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Automatic corn plant location and spacing measurement using laser line-scan technique

机译:使用激光线扫描技术自动测量玉米植株的位置和间距

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Identifying corn plant location and/or spacing is important for predicting yield potential and making decisions for in-season nitrogen application rate. In this study, an automatic corn stalk identification system based on a laser line-scan technique was developed to measure stalk locations during corn mid-growth stages. A laser line-scan technique is advantageous in this application because the line-scan data sets taken from various points of view of a plant stalk results in less interference and higher probability of plant recognition. Data were collected for two 10-meter-long corn rows at the growth stages of V8 and V10 using a mobile test platform in 2011. Each potential stalk cluster was identified in a scan and registered with the same stalks in previous scans. The final location of a stalk was the average of the measured locations in all scans. The current system setup with data processing algorithms achieved 24.0 and 10.0 % of mean total errors in plant counting at the V8 and V10 growth stages, respectively. The root-mean-squared error (RMSE) between system measured plant locations and manually measured ones were 2.3 and 2.6 cm at the V8 and V10 growth stages, respectively. The interplant spacing measured by the developed system had a good correlation with the manual measurement with an R (2) of 0.962 and 0.951 for the V8 and V10 growth stages, respectively. This system can be ultimately integrated in a variable-rate-spraying system to improve real-time, high spatial resolution variable-rate nitrogen applications.
机译:确定玉米植株的位置和/或间距对于预测单产潜力和确定季节氮肥施用量至关重要。在这项研究中,开发了基于激光线扫描技术的自动玉米秸秆识别系统,以测量玉米中期生长阶段的秸秆位置。激光线扫描技术在该应用中是有利的,因为从植物茎的各种角度获取的线扫描数据集导致较少的干扰和较高的植物识别概率。在2011年,使用移动测试平台在V8和V10的生长阶段收集了两个10米长的玉米行的数据。在一次扫描中识别了每个潜在的茎簇,并在之前的扫描中向相同的茎进行了注册。茎的最终位置是所有扫描中测得位置的平均值。使用数据处理算法的当前系统设置分别在V8和V10生长阶段达到了植物计数平均总错误的24.0%和10.0%。在V8和V10生长阶段,系统测量的植物位置和手动测量的植物位置之间的均方根误差(RMSE)分别为2.3和2.6 cm。 V8和V10生长阶段,通过开发的系统测量的株间间距与手动测量具有良好的相关性,R(2)分别为0.962和0.951。该系统最终可以集成到可变速率喷涂系统中,以改善实时,高空间分辨率可变速率氮气应用。

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