SEMAGI - An expert system for weed control decision making in sunflowers

To use herbicides efficiently, decision makers must estimate when weed populations exceed economic treatment thresholds. An interactive microcomputer program named SEMAGI has been developed for sunflower (Helianthus annuus L.) to evaluate the potential yield reduction from multi-species weed infestations and from the parasitic weed broomrape (Orobanche cernua/O. cumana), and to determine the appropriate selection of herbicides. It combines relational databases on herbicides, weeds and their interaction. Originally, 34 weed species and twenty-six herbicides were introduced specifying each weed/herbicide efficacy combination. For other agricultural situations, SEMAGI permits the introduction of new weeds (up to 80), new herbicides (up to 40) and each herbicide-weed efficacy combination. The expert system processes and selects the herbicide(s) under the constraints of herbicide efficacy data and of a weed-crop competition model. This relates weed-infested crop yield (SYI), potential weed-free yield (SYF), weed density (RD) and weed biomass (RBio). The user evaluates the weed infestation by field survey or density counting and the program converts it into equivalent weed biomass. Weed species are classified in three groups according to their final size. A relationship between weed density, weed size and equivalent biomass is established for any weed group. In addition, SEMAGI provides an economic study of any herbicide treatment selected or introduced by the user, based on herbicide treatment cost, expected yield increase from the weed control treatment and sunflower selling price. A computer capable of running MS-DOS or PC-DOS version 2.0 or greater with a minimum of 2 M bytes of RAM is required. This approach should be applicable to other crops.