A ROBUST DECISION SUPPORT TOOL FOR PROMOTING HERBICIDE RESISTANCE BEST MANAGEMENT PRACTICES

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1022783
• Grant No.: 2020-68008-31461
• Cumulative Award Amt.: $299,977.00
• Proposal No.: 2019-07060
• Project Start Date: Jun 15, 2020
• Project End Date: Jun 14, 2024
• Grant Year: 2020
• Program Code: [A1701]- Critical Agricultural Research and Extension: CARE

Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001

Performing Department
Soil & Crop Sciences

Non Technical Summary
Problem and BackgroundHerbicides remain the cornerstone of effective weed management in broad-acre farming, but over-reliance on few herbicide options has resulted in the evolution of herbicide-resistant weeds. In the southern US, herbicide-resistant weeds have become a critical crop production challenge in recent times (Riar et al. 2013a). Multiple resistance to more than one herbicide site of action (SOA) is particularly a growing concern in the region. Palmer amaranth (Amaranthus palmeri S. Wats.) and waterhemp (Amaranthus tuberculatus Moq.) (a weed similar to Palmer amaranth in its biology) are two major resistance-prone broadleaf weed species in the agronomic crop-production systems of the southern and mid-western US, whereas barnyardgrass (Echinochloa crus-galli L.) is an important grass weed with high potential for evolving herbicide resistance in these systems (Heap 2019). Multiple herbicide resistance in Palmer amaranth (Sosnoskie et al. 2011), waterhemp (Shergill et al. 2018), and barnyardgrass (Talbert and Burgos 2007; Liu et al. 2017) has been causing serious economic and environmental damages.Importance of a proactive, IPM approach to tackling the problemWhen looking at how herbicide resistance in weeds has been dealt with thus far, it is more often reactive rather than proactive. A reactive approach attempts to manage resistance after resistance has already evolved, whereas a proactive approach is geared towards preventing resistance from appearing in the first place (Mueller et al. 2005). A proactive approach advocates more diversified management options right from the start. Soil weed seedbank management is an important element of proactive resistance management. Simulation models have emphasized that the risk of herbicide resistance is strongly and positively associated with soil seedbank size (Bagavathiannan et al. 2013; Neve et al. 2011). Traditional weed control recommendations were based on an economic threshold (ET) concept, which advocates control when weed densities exceed a yield loss threshold. However, the ET concept does not adequately address the likelihood of weed seedbank addition, which might increase future weed management costs and also elevate the risk of resistance evolution (Norris 1999; Bagavathiannan and Norsworthy 2012). Therefore, a proactive approach to resistance management requires a strong focus on minimizing soil weed seedbank levels.Obstacles to IPM adoptionBest management practices (BMPs) based on an IPM approach to herbicide resistance management have been developed with collaborative efforts between USDA-APHIS and Weed Science Society of America, utilizing the knowledge gained from a wealth of research activities concerning this issue (Norsworthy et al. 2012). The level of adoption of the BMPs, however, has been slow. A survey by Riar et al. (2013b) indicated that one of the major constraints to BMP adoption by growers is the failure to recognize the long-term benefits of BMP adoption. Convincing growers of the economical competence of a proactive, IPM approach to herbicide resistance management remains a significant challenge. A number of BMPs for the management of herbicide resistance in Palmer amaranth (Neve et al. 2011) and barnyardgrass (Bagavathiannan et al. 2013) were developed with guidance from simulation modeling efforts, but these models were only intended as research tools and are not suitable for use as decision-aid tools in Extension activities. The lack of an effective, user-friendly, education/extension tool to demonstrate the long-term biological and economic viability of IPM strategies represents a substantial limitation to the promotion of IPM tactics by extension personnel.PAM: A bio-economic model to guide Palmer amaranth managementWith the need for an effective decision-support tool to assist the dissemination of IPM tactics by extension personnel, our team has developed a Microsoft Excel™ based tool, known as the Palmer amaranth integrated management (PAM) model. This tool has been effective for demonstrating the long-term biological and economic benefits of adopting integrated strategies for Palmer amaranth management (Lindsay et al. 2017). The model simulates long-term (10 year) average economic returns as well as the seedbank size of Palmer amaranth. It allows the user to build various crop rotation and weed management strategies for a 10-year period and see for themselves the economic and biological benefits of using, or drawbacks of not using, a diversified IPM strategy to weed management. Specific non-chemical options incorporated in the model include crop rotation, row spacing, cover crops, seedbed preparation, moldboard plowing and harvest-time weed seed control, among others. This tool also includes a resistance risk calculator that automatically displays the risk of herbicide resistance to the host of management options selected by the user. The PAM model was developed based on constant feedback provided by end users. The PAM model is currently available for download at http://agribusiness.uark.edu/decision-support-software.php#PAM. This tool has been widely circulated through various outreach outlets and is currently used in extension activities. The major target audience for this tool is crop consultants and extension personnel, who run various scenarios and use the information in their weed management planning and outreach activities, while some progressive farmers also use this by themselves. A number of weed management and crop production scenarios can be simulated by the software and the outputs can be used to demonstrate the long-term benefits of diversified weed management.The PlanThe focus of this proposal is to improve the PAM model to provide system-based herbicide resistance management education and to expand its application to the mid-western US. As mentioned earlier, barnyardgrass is a dominant grass weed in various agronomic crop production systems across the southern and mid-western US. It is the second most important weed species globally that shows high-risk for the evolution of herbicide resistance, with resistance to at least 10 different herbicide SOA as of today (Heap 2019). The PAM model will be revised and improved to include waterhemp and barnyardgrass. Further, these improvements will be implemented in a website interface to achieve wider accessibility and utilization. It is anticipated that such improvements will make this a robust-decision support tool to promote IPM-based strategies for herbicide resistance management.The short-term goal of this project is to develop and deliver a robust system-based decision-support tool for demonstrating to consultants, dealers, distributors, extension personnel and growers, the benefits of adopting and the penalties of not adopting IPM tactics for herbicide resistance management encompassing both grass and broadleaf weeds. The long-term goal of the project is to demonstrate to the clientele the value of system-based IPM approaches to weed management and thereby minimize the economic, human health, and environmental impacts associated with weed management in general and herbicide resistance in particular.

