|Sripada, Ravi - CANAAN VALLEY INSTITUTE|
Submitted to: Proceedings of the Annual Precision Ag Conference
Publication Type: Proceedings
Publication Acceptance Date: June 15, 2008
Publication Date: July 18, 2008
Citation: Sripada, R.P., Schmidt, J.P. 2008. Variability in Observed and Sensor Based Estimated Optimum N Rates in Corn. Proceedings of the Annual Precision Ag Conference. p. 10. Interpretive Summary: Ground-based sensors have been used for making in-season N recommendations for corn (Zea mays L.). This study attempts to validate an in-season remote sensing based N recommendation model for corn in Pennsylvania and to identify the causes for variability in estimated and observed optimum N rates in corn. Corn canopy reflectance measurements were obtained at the same time when N applications were made when corn was 40-45 cm tall (NV6). The spectral index Relative Green Normalized Difference Vegetation Index (RGNDVI) was used to calculate the estimated optimum N rates and observed optimum N rates were calculated using the standard corn yield response curves. The remote sensing model accurately estimated the optimum N rates at three of the five sites. Grain yield did not respond to NV6 applications at two sites, where the remote sensing model over-estimated the optimum N rates. The soil nitrate-N and total N uptake measured during the growing season indicated that the interactive effect of changes in soil moisture and N availability from N applications to maturity (after the N application) can influence the accuracy of estimated optimum N rates.
Technical Abstract: Recent research showed that active sensors such as Crop Circle can be used to estimate in-season N requirements for corn. The objective of this research was to identify sources of variability in the observed and Crop Circle-estimated optimum N rates. Field experiments were conducted at two locations for a total of five sites during the 2007 growing season using a randomized complete block design with increasing N rates applied at V6-V8 (NV6) as the treatment factor. Field sites were selected from different landscape positions representing variable soil moisture regimes so as to generate a range of optimum N rates at V6. Corn canopy reflectance was measured using Crop Circle prior to N application at V6. Soil and plant biomass samples were obtained at planting, V6, R1 and physiological maturity. A significant grain yield response to NV6 was observed at three of the five sites. The remote sensing model accurately estimated the optimum NV6 rates at three of the five sites. Grain yield did not respond to NV6 applications at two sites, where the remote sensing model over-estimated the optimum NV6 rates. The soil NO3-N and total N uptake data measured during the growing season indicated that the interactive effect of changes in soil moisture and N availability after the NV6 application can influence the accuracy of estimated optimum NV6 rates. A better understanding of the soil moisture redistribution to the depth of root zone in relation to landscape position could help in understanding the influence of water stress on the N utilization of corn and thereby improve estimates of in-season N requirements.