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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Agron.</journal-id>
<journal-title>Frontiers in Agronomy</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Agron.</abbrev-journal-title>
<issn pub-type="epub">2673-3218</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fagro.2025.1601328</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Agronomy</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Stakeholder assessment of weed management practices and perceptions of targeted spraying technologies in corn-soybean systems</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ugljic</surname>
<given-names>Zaim</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Mobli</surname>
<given-names>Ahmadreza</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<contrib contrib-type="author">
<name>
<surname>Oliveira</surname>
<given-names>Maxwel  Coura</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<contrib contrib-type="author">
<name>
<surname>Proctor</surname>
<given-names>Christopher A.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Dille</surname>
<given-names>J. Anita</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Werle</surname>
<given-names>Rodrigo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
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<aff id="aff1">
<sup>1</sup>
<institution>Department of Plant and Agroecosystems Sciences, University of Wisconsin-Madison</institution>, <addr-line>Madison, WI</addr-line>,&#xa0;<country>United States</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Agronomy and Horticulture, University of Nebraska-Lincoln</institution>, <addr-line>Lincoln, NE</addr-line>,&#xa0;<country>United States</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Agronomy, Kansas State University</institution>, <addr-line>Manhattan, KS</addr-line>,&#xa0;<country>United States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Simerjeet Virk, Auburn University, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Stephen Christopher Marble, University of Florida, United States</p>
<p>Simerjeet Kaur, Punjab Agricultural University, India</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Rodrigo Werle, <email xlink:href="mailto:rwerle@wisc.edu">rwerle@wisc.edu</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>03</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="ecorrected">
<day>11</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>7</volume>
<elocation-id>1601328</elocation-id>
<history>
<date date-type="received">
<day>27</day>
<month>03</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>05</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Ugljic, Mobli, Oliveira, Proctor, Dille and Werle</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Ugljic, Mobli, Oliveira, Proctor, Dille and Werle</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Understanding regional weed control practices and stakeholder perspectives is essential to guide the development and adoption of novel weed management technologies. This survey aimed to evaluate chemical weed control practices, major weed escapes, and stakeholder perceptions of targeted spraying technologies in corn and soybean cropping systems across the U.S. Midwest.</p>
</sec>
<sec>
<title>Methods</title>
<p>A survey was conducted from fall 2021 to spring 2022 in corn (<italic>Zea mays</italic> L.) and soybean [<italic>Glycine max</italic> (L.) Merr.] cropping systems across the Western U.S. Midwest Region (WUMR: Kansas and Nebraska) and the Eastern U.S. Midwest Region (EUMR: Illinois, Minnesota, and Wisconsin). It assessed currently adopted herbicide programs, end-of-season weed escapes, and awareness of targeted spraying technologies among growers, advisors, and applicators.</p>
</sec>
<sec>
<title>Results</title>
<p>Survey responses (128 participants) indicated that over 50% of growers used a two-pass herbicide application program [preemergence (PRE) followed by postemergence (POST) with layered residual] in soybean and corn across both regions in 2021. The top weed escapes in WUMR corn fields were Palmer amaranth (<italic>Amaranthus palmeri</italic> S.Wats.), waterhemp [<italic>Amaranthus tuberculatus</italic> (Moq.) J.D.Sauer], and foxtail species (<italic>Setaria</italic> spp.), while for soybean fields, Palmer amaranth, waterhemp, and volunteer corn were most common. Conversely, EUMR respondents primarily reported foxtail spp., waterhemp, and giant ragweed (<italic>Ambrosia trifida</italic> L.) escapes in corn and waterhemp, giant ragweed, and volunteer corn in soybean fields. Over 49% of respondents believe that novel targeted spraying technologies could help control late season weed escapes. However, more than 75% are unsure whether these technologies will be adopted in the operations they manage in the future, with 48% indicating the need of more information to support their decision. The survey results showed a greater reliance on commercial applicator services in the EUMR than WUMR, highlighting the potential role of commercial applicators in advancing effective herbicide strategies and targeted spraying technologies adoption while reducing the need for farmers to invest in new equipment within the EUMR region.</p>
</sec>
<sec>
<title>Discussion</title>
<p>This survey highlights substantial opportunities for targeted herbicide application technologies research and outreach education involving regulatory agencies, spray manufacturers, chemical companies, decision influencers, University Extension and other parties.</p>
</sec>
</abstract>
<kwd-group>
<kwd>chemical weed management</kwd>
<kwd>site-specific weed management</kwd>
<kwd>weed management survey</kwd>
<kwd>weed management strategies</kwd>
<kwd>precision agriculture</kwd>
</kwd-group>
<counts>
<fig-count count="11"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="72"/>
<page-count count="14"/>
