Detection of associated fungi in mulberry using a quantitative realtime PCR
2017
Castañeda-Cuizon, N. | Undan, J.R.
Early and precise identification of pathogens is considered essential in environmental monitoring and plant disease control. This research was designed to identify the fungi associated found in diseased mulberry through Quantitative Real-Time Polymerase Chain Reaction (qPCR) as a rapid detection method. The rDNA of the ITS region was used to identify the fungi associated with diseased mulberry. Subsequently, specific primers from the ITS region of these specific fungi were designed using Primer 3. Newly designed primers successfully detected the four fungi using qPCR. The results showed significant correlation with the qPCR results of the samples along with the standards. The r square values for N. sphaeric arranged from 99.7% to 99.8%; for C. lunata, 99.4% to 100%; for A. aculeatus 99.8% to 99.9% and for L. theobromae, 99.8% to 99.9%. With this approach, approximately 20 cycles run or about 30 minutes could be enough to sensitively and accurately detect and identify the fungi on hand.
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Este registro bibliográfico ha sido proporcionado por University of the Philippines at Los Baños