Animal Health Component

75%

Research Effort Categories

Basic

25%

Applied

75%

Developmental

0%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
213	1820	1140	35%
213	1710	1140	30%
213	1510	1140	35%

Knowledge Area
213 - Weeds Affecting Plants;

Subject Of Investigation
1510 - Corn; 1820 - Soybean; 1710 - Upland cotton;

Field Of Science
1140 - Weed science;

Keywords

bmp

barnyardgrass

bioeconomic model

resistance risk

waterhemp

Goals / Objectives
The short-term goal of this project is to develop and deliver a robust system-based decision-support tool for demonstrating to consultants, dealers, distributors, extension personnel and growers, the benefits of adopting and the penalties of not adopting IPM tactics for herbicide resistance management encompassing both grass and broadleaf weeds. The long-term goal of the project is to demonstrate to the clientele the value of system-based IPM approaches to weed management and thereby minimize the economic, human health, and environmental impacts associated with weed management in general and herbicide resistance in particular.The specific objectives are: 1) develop a system-level decision-support tool for guiding the implementation of herbicide resistance BMPs, with an emphasis on long-term soil seedbank size and economics (research objective). 2) deliver the Extension/education tool and the IPM-based BMPs to the broader clientele through various outreach activities. These objectives directly support the fundamental goals of the CARE program (Extension objective).

