It’s no secret that weed resistance has evolved into one of the top issues for growers across the country. With each additional year of using ineffective herbicide chemistries and weed management strategies, weeds have the opportunity to adapt and develop resistance.
In an effort to delay the development of weed resistance, most universities say it’s important to implement a combination of cultural practices in conjunction with a strong herbicide program containing overlapping residuals. This includes using multiple, effective sites of action (SOAs) that directly target the spectrum of weeds present.
Syngenta has recently developed a resistance modeling software to predict how many years it will take for weed resistance to develop under various scenarios, taking into account the number of herbicide applications and SOAs within the herbicide.
“This project started several years ago,” said Joe Wuerffel, Research and Development scientist at Syngenta. “We essentially wanted to develop a herbicide model that would give the ability to make relative comparisons of different herbicide programs to understand how long a particular program would last.
“We started with a few different weed species that were thought to be key – Palmer amaranth and water hemp. Those two were really a key focus of the model at the very beginning,” he added.
The program was developed by Syngenta’s fulltime herbicide resistance modeler in the United Kingdom, Chung Liu. She built the program from the ground up, writing tens of thousands of lines of code.
According to Wuerffel, what makes the model unique from others is the fact that it tracks every “individual viable weed seed” in a given field.
“The model starts with some assumptions. It assumes that we’re starting with one particular field that simulates what a typical grower’s field would look like,” he said. “It could be anywhere from 10-100 acres. We then input some biological parameters – how many water hemp plants are in that field and how many of them have resistance. We then run the model over a 20-year period with some herbicide programs we pick out.”
After running the model with those various programs, Wuerffel says they deem how sustainable that program in particular would last over that 20-year period and give it a rating – low, medium or high sustainability based on the model.
“Like I said earlier, the model tracks every individual in that field,” he said. “If you have a million water hemp seeds in that field, it tracks a million seeds. It allows us to check the variability you may see in a biological system. It’s a really powerful model.”
Wuerffel says the basis of the program was that they wanted to ensure growers understood that they needed to have a strong residual program with multiple sites of action – pre-emergence and post-emergence. To help this, they developed four scenarios:
- Single SOA program: No pre-emergence herbicide, followed by 2 post-emergence applications of dicamba; SOAs: Group 4; Predicted results: Repeated use of a single SOA program like this one could lead to the development of resistance after only a few years.
- Three SOAs program: Boundary®5 EC herbicide pre-emergence, followed by dicamba post-emergence; SOAs: Groups 4, 5 and 15; Predicted results: Applying a pre-emergence herbicide with multiple, effective SOAs can help extend the life of the technologies, but it won’t make up for applying a post-emergence herbicide with only a single SOA. Resistance could develop in several years.
- Three SOAs program with overlapping residuals: Boundary pre-emergence, followed by a tank mix of dicamba plus Dual Magnum® post-emergence; SOAs: Groups 4, 5 and 15; Predicted results: Overlapping residuals and utilizing a herbicide program with multiple, effective SOAs in both the pre-emergence and post-emergence applications can delay the development of resistance for many years.
- Four SOAs program: Boundary herbicide pre-emergence, followed by a tank mix of dicamba plus Prefix® herbicide post-emergence; SOAs: Groups 4, 5, 14 and 15; Predicted results: Continual use of a strong soybean herbicide program with multiple, effective SOAs in both the pre-emergence and post-emergence applications that directly target the spectrum of weeds on your farm has the potential to delay the development of resistance for up to 2 decades longer than a program with a single SOA.
“With three different sites of action, we were more sustainable than a single site of action, but that didn’t take us to the level of sustainability we were looking for – a decade or more,” he said. “We start to layer in more sites of action, or even overlap those sites of action, and in those scenarios, we were able to add more years on those various programs. It wasn’t until we got to four sites of action where we were confident we had the sustainability we were looking for.”
According to Wuerffel, the program allows agronomists to reinforce the importance of best management practices to best mitigate herbicide resistance.
“One of the most challenging parts of mitigating resistance is that it’s really a numbers’ game. There’s a misconception that by spraying herbicide we’re changing something in the weeds and causing resistance. In reality, we don’t cause resistance, but we’re just finding resistance by spraying the herbicide. This model helps us play out this numbers’ game over a 20-year period and look at the best management practices,” Wuerffel concluded.