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Computer vision for detecting field-evolved lepidopteran resistance to Bt maize.

Seth J DormanMichael W KudenovAmanda J LytleEmily H GriffithAnders S Huseth
Published in: Pest management science (2021)
Automated detection and tracking of lepidopteran resistance evolution to Bt toxins are critical for genetically engineered crop stewardship to prevent the use of additional insecticides to combat resistant pests. Advantages of this computerized screening are: (i) standardized Bt injury metrics in space and time, (ii) preservation of digital data for cross-referencing when thresholds are reached, and (iii) the ability to increase sample sizes significantly. This technological solution represents a significant step toward improving confidence in resistance monitoring efforts among researchers, regulators and the agricultural biotechnology industry.
Keyphrases
  • climate change
  • deep learning
  • risk assessment
  • machine learning
  • heavy metals
  • high throughput
  • transcription factor
  • electronic health record
  • big data
  • clinical decision support
  • data analysis
  • water quality