Project Methods
Objective 1 (Research Objective)The proposed decision-support tool will be an improvement of the existing, fully-functional PAM model (Lindsey et al. 2017) which simulates bio-economic implications of various Palmer amaranth management strategies in cotton, corn and soybean in the US Midsouth. The basic framework of the PAM model is based on the ryegrass integrated management (RIM) model developed in Australia (Lacoste and Powles 2014), in terms of how the features are executed and how calculations are performed. The PAM model was developed on the Microsoft® Excel™ platform, using the Visual Basic™ interface to provide a software-like appearance. The proposed web-application will utilize the existing framework of the PAM model as the foundation. The structure of the web application will be identical to that of the Excel platform, except that it will be implemented on a web browser.Core components In its core, this decision-support tool has three integral components: 1) weed population dynamics, 2) management, and 3) economics. These components interact with each other in delivering the final outputs, the weed seedbank size, yield and net cash flows associated with implemented weed management control options.The population dynamics sub-model simulates the weed life cycle from seeds in the soil seedbank to seedbank replenishment at the end of the growing season. This model particularly tracks soil seedbank size and above ground weed density at different time points within a season. The management component of the model represents various crop and weed management options. Efficacies are assigned for each crop/management option based on its effects on overall weed control. Ultimately, the crop and weed management choices interact with long-term weed population dynamics as well as economic returns. A key economic consideration is to allow the user to recognize the extent of long-term benefits through short-term compromises in profit. The model uses NPV analysis as a dollar received or spent today is different from a dollar received or spent in the future, given opportunity cost of delayed earning (Robinson and Barry 1996).Proposed improvementsIn the proposed project, three major improvements will transform the PAM model into a more robust system-based decision-support tool with broader applicability through: (1) addition of barnyardgrass as an important grass weed species to simulate impacts at a system level, (2) addition of waterhemp as an important broadleaf weed species to expand the geographical utility of the tool, and (3) development of a web application version of the tool to enhance wider accessibility and utilization.(1) Inclusion of barnyardgrass: A complete set of sub-models will be developed for simulating the population dynamics of barnyardgrass. These sub-models will be consistent with the sub-models used by Bagavathiannan et al. (2014) for simulating glyphosate resistance evolution in this species. This stage-structured model will simulate four key life history stages: seeds in the soil seedbank, emerged seedlings for each cohort, seedlings that escape control measures and seedbank addition of fresh seeds produced by weed escapes. The efficacy of different barnyardgrass control measures will influence the number of individuals escaping control.(2) Inclusion of waterhemp: The population dynamics model used by Liu et al. (2017) for simulating herbicide resistance in waterhemp will be used as a foundation for this update. Given the many biological similarities between waterhemp and Palmer amaranth (annual life cycle, dioeceous biology, wind pollination, etc.), the overall structure of the waterhemp model will be similar to that of the Palmer amaranth model described above. Waterhemp also exhibits a prolonged emergence pattern (Schutte and Davis 2014), and six individual emergence cohorts will be simulated in the model. Preemergence and postemergence herbicide options pertinent to waterhemp control in corn-soybean rotation will be added to the drop-down lists.Several updates to the economic component of the model, associated with the inclusion of barnyardgrass and waterhemp, will also be carried out. This tool will employ partial and capital budgeting techniques to evaluate various proactive strategies surrounding holistic weed management. Gross margins will be calculated each year based on proceeds from commodity sales and expenses incurred. Using conventional discounting techniques, the user will be informed of changes in the NPV of production strategies. Specifying different interest rates, to reflect differences in risk will provide answers about how sensitive model outcomes are to the discount rate used. A higher discount rate, for example, would imply not only greater production risk but also greater expected changes in input cost and output price expectations. Regional differences in cost of production and production practices will be offered as default values for users.(3) Implementation of a web application: The web application will be designed to be easily accessible to inexperienced web users and offer BMP recommendations that are tailored to individual operations. This web application will be implemented using the open source platform Ruby on Rails (RoR) (Hansson 2017). RoR is a server-side web application framework written in Ruby. RoR utilizes a model-view-controller (MVC) framework, which offers active record database functionality, customizable web pages, and user interaction. There are five base modules: user, farm, field, crop, and strategy. The user provides a farm name, field name, and a user ID. They can then specify a field ID and begin simulating various crop production and weed management scenarios for a given field. Each crop has a sub-model associated with it to capture expected yields and prices. The output is a 10-year simulation that projects weed seedbank sizes for Palmer amaranth, waterhemp, and barnyardgrass, as well as net economic returns.Objective 2 (Extension Objective)We will develop an outreach program surrounding the use of the decision-support tool, educating growers and weed management practitioners on the benefit of BMPs for proactive herbicide resistance management, focusing on long-term soil seedbank and economic returns. We have a well-established extension system that has strong collaborations among weed scientists, growers, consultants, distributors, and other stakeholders. We will create a coordinated educational program across the southern and mid-western regions dealing with a system-based approach for herbicide resistance management that will include the following features:-'Train the trainers' for facilitating the use of the decision-support tool on a 'learning-by-doing' basis.-Promote the use of the decision-support tool through presentations/demonstrations in county extension meetings and other grower-relevant events conducted in the region.-Prepare videos that demonstrate the use of the decision-support tool and its applications for proactive herbicide resistance management.-Publish factsheets comparing key management scenarios using the decision-support tool, demonstrating the value of diversified IPM strategies on long-term seedbank size and economic returns.-Publish articles in the popular news media such as Delta Farm Press, Southern Farm Press, Southwestern Farm Press, MidAmerica Farmer, etc., which are accessed weekly by thousands of growers and consultants during the growing season.-Deliver presentations/demonstrations of the decision-support tool in applied professional meetings such as the Texas Plant Protection Association Conference, Arkansas Crop Protection Association Meeting, etc. Additionally, presentations will be made at the professional weed science society meetings.-Publish scientific articles on the development and applications of the decision-support tool in applied weed management journals.