<word-count count="5282"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Weed Management</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The US Midwest region comprises approximately 51 million agricultural hectares, with 75% of arable area planted with corn and soybean (<xref ref-type="bibr" rid="B62">USDA - NASS, 2024</xref>). Weed interference can reduce corn and soybean yields by 50% and 52%, respectively, in U.S. and Canadian production systems, leading to annual losses exceeding 42 billion U.S. dollars (<xref ref-type="bibr" rid="B54">Soltani et&#xa0;al., 2016</xref>, <xref ref-type="bibr" rid="B55">2017</xref>). Tillage and herbicide application are the primary practices for weed management in the US Midwest region (<xref ref-type="bibr" rid="B25">Dong et&#xa0;al., 2017</xref>). In 2020, over 95% of corn and soybean hectares in the US received at least one herbicide application (<xref ref-type="bibr" rid="B61">USDA - NASS, 2021</xref>). The significant use of herbicides in weed management for corn and soybean production highlights the benefits of chemical weed control for sustaining yield potential (<xref ref-type="bibr" rid="B43">Oerke and Dehne, 2004</xref>; <xref ref-type="bibr" rid="B21">Cooper et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B22">Damalas and Eleftherohorinos, 2011</xref>). Moreover, the use of herbicides provides economic benefits to growers by reducing the need for tillage and other labor and energy intensive weed control strategies (<xref ref-type="bibr" rid="B29">Gianessi, 2013</xref>). However, herbicide off-target movement (<xref ref-type="bibr" rid="B56">Soltani et&#xa0;al., 2020</xref>), environmental contamination (<xref ref-type="bibr" rid="B37">Maroni et&#xa0;al., 2006</xref>), and the growing issue of herbicide resistance (<xref ref-type="bibr" rid="B31">Heap, 2025</xref>) are significant challenges posed to chemical weed control.</p>
<p>Herbicide off-target movement can reduce pesticide efficacy and potentially cause injury to neighboring non-labeled crops, native species, and contaminate surrounding environments (<xref ref-type="bibr" rid="B24">De Snoo and van der Poll, 1999</xref>; <xref ref-type="bibr" rid="B64">Vieira et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B14">Bish et&#xa0;al., 2021</xref>). More precise and efficient herbicide applications are necessary to increase application accuracy and decrease off-target movement, environmental contamination, and public concerns regarding pesticide use in agriculture (<xref ref-type="bibr" rid="B22">Damalas and Eleftherohorinos, 2011</xref>; <xref ref-type="bibr" rid="B53">Sishodia et&#xa0;al., 2020</xref>). <xref ref-type="bibr" rid="B16">Brown et&#xa0;al. (2008)</xref> documented 40% reduction in spray application rate and 44% reduction in runoff with targeted applications when compared to traditional broadcast application methods. Therefore, precision agricultural technologies can have a critical role in reducing herbicide inputs and off-target movement (<xref ref-type="bibr" rid="B42">Myers et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B17">Camargo et&#xa0;al., 2020</xref>).</p>
<p>Site-specific precision agricultural tools such as unmanned aerial vehicle (UAV) systems and targeted spraying technologies can contribute to optimized agrochemical applications (<xref ref-type="bibr" rid="B32">Hunter et&#xa0;al., 2020</xref>). Unmanned aerial vehicles can be used for agrochemical applications when traditional sprayers cannot be employed (e.g., wet conditions) or in areas with limited access (e.g., forestry, around trees, electrical poles) (<xref ref-type="bibr" rid="B47">Qin et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B5">Anonymous, 2023a</xref>). Furthermore, UAVs are being increasingly used in precision agriculture to collect high-resolution remotely sensed data, aiding field management decisions and potentially reducing agrochemical impact on the environment (<xref ref-type="bibr" rid="B23">De Sa et&#xa0;al., 2018</xref>). For instance, <xref ref-type="bibr" rid="B23">De Sa et&#xa0;al. (2018)</xref> reported that early detection of weed infestations using aerial images enables the development of site-specific weed maps for ground sprayers, which can lead to significant herbicide savings. As advancements in precision agriculture continue, targeted spraying technologies are emerging as another innovative tool that leverages site-specific data to optimize agrochemical applications and further enhance their weed management efficiency.</p>
<p>Since the early 1990s, targeted spraying technology for ground sprayers is being developed, initially focusing on fallow applications (green-on-brown) with systems like Trimble WeedSeeker and WeedIt (<xref ref-type="bibr" rid="B4">Anonymous, 2021</xref>; <xref ref-type="bibr" rid="B11">Azghadi et&#xa0;al., 2024</xref>). In recent years, advancements in ground-based sprayer technology have enabled several manufacturers to develop targeted spraying technologies capable of real-time weed detection while differentiating weeds from established crops (green-on-green application) (<xref ref-type="bibr" rid="B38">McCarthy et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B2">Allmendinger et&#xa0;al., 2022</xref>). Ground-based targeted spraying technologies equipped with cameras can distinguish weeds from crops using artificial intelligence (AI)-driven algorithms and powerful computer units (multiple units mounted on the sprayer&#x2019;s boom). These systems can process images within milliseconds, triggering the necessary nozzle(s) to deliver herbicides only where weeds are present, in contrast to traditional broadcast systems (<xref ref-type="bibr" rid="B45">Partel et&#xa0;al., 2019</xref>, <xref ref-type="bibr" rid="B46">2020</xref>; <xref ref-type="bibr" rid="B65">Vijayakumar et&#xa0;al., 2023</xref>; <xref ref-type="bibr" rid="B7">Anonymous, 2024a</xref>). Delivering herbicides only where necessary can significantly reduce the amount of herbicide use and off-target movement in large scale agricultural commodity crops such as corn and soybean (<xref ref-type="bibr" rid="B57">Spaeth et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B10">Avent et&#xa0;al., 2024</xref>). Moreover, these targeted spraying technologies can generate high resolution geo-referenced weed infestation maps within the machine&#x2019;s linked software (for example Xarvio&#x2019;s Field Manager, John Deere&#x2019;s See &amp; Spray Field Analyzer, Greeneye&#x2019;s Selective Spraying System) as soon as application is completed. Such maps can provide useful insight into weed infestation levels across the fields, helping end users make informed management decisions for future growing seasons. Since this is an emerging technology (green-on-green targeted spraying technology for ground sprayers), stakeholder awareness and adoption remain uncertain. Understanding the needs and challenges to adoption among stakeholders (agronomists, growers, crop consultants, and industry representatives) is essential for facilitating the integration of targeted spraying technologies in crops such as corn and soybean across the U.S. Midwest and beyond.</p>
