Submitted to: Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 18, 2003
Publication Date: October 20, 2003
Citation: DIKER, K., BAUSCH, W.C. RADIOMETRIC FIELD MEASUREMENTS OF MAIZE FOR ESTIMATING SOIL AND PLANT NITROGEN. BIOSYSTEMS ENGINEERING. 2003. Interpretive Summary: Nitrogen (N) is the most common and widely used fertilizer. Excess amounts of N as well as N deficiency adversely impact crop development and yield as well as groundwater quality. Timely determination of available soil N during the growing season could reduce potential pollution of environment. This research was undertaken to develop a methodology to estimate the available soil N through remote sensing using the corn plant as an indicator. Soil and plant N data as well as corn canopy reflectance data were collected during two growing seasons from a N level and a verification study. The former study was conducted to develop interrelationships between the variables and the later was conducted to verify the developed interrelationships. Remotely sensed data was used to calculate the Nitrogen Reflectance Index (NRI) which has been shown to correlate with plant N. Equations for NRI vs. plant N and plant N vs. soil N (NO3-N + NH4-N) were developed at several growth stages. GIS maps developed for the estimated available soil N showed that the N stress areas could be determined and that variable N rate applications could be determined as designated growth stages.
Technical Abstract: Conventional recommendations of nitrogen (N) fertiliser are based on composite soil samples. This may result in either underfertilisation or overfertilisation due to the neglected spatial variability. This paper shows a procedure to estimate in season plant and soil nitrogen by using remote sensing. The study was conducted on two experimental sites. The first experiment consisted of six non-replicated fertiliser plots. These data were used to develop the relationships between reflectance data and the plant and soil N. The second experiment had four plots with various N and water treatments on which the developed relationships were verified. Plant N, soil N and reflectance data from both nadir and 75 view angles were collected almost weekly. The nitrogen reflectance index (NRI) was employed to estimate plant N. Regression analysis was used to develop relationships. Spatial variability was mapped in ArcView geographical information system. Regression analysis between reflectance data and plant N, and soil N and plant N showed good relationships at various stages. The nadir view tended to underestimate the plant and soil parameters, whereas the 75 view slightly overestimated. Geographic information system (GIS) mapping of measured and estimated soil N showed an agreement except in locations where high N spots were encountered.