基于点云和作物根区定位的油菜单株高度全生命周期动态测量

IF 8.9 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Xuan lv , Xiaole Wang , Yu Wang , Fugui Zhang , Lu Liu , Zhenchao Wu , Yujie Liu , Yuang Yang , Xueqing Li , Liqing Chen , Yang Yang
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引用次数: 0

摘要

油菜株高(PH)作为一项重要的表型指标,在单株生命周期内进行准确监测,可为油菜幼苗诊断和育种选择提供重要数据。然而,获得精确的PH值是一个挑战,因为油菜籽叶和其他作物在开花后相互遮蔽。本研究设计并制造了一个基于轨道的平台,该平台配备了激光雷达和北斗差分定位系统,可自动采集油菜种群的时间序列点云。采用改进的快速欧几里得聚类算法对油菜返青阶段的点云数据进行分割,然后通过目标函数提取根领区域。以已识别的根领区域为中心,根据相邻植物之间的距离生成自适应植物包膜区(PEA),以分离油菜籽个体标本。在每个植物根颈区对应的PEA中,播种期间的地面位置和不同生长阶段的冠层顶端被精确定位,从而能够自动提取整个生命周期的单个PH。播种后140、150、165 d,算法与人工测量结果的决定系数(R2)分别为0.9742、0.9667、0.9208。算法与人工测量结果在140、150、165天的均方根误差(RMSE)分别为0.038、0.043、0.061 m。这些结果证实,将北斗定位与三维点云处理相结合,实现了作物高度动态的高精度表型分析。利用ph进行霜冻危害和倒伏敏感性分析,结果表明,随着霜冻危害程度的增加,油菜籽的生长速度减慢,开花期高度达到1 m左右的植株在降雨后容易倒伏。这些结果有可能为智能农业应用中的霜冻危害评估和品种选择提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic whole-life cycle measurement of individual plant height in oilseed rape through the fusion of point cloud and crop root zone localization
Plant height (PH) of oilseed rape, as a crucial phenotypic indicator, provides essential data for seedling diagnosis and breeding selection when accurately monitored throughout the life cycle of individual plants. However, it is a challenge to obtain precise PH measurements as rapeseed leaves and other crops shade each other after flowering. In this study, a rail-based platform equipped with LiDAR and the BeiDou differential positioning system was designed and manufactured to autonomously collect time-series point cloud of oilseed rape populations in the field. The point cloud data of oilseed rape during the regreening stage was segmented using an improved fast Euclidean clustering algorithm, followed by extraction of the root collar region via an objective function. Centered on the identified root collar region, an adaptive plant envelope area (PEA) was generated based on the distance between adjacent plants to isolate individual rapeseed specimens. Within the PEA corresponding to each plant’s root collar region, the ground position during sowing and the canopy apex at distinct growth stages were precisely localized, enabling automated extraction of individual PH across the full life cycle. The coefficient of determination (R2) between the algorithm and the manual measurement results at 140, 150 and 165 days after sowing were 0.9742, 0.9667, and 0.9208, respectively. And Root Mean Square Error (RMSE) between the algorithm and the manual measurement results at 140, 150 and 165 days were 0.038, 0.043 and 0.061 m, respectively. These results confirm that integrating BeiDou positioning with 3D point cloud processing achieves high-precision phenotyping of crop height dynamics. Furthermore, PHs were applied to frost damage and lodging susceptibility analysis, which indicate that the growth rate of rapeseed slows down as the severity of frost damage increases, and plants that reach a height of approximately 1 m during the flowering stage are prone to lodging after rainfall. These results have the potential to provide guidance for frost damage assessment and variety selection in smart agriculture applications.
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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