Proximal phenotyping and machine learning methods to identify septoria tritici blotch disease symptoms in wheat

Frontiers in Plant Science

Volumn 9, Issue , 2018, Pages

  Odilbekov, Firuz ^a   Armoniené, Rita ^a   Henriksson, Tina ^b   Chawade, Aakash ^a  

^a SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES   (Sweden)

^b Lantmännen Lantbruk   (Sweden)

Author keywords

Disease detection; Machine learning; Proximal phenotyping; Random forest; Septoria tritici blotch; Wheat

Indexed keywords

EID: 85047509282     PISSN: None     EISSN: 1664462X     Source Type: Journal    
DOI: 10.3389/fpls.2018.00685     Document Type: Article

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