DEVELOPMENT OF A WEED EMERGENCE MODEL FOR THE NORTHEASTERN UNITED STATES

Project Details

Description

Weed management is a priority issue for Northeastern farmers, particularly with the increasing prevalence of organic production, the rise of herbicide resistant weeds, and the recent increase in small farms and urban farming. Providing seedling emergence information so that farmers can effectively time their weed management operations can increase efficacy of control, reduce labor costs, and minimize any negative environmental impacts. Therefore, there is an urgent need for the development of time-specific weed management tools to help address the frequently asked, yet to be answered, question ofwhen is the 'right' time to control weeds? Weed seedling emergence is a complex process regulated by a multitude of internal (e.g. species-specific parameters such as base temperature, base water potential) and environmental (e.g. soil temperature and moisture) factors. No weed management decision support tool exists for the Northeastern region of the United States, despite recent advances in our understanding of regional weed emergence patterns and developments in fine-scale weather prediction and soil moisture modeling. Therefore, there is a need for collecting weed emergence data across the region to validate and refine existing weed emergence models in order to produce a web-hosted weed emergence predictive tool for use by farmers, extension personnel, crop consultants, and the general public.Research plots will be established in various sites across the northeastern US. Each site will include two treatments, one with initial tillage in a field with a history of tillage and one with no tillage in a field with a history of no-till agriculture. Eight 1 m2 plots for each treatment will be established, for a total of sixteen plots per site. All emerged weeds of the selected species of interest will be identified and counted on a weekly basis and emerged plants will be removed. Simultaneously, environmental data (precipitation, air and soil temperature) will be collected at each experimental site. Collection of these data for the targeted weed species will help to validate/refine the preliminary emergence prediction tool developed by Cornell University.Ultimately, our goal is to develop and validate a user-friendly, online decision support tool for the real time prediction of weed emergence in the northeastern US. The decision support tool will consider GPS location, soil type, tillage, crop data, and accesses weather history to provide percent emergence of the farmer's problem weeds at that location.
StatusFinished
Effective start/end date12/3/189/30/23

Funding

  • National Institute of Food and Agriculture

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