A remote sensing technique for detecting laurel wilt disease in avocado in presence of other biotic and abiotic stresses

Computers and Electronics in Agriculture

Volumn 156, Issue , 2019, Pages 549-557

  Abdulridha, Jaafar ^a   Ehsani, Reza ^b   Abd Elrahman, Amr ^c   Ampatzidis, Yiannis ^a  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF FLORIDA   (United States)

Author keywords

Avocado; Disease detection; Multispectral; Neural networks; Spectral reflectance analysis

Indexed keywords

CAMERAS; DAMAGE DETECTION; DIAGNOSIS; FORESTRY; FRUITS; IMAGE ACQUISITION; IMAGE SEGMENTATION; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; PLANTS (BOTANY); REMOTE SENSING;

AVOCADO; BIOTIC AND ABIOTIC STRESS; DISEASE DETECTION; EARLY DISEASE DETECTION; FEATURE EXTRACTION AND CLASSIFICATION; MULTI-SPECTRAL; REMOTE SENSING TECHNIQUES; SPECTRAL REFLECTANCES;

FEATURE EXTRACTION;

ANGIOSPERM; ARTIFICIAL NEURAL NETWORK; AUTOMATION; BIOTIC FACTOR; DETECTION METHOD; ENVIRONMENTAL STRESS; IMAGE ANALYSIS; REMOTE SENSING; SPECTRAL ANALYSIS; SPECTRAL REFLECTANCE; SYMPTOM; WILT;

PERSEA AMERICANA; PHYTOPHTHORA;

EID: 85058235908     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2018.12.018     Document Type: Article

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