New project to develop detection tool for fungicide-resistant isolates

University of the Philippines in Diliman (UPD) will develop a detection tool for fungicide resistant isolates of fungal pathogens affecting vegetable and strawberry in Northern Philippines, through the Grants-in-Aid Program of the Philippine Council for Agriculture Aquatic and Natural Resources Research and Development of the Department of Science and Technology (DOST-PCAARRD).

In a project inception meeting with PCAARRD, UPD project leader, Dr. Leilani S. Dacones said that their team was driven to propose the project because fungal pathogens causing diseases in major crops significantly decrease yield and income of farmers.

Dr. Dacones said that research reports show that diseases caused by fungal pathogen such as Rhizoctonia spp caused marketable yield loss of up to 30% in potatoes. Losses in cabbage seed yield due to diseases caused by Alternaria spp rose to up to 59%. Disease caused by Botrytis spp led to 100% marketable yield losses in strawberry.
 
However, she said that “fungicides that are oftentimes used to manage fungal diseases have been reported to show indications of reduced effectivity, or produce fungicide-resistant pathogens.

The project team will develop multiplexed Polymerase Chain Reaction (PCR)-based tool for fungicide resistant isolates that infect economically important vegetable crops and strawberry in Benguet. Samples previously collected from Nueva Vizcaya and Ilocos Sur will also be included in the analyses.

This tool was further explained by Dr. Dacones. She said that molecular tools for detection of fungicide resistance and sensitivity of isolates in the field will provide information that in turn, can be used in developing effective fungicide resistance management strategies. “The project will include designing molecular markers that can specifically amplify gene targets of three fungicide classes. Through an initial characterization of the patterns of these genes of interest associated with the response to fungicides, the project team will be able to delineate those that are either resistant or sensitive.”

The detection tool will be a more rapid method for disease diagnosis, monitoring, and assessment. The information it will generate is important in providing recommendations to farmers on the use of fungicides. The project’s technology output is expected to reduce cost of managing diseases and unnecessary use of fungicides. Production yield is also expected to improve with effective and appropriate disease management strategy.