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Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers.

Spyridon MourtzinisChristian H KrupkePaul David EskerAdam VarenhorstNicholas J ArnesonCarl A BradleyAdam M ByrneMartin I ChilversLoren J GieslerAmes HerbertYuba R KandelMaciej J KazulaCatherine HuntLaura E LindseySean MaloneDaren S MuellerSeth NaeveEmerson NafzigerDominic D ReisigWilliam J RossDevon R RossmanSally TaylorShawn P Conley
Published in: Scientific reports (2019)
Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + NST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + NST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike.
Keyphrases
  • randomized controlled trial
  • primary care
  • systematic review
  • electronic health record
  • machine learning
  • transcription factor
  • social media
  • big data
  • double blind
  • phase iii
  • life cycle
  • meta analyses