Detection of citrus canker and Huanglongbing using fluorescence imaging spectroscopy and support vector machine technique

Author(s)

Wetterich, Caio Bruno ; de Oliveira Neves, Ruan Felipe ; Belasque, Jose ; Marcassa, Luis Gustavo

• Document type: Journal article
• Source: APPLIED OPTICS; v. 55, n. 2, p. 8-pg., 2016-01-10.

Abstract

Citrus canker and Huanglongbing (HLB) are citrus diseases that represent a serious threat to the citrus production worldwide and may cause large economic losses. In this work, we combined fluorescence imaging spectroscopy (FIS) and a machine learning technique to discriminate between these diseases and other ordinary citrus conditions that may be present at citrus orchards, such as citrus scab and zinc deficiency. Our classification results are highly accurate when discriminating citrus canker from citrus scab (97.8%), and HLB from zinc deficiency (95%). These results show that it is possible to accurately identify citrus diseases that present similar symptoms. (C) 2016 Optical Society of America (AU)

• FAPESP's process: 11/22275-6 - Fluorescence Imaging using variable liquid crystal tunable filter for citrus diseases
• Grantee: Caio Bruno Wetterich
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 10/16536-9 - Fluorescence Imaging Applied to Citrus Diseases
• Grantee: Luis Gustavo Marcassa
• Support Opportunities: Regular Research Grants