Identifying control strategies for tomato leaf curl virus disease using an epidemiological model
1. A number of insect vectors of plant-virus diseases make only transitory visits to the crop in which the economic effects of the disease are important. The incidence of disease in the crop depends primarily on the immigration of vectors from alternative hosts which act as a reservoir of both the virus and vector.
2. An epidemiological model was developed to represent this situation and parameters were estimated for the case of tomato leaf curl virus disease (TLCVD) (Geminiviridae, Subgroup III) in India. From an analysis of the model, the following possibilities for the management of TLCVD emerged.
3. It was clear that varietal resistance to infection could be an important component of disease management but whether, once infected, the tomato plants acted as a source of inoculum had little impact on disease incidence in the tomato crop.
4. A very low rate of simulated vector immigration into a tomato crop sufficed to cause almost total infection. Around Bangalore, vectors may migrate into tomato crops in numbers in excess of those required for disease ‘saturation’, explaining why, using conventional insecticides, very efficient and intensive vector control is currently required to reduce disease incidence.
5. Disease incidence was sensitive to vector mortality only when vector numbers were low. In most cases, the immigration of viruliferous vectors made disease incidence insensitive to the mortality of vectors within the tomato crop.
6. A strategy for disease management which targets more than one of the parameters to which the model proved most sensitive is likely to be necessary. In particular, the use of protective netting combined with the growing of resistant varieties has the potential to reduce both B. tabaci immigration to the crop and to reduce virus inoculation by those insects which do reach the crop.
Holt, J.; Colvin, J.; Muniyappa, V. Identifying control strategies for tomato leaf curl virus disease using an epidemiological model. Journal of Applied Ecology (1999) 36 (5) 625-633. [DOI: 10.1046/j.1365-2664.1999.00432.x]