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Optimizing metribuzin rates for herbicide-resistant Amaranthus weed control in soybean

Published online by Cambridge University Press:  22 September 2025

Rishabh Singh
Affiliation:
Graduate Research Assistant, Department of Agronomy, Kansas State University, Manhattan, KS, USA
Aaron Hager
Affiliation:
Professor, Department of Crop Sciences, University of Illinois, Urbana, IL, USA
Sarah Lancaster
Affiliation:
Assistant Professor, Department of Agronomy, Kansas State University, Manhattan, KS, USA
Jason K. Norsworthy
Affiliation:
Distinguished Professor, Department of Crop, Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Karla Gage
Affiliation:
Associate Professor, School of Agricultural Sciences, Southern Illinois University, Carbondale, IL, USA
William Johnson
Affiliation:
Professor, Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA
Bryan Young
Affiliation:
Professor, Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA
Daniel Stephenson
Affiliation:
Professor, Dean Lee Research and Extension Center, Louisiana State University, Alexandria, LA, USA
Jason Bond
Affiliation:
Professor, Delta Research and Extension Center, Mississippi State University, Stoneville, MS, USA
Kevin Bradley
Affiliation:
Professor, Division of Plant Science and Technology, University of Missouri, Columbia, MO, USA
Amit Jhala
Affiliation:
Professor, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
Alyssa Essman
Affiliation:
Assistant Professor, Department of Horticulture and Crop Science, The Ohio State University, Columbus, OH, USA
Lawrence E. Steckel
Affiliation:
Professor, Department of Plant Science, University of Tennessee, Knoxville, TN, USA
Thomas C. Mueller
Affiliation:
Professor, Department of Plant Science, University of Tennessee, Knoxville, TN, USA
Christy Sprague
Affiliation:
Professor, Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
Travis Legleiter
Affiliation:
Associate Professor, Department of Plant and Soil Sciences, University of Kentucky, Lexington, KY, USA
Rodrigo Werle
Affiliation:
Associate Professor, Department of Plant and Agroecosystem Sciences, University of Wisconsin-Madison, Madison, WI, USA
Joseph Ikley
Affiliation:
Associate Professor, Department of Plant Sciences, North Dakota State University, Fargo, ND, USA
Prashant Jha
Affiliation:
Professor, School of Plant, Environmental and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA
Mithila Jugulam*
Affiliation:
Professor and Center Director, Texas A&M University, Beaumont, TX, USA
*
Corresponding author: Mithila Jugulam; Email: m.jugulam@ag.tamu.edu
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Abstract

Palmer amaranth and waterhemp are troublesome weeds in U.S. corn, soybean, and cotton production systems. Rapid evolution of resistance to herbicide from multiple sites of action in these species warrant alternate weed control options. Metribuzin applied preemergence can provide effective control of herbicide-resistant Amaranthus species. However, despite its decades of efficacy, many growers remain unaware of its weed control potential or are hesitant to use it due to concerns over crop injury. Field experiments were conducted in 2022 and 2023 in 15 states across the United States to investigate residual control of Palmer amaranth and waterhemp with metribuzin applied preemergence to soybean. Sites had either herbicide-resistant Palmer amaranth or waterhemp as the dominant weed species. Seventeen preemergence treatments were evaluated, including 13 doses of metribuzin (210 to 841 g ai ha-1), a dose of sulfentrazone (420 g ai ha-1), and a dose of S-metolachlor (1,790 g ai ha-1), along with nontreated and a weed-free control plots. Weed control and soybean injury were visually assessed and recorded at 14, 28, and 42 d after application (DAA) of preemergence herbicides. Additionally, weed density, weed biomass, and soybean height were recorded 28 DAA followed by a measure of soybean yield at maturity. Weed control was analyzed as a function of metribuzin dose and environmental factors using a generalized additive model. Crop injury of not more than 5% was predicted even with 841 g ai ha-1 of metribuzin. Metribuzin at 630 g ai ha-1 was more effective than sulfentrazone in delaying weed emergence and reducing weed density, while 315 g ai ha-1 of metribuzin outperformed S-metolachlor in both metrics. Metribuzin doses of 578 to 841 g ai ha-1 provided greater than 95%, 90%, and 80% weed control, respectively, at 14, 28, and 42 DAA. Higher metribuzin doses of 578 to 841 g ai ha-1could be safely to effectively control herbicide-resistant Amaranthus weeds.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Weed Science Society of America
Figure 0

Table 1. Management practices for 32 site-years included in this study.a

Figure 1

Table 2. Soil characteristics and precipitation records across 27 site-years.a

Figure 2

Table 3. Herbicide treatments applied before soybean emergence.

