ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

The key to monitoring plant drought stress lies in how to accurately locate and identify targets, and for this reason, an efficient plant phenotype extraction system has become a necessity. Because of its ability to provide high-precision 3D description, 3D point cloud information has become an important data support in this system, which provides a solid technical foundation for the monitoring of plant growth in arid environments. Ground based lidar technology was used to collect the three-dimensional point cloud data of poplar seedlings, and an L1 median skeleton extraction algorithm combined with pre-segmentation was proposed to realize fine phenotype extraction and drought feature analysis. Firstly, the original point cloud was denoised and preprocessed by elevation analysis, radius filtering and color index filtering. Secondly, the improved DBSCAN algorithm was used to realize the single-tree segmentation of the group point cloud, and the octree based on the greedy algorithm was combined with the global search to optimize the segmentation accuracy. Finally, the KNN algorithm and MRF algorithm were used to pre-segment the point cloud of a single plant, so as to improve the spatial consistency of the point cloud data, reduce the computational complexity of the L1 median algorithm, and calculate the phenotypic characteristics of poplar seedlings through the obtained skeleton point cloud. Two new indexes were introduced to reveal the adaptation mechanism of poplar seedlings under drought stress by optimizing resource allocation and reducing water consumption. Among them, the crown length rate ranked first in the gray correlation degree of drought resistance evaluation in the CK group and DT group, with a correlation coefficient of -0.85, indicating that it was highly sensitive to water supply and could fully reflect the resource use efficiency and drought resistance of plants, which was the core index to evaluate the drought adaptability of poplar seedlings. By combining three-dimensional point cloud technology and fine phenotypic analysis, the research can provide technical support for efficient and accurate monitoring of early drought stress in poplar seedlings, which was of significance for determining drought phenotypic indicators and optimizing the drought resistance evaluation system.