Measuring and modeling the effects of inoculation date and aphid flights on the secondary spread of Beet mosaic virus in sugar beet.

• Autor(a) principal: DUSI, A. N.
• Data de Publicação: 2000
• Outros Autores: PETERS, D., WERF, W. van der.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/767676
• topic: BtMV; Inoculation; Beta Vulgaris; Beterraba Açucareira; Inoculação; Vírus; sugar beet

The effect of the inoculation date on the spread of Beet mosaic virus (BtMV) in sugar beet field plots was studied. Two plants in the centre of each plot were inoculated with BtMV using Myzus persicae. The spread of the infection around these sources was monitored by inspecting the plants on two diagonal transects through the centre of the plot. Early inoculations resulted in a greater spread than late inoculations, but any inoculation before the onset of the aphid migration resulted in a similar-sized spread. The spread was concentrated in patches around the inoculated plants, and its rate was explained by vector pressure, as shown by regression analysis and a mechanistic simulation model. This vector pressure was quantified using data obtained by catching aphids in a green water trap in the crop, catching aphids in a 12 m high suction trap at a distant location, and infection of bait plants from adjacent virus source plants. The daily total aphid catches obtained by a suction trap provided the best statistical explanation for the spread of this virus. The parameter r, describing the relationship between vector pressure and the rate of disease progress, was remarkably robust. This parameter varied less than 10% between treatments (infection date) within a single experiment, and less than a factor two between four experiments performed at different sites in two years. The robustness of this parameter suggests that the spread of a potyvirus may be predicted on the basis of the initial infection date and vector abundance.