Empirical Predictions of Wheat Head Blight in the Northern Argentinean Pampas Region

• Published in: Crop science 2001-09, Vol.41 (5), p.1541-1545
• Main Authors: Moschini, Ricardo C., Pioli, Rosanna, Carmona, Marcelo, Sacchi, Oscar
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Crop diseases; Crops; Fundamental and applied biological sciences. Psychology; Fungal plant pathogens; Fusarium graminearum; Grain industry; head blight; Meteorology; Pathology, epidemiology, host-fungus relationships. Damages, economic importance; Phytopathology. Animal pests. Plant and forest protection; Prediction models; Triticum aestivum; Wheat
• ISSN: 0011-183X; 1435-0653
• DOI: 10.2135/cropsci2001.4151541x

In Argentina, head blight (caused by Fusarium graminearum Schwabe), is a highly risky disease of wheat (Triticum aestivum L. emm. Thell), although its occurrence is sporadic, depending on prevalent environmental variables. This unpredictability has stimulated the development of predictive models of head blight occurrence that, if successful, would help growers in the selection of control strategies. As a result of our earlier work, empirical equations for predicting head blight incidence were developed at Pergamino INTA Experiment Center (Lat., 33° 56′S), associating temperature and moisture variables with mean disease observations from many wheat cultivars. In the current study our objective was to validate two of these meteorological based equations developed for Pergamino to predict wheat head blight incidence and severity at Zavalla (Lat., 33° 1′S) and Oliveros (Lat., 32° 33′S) in moderately susceptible to susceptible cultivars for the years 1993 to 1995. Even though the t‐test determined nonsignificant differences between mean observed disease values versus predicted values, a graphic method and a deviation examination showed an underestimation at high disease levels. Simple analyses of sensitivity were able to detect the improvement in incidence and severity goodness of fit estimations that resulted from increasing the maximum temperature threshold and the heat accumulation defining the length of the wheat critical period for infection. This study showed that meteorological based empirical equations developed for Pergamino can be useful for predicting disease intensity at more northern locations in the Pampas region, making only a few changes in temperature thresholds.