Progress 06/15/20 to 06/14/24

Outputs
Target Audience:The key target audiences for this project include growers, crop consultants, extension personnel, county agents and agrichemical distributors. Changes/Problems:COVID-19 led to a major setback with personnel hiring and implementation of project activities. Despite this disruption, we were able to complete multi-site field experiments and greenhouse weed-crop competition studies to generate critical weed biology and ecology data for parameterizing the model, and successfully implemented it in the Excel platform. However, a web-platform could not be developed due to the limited timeline and resources. This has been identified as a future line of work and we will explore additional funding opportunities to accomplish this. What opportunities for training and professional development has the project provided?The project has provided training on data mining and meta-analysis for a partial Postdoctoral Associate, two partial Research Assistants, and two partial Graduate Students over the five-year period. They also gained valuable insight into systems thinking, best practices for herbicide resistance management, and sustainable agriculture. How have the results been disseminated to communities of interest?Project updates were communicated to growers and crop consultants at the Texas Plant Protection Association Annual Meetings, Arkansas Crop Protection Association Annual Meetings, Southern Weed Science Society Meetings, Weed Science Society of America Meetings, and the ASA-CSSA-SSSA Annual Meetings. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? This project is based on a previously developed decision support tool namely PAM or Palmer Amaranth Management model. This tool was implemented in Microsoft Excel platform using the Visual Basic functionality. Three major improvements were proposed in the current research project: 1) inclusion of the dominant grass weed species barnyardgrass, 2) inclusion of the broadleaf weed waterhemp, which is the most problematic herbicide-resistant weed species in the Midwest, and 3) implementation of the decision support tool in a website platform. In this research, multi-state field experiments were conducted to determine waterhemp and barnyardgrass seedling emergence across latitudinal gradients in the US, as influenced by tillage regimes and cover crop implementation. The study sites included College Station, TX; Fayetteville, AR; Urbana-Champaign, IL; and Madison, WI. This study provided critical weed seedling emergence data required for parameterizing the models. Further, greenhouse experiments were conducted to elucidate cotton growth and yield response as influenced by multi-species weed competition. As a parallel activity, published data on the ecology and biology of waterhemp and barnyardgrass were mined from literature. The WEEDS model has been developed as an improvement of the PAM model, to include waterhemp and barynardgrass in the simulations. The economic components pertaining to the management options for both species in the three major crops (soybean, corn, and cotton) have also been updated. We also actively communicated the research findings to growers and the scientific community through various outreach platforms.

