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| Author(s): |
Caio Bruno Wetterich
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC/BT) |
| Defense date: | 2016-05-31 |
| Examining board members: |
Luis Gustavo Marcassa;
José Belasque Júnior;
Leonardo De Boni;
Vinicius Tribuzi Rodrigues Pinheiro Gomes;
Bárbara Janet Teruel Mederos
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| Advisor: | Luis Gustavo Marcassa |
| Abstract | |
In recent years, there has been an increasing interest in early detection of diseases that affect agricultural crops to avoid great economic losses due to contamination of new plants. The main citrus diseases, citrus canker and HLB, are a serious threat to citrus production worldwide, including regions in Brazil and the United States. The rapid spread of the diseases leads to the reduction of cultivated orchards resulting in economic losses to producers and industries. The development of methods for early diagnosis can result in an important tool for the control and management of citrus. Some nutritional deficiencies such as iron and zinc have similar visual symptoms to HLB, while the citrus canker can be confused with citrus scab and citrus leprosies, which may lead to incorrect diagnosis. Currently, only biochemical tests are able to detect, specifically, citrus canker and HLB, and thus distinguish them from other diseases and nutrient deficiencies. In this work, the fluorescence imaging spectroscopy technique with the learning and classification methods, SVM (Support Vector Machine) and ANN (Artificial Neural Network), were used to identify and discriminate the main diseases that affect citrus production in the states of São Paulo/Brazil and Florida/USA. The samples studied are citrus canker, citrus scab, HLB and zinc deficiency. The objective is to discriminate the diseases with similar visual symptoms, such as citrus canker from citrus scab and HLB from zinc deficiency for samples from Brazil and HLB from zinc deficiency for samples from the United States. The results show that it is possible to use the fluorescence imaging spectroscopy technique together with the classification methods for the discrimination of the diseases that have similar visual symptoms. Both classifiers showed high accuracy in the classification of the samples from Brazil and the United States, highlighting the efficiency of the technique under different conditions. (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 |