MINNEAPOLIS — As you continue to assess and document the impact of dicamba injury on soybean yield, I thought it would be timely to make you aware of an excellent summary of Dr. Andy Robinson’s research conducted when he was a graduate student at Purdue University. This summary came from Purdue Extension and was authored by Joe Ikley and Bill Johnson: https://z.umn.edu/2vhs
The published manuscript can be accessed at: https://z.umn.edu/dicamba-purdue
- This study uses 8 very low rates of dicamba ranging from 1/10,000th to 1/25th of the 0.5 lb per acre labeled use rate of dicamba. The 0.5 lb per acre rate translates to 12.8 oz/A of Engenia or 22 oz/A of Xtendimax/Fexapan.
- The 8 rates were applied at either the V2, V5 or R2 soybean growth stage.
- Visual injury symptoms were taken 14 and 28 days after treatment and plots were taken to yield.
- Data were collected in 2009 and 2010 over three site years and data were used to model the effective dose of dicamba to cause various levels of injury and yield loss.
Visual injury symptoms: Key take-a-ways based on modeled dose rates
- Rates ranging from 1/1563rd to 1/410th of the labeled rate of dicamba were required to cause 20% visual injury symptoms.
- Dicamba rates of 1/250th of the labeled rate of dicamba or greater caused death of the apical meristem, resulting in branching at the cotyledon or unifoliate node and initiating regrowth from multiple lower nodes.
- Dicamba rates of 1/1000th to 1/250th of the labeled rate of dicamba caused a 10% reduction in plant height.
Yield loss: Key take-a-ways based on modeled dose rates
- Drought conditions during reproduction growth stages can influence yield response. In this study, the droughty site (2.75 inches of rain in July-September) experienced a 10% yield loss at a dicamba rate of 1/3333rd of the labeled rate of dicamba.
- The other two site locations received 5.25 inches of rain in July-September and a 10% yield loss occurred at a dicamba rate of 1/1064th to 1/510th of the labeled rate of dicamba.
Looking beyond the parameters of this study, predicating yield loss based solely on injury symptoms is not a consistent method for predicting yield, because injury ratings can be quite subjective. Without knowledge of soybean growth stage at the time of dicamba exposure and knowledge of other soybean stressors (e.g. drought), yield predictions can vary.
Therefore, due to the challenges of associating dicamba injury symptoms to yield loss, the only equitable way that I can think of to assess impact of dicamba on yield is to determine the most accurate in-field assessment based on the injury symptom criteria presented above and have all affected parties agree to accept the yield comparison results at harvest.
— Jeff Gunsolus, University of Minnesota Extension weed scientist
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