<p>Surveys are essential for gathering information, supporting decision-making processes, and identifying current perceptions. By understanding the needs and challenges of regional agricultural communities, future educational and research initiatives can be better shaped. For example, a Missouri survey demonstrated the importance of pesticide applicators education regarding application of synthetic herbicides (<xref ref-type="bibr" rid="B13">Bish and Bradley, 2017</xref>). Currently, our understanding of the adoption rate and challenges associated with the incorporation of targeted spraying technologies in the U.S. Midwest, particularly in corn and soybean production, is limited. Stakeholder surveys can provide a broader perspective on the community&#x2019;s perceptions regarding adoption of targeted spraying technology. Therefore, the objectives of this survey were (1) to assess current weed management practices, and identify which weeds are escaping current chemical weed control practices and 2) to understand stakeholders&#x2019; perceptions of new targeted spraying technologies and explore challenges and opportunities this technology may face in the future. These insights can support and structure research and extension efforts to better serve US Midwest corn and soybean producers with weed management strategies and anticipated challenges associated with adoption of emerging targeted spraying technologies.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Survey&#x2019;s structure</title>
<p>During the fall of 2021 and spring of 2022, an 18-question survey (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) was designed to (1) document the main chemical weed control strategies utilized and the main end-of-season weed escapes (left uncontrolled due to herbicide-resistance or late emergence) detected in corn and soybean cropping systems across Kansas and Nebraska (WUMR) compared to Illinois, Minnesota, and Wisconsin (EUMR) in the 2021 growing season and to (2) understand stakeholders&#x2019; perceptions of new targeted spraying technologies and explore challenges and opportunities of their adoption. A digital (QualtricsXM; Provo, UT) survey was circulated via the social media platform X (former Twitter) (San Francisco, CA), email listservs, extension websites (e.g., K-State eUpdate, UNL-CropWatch, UW-Madison WiscWeeds.info), and promoted during Extension meetings in Kansas, Nebraska, and Wisconsin. The survey was organized into four sections. The first section (questions 1-4) focused respondent demographics (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). The second (questions 5-9) and third (questions 10-15) sections focused on soybean and corn cropping system practices, respectively. The last section (questions 16-18) was focused on the adoption of and perceptions regarding targeted spraying technologies. The survey questions were designed as fill-in-the-blank, yes/no, and multiple choice. Not all participants answered every survey question (<xref ref-type="bibr" rid="B44">Oliveira et&#xa0;al., 2021</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Survey of Corn-Soybean Weed Management During the 2021&#x2013;2022 Growing Season and Current Stakeholder Perception on Targeted Spraying Technologies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" colspan="2" align="left">Part one: Demographic information</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Q1</td>
<td valign="top" align="left">Name and email (optional). ______________</td>
</tr>
<tr>
<td valign="top" align="left">Q2</td>
<td valign="top" align="left">Describe your main occupation:<break/>&#x2003;a)&#x2003;Farmer<break/>&#x2003;b)&#x2003;Agronomist/Crop Consultant<break/>&#x2003;c)&#x2003;Industry representative<break/>&#x2003;d)&#x2003;Extension/State/Fed Agency<break/>&#x2003;e)&#x2003;Other (please describe)</td>
</tr>
<tr>
<td valign="top" align="left">Q3</td>
<td valign="top" align="left">Which county(ies) and state(s) do you farm/manage crops?______________</td>
</tr>
<tr>
<td valign="top" align="left">Q4</td>
<td valign="top" align="left">How many acres of soybean did you farm/manage in 2021?______________</td>
</tr>
</tbody>
</table>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="left">Part Two: Soybean</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Q5</td>
<td valign="top" align="left">How many herbicide passes did you spray in the soybean fields you farm/manage in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;PRE only (1 pass)<break/>&#x2003;b)&#x2003;PRE followed by POST (2 passes)<break/>&#x2003;c)&#x2003;PRE followed by POST with layered residuals (2 passes)<break/>&#x2003;d)&#x2003;PRE followed by 2 POST applications (3 passes)<break/>&#x2003;e)&#x2003;POST followed by POST (2 passes)<break/>&#x2003;f)&#x2003;POST followed by POST with layered residuals (2 passes)<break/>&#x2003;g)&#x2003;POST with layered residuals followed by POST with layered residuals (2 passes)<break/>&#x2003;h)&#x2003;PRE followed by 2 POST applications with layered residuals (3 passes)<break/>&#x2003;i)&#x2003;POST only (1 pass)<break/>&#x2003;j)&#x2003;Other</td>
</tr>
<tr>
<td valign="top" align="left">Q6</td>
<td valign="top" align="left">What percentage of the soybean acres you farm/manage were sprayed by a commercial applicator service (co-op) in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;0-10%<break/>&#x2003;b)&#x2003;10-20%<break/>&#x2003;c)&#x2003;20-30%<break/>&#x2003;d)&#x2003;30-40%<break/>&#x2003;e)&#x2003;40-50%<break/>&#x2003;f)&#x2003;50-60%<break/>&#x2003;g)&#x2003;60-70%<break/>&#x2003;h)&#x2003;70-80%<break/>&#x2003;i)&#x2003;80-90%<break/>&#x2003;j)&#x2003;90-100%</td>
</tr>
<tr>
<td valign="top" align="left">Q7</td>
<td valign="top" align="left">How satisfied were you with weed control in the soybean fields you farm/manage in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;Very satisfied (excellent weed control)<break/>&#x2003;b)&#x2003;Satisfied (good weed control)<break/>&#x2003;c)&#x2003;Somewhat satisfied (fair weed control)<break/>&#x2003;d)&#x2003;Dissatisfied (poor weed control)<break/>&#x2003;e)&#x2003;Very dissatisfied (very poor weed control)</td>
</tr>
<tr>
<td valign="top" align="left">Q8</td>
<td valign="top" align="left">What was the average chemical weed control cost per hectare (including chemical and application cost) in the soybean fields you farm/manage in 2021?______________</td>
</tr>
<tr>
<td valign="top" align="left">Q9</td>
<td valign="top" align="left">What weeds escaped control in the soybean fields you farm/manage in 2021? Select all that apply:<break/>&#x2003;a)&#x2003;Volunteer corn<break/>&#x2003;b)&#x2003;Waterhemp<break/>&#x2003;c)&#x2003;Palmer amaranth<break/>&#x2003;d)&#x2003;Giant ragweed<break/>&#x2003;e)&#x2003;Velvetleaf<break/>&#x2003;f)&#x2003;Lambsquarters<break/>&#x2003;g)&#x2003;Foxtail species<break/>&#x2003;h)&#x2003;Barnyardgrass<break/>&#x2003;i)&#x2003;Horsweed (aka marestail)<break/>&#x2003;j)&#x2003;None<break/>&#x2003;k)&#x2003;Other (please describe)</td>
</tr>
</tbody>
</table>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="left">Part three: Corn</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Q10</td>
<td valign="top" align="left">How many acres of corn did you farm/manage in 2021?______________</td>
</tr>
<tr>
<td valign="top" align="left">Q11</td>
