Abstract
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.
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Claims 4
Claim · model-written summary
A t-test found no significant difference between mean observed and predicted head blight values.
Verbatim
e0“determined nonsignificant differences between mean observed disease values versus predicted values”
Claim · model-written summary
A graphic method and deviation examination showed the equations underestimated head blight at high disease levels.
Verbatim
e0“a graphic method and a deviation examination showed an underestimation at high disease levels”
Claim · model-written summary
Sensitivity analyses showed that increasing the maximum temperature threshold and the heat accumulation defining the wheat critical period improved goodness of fit of incidence and severity estimates.
- Taxon
- wheat
Triticum aestivume0 - Treatment
- increasing the maximum temperature threshold and the heat accumulation defining the length of the wheat critical period for infectione0
- Outcome
- incidence and severity goodness of fit estimationse0
- Direction
- improvemente0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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”
Claim · model-written summary
The authors conclude the Pergamino equations can be useful for predicting disease intensity at more northern Pampas locations with only a few changes in temperature thresholds.
- Outcome
- predicting disease intensity at more northern locationse0
- Qualifier
- making only a few changes in temperature thresholdse0
- Setting
- Pampas regione0
Not reportedTaxon
Verbatim
e0“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”
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