Abstract
Within the oomycetes, the Peronosporales consist of many fungal pathogens capable of causing substantial losses to important crops, such as, for example, Plasmopara viticola on grapes and Bremia lactucae on lettuce (Spencer, 1981). Growers are faced with many problems in controlling downy mildew diseases: (i) many varieties are not completely resistant to downy mildew infections or major gene resistances bred into cultivars can become ineffective within a few seasons by adaptation of downy mildew populations; (ii) downy mildew pathogens often have a short period of latency following infection leading to rapid disease increases over time, (iii) populations of downy mildew pathogens can acquire resistance to fungicides; (iv) governments and supermarket chains have imposed limits on the number of fungicide applications during crop production and fungicide residues at the time of harvesting; and (v) the number of registered fungicides has been substantially reduced. Disease forecasting systems could assist growers to achieve effective control of downy mildew within these constraints. Forecasting models could predict when crops are at risk of significant downy mildew development so that they can be treated to avoid or minimise such risks.
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Gilles, T. (2004). Forecasting Downy Mildew Diseases. In: Spencer-Phillips, P., Jeger, M. (eds) Advances in Downy Mildew Research — Volume 2. Developments in Plant Pathology, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-2658-4_2
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