Study of Spectral Response Characteristics of Oilseed Rape (Brassica napus) to Particulate Matters Based on Hyper-Spectral Technique

Study of Spectral Response Characteristics of Oilseed Rape (Brassica napus) to Particulate Matters Based on Hyper-Spectral Technique
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基于高光谱技术的油菜对颗粒物的光谱响应特性研究

DOI:
10.32604/phyton.2021.014190
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发表时间:
2021-01-01
影响因子:
1.7
通讯作者:
Sui, Yuanyuan
Sui, Yuanyuan
中科院分区:
生物学4区
文献类型:
--
作者:
Kong, Lijuan;Yu, Haiye;Sui, Yuanyuan

文献摘要

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灰霾主要是由空气中的悬浮颗粒物引起的,其中颗粒物污染危害叶菜类蔬菜。在模拟大气颗粒物污染的环境中,研究了不同生育期的油菜对大气颗粒物的污染情况。采用高光谱技术与显微检测相结合的方法,深入研究了叶片的高光谱特征对颗粒物的响应。结果表明,叶片的高光谱、叶绿素含量、净光合速率和气孔导度均随温度的升高而升高。用环境扫描电镜(ESEM)观察了颗粒物在叶片上的沉积和吸附。选取归一化差值植被指数(NDVI)、修正红边归一化(mNDMI 705)和修正红边简单比值指数(mSR705)作为特征参数,选取与620 nm相近的510 nm波段作为敏感波段。采用16种方法建立生理信息反演模型。主要研究结果如下:在颗粒物的影响下,光谱反射率总体上呈下降趋势。随着叶龄的增加,蓝移现象加重。黄边和蓝边的幅值随着植被指数的降低而降低。叶片上的沟和不规则带状突起有利于颗粒物的滞留。随着作用时间的延长,叶片上沉积的颗粒物质增多,气孔开度变小。通过比较,确定了主成分回归(PCR)+多重散射校正(MSC)+二阶导数(SD)+ Savitzky-Golay平滑(SG)和偏最小二乘法(PLS)+多重散射校正(MSC)+一阶导数(FD)+ Savitzky-Golay平滑(SG)分别是建立叶绿素含量和净光合速率反演模型的最佳方法。该研究为利用高光谱技术诊断和分析叶菜类蔬菜对颗粒物污染的生理响应提供了新的思路。
Haze is mainly caused by the suspended particulate matters in the air, of which the particulate matters pollution harms leaf vegetables. In this paper, oilseed rapes at four different growing periods were investigated in a simulated particulate pollution environment. In combination of hyper-spectral technology and micro examination, the response of hyper-spectral characteristics of the leaf to particulate matters was investigated in-depth. The hyperspectral, chlorophyll content, net photosynthetic rate and stomatal conductance of leaf were obtained. The deposition and adsorption of particulate matters on the leaf were observed by Environmental Scanning Electron Microscope (ESEM). Normalized difference vegetation index (NDVI), modified red edge normalized (mNDVI705) and modified red edge simple ratio index (mSR705) were selected as characteristic parameters and the range of 510 nm similar to 620 nm as the sensitive band. 16 methods were used to establish the physiological information inversion model. The main results were as follows: Under the influence of particulate matters, the spectral reflectance decreased as a whole. With the increase of leaf age, the phenomenon of blue shift aggravated. The amplitude of yellow and blue edge decreased with overall decreasing vegetation indices. The furrows and irregular band protrusions in leaves were favorable for keeping particulate matters. With longer affecting time and more deposition of particle matters on the leaf, the stomatal opening became smaller. After comparing, principal component regression (PCR) + multiple scatter correction (MSC) + second derivative (SD) + Savitzky-Golay smooth (SG), and partial least square (PLS) + multiple scatter correction (MSC) + first derivative (FD) + Savitzky-Golay smooth (SG) were determined the best method to establish the inversion model of chlorophyll content and net photosynthetic rate respectively. This study may bring novel ideas for the diagnosis and analysis of the physiological response of leaf vegetables under particulate matters pollution using hyper-spectral technology.