Figure 3

Figure 1. Principal component biplot for soil texture (sand, silt and clay), soil organic matter (OM), soil temperature at herbicide application, soil moisture, soil pH, precipitation interval after herbicide application (interval of first precipitation), amount of first precipitation, interval for cumulative 12.7 mm precipitation, and cumulative precipitation 42 d after application for all site-years. Site-years are represented by state location followed by experimental year: Arkansas (AR'22, AR'23), Illinois (IL'23, SIL'22, SIL'23), Indiana (IN'22, IN'23), Kansas (KS'22, KS'23), Kentucky (KY'22, KY'23), Louisiana (LA'22), Michigan (MI'22, MI'23), Missouri (MO'22, MO'23), Nebraska (NE'22, NE'23), North Dakota (ND'22, ND'23), Ohio (OH'22, OH'23), Tennessee (TN'22, TN'23) and Wisconsin (WI'22, WI'23).

Figure 4

Figure 2. Variable importance plot for covariates determining weed control based on random forest model for all site-years except Illinois 2023 and Michigan 2023. Abbreviations: DAA, days after application of herbicide; OM, organic matter.

Figure 5

Table 4. Estimated parameter values of the generalized additive model for weed control as a function of predicting variables for all site-years except Illinois 2023 and Michigan 2023.a

Figure 6

Figure 3. Soybean injury and Amaranthus weed control across metribuzin doses at 14, 28, and 42 d after application (DAA) for all site-years except Illinois 2023 and Michigan 2023. The shaded area around the regression line indicates the 95% confidence interval. The dotted black line represents 5% crop injury levels, and the dotted purple lines represent 100%, 95%, 90%, and 85% weed control, respectively. Each dot represents an individual weed control data point across treatments.

Figure 7

Table 5. Percent weed control estimates as a function of herbicide treatment for all site-years except Illinois 2023 and Michigan 2023.a,b

Figure 8

Figure 4. Amaranthus weed control across metribuzin doses at 14, 28, and 42 d after application (DAA) at the Illinois 2023 and Michigan 2023 site-years. The shaded area around the regression line indicates the 95% confidence interval. The dotted purple lines represent 100%, 90%, and 80% weed control, respectively. Each dot represents an individual weed control data point across treatments.

Figure 9

Table 6. Percent weed control estimates as a function of herbicide treatment for Illinois 2023 and Michigan 2023 site-yearsa,b.

Figure 10

Figure 5. Amaranthus weed emergence from 9 site-years across metribuzin doses. The regression line represents weed emergence as a function of metribuzin dose. The shaded area around the line indicates the 95% confidence interval. The dashed lines represent mean weed emergence for sulfentrazone (S; 27 d after planting), and S-metolachlor (M; 20 d after planting). Each dot represents an individual weed emergence data collection point.

Figure 11

Figure 6. Amaranthus weed density from 20 site-years across metribuzin doses 28 d after application. The regression line represents weed density as a function of metribuzin dose. The shaded area around the line indicates the 95% confidence interval. The dashed lines represent mean weed density for sulfentrazone (S; 21 plants) and S-metolachlor (M; 66 plants). Each dot represents an individual weed density data collection point.

Figure 12

Figure 7. Amaranthus weed biomass from 16 site-years across metribuzin doses 28 d after application. The regression line represents weed biomass as a function of metribuzin dose. The shaded area around the line indicates the 95% confidence interval. The dashed lines represent mean weed biomass for sulfentrazone (S; 6 g) and S-metolachlor (M; 9 g). Each dot represents an individual weed biomass data collection point.

Figure 13

Table 7. Percent crop injury estimated as a function of herbicide treatment for all site-years except Illinois 2023 and Michigan 2023a,b.

Figure 14

Figure 8. Soybean height from 20 site-years across herbicide treatment 28 d after application. Each dot represents an average soybean height data point. The boxes represent the 25th to 75th percentiles of interquartile ranges with the horizontal line inside each box indicating the median yield. The whiskers extend to the smallest and largest values within 1.5 times the interquartile range. Abbreviations: M, S-metolachlor; ns, no significant differences (identified by separation of means using Tukey’s honestly significant difference test; α = 0.05); NT, nontreated; S, sulfentrazone; WF, weed-free.

Figure 15

Figure 9. Soybean yield from 7 site-years plotted with herbicide treatment. Lowercase letters represent significant differences identified by separation of means using Tukey’s honestly significant difference test (α = 0.05). Each dot represents an individual soybean yield data point. The boxes represent 25th to 75th percentiles of interquartile ranges with the horizontal line inside each box indicating the median yield. The whiskers extend to the smallest and largest values within 1.5 times the interquartile range. Abbreviations: M, S-metolachlor; NT, nontreated; S, sulfentrazone; WF, weed-free.

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