小麦个体间相互竞争是影响根系发展的主要因素之一，而麦苗群体中个体空间的关系可以用群体几何特征来描述。本项目拟通过图像分析技术获取小麦群体的几何结构，并探明小麦群体几何结构对根系生长的影响。利用大田试验，通过播种密度、播种方式和品种类型来构建不同几何结构的小麦群体，通过数码相机和无人机获取不同高度的麦苗图像，并通过不同的图像处理方法提取空间结构参数。同时利用方格法调查小麦根系性状，得到根系生长的生理和形态指标以及根系生长的动态变化。研究主要实现基于不同高度图像的麦苗群体分形几何特征（麦苗数量、个体间距离特征和群体分形维数）的智能获取方法，明确麦苗几何特征对根系形态指标、生理指标和生长动态的影响。研究从特定空间内麦苗个体间相互竞争的原理出发，阐明麦苗群体几何特征与根系生长状态之间的关系，研究结果可为未来小麦群体数量调查、群体结构分析以及为提高小麦根系研究的精确性和便捷性提供理论依据和技术支撑。

The competition between individuals of wheat is one of the main factors affecting the development of root system, and the relationship between the individual spaces in wheat seedling groups can be described by using fractal geometry characteristics. This project plans to obtain the spatial fractal geometry structure of wheat groups by image analysis technique, and finds out the influence of wheat population spatial structure on root growth. The wheat group of different spatial structure is to be built through the way of planting density, sowing method and variety type in field experiments and the wheat seedling images at different height are obtained through digital cameras and unmanned aerial vehicle, and the spatial structure parameters are extracted through different image processing methods. At the same time, grid method is used to investigate wheat root traits, and the corresponding root growth indexes will be got. The intelligent acquisition methods of wheat group fractal geometry characteristics (wheat seedling quantity, distance between individuals and group fractal dimension) are mainly implemented based on the images at different height, and the influences of fractal geometry characteristics of wheat seedling group on root morphological indexes, physiological indexes and dynamic growth are cleared. The relationship between the fractal geometry characteristics of wheat seedling group and the state of root growth are expounded based on the competing principle of wheat seedling individuals within a unit space. The results of the study can provide theoretical basis and technical support for the wheat population survey, analysis of population structure and improving the accuracy and convenience of wheat root research in the future.