| Nutrient diagnosis of crops is the means to investigate the nutritional status and nutritional condition of crops. Non-destructive monitoring crop nutritional status in spots is a significant research area in remote sensing and informational agriculture, and is essential for knowing and mastery the way crop is growing the nutritional composition content and the information of quality or output. This paper is combined with national high tech project (863) "The research of detect technical in nutrient information and modal parameter of crops". On the basis of summarizing literature throughout domestic and overseas, we take the soybean and corn as our investigative object; rely on a series of experiment and bring lots of measure to bear synthetically such as modern remote sensing information ,vegetal analysis ,biophysical and biochemical parameter test and symbolic statistic. We study the relationships between reflectance characteristics of soy and plant nitrogen status and chlorophyll growth characters under various irrigation -fertilization condition; at the same time we also estimate the water content of corn leaf by absorption depth or area. The results show that favorable correlative relationship exit in all review factors, and then we set up remote regression model. After checkout, we find the precision of each models sufficing requirement because of their correlative modulus are nearly all among 0.7~0.8 homogeneously. Finally we conduct primary models for nutrient diagnosis of crops and monitoring growth traits based on canopy or leaf spectral characteristics. Leading matter are recited below: The correlative relationship between red edge swing and TN of soy vane is studied. The red edge is the key point for measuring vegetal biophysical and biochemical parameter based on spectral positional changes. It is the most important spectral characteristics of all plants'. The methods using differential spectral coefficient excelled general spectral vegetation index of wide wave band: general vegetation indexes aren't sensitive to the change of vane color due to the influence of bestrow ratio. Former people's study have substantiated the variational characteristics of crop spectrum can be reflected clearly by differential coefficient of spectral reflectivity because of weakening effect of background. That's it; differential coefficient of spectral reflectivity can inspect gradual changes of pigment and catch changes of plants'nitric content sensitively. Based on this theory, we find that red edge swing at 740nm can size up TN of soy leafs after calculating differential coefficient of reflected canopy spectrum. It takes on remarkable linear relation: Y=590.26419 *X+0.82932 and it's interrelated parameter is 0.6452;we attain correlative equation between anticipative numerical value and actual value is Y=1.32573X-1.49542 by inspection, and it's interrelated parameter is 0.80344.All these validate fully the reliability of correlative model between red edge swing and TN content. At the same time, we also make use of absorption depth or area of spectral characteristics in simulating TN content .The simulant model is established as Y=2.62643X-12.93889 after wiping off eery-data. Its correlative parameter is 0.73536.We select another eight suits of data to validate the model by using international common statistical means and get correlative equation: Y=1.00264+0.69287*X(R=0.81829)。The quantified relationship of soybean leaf SPAD value and leaf spectrum reflection character is established in varied soil water and nitrogen. Five kinds of spectrum vegetation index is used for reflecting reversely the CHL.C of the soybean; The notion of vegetation index is put forward on the assumption of vegetation index action correlating with vegetation unique biophysics character. Multi-spectrum signals in different spectrum regions are a kind of combination by proportion or linearity. It can estimate vegetation parameter more precisely and reduce the affectof outside factors. The reflection ratio of leaf in visible light band is complete different from that in infrared band, so vegetation index in varied band can forecast CHL.C. Five spectrum index including CARI, SAVI, RVI, NDVI, NIR/G5 is selected for reflecting reversely CHL.C and the recursive diagnosed model is established. This model has good forecast and popularity to relative content of soybean CHL.C with different fertilizer, no affect by nitrogen and bearing dates. We make a contrast of validity between applying simple equation and high equation in simulating chlorophyll relative content by red slope. The result makes it clear that the later equation enhance 7 percent over the former one. This approve differential spectrum have behaved favorable effect in eliminating the infection of background information. Using characteristic absorption apex parameter estimates the water amount of corn leaf's slice. Under the base of clarifying the main calculation method of spectrum absorption characteristic parameter, we could predict the water amount of corn leaf's slice with the spectrum of the 1450 nm characteristic absorption apex. The result shows that there is a distinct linear relation between the characteristic absorption apex depths; the areas and water amount .The correlative quotiety of the statistical regress model (Y1=0.9719-0.23961*X1 and Y2=0.97193-0.000798783*X2) are all above 0.8. The error examination manifest that the relative errors of forecast values and true values are all within 0-5%, and indicate that the climactic reflected spectrum data and evolvement form could better reflect moisture situation of corn leaf's slice. Having discussed the effects resulting from background factors, such as soil, and interferential phenomena, such as yawp resulting from the climactic reflected spectrum .In order to solve this issue, considering the influence of soil nutrition to the bio-chemical content of plant, thus educing the research direction of the following work: Before predicting the climactic reflected spectrum during different growth epoch, analyzing correlation between the soil spectrum characteristic and... |
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