<td valign="top" align="left">How many herbicide passes did you spray in the corn fields you farm/manage in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;PRE only (1 pass)<break/>&#x2003;b)&#x2003;PRE followed by POST (2 passes)<break/>&#x2003;c)&#x2003;PRE followed by POST with layered residuals (2 passes)<break/>&#x2003;d)&#x2003;PRE followed by 2 POST applications (3 passes)<break/>&#x2003;e)&#x2003;POST followed by POST (2 passes)<break/>&#x2003;f)&#x2003;POST followed by POST with layered residuals (2 passes)<break/>&#x2003;g)&#x2003;POST with layered residuals followed by POST with layered residuals (2 passes)<break/>&#x2003;h)&#x2003;PRE followed by 2 POST applications with layered residuals (3 passes)<break/>&#x2003;i)&#x2003;POST only (1 pass)<break/>&#x2003;j)&#x2003;Other</td>
</tr>
<tr>
<td valign="top" align="left">Q12</td>
<td valign="top" align="left">What percentage of the corn acres you farm/manage were sprayed by a commercial applicator service (co-op) in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;0-10%<break/>&#x2003;b)&#x2003;10-20%<break/>&#x2003;c)&#x2003;20-30%<break/>&#x2003;d)&#x2003;30-40%<break/>&#x2003;e)&#x2003;40-50%<break/>&#x2003;f)&#x2003;50-60%<break/>&#x2003;g)&#x2003;60-70%<break/>&#x2003;h)&#x2003;70-80%<break/>&#x2003;i)&#x2003;80-90%<break/>&#x2003;j)&#x2003;90-100%</td>
</tr>
<tr>
<td valign="top" align="left">Q13</td>
<td valign="top" align="left">How satisfied were you with weed control in the corn fields you farm/manage in 2021? Select the response that best applies:<break/>&#x2003;a)&#x2003;Very satisfied (excellent weed control)<break/>&#x2003;b)&#x2003;Satisfied (good weed control)<break/>&#x2003;c)&#x2003;Somewhat satisfied (fair weed control)<break/>&#x2003;d)&#x2003;Dissatisfied (poor weed control)<break/>&#x2003;e)&#x2003;Very dissatisfied (very poor weed control)</td>
</tr>
<tr>
<td valign="top" align="left">Q14</td>
<td valign="top" align="left">What was the average chemical weed control cost per hectare (including chemical and application cost) in the corn fields you farm/manage in 2021? ______________</td>
</tr>
<tr>
<td valign="top" align="left">Q15</td>
<td valign="top" align="left">What weeds escaped control in the corn fields you farm/manage in 2021? Select all that apply:<break/>&#x2003;a)&#x2003;Volunteer corn<break/>&#x2003;b)&#x2003;Waterhemp<break/>&#x2003;c)&#x2003;Palmer amaranth<break/>&#x2003;d)&#x2003;Giant ragweed<break/>&#x2003;e)&#x2003;Velvetleaf<break/>&#x2003;f)&#x2003;Lambsquarters<break/>&#x2003;g)&#x2003;Foxtail species<break/>&#x2003;h)&#x2003;Barnyardgrass<break/>&#x2003;i)&#x2003;Horsweed (aka marestail)<break/>&#x2003;j)&#x2003;Kochia<break/>&#x2003;k)&#x2003;None<break/>&#x2003;l)&#x2003;Other (please describe)</td>
</tr>
</tbody>
</table>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="left">Part four: Novel targeted spraying technologies</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Q16</td>
<td valign="top" align="left">Are you familiar with targeted spraying technologies (e.g., Seek &amp; Spray systems, Drone-Mounted Weed Sensors, and Sprayers)?<break/>&#x2003;a)&#x2003;Yes<break/>&#x2003;b)&#x2003;No</td>
</tr>
<tr>
<td valign="top" align="left">Q17</td>
<td valign="top" align="left">Do you foresee targeted spraying technologies being adopted in the hectares you farm/manage in the near future?<break/>&#x2003;a)&#x2003;Yes<break/>&#x2003;b)&#x2003;No<break/>&#x2003;c)&#x2003;Not sure (need more information)</td>
</tr>
<tr>
<td valign="top" align="left">Q18</td>
<td valign="top" align="left">How do you foresee targeted spraying technologies being adopted in corn and soybean production fields in the near future?<break/>&#x2003;a)&#x2003;As a part of all herbicide applications<break/>&#x2003;b)&#x2003;As part of burndown (pre-plant/pre-emergence) herbicide applications<break/>&#x2003;c)&#x2003;As part of POST herbicide applications<break/>&#x2003;d)&#x2003;For control of late season weed escapes<break/>&#x2003;e)&#x2003;Not sure (need more information)<break/>&#x2003;f)&#x2003;Other (please describe)</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Data analysis</title>
<p>All results were exported from Qualtrics into a Microsoft Excel (Microsoft Office, Redmond, WA) spreadsheet, with responses to each question organized in separate columns. Survey data were sorted and analyzed in Microsoft Excel using the &#x201c;count,&#x201d; &#x201c;filter,&#x201d; and &#x201c;sort&#x201d; functions (<xref ref-type="bibr" rid="B67">Werle et&#xa0;al., 2018</xref>). Data visualization was performed using the <italic>tidyverse</italic> (<xref ref-type="bibr" rid="B69">Wickham et&#xa0;al., 2019</xref>) and <italic>ggplot2</italic> (<xref ref-type="bibr" rid="B68">Wickham, 2016</xref>) packages in the R statistical software (<xref ref-type="bibr" rid="B48">R Development Core Team, 2024</xref>). For most questions, results were presented as the percentage of respondents selecting each answer choice (<xref ref-type="bibr" rid="B67">Werle et&#xa0;al., 2018</xref>). The respondents&#x2019; familiarity with targeted spraying technologies (ground-based sprayers) and their perspectives on the likelihood of adopting these technologies on the hectares they farm or manage in the future (binary response: Yes/No) were reported.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results and discussion</title>
<sec id="s3_1">
<label>3.1</label>
<title>Response rate and stakeholder composition</title>
<p>A total of 128 respondents participated in the survey (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Of these, 26% (n=33) were from the WUMR and 74% (n=95) were from the EUMR. In the WUMR, 33% of respondents identified as farmers, 21% as agronomists, and 21% as crop consultants, while in the EUMR, 24% of respondents identified as farmers, 30% as agronomists, and 29% as crop consultants. Industry representatives accounted for 16% of respondents in the WUMR and 11% in the EUMR.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Q2-Describe your main occupation. Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g001.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Area farmed or managed</title>
<p>In 2021, survey respondents farmed or managed a total of 217,000 hectares of soybean and 318,000 hectares of corn (Question 4). Of the soybean hectares, WUMR accounted for 47,000 hectares, representing 1% of soybean hectares in Nebraska and Kansas, while EUMR covered 170,000 hectares, representing 2% of Soybean hectares in Illinois, Minnesota and Wisconsin (<xref ref-type="bibr" rid="B7">Anonymous, 2024a</xref>; <xref ref-type="bibr" rid="B62">USDA - NASS, 2024</xref>). For corn, WUMR accounted for 42,000 hectares, representing 1% of corn hectares in Nebraska and Kansas, while EUMR covered 276,000 hectares, representing 3% of corn hectares in Illinois, Minnesota and Wisconsin (<xref ref-type="bibr" rid="B7">Anonymous, 2024a</xref>; <xref ref-type="bibr" rid="B62">USDA - NASS, 2024</xref>).</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Soybean herbicide strategies, operations and weed control satisfaction</title>
