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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #346985

Research Project: Sustainable Intensification of Grain and Biomass Cropping Systems using a Landscape-Based GxExM Approach

Location: Cropping Systems and Water Quality Research

Title: Active-optical reflectance sensing evaluated for red and red-edge waveband sensitivity

item BEAN, G - University Of Missouri
item Kitchen, Newell
item CAMBERATO, J - Purdue University
item FERGUSON, R - University Of Nebraska
item FERNANDEZ, F - University Of Minnesota
item FRANZEN, D - North Dakota State University
item LABOSKI, C.A.M. - University Of Wisconsin
item NAFZIGER, E - University Of Illinois
item RANSOM, C - University Of Missouri
item SAWYER, J - Iowa State University
item SCHARF, P - University Of Missouri
item SCHEPERS, J - Retired Non ARS Employee
item SHANAHAN, J - Fortigen

Submitted to: North Central Extension Industry Soil Fertility Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 10/25/2017
Publication Date: 11/15/2017
Citation: Bean, G.M., Kitchen, N.R., Camberato, J.J., Ferguson, R.B., Fernandez, F.G., Franzen, D.W., Laboski, C., Nafziger, E.D., Ransom, C.J., Sawyer, J.E., Scharf, P.C., Schepers, J.S., Shanahan, J.F. 2017. North Central Extension Industry Soil Fertility Conference, November 15-16, 2017, Des Moines, Iowa. p. 121-132.

Interpretive Summary: Canopy reflectance sensing has been used on many farmers’ fields for assessing corn nitrogen (N) health and making in-season N fertilizer applications. However, the unique growing conditions under which various sensor types were developed and tested, including the wavebands selected for reflectance measurements, may limit their utility over larger geographic areas. The specific question this study addressed was “over a large geographic region is the red or the red-edge waveband more sensitive to corn nitrogen health?” We found that when using canopy reflectance sensing for waist-high corn the red-edge waveband was better than the red waveband when the wavebands were related to: 1) at-planting N fertilizer rate; 2) soil nitrate when the corn was about 1-ft high; and 3) end-of-season relative yield. These findings suggest algorithms that rely on the red-edge waveband will likely be more accurate in producing nitrogen fertilizer recommendations than those that utilize only the red waveband. As sensors and associated algorithms are developed that utilize the most sensitive reflectance information relative to crop nitrogen health, farmers using this technology will benefit because it will result in fertilizer rates that better match crop needs. Further, a reduction of excess N applications will not only save them money, but will reduce environmental loss of nitrogen into streams and lakes.

Technical Abstract: Uncertainty exists with corn (Zea mays L.) N management due to year-to-year variation in crop N need, soil N supply, and N loss from leaching, volatilization, and denitrification. Active-optical reflectance sensing (AORS) has proven effective in some fields for generating N fertilizer recommendations. However, various sensors utilize different wavebands of light to calculate N fertilizer recommendations making it difficult to know which waveband is most sensitive to plant health. The objective of this research was to evaluate across the US Midwest Corn Belt the performance and sensitivity of the red (R) and red-edge (RE) wavebands. Forty-nine N response trials were conducted across eight states and three growing seasons. Reflectance measurements were collected and topdress N rates (40 to 240 lbs N/ac on 40 lbs/ac increments) applied at approximately V9 corn development stage. Both R and RE wavebands were related to the at-planting N fertilizer rate, V5 soil nitrate-N, and end-of-season calculated relative yield. In every comparison the RE waveband demonstrated higher coefficient of determination values over the R waveband. These findings suggest the RE waveband is more sensitive to variations in N management and would work best for in-season AORS management over a geographically-diverse soil and weather region.