Three-Dimensional Quantification of Intercropping Crops in Field by ground and aerial photography

Binglin Xhu, Fusang Liu, Yingpu Che, Fang Hui, Yuntao Ma
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Abstract

High-throughput phenotyping of plant three-dimensional (3D) architecture is critical for determining plant phenotypic characteristics. The acquisition of 3D architecture of plant phenotypic traits based on multi-view photographing has been widely applied in greenhouse research. Growth process of the plants can be dynamically monitored. However, the application of this method in the field is more difficult and less due to the complex environment. In this study, maize/soybean intercropping plant populations in the field were selected as the research objects. We combined ground and aerial photography to obtain the image sequences. at the stage of seedling, jointing, tasseling and grain filling. The targeted plants were photographed with fixed point from multi-view hemispherical directions on ground photography before tasseling stage. Then, Unmanned Aerial Vehicle was used to take photos in the way of concentric circles with different radius. We preprocessed the image sequences by Support Vector Machine (SVM) method, and pixel information only containing targeted plants were achieved. We evaluated the accuracy of calculated individual height, blade length and maximum width with the measured data. Image sensitivity analysis was also done at 25 and 79 days after emergence by reducing the image numbers. Canopy coverage and plant height were compared between different scenarios. The results showed that there was a good agreement between measured and calculated plant height, blade length and blade maximum width with R2>0.90. Then the dynamic changes of plant height, crown surface and organ growth were extracted based on reconstructed 3D architecture. Sensitivity analysis showed that at the early growth stage, 50 images are enough for 3D reconstruction of the plant. However, all 300 images need to be included at the late growth stage of plants. The results can provide a basis for high-throughput phenotypic analysis related to genotypes and help to evaluate the plant architecture and canopy radiation interception.
利用地面和航空摄影技术对大田间作作物进行三维定量化
植物三维结构的高通量表型分析是确定植物表型特征的关键。基于多视角拍摄的植物表型性状三维结构获取技术在温室研究中得到了广泛应用。植物的生长过程可以动态监测。但由于环境复杂,该方法在野外的应用难度较大,应用较少。本研究以大田玉米/大豆间作植物群体为研究对象。我们结合地面和航空摄影获得图像序列。苗期、拔节期、抽雄期和灌浆期。在抽雄期前的地面摄影中,对目标植株进行多视角半球面定点拍摄。然后利用无人机以不同半径的同心圆方式进行拍摄。采用支持向量机(SVM)方法对图像序列进行预处理,得到只包含目标植物的像素信息。用实测数据对计算的单株高度、叶片长度和最大宽度的精度进行了评价。通过减少图像数量,在出现后25天和79天进行图像敏感性分析。不同情景下的冠层盖度和株高比较。结果表明,植株高、叶片长和叶片最大宽度的实测值与计算值吻合较好,R2为0.90。然后基于重建的三维结构提取植物株高、冠面和器官生长的动态变化。灵敏度分析表明,在植物生长初期,50张图像就足够进行植物的三维重建。但是,所有300张图像都需要在植物生长后期包含。研究结果可为相关基因型的高通量表型分析提供基础,并有助于评价植物结构和冠层辐射拦截能力。
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