<p>According to survey respondents, 52% of soybean producers in the WUMR and 50% in the EUMR utilized the two-pass program (PRE followed by POST) with layered residuals in 2021 (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Additionally, 26% of soybean growers in the WUMR and 11% in the EUMR utilized the two-pass program without the layered residual approach. In both regions, only 4% of respondents utilized a one-pass program in soybean production systems. Therefore, two pass herbicide programs are common practice in both regions.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>How many herbicide passes did you spray in the soybean fields you farm/manage in 2021?</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="3" align="left">Herbicide program <xref ref-type="table-fn" rid="fnT2_1">
<sup>a</sup>
</xref>
</th>
<th valign="top" colspan="2" align="center">Region</th>
</tr>
<tr>
<th valign="top" align="center">WUMR</th>
<th valign="top" align="center">EUMR</th>
</tr>
<tr>
<th valign="top" colspan="2" align="center">%</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">POST only (1 pass)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb POST with residual</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">52</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb POST</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">26</td>
</tr>
<tr>
<td valign="top" align="left">POST fb POST</td>
<td valign="top" align="center"/>
<td valign="top" align="center">3</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb 2 POST with residual</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td valign="top" align="left">POST with residual fb POST with residual</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td valign="top" align="left">POST with residual fb POST</td>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb 2 POST</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">PRE only (1 pass)</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">6</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="fnT2_1">
<label>a</label>
<p>Total number of respondents, n= 88 (WUMR n=18; EUMR n=70).</p>
</fn>
<fn>
<p>Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</fn>
<fn>
<p>Select the response that best applies.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In WUMR, most soybean growers (54%) depend on commercial applicator services for 0 to 10% of their hectares, while 12% heavily depend on commercial application services for 91 to 100% of their managed hectares (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). In the EUMR, 32% of soybean growers rely on commercial applicator services for herbicide applications on 0 to10% of their managed hectares, while 21% depend on commercial applicator services for 91 to 100% of their managed hectares (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). Commercial applicator services play a crucial role in supporting farmers by investing in large scale equipment, providing expert advice and a variety of herbicide offerings, and integrating digital management tools (<xref ref-type="bibr" rid="B8">Anonymous, 2024b</xref>). The greater reliance on commercial applicator services in the EUMR highlights their important role in fostering the adoption of more cost-effective herbicide strategies and potentially impacting the implementation of targeted spraying technologies across a larger portion of farming operations, reducing the need for farmers to invest in new equipment.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Q6-What percentage of the soybean acres you farm/manage were sprayed by a commercial applicator service (co-op) in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g002.tif"/>
</fig>
<p>In the WUMR, 32% of respondents reported being very satisfied (excellent weed control) with the performance of their weed control program (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Furthermore, 48% indicated they were satisfied (good weed control), while 12% were somewhat satisfied (fair weed control). In the EUMR, 25% of respondents reported being very satisfied, 55% were satisfied, and 15% were somewhat satisfied with their weed control program. Most respondents in both regions reported utilizing the two-pass program in soybean, a practice aligned with research recommendations to achieve effective (&gt;90%) season long control of herbicide-resistant weeds such as Palmer amaranth (<xref ref-type="bibr" rid="B35">Kumar et&#xa0;al., 2021</xref>), waterhemp (<xref ref-type="bibr" rid="B26">Duenk et&#xa0;al., 2023a</xref>), horseweed (<italic>Erigeron canadensis</italic> L.) (<xref ref-type="bibr" rid="B27">Duenk et&#xa0;al., 2023b</xref>), and giant ragweed (<xref ref-type="bibr" rid="B58">Striegel et&#xa0;al, 2021</xref>; <xref ref-type="bibr" rid="B40">Mobli et&#xa0;al., 2025</xref>). However, growers should prioritize adopting a diverse and integrated weed management program to ensure sustainability and prolong the effectiveness of available herbicide options.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Q7- How satisfied were you with weed control in the soybean fields you farm/manage in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g003.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Cost of herbicide application in soybeans</title>
<p>In 2021, soybean producers reported chemical weed control costs (including chemical and application cost) ranging from $55 to $100 per hectare in the WUMR and from $31 to $70 per hectare in the EUMR, depending on their herbicide program strategies (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). In the WUMR, a two-pass herbicide program with layered residual herbicides costed an average of $66 per hectare, compared to $55 per hectare for a two-pass program without residual herbicides. Similarly, in the EUMR, soybean producers spent an average of $45 per hectare for a two-pass herbicide program with layered residual herbicides, compared to $58 per hectare for a program without residual herbicides in 2021. The cost of chemical weed control in soybean production can vary widely depending on the selected herbicide program, application rate, application technology, and the demographic and density of the weed community (<xref ref-type="bibr" rid="B39">Meseld&#x17e;ija et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B35">Kumar et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B66">Vishwakarma et&#xa0;al., 2023</xref>; <xref ref-type="bibr" rid="B10">Avent et&#xa0;al., 2024</xref>). Moreover, the presence of herbicide-resistant weed species, combined with adverse environmental interactions that reduce herbicide efficacy (<xref ref-type="bibr" rid="B71">Yu and Powles, 2014</xref>; <xref ref-type="bibr" rid="B36">Landau et&#xa0;al., 2024</xref>), can further increase these costs. Developing effective herbicide strategies requires balancing economic feasibility with the goals of achieving effective weed control.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Q8 What was the average chemical weed control cost per hectare (including chemical and application cost) in the soybean fields you farm/manage in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g004.tif"/>
