Influence of freezing on the survival of Magnaporthe oryzae and weather conditions that favor blast epidemics in rice

Abstract

Wheat blast, caused by Magnaporthe oryzae pathotype triticum, has emerged as a serious problem for wheat production in South America and recently emerged as a threat to wheat production in Bangladesh. To prepare for the possible introduction of wheat blast in to the United States, it would be helpful to identify areas of the country most at risk for blast epidemics. Because wheat blast occurs primarily in tropical and subtropical regions of the world, cold winter temperatures may restrict the establishment of the blast pathogen in the United States. Therefore, the first objective of this research was to quantify the freeze-thaw tolerance of the wheat blast pathogen in naturally infected wheat rachises from Bolivia and to measure the viability of the conidia after exposure to various treatments. The results indicate that exposing the fungus in moist residue to multiple freeze-thaw cycles is more damaging than exposing the fungus in moist residue to longer, single freezes. When in dry residue, the fungus was not harmed by the freeze-thaw cycles. Freezing and thawing of the wheat blast fungus in moist residue significantly affected its ability to produce viable conidia. The second objective of this research was to identify environmental conditions that could be conducive for wheat blast epidemics by examining historical epidemics of rice blast, caused by Magnaporthe oryzae pathotype oryza. The dataset used in this analysis consisted of 60 site-years of historical observations of rice blast levels from Arkansas, Louisiana, and Texas. These observations were coupled with monthly and weekly summaries of hourly weather variables based on temperature, relative humidity, precipitation, and regional moisture indices. Classification trees and logistic regression were used to identify variables associated with rice blast epidemics. The results indicate that rice blast epidemics are favored by cooler April temperatures and higher levels of precipitation in June. Preliminary models for rice blast based on these variables were able to correctly classify epidemic years with >75% accuracy. In the future, the results of this project will be used as part of a risk assessment for a wheat blast introduction and establishment in the United States.