Automatic recognition of quarantine citrus diseases
Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them, like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is important to perform strict controls before fruits are exported to avoid the inclusion of citrus affected by...
| Main Authors: | , , , |
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.12123/2784 https://doi.org/10.1016/j.eswa.2012.12.059 |
| _version_ | 1855035025752326144 |
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| author | Stegmayer, Georgina Milone, Diego Humberto Garran, Sergio Mario Burdyn, Lourdes |
| author_browse | Burdyn, Lourdes Garran, Sergio Mario Milone, Diego Humberto Stegmayer, Georgina |
| author_facet | Stegmayer, Georgina Milone, Diego Humberto Garran, Sergio Mario Burdyn, Lourdes |
| author_sort | Stegmayer, Georgina |
| collection | INTA Digital |
| description | Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them, like citrus
canker, black spot and scab, are quarantine for the markets. For this reason, it is important to perform
strict controls before fruits are exported to avoid the inclusion of citrus affected by them. Nowadays,
technical decisions are based on visual diagnosis of human experts, highly dependent on the degree of
individual skills. This work presents a model capable of automatic recognize the quarantine diseases. It
is based on the combination of a feature selection method and a classifier that has been trained on quarantine
illness symptoms. Citrus samples with citrus canker, black spot, scab and other diseases were evaluated.
Experimental work was performed on 212 samples of mandarins from a Nova cultivar. The
proposed approach achieved a classification rate of quarantine/not-quarantine samples of over 83% for
all classes, even when using a small subset (14) of all the available features (90). The results obtained
show that the proposed method can be suitable for helping the task of citrus visual diagnosis, in particular,
quarantine diseases recognition in fruits. |
| format | info:ar-repo/semantics/artículo |
| id | INTA2784 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | INTA27842018-07-12T18:53:58Z Automatic recognition of quarantine citrus diseases Stegmayer, Georgina Milone, Diego Humberto Garran, Sergio Mario Burdyn, Lourdes Citrus Enfermedades de las Plantas Cuarentena Métodos de Control Clasificación Classification Control Methods Quarantine Plant Diseases Neural Networks Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them, like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is important to perform strict controls before fruits are exported to avoid the inclusion of citrus affected by them. Nowadays, technical decisions are based on visual diagnosis of human experts, highly dependent on the degree of individual skills. This work presents a model capable of automatic recognize the quarantine diseases. It is based on the combination of a feature selection method and a classifier that has been trained on quarantine illness symptoms. Citrus samples with citrus canker, black spot, scab and other diseases were evaluated. Experimental work was performed on 212 samples of mandarins from a Nova cultivar. The proposed approach achieved a classification rate of quarantine/not-quarantine samples of over 83% for all classes, even when using a small subset (14) of all the available features (90). The results obtained show that the proposed method can be suitable for helping the task of citrus visual diagnosis, in particular, quarantine diseases recognition in fruits. Fil: Stegmayer, Georgina. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria en Sistemas de Informacion; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico Santa Fe. Instituto de Investigacion en Señales, Sistemas e Inteligencia Computacional; Argentina; Argentina Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico Santa Fe. Instituto de Investigacion en Señales, Sistemas e Inteligencia Computacional; Argentina; Argentina Fil: Garran, Sergio Mario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concordia; Argentina Fil: Burdyn, Lourdes. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concordia; Argentina 2018-07-12T18:47:30Z 2018-07-12T18:47:30Z 2013 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/2784 0957-4174 https://doi.org/10.1016/j.eswa.2012.12.059 eng info:eu-repo/semantics/restrictedAccess application/pdf Expert systems with applications 40 : 3512–3517. (2013) |
| spellingShingle | Citrus Enfermedades de las Plantas Cuarentena Métodos de Control Clasificación Classification Control Methods Quarantine Plant Diseases Neural Networks Stegmayer, Georgina Milone, Diego Humberto Garran, Sergio Mario Burdyn, Lourdes Automatic recognition of quarantine citrus diseases |
| title | Automatic recognition of quarantine citrus diseases |
| title_full | Automatic recognition of quarantine citrus diseases |
| title_fullStr | Automatic recognition of quarantine citrus diseases |
| title_full_unstemmed | Automatic recognition of quarantine citrus diseases |
| title_short | Automatic recognition of quarantine citrus diseases |
| title_sort | automatic recognition of quarantine citrus diseases |
| topic | Citrus Enfermedades de las Plantas Cuarentena Métodos de Control Clasificación Classification Control Methods Quarantine Plant Diseases Neural Networks |
| url | http://hdl.handle.net/20.500.12123/2784 https://doi.org/10.1016/j.eswa.2012.12.059 |
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