Weed Science

Published by: Weed Science Society of America

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Weed Science 50(5):662-671. 2002
doi: 10.1614/0043-1745(2002)050[0662:SVOAAA]2.0.CO;2

Spatial variability of atrazine and alachlor efficacy and mineralization in an eastern South Dakota field

Zhuojing Liua, Sharon A. Clayb, David E. Clayc

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

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

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

Abstract

Landscape-induced differences in soil variability and other parameters have potential effects on herbicide sorption, persistence, degradation, and, ultimately, efficacy. This study examined the spatial variability of herbicide efficacy across an eastern South Dakota field in continuous corn. Atrazine and alachlor had been applied for the previous 10 yr. The spatial variability observed in weed control was compared with herbicide sorption (Kd), mineralization rate, and first-order half-life (t1/2), and field herbicide dissipation rates (DT50). Spatial structure was present in atrazine mineralization, weed biomass, and corn biomass data. The amount of atrazine and alachlor sorbed to soil collected from the summit position of the field was 10 and 20% less, respectively, than the amounts sorbed to backslope or toeslope soils. Generally, both herbicides had faster mineralization rates and shorter t1/2 in summit than in backslope or toeslope soils. Weed biomass was correlated positively with elevation and total amount of atrazine mineralized, whereas corn biomass was correlated negatively with these parameters. These findings suggest that weed control can be improved by accounting for the landscape positional effects on differential herbicide mineralization and dissipation in fields.

Nomenclature: Alachlor; atrazine; corn, Zea mays L.

Received: June 12, 2001; Accepted: March 5, 2002

Keywords: Precision application, kriging, sorption, dissipation, site-specific management



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Figure 1. Field topography, soil types and locations, and grid point position in a continuous corn (Zea mays L.) field near Brookings, SD

Figure 2. Interpolated map of percentage of atrazine mineralized after an 8-wk laboratory incubation in 1997 across the landscape of a field near Brookings, SD

Figure 3. Interpolated maps of weed biomass collected on August 20, 1997 and June 23, 1998 across the landscape of a field near Brookings, SD

Figure 4. Interpolated maps of corn (Zea mays L.) biomass collected in 1997 and 1998 across the landscape of a field near Brookings, SD

table

Table 1.Soil types present, and the location and physical characteristics of each soil in an eastern South Dakota study site, Brookings, SD, in 1997 and 1998

table

Table 2.Herbicide partition coefficients (Kd), amount of herbicide mineralized after an 8-wk laboratory incubation at 20 C, mineralization rate, and calculated half-life (t1/2) of atrazine and alachlor by topographic position taken in an eastern South Dakota continuous corn (Zea mays L.) field near Brookings, SD, from samples collected in 1997 and 1998. Data from backslope and toeslope soils were similar, and average values for these areas are presented

table

Table 3.Correlation coefficients (r values) of parameters measured in an eastern South Dakota corn (Zea mays L.) field, near Brookings, SD. Data presented are from measurements taken in 1997. Data from 1998 had similar correlations. NC indicates that parameters were not correlated at the P ≤ 0.05 level of significance

table

Table 4.Weed and corn (Zea mays L.) biomass from different topographic positions in 1997 and 1998 from an eastern South Dakota field in continuous corn near Brookings, SD

table

Table 5.The correlation coefficients (r values) of weed and corn (Zea mays L.) biomass with selected parameters for data collected in the same year from an eastern South Dakota field in continuous corn near Brookings, SD. NC indicates that the parameters were not correlated at the P ≤ 0.05 level of significance

table

Table 6.Estimated semivariogram parameters for best-fit isotropic variogram models

Mention of a trade name does not imply an endorsement or recommendation by South Dakota State University.

Aatrex® 4L, Norvartis Crop Protection, Inc., 410 Swing Road, P.O. Box 18300, Greensboro, NC 27419.

Lasso® 4EC, Monsanto Agricultural Company, 700 Chesterfield Parkway North, St. Louis, MO 63167.

Solid-phase C18 cartridge, Alltech Assoc., Inc., 2051 Waukegan Road, Deerfield, IL 60015.

Hewlett Packard gas chromatograph (Model 5890 Series II plus), Hewlett Packard, 2850 Centerville Road, Wilmington, DE 19808.

Analytical grade atrazine and alachlor, Chem Service, P.O. Box 3108, 660 Tower Lane, West Chester, PA 19381.

DB-17 and DB-5 columns, J & W Scientific, 91 Blue Ravine Road, Folson, CA 95630.

14C uniformly ring-labeled atrazine and alachlor, Sigma Chemical Company, P.O. Box 14508, St. Louis, MO 63178.

Ultima Gold, Packard Instrument Company, 800 Research Parkway, Meriden, CT 06450.

Environmental Sciences version 5.03 software, Gamma Design Software, LCC P.O. Box 201, Plainwell, MI 49080.

Cited by

M. Jurado-Expósito, F. López-Granados, J. M. Peña-Barragán, L. García-Torres. (2009) A digital elevation model to aid geostatistical mapping of weeds in sunflower crops. Agronomy for Sustainable Development 29:2, 391-400
Online publication date: 1-May-2009.
CrossRef
Dale L. Shaner, Hamid J. Farahani, Gerald W. Buchleiter. (2008) Predicting and Mapping Herbicide–Soil Partition Coefficients for EPTC, Metribuzin, and Metolachlor on Three Colorado Fields. Weed Science 56:1, 133-139
Online publication date: 1-Jan-2008.

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