Publications

• Type: Conference Papers and Presentations Status: Accepted Year Published: 2025 Citation: Gyawali, P., Redwitz, C., & Bagavathiannan, M. (2025). Elucidating Competitive Interactions Between Cotton and Multiple Weed Species in Diverse Mixes [Abstract]. Southern Weed Science Society  2025, Charleston Marriott in Charleston, SC, USA.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2025 Citation: Gyawali, P., Lindsay, K., Mirsky, S. B., Popp, M., Norsworthy, J.K., & Bagavathiannan, M. (2025). WEEDS: A Multiregional Decision Support System for Integrated Weed Management [Abstract]. Southern Weed Science Society  Charleston Marriott in Charleston, SC, USA
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2025 Citation: Gyawali, P., Pavlovic, P., Kerr, D., Mobli, A., Werle, R., Norsworthy, J., Williams, M. II, & Bagavathiannan, M. (2025) Waterhemp Seedling Emergence Pattern is Influenced by Tillage and Cereal Rye Cover Across a Latitudinal Gradient [Abstract], Southern Weed Science Society  Charleston Marriott in Charleston, SC, USA
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Lindsay, K., Raturi, A., Mirsky, S. B., Popp, M., Norsworthy, J., & Bagavathiannan, M. (2024) Weeds: A Robust Multiregional Decision Support System (DSS) for Integrated Weed Management [Abstract]. ASA, CSSA, SSSA International Annual Meeting, San Antonio, TX. https://scisoc.confex.com/scisoc/2024am/meetingapp.cgi/Paper/158509
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Lindsey, K., Ratouri, A., Mirsky, S. B., Popp, M., Norsworthy, J.K., and Bagavathiannan, M. (2024). Integrating Ecology and Economics for Achieving Effective Weed Management Decisions [Abstract]. The 24th Annual Meeting of the Ecological Integration Symposium (EIS), Rudder Tower, Texas A&M University College Station, Texas, April 4-5, 2024.
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Lindsey, K., Ratouri, A., Mirsky, S. B., Popp, M., Norsworthy, J.K., and Bagavathiannan, M. (2024). WEEDS: A Multi-Regional Bioeconomic Decision Support Tool for Guiding Integrated Weed Management [Abstract]. Weed Science Society of America  Southern Weed Science Society Joint Meeting  2024, Hyatt Regency Riverwalk, San Antonio, TX, USA.
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Redwitz, C., & Bagavathiannan, M. (2024) Intricacies of Agroecosystems: Elucidating Competitive Dynamics in Multi-Species Crop-Weed Mixes [Abstract]. ASA, CSSA, SSSA International Annual Meeting, San Antonio, TX. https://scisoc.confex.com/scisoc/2024am/meetingapp.cgi/Paper/158536
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Pavlovic, P., Mobli, A., Werle, R., Norsworthy, J., Williams, M. II, & Bagavathiannan, M. (2024) Cereal Rye Cover Crop and Tillage Influence on Waterhemp Seedling Emergence Patterns across US Latitudes [Abstract]. ASA, CSSA, SSSA International Annual Meeting, San Antonio, TX. https://scisoc.confex.com/scisoc/2024am/meetingapp.cgi/Paper/158517
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2024 Citation: Gyawali, P., Mobli, A., Pavlovic, P., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. (2024). Cereal Rye Cover Crop and Tillage Regime Alters Waterhemp Emergence Pattern Across a Latitudinal Gradient in the United States [Abstract]. Weed Science Society of America  Southern Weed Science Society Joint Meeting  2024, Hyatt Regency Riverwalk, San Antonio, TX, USA.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Gyawali, P., Popp, M., Norsworthy, J.K., and Bagavathiannan, M. V., (2022). WEEDS: A Decision Support System (DSS) for guiding integrated weed management across multiple regions [Abstract]. 3rd International Weed Conference on "Weed problems and management challenges: Future perspectives", Anand Agricultural University, Anand, Gujarat, India. https://isws.org.in/Documents/Proceedings_of_conference/2022_3IWC_(Abstract_Book).pdf
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Lindsay, K., Raturi, A., Mirsky, S. B., Popp, M., Norsworthy, J.K., & Bagavathiannan, M. V. (2023) Weeds: A Robust Ecological and Economic Decision Support Tool for Guiding Integrated Weed Management [Abstract]. ASA, CSSA, SSSA International Annual Meeting, St. Louis, MO, USA https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150479
• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Gyawali, P., Mobli, A., Jha, P., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023) Influence of Cereal Rye Cover Crop and Tillage on the Emergence Pattern of Waterhemp across a Latitudinal Gradient in the United States [Abstract]. ASA, CSSA, SSSA International Annual Meeting, St. Louis, MO, USA. https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150536
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Pavlovic, P., Mobli, A., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023). Waterhemp Emergence Pattern is Altered by Cereal Rye Cover Crop and Tillage Regimes Across a Latitudinal Gradient in the United States [Abstract]. 35th Annual Texas Plant Protection Conference. Bryan, TX, USA.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Pavlovic, P., Mobli, A., Jha, P., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023). Influence of Cereal Rye Cover Crop and Tillage on the Emergence Pattern of Waterhemp Across a Latitudinal Gradient in the United States [Abstract]. 78th Annual Meeting North Central Weed Science Society, Minneapolis, MN, USA. https://ncwss.org/wp-content/uploads/NCWSS-2023-Program-11-27.pdf

