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基于无人机航拍图像的大田玉米冠层结构建模

Modeling of Canopy Structure of Field-grown Maize Based on UAV Images

  • 摘要: 针对目前采用三维数字化等方法获取大田作物冠层结构信息时需要手动干预、费时费力的问题,利用超微小型无人机分别获取了苗期大田玉米群体的航拍图像、去掉周边植株后成熟期单株及多株的玉米小群体航拍图像。基于伪极点-Crust方法构建了玉米苗期和成熟期的冠层结构模型,并基于大田原位手动测量的株高、叶长、最大叶宽、叶面积等参数对所构建的冠层结构模型进行了精度评估。结果表明,苗期、成熟期玉米株高、叶长、最大叶宽的R2均不小于0.91,RMSE、rRMSE、ME均较小;苗期叶面积的R2为0.96,RMSE、rRMSE、ME均较小;成熟期叶面积的R2为0.76,RMSE、rRMSE、ME稍大。本研究可为大田冠层结构、表型信息的高通量获取提供新的途径。

     

    Abstract: It is of vital significance to efficiently collect the information of crop canopy structure for new cultivar breeding and field management optimization.At present,methods such as three-dimensional digitizing have been used to obtain canopy structure information of field-grown crops,but most of them require manual intervention,which is time-consuming and laborious.Therefore,it is urgent to develop novel methods with high-efficiency.A micro UAV was used in the field to acquire image sequences of maize canopy at the seedling stage,and individual plants as well as several neighboring plants at the later mature stage.Considering the heavy shading among plants at the late stage,surrounding plants of the target plants were removed before images were taken.Based on the point clouds reconstructed using the UAV images,the canopy structure model was efficiently built by creating pseudo poles.Then,the model was evaluated according to the field measurements of plant height,leaf length,max width and leaf area.There was a good agreement between the measured and calculated plant height,leaf length and max width with R~2 no less than 0.91 and RMSE,rRMSE and ME were small for both growth stages.The R~2 of leaf area at both growth stages were 0.96 and 0.76,respectively.RMSE,rRMSE and ME were small at the seedling stage while marginally larger at the mature stage.The proposed method provided a novel way for high-throughput plant structure modeling and phenotyping of field-grown crops.

     

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