Using Active Canopy Sensors to Quantify Corn Nitrogen Stress and Nitrogen Application Rate

Abstract

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. P recision agriculture technologies are becoming an integral part of farming operations for crop production, including fertilizer management in the U.S. Corn Belt. Active canopy sensors are continually being developed and tested as an input variable used to implement variable rate N fertilizer management strategies in corn. Canopy sensors can diff erentiate site-specifi c N need, thus potentially reducing N fertilizer application across fi elds while maintaining crop yields. Improving N use effi ciency by addressing spatial variability of corn fertilizer N requirements can increase profi tability and promotes equitable land stewardship.Since the early 1990s, ongoing research has been conducted using the SPAD chlorophyll meter (SPAD-502) as a plant based testing method to determine N fertilization need. Schepers et al. (1992) found signifi cant diff erences in SPAD readings between sites, corn hybrids, and growth stages suggesting that normalization procedures are needed to standardize readings in order for the SPAD-502 to be a practical N management tool. Normalization procedures require a nonlimiting N fertilized fi eld area as a comparison to areas where N may be defi cient. Th is normalization produces a relative SPAD value (rSPAD), sometimes called a suffi ciency index (Schepers et al., 1992). Th is normalization has been shown to be important by others with the SPAD-502 (Varvel et al., 1997;Scharf et al., 2006;Hawkins et al., 2007;Varvel et al., 2007;Ziadi et al., 2008).Researchers from Missouri summarized a regional experiment in the north central United States evaluating the SPAD-502 to predict corn N fertilization (Scharf et al., 2006). Th ey found rSPAD values correlated well to the economic optimum N rate (EONR) and yield response to N in corn, and were more accurate in predicting N need when N fertilizer was not previously applied, when sensing was performed later in the growing season, and when readings were normalized. Findings from Hawkins et al. (2007) in Iowa and Varvel et al. (2007) in Nebraska indicated that in-season N stress in corn can be detected with the SPAD-502 and N rate algorithms could be developed to make in-season N rate applications between the V8 to V12 growth stages. Although, the SPAD-502 can detect N defi ciencies, a study by Zhang et al. (2008) indicated limited potential for use in production corn fi elds under moderate N stress and near optimum N.Canopy refl ectance measurement at optical wavelengths with active canopy sensors is a relatively new method of remote sensing. ABSTRACTIn-season corn (Zea mays L.) N sensing with active canopy sensors can provide input variables that direct variable rate N fertilizer applications. Th e objectives of this study were to assess corn N stress at the V10 to V12 growth sta...

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

“…The most widely published approach for developing N rate recommendations for corn has been to measure the EONR and reflectance across a range of environments, then regress EONR vs. reflectance (Kitchen et al, 2010;Dellinger et al, 2008;Schmidt et al, 2009;Scharf and Lory, 2009;Barker and Sawyer, 2010). This regression relationship can then be used to predict EONR in the future.…”

Comparison of Satellite Imagery and Ground‐Based Active Optical Sensors as Yield Predictors in Sugar Beet, Spring Wheat, Corn, and Sunflower

“…The use of the CC sensors has been directed toward development of algorithms for in-season N application. Relationships of sensor readings to yield and in-season N status, as well as algorithms for use in determining in-season N rates have been developed by several researchers Solari et al, 2008;Sripada et al, 2008;Scharf and Lory, 2009;Barker and Sawyer, 2010;Solari et al, 2010;Oliviera et al, 2013;Franzen et al, 2014).…”

Corn Nitrogen Fertilization Requirement and Corn-Soybean Productivity with a Rye Cover Crop

“…At the time of sensing, corn stages varied from V8 to V11 depending on the N rate. The overall method for canopy sensing was that described by Barker and Sawyer (2010). Approximately 10 VIS and NIR band reflectance values were captured from each plot, the values averaged, and used to calculate a per plot normalized difference vegetative index (NDVI; Gitelson et al, 1996;Teillet et al, 1997).…”