</fig>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Weed escapes in soybean fields</title>
<p>In the WUMR, the most dominant weed species that escaped weed management practices in soybean fields were Palmer amaranth, waterhemp, volunteer corn, and velvetleaf (<italic>Abutilon theophrasti</italic> Medik) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>). In the EUMR, the dominant weed species that escaped herbicide control included waterhemp, giant ragweed, volunteer corn, velvetleaf, and horseweed. Palmer amaranth, waterhemp, giant ragweed, velvetleaf, and horseweed are consistently recognized as major threats to soybean production across the Midwest (<xref ref-type="bibr" rid="B70">WSSA, 2017</xref>; <xref ref-type="bibr" rid="B9">Arsenijevic et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B20">Chudzik et&#xa0;al., 2024</xref>) due to their rapid growth, high seed production, and resistance to multiple herbicide modes of action (<xref ref-type="bibr" rid="B30">Harrison et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B51">Shrestha et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B9">Arsenijevic et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B31">Heap, 2025</xref>). Likewise, volunteer corn, often underestimated as a weed in soybean fields (<xref ref-type="bibr" rid="B18">Chahal and Jhala, 2015</xref>; <xref ref-type="bibr" rid="B3">Alms et&#xa0;al., 2016</xref>), has been shown to cause yield losses of up to 40% at low densities with maximum yield loss reaching 71%, highlighting its competitiveness similar to many common Midwestern weed species (<xref ref-type="bibr" rid="B3">Alms et&#xa0;al., 2016</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Q9-What weeds escaped control in the soybean fields you farm/manage in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g005.tif"/>
</fig>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Corn herbicide strategies, operations and weed control satisfaction</title>
<p>In the WUMR, the PRE followed by (fb) POST without layered residual herbicides (45%) and the PRE fb POST with layered residual herbicides (36%) were the most dominant herbicide strategies in corn production systems (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). In contrast, in the EUMR, commonly used herbicide strategies included POST-only (20%), PRE fb POST with layered residual herbicides (25%), PRE fb POST without layered residual herbicides (25%), and PRE-only (22%). Selecting effective herbicide strategies is critical for corn growers. While a single pass herbicide strategy is still common in the EUMR, recent research recommends two-pass herbicide strategies as the most effective and reliable option for achieving consistent, end-of-season weed control, regardless of weed species composition or environmental conditions (<xref ref-type="bibr" rid="B41">Mobli et&#xa0;al., 2023</xref>, <xref ref-type="bibr" rid="B40">2025</xref>). However, a one-pass herbicide strategy may still be effective for managing specific weed communities with low densities in conventional tillage corn production (<xref ref-type="bibr" rid="B40">Mobli et&#xa0;al., 2025</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Q12 How many herbicide passes did you spray in the corn fields you farm/manage in 2021?</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="3" align="left">Herbicide program <xref ref-type="table-fn" rid="fnT2_1">
<sup>a</sup>
</xref>
</th>
<th valign="top" colspan="2" align="center">Region</th>
</tr>
<tr>
<th valign="top" align="center">WUMR</th>
<th valign="top" align="center">EUMR</th>
</tr>
<tr>
<th valign="top" colspan="2" align="center">%</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">POST only (1 pass)</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">20</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb POST with residual</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">25</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb POST</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">25</td>
</tr>
<tr>
<td valign="top" align="left">POST fb POST</td>
<td valign="top" align="center"/>
<td valign="top" align="center">3</td>
</tr>
<tr>
<td valign="top" align="left">PRE fb 2 POST with residual (3 pass)</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">POST with residual fb POST with residual</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">POST with residual fb POST</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">PRE fb 2 POST</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">PRE only</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center"/>
<td valign="top" align="center">4</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="fnT3_1">
<label>a</label>
<p>Total number of respondents, n= 98 (WUMR n=22; EUMR n=76).</p>
</fn>
<fn>
<p>Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</fn>
<fn>
<p>Select the response that best applies.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In the WUMR, most corn growers (64%) relied on commercial applicator services for 0 to 10% of their land, while 9% were highly dependent on commercial applicator services for 91 to 100% of their managed hectares (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). In contrast, in the EUMR, reliance on commercial applicator services varied among corn growers, with 36% dependent on commercial applicator services for 0 to 10% of their land and over 30% relied on commercial applicator services for herbicide applications on 50 to 100% of their hectares. This highlights the significant dependence of EUMR producers on commercial applicator services, underscoring the need for specialized support to address logistical challenges that impact profitability and increase operational costs.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Q12-What percentage of the corn acres you farm/manage were sprayed by a commercial applicator service (co-op) in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g006.tif"/>
</fig>
<p>In the WUMR, 36% of respondents were very satisfied with their weed control program, while 45% were satisfied, and 18% reported they were somewhat satisfied (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). In the EUMR, 25% of respondents were very satisfied, 64% were satisfied, and 11% reported they were somewhat satisfied with their weed control program.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Q13-How satisfied were you with weed control in the corn fields you farm/manage in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g007.tif"/>
