Association of “Greenness” in Corn with Yield and Leaf Nitrogen Concentration

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. 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...

Assessment of Leaf Color Chart Observations for Estimating Maize Chlorophyll Content by Analysis of Digital Photographs

“…Although the human eye is sensitive to slight changes of green in leaves (Stockman and Sharpe, 2000), it is very difficult to identify levels of color on a consistent basis without some sort of aid (Singh et al, 2002). The subjectivity of LCCs led to the conclusion that the resulting values are not accurate compared with other methods (Saberioon et al, 2014). However, there are several steps in the relationship between leaf greenness and N content that affect accuracy, so inaccuracies in N status may not be the result of leaf color observations.…”

Determination of Canopys Average SPAD Readings Based on the Analysis of Digital Images

“…One instance of this calibration occurred when farmer's took digital images of corn leaves alongside calibration disks, which then served as internal standards in a two-point regression of actual DGCI values [17]. Additionally, it is important that attempts be made to standardize a field's ambient lighting condition, because a crop's solar angle and cloudiness are likely to change a digital image's R, G, and B values (Figure 3).…”

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping

“…Partial discoloration could be seen as an increase in the number of pixels that fall into the range of a specific bin (BlCalcColorHistograms). Some of the color-dependent features could further be used to calculate derived indicators like dark green color index (Rorie et al, 2011) or the normalized differenced vegetation index (Barnes et al, 2001). The calculation of such indices also requires proper setup and calibration of the cameras and optical filters used.…”