Automatic disease diagnosis in plants using digital images

• Grant number: 13/06884-8
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2013
• End date: July 31, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Jayme Garcia Arnal Barbedo
• Grantee: Jayme Garcia Arnal Barbedo
• Host Institution: Embrapa Informática Agropecuária. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA). Ministério da Agricultura, Pecuária e Abastecimento (Brasil). Campinas , SP, Brazil
• Associated researchers: Alessandra de Jesus Boari ; Alessandra Keiko Nakasone Ishida ; Bernardo de Almeida Halfeld Vieira ; Célia Regina Tremacoldi ; Christiana de Fátima Bruce da Silva ; Claudia Vieira Godoy ; Daniel Terao ; Eudes de Arruda Carvalho ; Fabio Rossi Cavalcanti ; Flávia Rodrigues Alves Patrício ; Jose Mauricio Cunha Fernandes ; José Roberto Vieira Júnior ; Katia de Lima Nechet ; Luciano Vieira Koenigkan ; Luiz Gonzaga Chitarra ; Murillo Lobo Junior ; Rodrigo Véras da Costa ; Saulo Alves Santos de Oliveira ; Silvia Maria Fonseca Silveira Massruhá ; Thiago Teixeira Santos ; Viviane Talamini

Abstract

The fast diagnosis of diseases in plants with economical value is essential to ensure food safety and avoid major losses caused by the spread of the malady. Two main problems may hamper such an objective: 1) permanently monitoring the whole crop by people capable of detecting the diseases is, in most cases, not viable; 2) in many cases the person that detects the symptoms does not have the necessary knowledge to identify its cause.Although there are some solutions that explore technology as a facilitator for a quick diagnostic, usually involving a reference database that can be consulted by the user, the arising of fully automated systems has been slow, especially in face of the importance of the problem. This situation is not due to lack of interest by the researchers, but to the lack of a database comprehensive enough to allow the development of really robust methods for disease diagnosis. Hence, as important as the development of the technique itself, is the need for databases capable of making it possible to completely validate the proposed methods.Therefore, this project has two main objectives: 1) to build a database containing images of symptoms and detailed descriptions of their causes and consequences; 2) to develop a method capable of providing a reliable diagnosis using the digital images provided by the users. The cultures to be considered initially will be cotton, soybean, maize, rice, bean, sorghum, sugarcane, citrus, grapevine, pineapple, coffee and cupuaçu, but others may be considered as the project evolves. (AU)

Scientific publications

(10)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BARBEDO, JAYME GARCIA ARNAL; KOENIGKAN, LUCIANO VIEIRA; SANTOS, THIAGO TEIXEIRA. Identifying multiple plant diseases using digital image processing. BIOSYSTEMS ENGINEERING, v. 147, p. 104-116, JUL 2016. (13/06884-8)

ARNAL BARBEDO, JAYME GARCIA; GULIAS GOMES, CLAUDIA CRISTINA; CARDOSO, FERNANDO FLORES; DOMINGUES, ROBERT; RAMOS, JEFERSON VIDART; MCMANUS, CONCEPTA MARGARET. The use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation. Veterinary Parasitology, v. 235, p. 106-112, FEB 15 2017. (13/06884-8)

ARNAL BARBEDO, JAYME GARCIA. An Automatic Method to Detect and Measure Leaf Disease Symptoms Using Digital Image Processing. PLANT DISEASE, v. 98, n. 12, p. 1709-1716, DEC 2014. (13/06884-8)

BARBEDO, JAYME G. A.; TIBOLA, CASIANE S.; FERNANDES, JOSE M. C.. Detecting Fusarium head blight in wheat kernels using hyperspectral imaging. BIOSYSTEMS ENGINEERING, v. 131, p. 65-76, MAR 2015. (13/06884-8)

ARNAL BARBEDO, JAYME GARCIA. A new automatic method for disease symptom segmentation in digital photographs of plant leaves. European Journal of Plant Pathology, v. 147, n. 2, p. 349-364, FEB 2017. (13/06884-8)

BARBEDO, J. G. A.. A novel algorithm for semi-automatic segmentation of plant leaf disease symptoms using digital image processing. TROPICAL PLANT PATHOLOGY, v. 41, n. 4, p. 210-224, AUG 2016. (13/06884-8)

BOCK, CLIVE H.; PETHYBRIDGE, SARAH J.; BARBEDO, JAYME G. A.; ESKER, PAUL D.; MAHLEIN, ANNE-KATRIN; DEL PONTE, EMERSON M.. A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter-disciplinary dialogues. TROPICAL PLANT PATHOLOGY, AUG 2021. (13/06884-8)

ARNAL BARBEDO, JAYME GARCIA; TIBOLA, CASIANE SALETE; PONTES LIMA, MARIA IRNACULADA. Deoxynivalenol screening in wheat kernels using hyperspectral imaging. BIOSYSTEMS ENGINEERING, v. 155, p. 24-32, MAR 2017. (13/06884-8)

ARNAL BARBEDO, JAYME GARCIA. A review on the main challenges in automatic plant disease identification based on visible range images. BIOSYSTEMS ENGINEERING, v. 144, p. 52-60, APR 2016. (13/06884-8)

BARBEDO, J. G. A.. A novel algorithm for semi-automatic segmentation of plant leaf disease symptoms using digital image processing. ROPICAL PLANT PATHOLOG, v. 41, n. 4, p. 15-pg., 2016-08-01. (13/06884-8)