Detection of biotic and abiotic stresses in crops by using hierarchical self organizing classifiers

Precision Agriculture

Volumn 18, Issue 3, 2017, Pages 383-393

  Pantazi, Xanthoula Eirini ^a,e   Moshou, Dimitrios ^a   Oberti, Roberto ^b   West, Jon ^c   Mouazen, Abdul Mounem ^d   Bochtis, Dionysios ^e  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b UNIVERSITY OF MILAN   (Italy)

^c ROTHAMSTED RESEARCH   (United Kingdom)

^d GHENT UNIVERSITY   (Belgium)

^e INFORMATION TECHNOLOGIES INSTITUTE   (Greece)

Author keywords

Crop disease; Hyperspectral sensing; Machine learning; Neural networks; Nitrogen stress

Indexed keywords

ABIOTIC FACTOR; ARTIFICIAL NEURAL NETWORK; BIOTIC FACTOR; CROP DAMAGE; DISEASE INCIDENCE; ENVIRONMENTAL STRESS; FUNGICIDE; MACHINE LEARNING; NITROGEN; SPECTRAL ANALYSIS;

EID: 85013465384     PISSN: 13852256     EISSN: 15731618     Source Type: Journal    
DOI: 10.1007/s11119-017-9507-8     Document Type: Article

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