Abstract

The advent of robust sensing technologies in remote and proximal sensing systems has led to the generation of accurate weed maps thus enabling precise weed management (PWM). The data from the weed maps are crucial input for crop-weed discriminating algorithms and also decision support models that quantify the risk posed by the weeds on the fields. The use of prescription maps combined with herbicide application technologies such as patch spraying or variable rate application has great potential in weed management. Continuous efforts are being made whereby the three procedures i. e. sensing, decision support and herbicide application are carried out in one operation (real time). There are indications that manual weed sensing is not economically sustainable thus remote sensing is the most attractive option. The pilot and spotter training costs can be offset by the herbicide savings due to reduced herbicide usage, which is also ecologically advantageous. Newly advanced image analysis technologies have led to the transcendence of the limitations associated with pixel based approaches. However, the current technologies still cannot sense a large number of unknown species and simultaneously make real time decisions on the type of herbicide and level of control. Site specific information in particular weed distribution, species composition and density if of paramount importance for precise weed management.