Deteriorating weed control and variable weather portends greater soybean yield losses in the future

Christopher A. Landau, Aaron G. Hager, Martin M. Williams

Research output: Contribution to journalArticlepeer-review

Abstract

Since the 1950's much of the US soybean growing region has experienced rising temperatures, more variable rainfall, and increased carbon emissions. These trends are predicted to continue throughout the 21st century. Variable weather and weed interference influence crop performance; however, their combined effects on soybean yield are poorly understood. Using machine learning techniques on a database of herbicide trials spanning 28 years and 106 weather environments we modeled the most important relationships among weed control, weather variability, and crop management on soybean yield loss. When late-season weeds were poorly controlled, average soybean yield losses of 48% were observed. Additionally, when weeds were not completely controlled, low rainfall and high temperatures during seed fill exacerbated soybean yield loss due to weeds. Since much of the US soybean growing region is heading towards drier, warmer conditions, coupled with growing herbicide resistance, future soybean yield loss will increase without significant improvements in weed management systems.

Original languageEnglish (US)
Article number154764
JournalScience of the Total Environment
Volume830
DOIs
StatePublished - Jul 15 2022

Keywords

  • (Glycine max)
  • Climate change
  • Machine learning
  • Weed interference

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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