Modelling the spatio-temporal deployment of resistant varieties to reduce the incidence of rice tungro disease in a dynamic cropping system

A dynamic cropping system was represented by a square lattice of fields in which crops were successively harvested and replanted. A spectrum of crop ages existed at any one time and the virus disease persisted by spread of inoculum between crops. Such a situation is typical of many areas of tropical irrigated rice cultivation in which rice tungro virus disease (RTVD) occurs. Using a mathematical model of the epidemiology of RTVD in the cropping system, the deployment of fields of a genotype expressing some resistance to the disease was investigated. Previous studies on the effect of genotype mixtures on disease progress within a single crop have shown that both the rate of disease increase and the rate of focus expansion were proportional to the logarithm of the fraction of susceptible plants in the mixture. Here, looking at long-term disease incidence in a dynamic cropping system, it was found that this same 'logarithmic rule' applied, provided that resistant crop deployment was spatially random. A relatively large proportion of fields had to be planted with resistant varieties in order to have sufficient area-wide impact on inoculum to reduce disease incidence in fields of susceptible varieties. In many rice cropping systems there are two growing seasons per year and the modelling indicated that the best strategy was to concentrate deployment of resistant varieties in the season of greatest disease spread. Attempts to minimize inoculum carry-over to the 'high spread' season by concentrating resistant varieties in the previous season had little effect over a range of simulated conditions. In considering recommendations for the management of RTVD, a conflict existed between the reduction of disease incidence strategically and in the individual fields of a newly deployed variety. To maximize area-wide strategic impact, small genotype units and random patterns were best, but to protect individual fields, large units and concentrated deployment were best.