Monitoring Nitrogen Status And Growth Characters With Hyper-spectral In Maize

Crop growing, nutrition monitoring and real-time estimation is the key technology to thedevelopment of the precision agriculture sustainable agricultural. The real-time and accuratemonitoring of crop of accumulated nitrogen by using hyper-spectral technology is in favorof conducting crop nitrogen diagnosis timely and reasonable, and it is of significance inenhancing nitrogen use efficiency, reducing the use of fertilize nitrogen and decreasingenvironmental pollution. In this study a series of field experiments with different maizevarieties and nitrogen levels were carried out. Based on analysis of canopy spectralreflectance and Physiological and biochemical test technology in corn.the characteristics ofcanopy spectral reflectance under different conditions and their correlation to nitrogen statusand growing index in corn were quantified computed in this paper, and the sensitive spectrumparameters and quantitative regression models were established for leaf pigment content、nitrogen status and growing index (leaf area index and dry matter accumulation)in corn. Themain contents and results of the present study are summarized as follows:1Comparison of variation patter in canopy hyper-spectral and red edge under differentnitrogen levels、growing stages and cultivars in corn, showed that the reflectance at visibleband（350-710nm）decreased with increasing nitrogen levels, whereas reflectance at nearinfrared fla（t760-1300nm）increased. Reflectance at visible light decreased and then increasedwith growth progress. However, reflectance in near infrared flat had opposite trend. Therewere “double peak” phenomenon for the red edge in corn. The double peak did not appearincrease or decrease phenomenon with increasing nitrogen levels, while Along with theadvancement of growth period, the double peak enhanced firstly and then weakened. Therewere “red shift” phenomenon for the position of red edge along with the growth period. but“blue shift” for the position of red edge after the flowering period. The position of the rededge was not sensitive to the nitrogen, it changed a little，with the increasing nitrogen levels. The slope of the red edge was sensitive to the nitrogen and the growth period, it appeared tobe an increased trend with the increasing nitrogen levels, but along with the growth period,the slope of red edge first increased then decreased.2The regression models with hyper-spectral vegetation index as NDVI(760460)、NDVI(810460)、NDVI(760510) produced better estimation of dry matter accumulation, andcompared with the determination of coefficients, NDVI(760460) was the best indicator toestimate the dry matter accumulation. The hyper-spectral vegetation index such as RVI(710460)、NDVI(710460)、RVI（710510）、NDVI（710510) produced better estimation of LAI,and compared with the determination of coefficients, RVI（710510）was the best indicator toestimate the dry matter accumulation.3The relationships of different pigment components to canopy hyper-spectral parameterswere quantified based on the experiment data. The results showed that the Ratio and thenormalized difference vegetation index which were established by the red edge band710nmand the visible bands460nm、510nm can be better used to estimate the contents of Chla、Chlband Chla+b of corn，and the RVI(710510) was the best inversion parameter. The carotenoidcould be well monitored by the red edge parameter D red.4The relationships of leaf and plant nitrogen status to canopy hyper-spectral parameters incorn were quantified. The results showed that the RVI(1100560)was the best parameter forpredicting leaf content(LNC), the NDVI(1100560) was the best parameters for predicting leafnitrogen accumulation(LNA).Compared with the leaf，the correlation between the above-ground nitrogen accumulationand the canopy hyper-spectral reflectance was relatively poor. Results showed that the Ratio,normalized and difference vegetation index which were established by the near infrared band950nm and the red edge band760nm can be well used to estimate the above-ground nitrogenaccumulation of maize. Compared with the determination of coefficients,the normalizedindex NDVI(950760) was the best inversion parameter to estimate the above-ground nitrogenaccumulation.