The Rice Plant Nitrogen Nutrition And Growth Monitoring Based On The Canopy Reflectance Spectra

As China’s major food crops of rice, rice yield and quality plays a vital role in solvingthe problem of the national food rations. In this study, Jiangxi Agricultural University inthe early planted plots Zhong Zao35and Gan Xin203as the research object, hyperspectraltechniques rice canopy reflectance spectra were measured and used to monitor the growthand nitrogen nutritional status of growing rice. Experimental set up five different nitrogenlevels, Canopy spectral characteristics under different conditions of nitrogen fertilizer inrice, as well as parameters and spectral characteristics of canopy leaf area index, shootdry weight, fresh and dry weight and leaf chlorophyll content relevance analysis. Selectedto reflect the growth of rice growing, sensitive spectral characteristics and chlorophyllcontent physicochemical parameters. The main findings are as follows:1. Through the different levels of nitrogen fertilizer in rice canopy spectral reflectancecurves, and " trilateral " characteristic variable value analysis, research on variation ofspectral reflectance curves under different levels of nitrogen fertilizer and the " trilateral "parameter. The results show that in the visible range400~700nm, the reflectivitydecreases with the increase of nitrogen; in the near infrared range700~1000nm, thereflectivity with increasing amount of nitrogen increases. In different growth stages, thespectral reflectance in the visible rice at400~700nm, with decreasing after transplantingto heading to maturity increases; within700~1000nm near infrared range, followed bytransplanting to heading after growing to maturity of decreases. Spectrum " trilateral "parameter values in the red and green valley reflectivity R0peak reflectance Rg withincreasing amount of nitrogen showed a decreasing trend, red and green valley location λ0peak position λg and blue occur with increasing amount of nitrogen shift. Red edgeposition λr with increasing amount of nitrogen obvious red shift from675nm to startposition, the red edge amplitude with increasing amount of nitrogen Dr showing anincreasing trend.2. In the analysis of different amount of nitrogen conditions, rice LAI andaboveground biomass varies with nitrogen rate and fertility periods, characterized byspectral analysis of the variables associated with screened-sensitive variable spectralfeatures. The results showed that the leaf area index and dry leaf weight increased withincreasing nitrogen rate, increased with advancing stage of growth and the largest heading,and then decreases; shoot fresh biomass and aboveground dry biomass with the amount ofnitrogen increased with increasing, with the growth and development of rice growing tomaturity. Correlation analysis by spectral characteristics variables, derived variables ricesensitive characteristics and growth ratio vegetation index R1200/R553growing wassignificantly positively correlated with a correlation coefficient above0.6.3. Characteristics of Rice under different conditions amount of nitrogen throughchlorophyll and nitrogen nutrition studies found that total chlorophyll and nitrogenfertilizer has a significant positive correlation, and chlorophyll content can come throughthe inversion in the process of planting rice the abundance of nitrogen shortage situation.Total chlorophyll and nitrogen content in rice leaf analysis found that the correlation between showing a significant positive correlation, according to the test analysis foundthat in total chlorophyll and nitrogen fertilizer and nitrogen content of leaves headingcorrelation the best, so the spectral reflectance and chlorophyll analysis, chlorophyll andthe best time heading Nitrogen monitoring two rice varieties. By the spectralcharacteristics of the original variable processing, analysis and correlation of different riceleaf chlorophyll, found in higher correlation spectral characteristic parameters, thevegetation index PSSRb, PSNDa, PSSRc, PSNDb, PSNDc was a significant positivecorrelation, as since variable chlorophyll content in rice estimation model is moreappropriate.