Progress 06/15/22 to 06/14/23

Outputs
Target Audience:The key target audiences for this project include growers, crop consultants, extension personnel, county agents and agrichemical distributors. Changes/Problems:COVID-19 led to a major setback with personnel hiring and implementation of project activities. However, a PhD student has been hired and began working on the project starting fall 2022. A postdoctoral associate has assisted the project in the previous year. What opportunities for training and professional development has the project provided?The waterhemp seedling emergence study will be repeated for the second study season. We will also continue to update the PAM model to include the parameters for the waterhemp and barnyardgrass. How have the results been disseminated to communities of interest?Project updates were communicated to growers and crop consultants at the Texas Plant Protection Association Annual Meeting, as well as the Arkansas Crop Protection Association Annual Meeting. What do you plan to do during the next reporting period to accomplish the goals?The waterhemp seedling emergence study will be repeated for the second study season. We will also continue to update the PAM model to include the parameters for the waterhemp and barnyardgrass.

Impacts
What was accomplished under these goals? This project is based on a previously developed decision support tool namely PAM or Palmer Amaranth Management model. This tool was implemented in Microsoft Excel platform using the Visual Basic functionality. Three major improvements were proposed in the current research project: 1) inclusion of the dominant grass weed species barnyardgrass, 2) inclusion of the broadleaf weed waterhemp, which is the most problematic herbicide-resistant weed species in the Midwest, and 3) implementation of the decision support tool in a website platform. In the reporting year, a multi-state field experiment was conducted to determine waterhemp seedling emergence across latitudinal gradients in the US, as influenced by tillage regimes and cover crop implementation. The study sites include College Station, TX; Fayetteville, AR; Urbana-Champaign, IL; and Madison, WI. Additionally, literature data mining has been completed for the two key weed species barnyardgrass and waterhemp.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Lindsay, K., Raturi, A., Mirsky, S. B., Popp, M., Norsworthy, J.K., & Bagavathiannan, M. V. (2023) Weeds: A Robust Ecological and Economic Decision Support Tool for Guiding Integrated Weed Management [Abstract]. ASA, CSSA, SSSA International Annual Meeting, St. Louis, MO, USA
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Mobli, A., Jha, P., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023) Influence of Cereal Rye Cover Crop and Tillage on the Emergence Pattern of Waterhemp across a Latitudinal Gradient in the United States [Abstract]. ASA, CSSA, SSSA International Annual Meeting, St. Louis, MO, USA.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Pavlovic, P., Mobli, A., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023). Waterhemp Emergence Pattern is Altered by Cereal Rye Cover Crop and Tillage Regimes Across a Latitudinal Gradient in the United States [Abstract]. 35th Annual Texas Plant Protection Conference. Bryan, TX, USA.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Gyawali, P., Pavlovic, P., Mobli, A., Jha, P., Werle, R., Norsworthy, J.K., Williams, M. II, & Bagavathiannan, M. V. (2023). Influence of Cereal Rye Cover Crop and Tillage on the Emergence Pattern of Waterhemp Across a Latitudinal Gradient in the United States [Abstract]. 78th Annual Meeting North Central Weed Science Society, Minneapolis, MN, USA.

