Predicting fusarium head blight epidemics with boosted regression trees

Phytopathology

Volumn 104, Issue 7, 2014, Pages 702-714

  Shah, D A ^a   De Wolf, E D ^a   Paul, P A ^b   Madden, L V ^b  

^a KANSAS STATE UNIVERSITY   (United States)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

Disease forecasting; Disease modeling; Machine learning; Plant disease epidemiology; Wheat scab

Indexed keywords

ARTICLE; COMPARATIVE STUDY; DISEASE FORECASTING; DISEASE MODELING; FUSARIUM; HUMIDITY; MACHINE LEARNING; MICROBIOLOGY; PHYSIOLOGY; PLANT DISEASE; PLANT DISEASE EPIDEMIOLOGY; STATISTICAL MODEL; STATISTICS; TEMPERATURE; WHEAT; WHEAT SCAB;

DISEASE FORECASTING; DISEASE MODELING; MACHINE LEARNING; PLANT DISEASE EPIDEMIOLOGY; WHEAT SCAB;

FUSARIUM; HUMIDITY; LOGISTIC MODELS; MODELS, STATISTICAL; PLANT DISEASES; TEMPERATURE; TRITICUM;

EID: 84902270722     PISSN: 0031949X     EISSN: None     Source Type: Journal    
DOI: 10.1094/PHYTO-10-13-0273-R     Document Type: Article

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