The first effort will be on harvest weed-seed control.
“Weeds that escape the herbicides mature with the crop; during harvest, weed seeds go through the combine and are dispersed throughout the field, contributing to future weed problems,” Bagavathiannan said. “We believe there is an opportunity at harvest to collect these weed seeds and destroy them.”
Different strategies exist to destroy the seed captured by the combine harvester, he said. In this proposal, the team will focus on seed impact mills. The impact mill concept was developed in Australia by a farmer named Ray Harrington to deal with rigid ryegrass seed in wheat. In this approach, the chaff-containing weed seed is separated from straw and is run through an impact mill, which kills weed seeds. Early generation mills were towed behind the combine. The technology has evolved rapidly, and now mills can be directly integrated with combines.
Seed impact mills and other harvest weed-seed control technologies have been broadly adopted by Australian growers. Among the advisors on the project is Michael Walsh, Ph.D., associate professor and director of weed research, University of Sydney. Walsh spent years developing and testing different harvest weed-seed control systems in Australia, including the Harrington Seed Destructor, HSD, and the improved integrated HSD, iHSD.
The team is partnering with DeBruin Engineering, Australia, that manufactures iHSD and REDEKOP, a Canadian manufacturer of seed impact mills. This project is acquiring 16 impact mills to be tested across eight U.S. states.
Walsh said introducing harvest weed-seed control as a new weed control technique into Australian cropping required a substantial and concerted effort, and he expects the same to be required in the U.S.
“This significant grant will enable the required research and development activities that the U.S. cropping industry needs to be able to adopt these systems with confidence,” he said.
Implementing the technology on U.S. soils
The GROW team members have already conducted preliminary studies on the feasibility of harvest weed seed control for the past five years. Preliminary research data indicates the technology is promising.
Bagavathiannan said most existing data on the efficacy of impact mills on U.S. weeds originate from stationary testing and on-station trials, which show greater than 95% destruction of weed seeds, even seeds smaller than those of pigweeds.
“We do need to conduct evaluations on-farm, under realistic production conditions, to demonstrate the potential of this technology, identify areas for further development, and promote farmer adoption,” he said. “This is exactly what this multi-state study is aiming to accomplish.”
The on-farm activities of the project will be conducted on participating farms, ranging in size from 1,000 to 5,000 acres, in three important agricultural regions — North Central, Mid-Atlantic and South Central U.S. Bagavathiannan said the team will integrate cereal rye cover crops with harvest-weed seed control to demonstrate how well these two non-chemical weed management tools can interact with herbicide programs. Field tests in Texas will be in the Upper Gulf Coast area and in the Blacklands region.
The precision agriculture component centers on the development of an image database for important agronomic weeds in the U.S., as well as data flow and cyber infrastructure to facilitate machine learning applications for weed detection and precision management. Drones will be used to assess how IWM practices influence shifts in weed population dynamics and how effectively weed escapes can be spot treated. Field robots will also be utilized for testing ground-level weed detection and actuation systems.
Soil conservation benefits as a result of adopting the IWM solutions will be calculated based on the potential reduction in tillage events that are otherwise required by farmers to manage herbicide-resistant weeds. This reduction will be modeled using WeedRID — a regional IWM decision support tool. The overall conservation benefit calculation will also take into account estimates of how cover crops can reduce herbicide use and decrease weed pressure. The WeedRID model will be parameterized and expanded to include additional weed species, with more regional relevance.
Source : tamu.edu