measured and predicted biomass between 0.74 and 0.93, root mean squared error (RMSE) between 0.295 ln(g) and 0.441 ln(g), and percentage error between 25% and 55%. These values include both dry and fresh biomass for lettuce and kale. The second experiment was conducted in a spinach field of a commercial farm in Sherrington, Quebec, Canada. The R-2 values were 0.78 and 0.94. The RMSE was, in turn, 4.18 t/ha and 2.16 t/ha. While only fresh biomass was considered for the spinach case, two approaches for processing laser-based height profiles are discussed: regression of profile-representative features and inference of a canopy density function. The results indicate that the developed sensor system would be a suitable tool for rapid assessment of fresh biomass in the field. Its application would be beneficial in the process of optimizing crop management logistics, comparing the performance of different varieties of crops, and detecting potential stresses in a field environment.
机译:本文报告了嵌入在低成本便携式叶片生产仪器中的原型传感器系统的评价。该系统涉及作物檐篷的圆形扫描,以使用距离传感器识别作物生物质产量。这些扫描的结果是沿着从0到360度的角度位置的高度分布,这是生物质估计的输入。开发了两个实验以测试系统原型的性能。第一个实验是在一个温室进行的生菜和羽衣甘蓝。从传感器系统的测量结果估计生物质,导致测定和预测生物质之间的回归系数(R-2),在0.74和0.93之间,从0.295Ln(g)和0.441Ln之间的根部平均平方误差(RMSE)之间的生物量之间的回归,百分比误差为25%和55%。这些值包括莴苣和羽衣甘蓝的干燥和新的生物量。第二个实验是在加拿大魁北克·昆士省Sherrington的商业农场的菠菜场上进行的。 R-2值为0.78和0.94。 RMSE又为4.18 T / HA和2.16 T / HA。虽然仅考虑了菠菜盒的新鲜生物量,但是讨论了用于处理基于激光的高度轮廓的两种方法:轮廓代表特征的回归是冠层密度函数的推断。结果表明,发达的传感器系统将是用于快速评估该领域的新生物量的合适工具。其应用在优化作物管理物流的过程中是有益的,比较不同品种的作物的性能,以及检测现场环境中的潜在应力。

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