The Evolution of Fungicide Resistance

• Published in: Advances in Applied Microbiology Vol. 90; p. 29
• Main Authors: Lucas, John A, Hawkins, Nichola J, Fraaije, Bart A
• Format: Book Chapter Journal Article
• Language: English
• Published: United States Elsevier Science & Technology 2015
• Subjects: Biological Evolution; Biotechnology; Crops, Agricultural - microbiology; Drug Resistance, Fungal; Fungi - drug effects; Fungi - genetics; Fungi - metabolism; Fungicides, Industrial - pharmacology; Microbiology (non-medical); Plant Diseases - microbiology; Molecular diagnostics; Directional selection; Risk assessment; Prediction of resistance; Resistance management; Cereal pathogens; Single-site inhibitors; Resistance mechanisms
• ISBN: 0128022752; 9780128022757
• ISSN: 0065-2164
• DOI: 10.1016/bs.aambs.2014.09.001

Fungicides are widely used in developed agricultural systems to control disease and safeguard crop yield and quality. Over time, however, resistance to many of the most effective fungicides has emerged and spread in pathogen populations, compromising disease control. This review describes the development of resistance using case histories based on four important diseases of temperate cereal crops: eyespot (Oculimacula yallundae and Oculimacula acuformis), Septoria tritici blotch (Zymoseptoria tritici), powdery mildew (Blumeria graminis), and Fusarium ear blight (a complex of Fusarium and Microdochium spp). The sequential emergence of variant genotypes of these pathogens with reduced sensitivity to the most active single-site fungicides, methyl benzimidazole carbamates, demethylation inhibitors, quinone outside inhibitors, and succinate dehydrogenase inhibitors illustrates an ongoing evolutionary process in response to the introduction and use of different chemical classes. Analysis of the molecular mechanisms and genetic basis of resistance has provided more rapid and precise methods for detecting and monitoring the incidence of resistance in field populations, but when or where resistance will occur remains difficult to predict. The extent to which the predictability of resistance evolution can be improved by laboratory mutagenesis studies and fitness measurements, comparison between pathogens, and reconstruction of evolutionary pathways is discussed. Risk models based on fungal life cycles, fungicide properties, and exposure to the fungicide are now being refined to take account of additional traits associated with the rate of pathogen evolution. Experimental data on the selection of specific mutations or resistant genotypes in pathogen populations in response to fungicide treatments can be used in models evaluating the most effective strategies for reducing or preventing resistance. Resistance management based on robust scientific evidence is vital to prolong the effective life of fungicides and safeguard their future use in crop protection.