首页 | 本学科首页   官方微博 | 高级检索  
     

基于激光扫描3D图像的植物亏水体态辨识与萎蔫指数比较
引用本文:郑力嘉,孙宇瑞,蔡祥. 基于激光扫描3D图像的植物亏水体态辨识与萎蔫指数比较[J]. 农业工程学报, 2015, 31(2): 79-86
作者姓名:郑力嘉  孙宇瑞  蔡祥
作者单位:1. 中国农业大学信息与电气工程学院,北京,100083
2. 北京林业大学信息学院,北京,100083
基金项目:国家自然科学基金资助项目(31371537)
摘    要:为实现植物水分状况的非接触式测量,最大程度减少测量对植物生长的影响,该文采用非接触式激光扫描测量方法获取植物叶片三维形态信息,通过测量植物叶片的体态萎蔫特征反映植物亏水胁迫状况。运用微分几何算法、二维傅里叶谱分析法、垂直投影叶面积法以及标准差法分别定义了4种植物萎蔫指数:基于微分几何算法的萎蔫体态指数、基于二维傅里叶谱分析的萎蔫指数、基于垂直投影叶面积的萎蔫指数和基于标准差方法的萎蔫指数,定量刻画植物萎蔫状态。试验分析了萎蔫指数的日变化过程,通过与植物茎秆直径的比较,得出定义的指数可以有效表征植物水分的结论。结合环境参数(太阳全辐射和环境温度)进行了相关分析,研究环境对植物水分的影响。最后比较了4种萎蔫指数刻画萎蔫状态的有效性。研究结果表明:萎蔫指数(以萎蔫体态指数为例)与太阳全辐射、环境温度和茎秆直径均线性相关,决定系数分别为0.736、0.785和0.845。4种指数比较中,萎蔫体态指数、基于二维傅里叶谱分析的萎蔫指数、基于垂直投影叶面积的萎蔫指数刻画叶片萎蔫效果相似,这3种指数与植物茎秆直径的线性相关系数分别为0.841、0.849、0.800。相比之下,基于标准差的萎蔫指数刻画萎蔫效果较差且与茎秆直径相关性也较低(R2=0.640)。该研究可为植物水分状况的非接触式测量提供一种有效的方法。

关 键 词:作物  图像识别  水分胁迫  萎蔫辨识  萎蔫指数  茎秆直径
收稿时间:2013-09-14
修稿时间:2014-12-12

Identification of plant morphology induced by water stress and comparison of indices using laser scan 3D images
Zheng Liji,Sun Yurui and Cai Xiang. Identification of plant morphology induced by water stress and comparison of indices using laser scan 3D images[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(2): 79-86
Authors:Zheng Liji  Sun Yurui  Cai Xiang
Affiliation:1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;,1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China; and 2. School of Information, Beijing Forestry University, Beijing 100083, China;
Abstract:Abstract: Leaf wilting is a common symptom in plants responding to drought stress. Early wilting detection is very important for precision crop management. In this paper, plant morphology was monitored to determine plant water status. A laser scanner was used to obtain three-dimensional (3D) images of plants based on the principle of triangulation. Four wilting indices based on plant morphology were developed and tested using different mathematical methods. The plant wilting indices included differential geometry; 2D Fourier transformatio; top projected leaf area (TPLA); and standard deviation (SD). Experiments were conducted to verify the effectiveness of each wilting index for characterizing plant water status. Zucchini plants were selected because of their sensitivity to variations in soil water content and environmental parameters. These parameters included solar radiation, air temperature and ambient relative humidity. Zucchini seeds were individually sown in greenhouse pots. Two weeks later, the young plant emerged from the pot soil, and three of the healthiest plants were chosen as test samples. The substrate water content for these plants was maintained at 0.06-0.08 kg/kg (relatively dry), 0.17-0.20 kg/kg (moderately dry) and 0.30-0.32 kg/kg (wet). The fourth leaf of each plant was scanned at 30-minute interval between 8 am and 5 pm over 10 days. Concurrently, the environmental parameters and plant stem diameter were measured at 5-minute interval. The data obtained indicated a correlation between the wilting indices and the environmental parameters. It also showed that the wilting indices were affected by the diameter of the plant stem. The results showed that the diurnal variation process on wilting index based on differential geometry correlated with environmental parameters. For example, stronger solar radiation and higher air temperature lead to a larger index value and vice versa. The wilting index exhibited strong linear correlations with solar radiation, ambient temperature and stem diameter, where the coefficients of correlation were 0.734, 0.785 and 0.845, respectively. The quantitative regression between wilting index based on differential geometry and stem diameter indicated that wilting index based on differential geometry could be used to reflect plant water deficit stress conditions, which was consistent with previous studies. A correlation analysis was carried out to determine the effectiveness of each index. The absolute values of correlation coefficients between TPLA and wilting index based on differential geometry, wilting index based on 2D Fourier transformation, were above 0.895, suggesting that these indices were well-correlated with plant wilting. The correlation coefficients between SD and other wilting indices were around 0.76, indicating a poor approach for comparison. To verify the accuracy of these indices, the correlations between each wilting index and the environmental parameters were analyzed. The regression results showed well-correlated linear relations with R2 above 0.806 between wilting index and air temperature, and R2 above 0.720 between wilting index and solar radiation. However, the correlation between wilting indices and stem diameter was poor. The correlation coefficients of wilting index based on differential geometry, wilting index based on 2D Fourier transformation and TPLA with stem diameter were above 0.800, while only 0.64 between SD and stem diameter. It was concluded that wilting index based on differential geometry, wilting index based on 2D Fourier transformation and TPLA performed better than SD for identifying plant water status. This paper suggests a novel, non-invasive and accurate method for monitoring plant water status.
Keywords:crops   image recognition   water stress   wilting identification   wilting index   stem diameter
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《农业工程学报》浏览原始摘要信息
点击此处可从《农业工程学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号