</fig>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Cost of herbicide application in corn</title>
<p>In 2021, corn producers estimated chemical weed control costs (including chemical and application cost) ranging from $54 to $61 per hectare in the WUMR and from $20 to $70 per hectare in the EUMR, depending on their herbicide application strategies (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). In the WUMR, a PRE fb POST application with layered residuals costed an average of $61 per hectare, compared to $57 per hectare for a two-pass herbicide program without layered residuals on average. In the EUMR, the average cost of a PRE fb POST program with layered residuals was $43 per hectare, while a two-pass program without residuals costed an average of $45 per hectare. Additionally, in the EUMR, the average cost of a one-pass PRE was $32 per hectare, compared to $39 per hectare for a one-pass POST. Herbicides remain the most common tools for weed management in corn and soybean production systems in US Midwest (<xref ref-type="bibr" rid="B25">Dong et&#xa0;al., 2017</xref>) however higher herbicide costs and lower commodity prices can greatly affect growers&#x2019; production profitability margins (<xref ref-type="bibr" rid="B6">Anonymous, 2023b</xref>).</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Q14-What was the average chemical weed control cost per hectare (including chemical and application cost) in the corn fields you farm/manage? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g008.tif"/>
</fig>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>Weed escapes in corn fields</title>
<p>The most common weed species that escaped herbicide control in the WUMR were Palmer amaranth, waterhemp, and foxtail species (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9</bold>
</xref>). In contrast, in the EUMR, the predominant weed species that escaped herbicide control were foxtail species, waterhemp, giant ragweed, and barnyardgrass. Weeds in corn can escape control due to factors such as herbicide resistance (<xref ref-type="bibr" rid="B49">Recker et&#xa0;al., 2015</xref>), poorly timed weed management practices, and adverse interactions between these practices and environmental conditions (<xref ref-type="bibr" rid="B50">Scursoni et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B33">Johnson et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B34">Kr&#xe4;hmer, 2016</xref>). Even if escaped weed species were to have minimal impact on crop yields, their seed production poses a significant concern by replenishing the soil seedbank and intensifying future weed challenges (<xref ref-type="bibr" rid="B12">Bagavathiannan and Norsworthy, 2012</xref>). Moreover, identifying escaped weeds is critical for developing effective weed management programs, as it offers valuable insights into missed weed management opportunities by current strategies.</p>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Q15- What weeds escaped control in the corn fields you farm/manage in 2021? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g009.tif"/>
</fig>
</sec>
<sec id="s3_9">
<label>3.9</label>
<title>Familiarity and perspective of growers on targeted spraying technologies</title>
<p>Most respondents in the WUMR (65%) and EUMR (68%) were familiar with targeted spraying technologies (Question 16). In the WUMR, 48% of respondents did not consider adoption of targeted spraying technologies a viable option and another 48% were unsure or indicated they needed more information about these technologies before considering their use (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10</bold>
</xref>), and only 2% of respondents in the WUMR anticipated adopting targeted spraying technologies for herbicide application in their future operations. In contrast, 17% of respondents in the EUMR anticipated adopting targeted spraying technologies for their herbicide application in future operations, though 31% of respondents did not consider targeted spraying technologies a viable option for adoption and another 53% were unsure or indicated they would need more information before considering their use.</p>
<fig id="f10" position="float">
<label>Figure&#xa0;10</label>
<caption>
<p>Q17- Do you foresee targeted spraying technologies being adopted in the hectares you farm/manage in the near future? Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g010.tif"/>
</fig>
<p>Nine percent of respondents in the WUMR and 6% in the EUMR anticipated targeted spraying technologies being adopted as part of all herbicide applications (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11</bold>
</xref>). The majority of respondents from the WUMR (57%) and the EUMR (49%) anticipated targeted spraying technologies being utilized for controlling late season weed escapes. However, current targeted spraying technologies face challenges in detecting weeds later in the season due to the advanced growth stages of both crops and weeds (<xref ref-type="bibr" rid="B1">Adhinata and Sumiharto, 2024</xref>). Moreover, escaped weeds in advanced growth stages late season are typically less susceptible to herbicides (<xref ref-type="bibr" rid="B15">Blackshaw and Harker, 1996</xref>; <xref ref-type="bibr" rid="B19">Chauhan and Abugho, 2012</xref>). Therefore, the adoption of this technology for controlling late season weed escapes may not be the most effective approach for its use thus further research is warranted. The survey results highlighted a critical need to raise awareness about targeted spraying technologies and increase understanding of their effectiveness across various application timings, with the goal of supporting best management practices for adoption of this emerging technology.</p>
<fig id="f11" position="float">
<label>Figure&#xa0;11</label>
<caption>
<p>Q18- How do you foresee targeted spraying technologies being adopted in corn and soybean production fields in the near future. Western U.S. Midwest Region (WUMR) = Kansas and Nebraska, and Eastern U.S. Midwest Region (EUMR) = Illinois, Minnesota, and Wisconsin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fagro-07-1601328-g011.tif"/>
</fig>
<p>Among respondents, 13% in the WUMR and 19% in the EUMR anticipated adopting targeted spraying technologies exclusively as part of POST herbicide applications (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11</bold>
