Simulating rice stem borer, Scirpophaga incertulas Wlk., damage for developing decision support tools

InfoCrop, a generic crop-pest simulation model, was used to validate yellow stem borer, Scirpophaga incertulas Wlk., damage mechanism on two rice cultivars, Pusa Basmati 1 and Ratna. Data sets consisted of three experiments, one under natural infestation of the pest and two involving artificial detillering. The simulated yields showed less than 10% variation from the observed yields, except in one treatment, where the difference was 10.5%. The simulated yield losses were also proximal to respective observed yield losses (R-2 = 0.922, RMSE = 3.825), indicating proper validation of damage mechanism of the stem borer. As the model simulated the pest damage appropriately under natural injury, as well under artificial detillering; artificial detillering seemed comparable to natural injury of the stem borer in its effect on rice growth and yield. Validated InfoCrop was used to simulate economic injury levels (EILs) of the stem borer at different rice growth stages for varied control expenditure, incurred on two and three sprays of monocrotophos and one granular application of carbofuran, and for three market prices of produce. The EIL consistently decreased with advancing crop age and it exhibited a positive relationship with control expenditure and a negative relationship with market value of the produce. The simulated EILs were observed to be comparable to empirical injury levels that were previously established. The validated model was also used to devise iso-loss curves that depicted same yield loss for different combinations of the stem borer injury and crop age. Crop simulation model-based EILs and iso-loss curves are useful in monitoring the stem borer injury and in need assessment for pesticide application, thereby avoiding unnecessary expenditure and environmental contamination. Due to their mechanistic nature, crop models can be used to formulate location-specific decision support tools and therefore, help improve decision making in pest management. (c) 2008 Elsevier Ltd. All rights reserved.