Weed Science

Published by: Weed Science Society of America

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Weed Science 53(1):23-29. 2005
doi: 10.1614/WS-04-070R1

13C discrimination in corn grain can be used to separate and quantify yield losses due to water and nitrogen stresses

David E. Claya, Sharon A. Clayb, Drew J. Lyonc, and Juerg M. Blumenthald

aPlant Science Department, South Dakota State University, Brookings, SD 57007

bCorresponding author. Plant Science Department, South Dakota State University, Brookings, SD 57007;

cPanhandle Research and Extension Center, University of Nebraska, Scottsbluff, NE 69361

dHeep Center, Texas A&M University, College Station, TX 77843

Abstract

It is difficult to quantify the mechanism(s) responsible for competition-induced yield loss using traditional experimental techniques. A technique using yield and 13C discrimination (Δ) for wheat, a C3 plant, has been developed to separate total yield loss (TYL) into yield loss due to N (YLNS) and water (YLWS) stresses. The objective of this research was to determine whether the Δ approach could be used in corn, a C4 plant, to separate TYL into YLNS and yield loss due to a combination of water and light stresses (YLWLS). The field study had a factorial design using five corn densities and five N rates and was conducted in western Nebraska in 1999 and 2000. Relationships for YLNS and YLWLS with TYL were derived from only a portion of the yield and Δ data collected in 1999 and validated based on the remaining data collected in 1999 and 2000. In 1999, 20 to 40% of TYL was due to YLWLS, whereas in 2000, a dry year, YLWLS accounted for 60 to 80% of the TYL. Results from using the Δ-based approach were consistent with analysis of variance results. For example, calculated YLWLS values were related to measured YLWLS by the equation: calculated YLWLS = 19 + 0.91 (measured YLWLS) (r2 = 0.95; P < 0.01). The Δ approach, based on a plant's physiological response to the environment, can be used to separate and quantify competition-induced YLNS and YLWLS in corn.

Nomenclature:Corn, Zea mays L.; wheat, Triticum aestivum L.

Received: March 19, 2004; Accepted: August 24, 2004

Keywords: Modeling yield loss, nitrogen stress, water stress



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Figure 1. A diagram showing how yield loss due to nitrogen stress and yield loss due to a combination of water and light stresses were calculated for corn, a C4 plant

Figure 2. A comparison between yield and Δ for data collected in Nebraska and South Dakota. The δΔwaterandlightstresses value was determined by plotting yield vs. Δ and empirically fitting a linear regression to the upper boundary of the data (Webb 1972). The South Dakota data (reported in Smeltekop et al. 2002) are included for comparative purposes

Figure 3. Validation of Δ approach: a comparison between yield loss due to (a) N stress vs. plant available N in 1999 and (b) measured and calculated yield losses due to a combination of water and light stresses in 1999 and 2000

Figure 4. Relationship between yield loss due to (a) N stress and (b) a combination of water and light stresses in 1999 and 2000

table

Table 1.The influence of N rate plant competition on grain yield, Δ, total N content, δ15N, YLNS, and YLWLS in 1999.a

table

Table 2.The influence of N rate plant competition on grain yield, Δ, total N content, δ15N, YLNS, and YLWLS in 2000.a

Europa 20-20 ratio mass spectrometer, SerCon, Wistaston Road, Crewe, Cheshire, U.K. CW2 7RP.

Cited by

W. Pansak, G. Dercon, T. Hilger, T. Kongkaew, G. Cadisch. (2007) 13C isotopic discrimination: a starting point for new insights in competition for nitrogen and water under contour hedgerow systems in tropical mountainous regions. Plant and Soil 298:1-2, 175-189
Online publication date: 12-Oct-2007.
CrossRef
David P. Horvath, Robert Gulden, Sharon A. Clay. (2006) Microarray analysis of late-season velvetleaf (Abutilon theophrasti) effect on corn. Weed Science 54:6, 983-994
Online publication date: 1-Nov-2006.

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