</xref>). Targeted sprayers equipped with green-on-green technology hold significant potential as an alternative to traditional POST applications. However, previous studies have demonstrated that under high weed densities, targeted spraying technologies function similarly to traditional broadcast systems, diminishing the benefit of targeted applications (<xref ref-type="bibr" rid="B60">Ugljic et&#xa0;al., 2024</xref>). Moreover, in the presence of troublesome weed species such as giant ragweed, at a high density, a single POST application showed the lack of effective weed control (<xref ref-type="bibr" rid="B40">Mobli et&#xa0;al., 2025</xref>). A robust PRE herbicide program can reduce weed populations throughout the growing season (<xref ref-type="bibr" rid="B59">Trolove et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B52">Silva et&#xa0;al., 2023</xref>) and enhance the effectiveness of POST herbicide applications with targeted spraying technologies.</p>
<p>The current survey revealed that most respondents utilized a two-pass herbicide program; however, problematic and common weeds such as Palmer amaranth, waterhemp, giant ragweed, foxtail species, and volunteer corn were reported to escape control. Eighty and 81% of soybean and corn growers in both regions reported satisfaction with their current weed management practices. Satisfactorily season-long chemical control depends on multiple factors, including environmental conditions, herbicide options, application strategies, operational costs, and the composition of the weed community (<xref ref-type="bibr" rid="B63">Varanasi et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B72">Zhao et&#xa0;al., 2017</xref>). To be widely adopted, novel targeted application technologies will likely need to provide at least equal, if not better, end-of-season weed control and economic return compared to standard broadcast applications. The integration of targeted application technologies as part of POST programs provides a unique opportunity for growers and applicators to apply robust rates of labeled foliar herbicides and herbicide mixtures that would be deemed unacceptable from a crop response and/or economic standpoint, while potentially enhancing weed control, thus grower satisfaction. Moreover, the recent updates regarding Endangered Species Act (<xref ref-type="bibr" rid="B28">EPA, 2024</xref>) will impose stricter runoff mitigation and spray drift reduction requirements for herbicides being registered and reregistered. In this context, adopting targeted spraying technologies offers a potential solution to reduce foliar herbicide use, herbicide off-target movement, herbicide runoff, and potential input costs (<xref ref-type="bibr" rid="B16">Brown et&#xa0;al., 2008</xref>). In addition, integrating non-chemical weed management strategies into corn and soybean programs should not be overlooked, as most Midwest farmers rely heavily on chemical control.</p>
<p>This survey highlights the importance of understanding growers&#x2019; perspectives in implementing targeted spraying technologies as part of effective weed management strategies for corn and soybean production that can either maintain or improve weed control satisfaction and reduce the number of weed escapes. Research priorities identified through the survey highlight the need to raise awareness about the efficacy of targeted spraying technologies in detecting and controlling weeds, ideal application timings, overall herbicide use, and technology and application costs. A common comment provided by participants at the end of the survey was regarding best management practices for the use of soil residual herbicides as part of POST applications where target application technologies are used, which warrants future research. Insights from surveys like this are invaluable for guiding research efforts and advancing innovative weed management strategies and Extension outreach initiatives that benefit corn and soybean farmers across the Midwest and beyond.</p>
</sec>
</sec>
</body>
<back>
<sec id="s4" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s5" sec-type="author-contributions">
<title>Author contributions</title>
<p>ZU: Writing &#x2013; original draft, Resources, Data curation. AM:&#xa0;Writing &#x2013; review &amp; editing, Investigation. MO: Investigation, Formal&#xa0;analysis, Visualization, Writing &#x2013; review &amp; editing. CP:&#xa0;Supervision, Writing &#x2013; review &amp; editing, Data curation, Methodology, Conceptualization. JD: Data curation, Methodology, Conceptualization, Supervision, Writing &#x2013; review &amp; editing. RW: Conceptualization, Funding acquisition, Data curation, Project administration, Supervision, Writing &#x2013; review &amp; editing, Methodology.</p>
</sec>
<sec id="s6" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. We thank the National Corn Growers Association (Grant No. MSN254842) and the North Central Soybean Research Program (Grant Nos. MSN266309 and MSN280182) for supporting this project. We also thank BASF Xarvio Digital Farming Solutions (Grant No. MSN258155) for partially sponsoring Zaim Ugljic's graduate research assistantship. BASF Xarvio Digital Farming Solutions was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We thank all survey respondents for taking the time to share valuable insights into their weed management practices in their respective regions.</p>
</ack>
<sec id="s7" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The reviewer SK declared a past co-authorship with the author(s) RW to the handling editor.</p>
<p>The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p>
</sec>
<sec id="s8" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s9">
<title>Correction note</title>
<p>This article has been corrected with minor changes. These changes do not impact the scientific content of the article.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<fn-group>
<title>Abbreviations</title>
<fn fn-type="abbr">
<p>barnyardgrass, <italic>Echinochloa crus-galli</italic> L. P. Beauv.; common cocklebur, <italic>Xanthium strumarium</italic> L.; common lambsquarters, <italic>Chenopodium album</italic> L.; common purslane, <italic>Portulaca oleracea</italic> L.; common ragweed, <italic>Ambrosia artemisiifolia</italic> L.; corn, <italic>Zea mays</italic> L.; fall panicum, <italic>Panicum dichotomiflorum</italic> Michx.; field bindweed, <italic>Convolvulus arvensis</italic> L.; giant foxtail, <italic>Setaria faberi</italic> Herrm.; giant ragweed, <italic>Ambrosia trifida</italic> L; horsenettle, <italic>Solanum carolinense</italic> L.; horseweed, <italic>Erigeron canadensis</italic> L.; johnsongrass, <italic>Sorghum halepense</italic> L. Pers; kochia, <italic>Bassia scoparia</italic> L.; large crabgrass, <italic>Digitaria sanguinalis</italic> L. Scop.; Palmer amaranth, <italic>Amaranthus palmeri</italic> S. Wats.; soybean, <italic>Glycine max</italic> L. Merr.; velvetleaf, <italic>Abutilon theophrasti</italic> Medik.; waterhemp, <italic>Amaranthus tuberculatus</italic> [Moq.] J.D. Sauer; yellow nutsedge, <italic>Cyperus esculentus</italic> L.</p>
</fn>
</fn-group>
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