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

Haze is mainly caused by the suspended particulate matters in the air, of which the particulate matters pollutionharms 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, theresponse 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) andmodified red edge simple ratio index (mSR705) were selected as characteristic parameters and the range of510 nm~620 nm as the sensitive band. 16 methods were used to establish the physiological information inversionmodel. The main results were as follows: Under the influence of particulate matters, the spectral reflectancedecreased as a whole. With the increase of leaf age, the phenomenon of blue shift aggravated. The amplitudeof 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 depositionof particle matters on the leaf, the stomatal opening became smaller. After comparing, principal componentregression (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 physiologicalresponse of leaf vegetables under particulate matters pollution using hyper-spectral technology.