Potato Nematode Decision Support with AI
PAPAS is developing computational tools with Artificial Intelligence (AI) and machine learning (ML) to support potato nematode detection, mitigation, and management.
PAPAS is developing computational tools with Artificial Intelligence (AI) and machine learning (ML) to support potato nematode detection, mitigation, and management.
Developing molecular markers of Columbia root-knot nematode (M. Chitwoodi) aids in faster identification of the potato nematode races.
Cysts from golden nematode, a yield-reducing potato pest, can survive in the soil for decades, making eradication difficult.
Research addressing the potential profitability of nematode resistant potato varieties.
Developing potato cyst nematode resistance in widely-grown russet market class potato varieties.
Researching molecular markers that identify different potato genes associated with nematode resistance.
Investigating the chemical composition of litchi tomato for potential nematicide formulations.
Continuous use of potato varieties with the same source of resistance causes genetic selection for stronger and/or more virulent pale cyst nematode populations.
Pale cyst nematode (G. pallida) is found 49 countries/regions and golden nematode (G. rostochiensis) is found in 74 countries/regions as of 2022.
Information about the life cycle and spread of potato cyst nematodes (Globadera spp.).