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. N itrogen is an important and costly input for nonleguminous grain crops, and producers are applying N fertilizer in large amounts to ensure high yields over a range of environmental conditions (Kyveryga et al., 2007). However, excessive N fertilization may lead to runoff , leaching, and nitrate pollution. A delayed N application and the use of remote sensing tools might allow a producer to apply a more economically benefi cial N rate to their fi elds. Scharf and Lory (2002) gave several reasons to delay N applications, including avoiding extra work during the busy planting season and lowering the in-season N loss during wet years. Th ey also suggested that diagnostic tools for plant N might increase fertilizer use effi ciency, and these tools include the SPAD meter, refl ectance measurements, and color analysis. Th e SPAD meter is used to make an optimum fertilizer N-rate decision by measuring N stress relative to an optimum N-rate strip within a fi eld (Hawkins et al., 2007). Th e SPAD meter is well documented as an accurate measure of the N status of corn at diff erent developmental stages (Piekielek and Fox, 1992; Blackmer et al., 1994; Schepers, 1994). Piekielek et al. (1995) showed that SPAD values expressed relative to SPAD values from a high-N strip (relative or normalized SPAD) could be compared over a wide range of sampling times when using a common critical value. Normalized SPAD values lessen the eff ect of diff erences in hybrid, soil type, growth stage, or environmental conditions (Piekielek et al., 1995). Scharf et al. (2006) found that the relationship between SPAD values and economically optimum N rate was much stronger when using normalized values as opposed to absolute values. Th e SPAD meter is a useful tool, but it has some potential limitations. Th e SPAD meter costs about $1500 USD, has a small sampling area (6 mm 2), is subject to operator bias, and Zhang et al. (2008) showed that SPAD meters have diffi culty in estimating chlorophyll levels when they are near or above optimum. Th eir observations indicate that increases in chlorophyll are not necessarily associated with increases in yield. Spectral refl ectance of crop leaves can be a valuable tool to estimate plant N status (Li et al., 2005). Spectral refl ectance is the refl ectance of certain plant components that are controlled by their visual properties and radiant energy exchange in a canopy (Huete, 1988). Th e refl ectance of certain wavelengths is related to diff erent amounts of chlorophyll a and b, which can be used to estimate the N status of certain crops (Huete, 1988). Th is method shows great potential because it off ers a method to deliver variable-rate N applications from a vehicle-mounted sensor (Kitchen et al., 2010). Tools for measuring refl ectance, howe...

Environmental concerns of nitrate pollution coupled with the cost of N fertilizers have led to increased interest in assessing plant N status. Our objective was to use a digital camera and image-analysis software to assess leaf N concentration in corn {Zea mays L.) leaves from the association between leaf N and green color of chlorophyll. In greenhouse experiments conducted at Fayetteville, AR, in 2008 and 2009, digital photographs of the uppermost collared leaf of 3-to 5-leaf corn plants grown over a range of soil N treatments were processed into a dark green color index (DGCI), which combines the hue, saturation, and brightness into one composite number. Soil plant analysis development (SPAD) and DGCI values agreed closely across both years with r^ > 0.91. There was a close relationship (r^ ranged from 0.80 to 0.89) between DGCI and leaf N concentration. Yellow and green disks of known DGCI values were successfully used as internal standards to correct for differences in color sensitivity among cameras. Similarly, DGCI standard disks were able to correct for differences in lighting conditions for corn grown in the field. Determination of leaf N concentration in corn by digital image analysis offers a potential new tool for assessing corn N status.