Progress 06/15/21 to 06/14/22

Outputs
Target Audience:The key target audiences for this project include growers, crop consultants, extension personnel, county agents and agrichemical distributors. Changes/Problems:COVID-19 led to a major setback with personnel hiring and implementation of project activities. However, a PhD student has been hired and began working on the project. A postdoctoral associate has assisted the project in the previous year. What opportunities for training and professional development has the project provided?The project has provided training on data mining and meta-analysis for a partial Postdoctoral Associate, a partial Research Assistant, and a partial Graduate Student. They also gained valuable insight into systems thinking, best practices for herbicide resistance management, and sustainable agriculture. How have the results been disseminated to communities of interest?Project updates were communicated to growers and crop consultants at the Texas Plant Protection Association Annual Meeting, as well as the Arkansas Crop Protection Association Annual Meeting. What do you plan to do during the next reporting period to accomplish the goals?We are hoping to complete data mining and construct sub-models that capture various biological interactions and management outcomes involving multiple weed species and tactics in a given crop rotation. We also expect to make progress with the web platform wireframing.

Impacts
What was accomplished under these goals? This project is based on a previously developed decision support tool namely PAM or Palmer Amaranth Management model. This tool was implemented in Microsoft Excel platform using the Visual Basic functionality. Three major improvements were proposed in the current research project: 1) inclusion of the dominant grass weed species barnyardgrass, 2) inclusion of the broadleaf weed waterhemp, which is the most problematic herbicide-resistant weed species in the Midwest, and 3) implementation of the decision support tool in a website platform. In the reporting year, data mining has begun to amass all published data pertaining to the ecology, biology and management of barnyardgrass and waterhemp. Further, information related to the associated herbicide products and other management costs have also been collected. Additionally, a draft wireframe was developed for the website application of the decision support tool. Progress has been slow due to COVID19 related project disruptions.

Publications

Progress 06/15/20 to 06/14/21

Outputs
Target Audience:The key target audiences for this project include growers, crop consultants, extension personnel, county agents and agrichemical distributors. Changes/Problems:COVID-19 led to a major setback with personnel hiring and implementation of project activities. However, considerable progress has been made so far, utilizing available personnel and resources. We are hoping to make more progress in the next reporting cycle. What opportunities for training and professional development has the project provided?The project has provided training on data mining and meta-analysis for a partial Postdoctoral Associate, a partial Research Assistant, and a partial Graduate Student. They also gained valuable insight into systems thinking, best practices for herbicide resistance management, and sustainable agriculture. How have the results been disseminated to communities of interest?Project updates were communicated to growers and crop consultants at the Texas Plant Protection Association Annual Meeting, as well as the Arkansas Crop Protection Association Annual Meeting. What do you plan to do during the next reporting period to accomplish the goals?We are hoping to complete data mining and construct sub-models that capture various biological interactions and management outcomes involving multiple weed species and tactics in a given crop rotation. We also expect to make progress with the web platform wireframing.

Impacts
What was accomplished under these goals? This project is based on a previously developed decision support tool namely PAM or Palmer Amaranth Management model. This tool was implemented in Microsoft Excel platform using the Visual Basic functionality. Three major improvements were proposed in the current research project: 1) inclusion of the dominant grass weed species barnyardgrass, 2) inclusion of the broadleaf weed waterhemp, which is the most problematic herbicide-resistant weed species in the Midwest, and 3) implementation of the decision support tool in a website platform. In the reporting year, data mining has begun to amass all published data pertaining to the ecology, biology and management of barnyardgrass and waterhemp. Further, information related to the associated herbicide products and other management costs have also been collected. Additionally, a draft wireframe was developed for the website application of the decision support tool. Progress has been slow due to COVID19 related project disruptions.

Publications