Submitted to: American Society of Agronomy Meetings
Publication Type: Abstract only
Publication Acceptance Date: 9/15/2007
Publication Date: 11/5/2007
Citation: Russ, A.L., Daughtry, C.S., Meisinger, J.J. 2007. Assessing spectral reflectance sensor for detecting N stress in corn [abstract]. American Society of Agronomy Meetings. 2007 CDROM. Interpretive Summary:
Technical Abstract: Variable rate sidedress applications of fertilizers can often improve N use efficiency in corn. While variable rate fertilizer prescriptions may be produced from previous years’ yield and soils data, an assessment of the spatial variability of a crop’s N status just prior to fertilizer application may be the optimal method. Corn grown with an insufficient supply of N will typically exhibit reduced leaf area index (LAI) and leaf chlorophyll content. Remote sensing offers an efficient method for surveying the variability of N status over large areas, however, background reflectance from soil and plant residue often confound detection of differences in LAI and leaf chlorophyll content while plants are small. Corn N rate experiments were conducted from 2004 to 2007 at two diverse locations in Maryland to evaluate active and passive remote sensing instruments for detecting N stress in corn. Remote sensing instrumentation included a Holland Scientific Crop Circle ACS-210 and a Cropscan MSR16. Plant height, LAI, leaf chlorophyll content, development stage, and the remotely sensed data were acquired weekly from growth stages V6 to R1. This enabled an examination of the relationship of growth stage with the expression of N stress in the corn and the sensors ability to detect the stress. Temporal exhibition of N stress varied from year to year due to residual soil N and meteorological variables (rainfall and temperature). Correlations between remotely sensed vegetation indices and leaf chlorophyll content typically increased as the corn developed, and N-stress intensified. Vegetation indices responded most strongly to LAI and percent cover in early developmental stages. Results suggest that an evaluation of corn N status with spectral remote sensing is best conducted at, or after, a growth stage of V8.