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Title: Detection of Colletotrichum coccodes causing anthracnose fruit rots in tomato using electronic nose
Other Titles: الكشف عن فطر coccodes Colletotrichum المسبب لعفن الفاكهة )anthracnose )في البندورة باستخدام األنف اإللكتروني
Authors: Shahwan, Shorouq
Keywords: Electronic Nose;Anthracnose fruit rots;Colletotrichum coccodes;Multivariate data analysis
Issue Date: 5-Jun-2022
Publisher: Palestine Technical University -Kadoorie
Citation: Shahwan,S.(2022). Detection of Colletotrichum coccodes causing anthracnose fruit rots in tomato using electronic nose.
Abstract: Colletotrichum coccodes are the most known Colletotrichum isolates to be hard to control. Once the tomato gets infected with C. coccodes, the anthracnose develops within a few days. Therefore, early detection of the fungal infection is vital for successful prevention and effective treatment of the infected fields. This study aimed to employ the electronic nose (EN), with metal-oxide sensors (MOS), to sense the presence of C. coccodes on tomato fruits at different stages and concentrations. Identification of C. coccodes was carried out using the polymerase chain reaction (PCR), where the identification of C. coccode fungus was achieved using three different primer sets: ITS1F/ITS4, Cc1F1/Cc2R1, and Cc1NF1/Cc2NR1. In which ITS1F/ITS4 was a general primer set for most Ascomycetes and Basidiomycetes. Cc1F1/Cc2R1 primer set was a specific primer to Colletotrichum spp., which gives a 447 bp product, and Cc1NF1/Cc2NR1 was a unique primer to C. coccodes, which results in a 349 bp product. In addition, three homogeneous tomato samples were injected with three different concentrations: 30*103 , 30*104 and 30*105 conidial fungal suspension, three other tomatoes were used as negative controls, and all were measured using an EN device every two days for ten days. Specific primers (ITS1F/ITS4, Cc1F1/Cc2R1, and Cc1NF1/Cc2NR1) could recognize and specify C. coccode fungus using a suitable PCR program and sequencing. xiv The data acquired from the EN sensors were analyzed using principal component analysis (PCA). It was found that the EN device could sense pathogen occurrence at early stages, i.e. after two days of the infection, and before the appearance of any symptoms, where the PCA scores plot explained 100% of the total variance. In addition, the overall scores plot explained 100% of the total variance indicating the ability of EN to differentiate between different stages of infection duration ( i.e. second, fourth, sixth, eighth, and tenth day). Moreover, the concentration of the infected samples was clearly differentiated on the sixth, eighth and tenth days.
Appears in Collections:Master Thesis/ Agricultural Biotechnology

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