Modelling for precision weed management.
Recently, the need for the development of weed management systems with a reduced dependency on herbicides has increased because of concern about environmental side-effects and cost. The development of such systems requires new strategies based on improvements with respect to (1) prevention, (2) decision making and (3) weed control technology. For the development of improvements in all three aspects, quantitative understanding of weed population dynamics and crop-weed interactions is needed. Models that integrate the available quantitative knowledge can be used to design preventive measures, to develop long-term and short-term strategies for weed management, to assist in decision making to determine if, when, where and how weeds should be controlled and to identify new opportunities for weed control. Ecophysiological simulation models for crop-weed competition simulate growth and production of species in mixtures, based on ecophysiological processes in plants and their response to the environment. Such models help improve insight into the crop-weed system and can be used for purposes such as the development of simple predictive yield-loss models, threshold levels or the design of competitive crop plant types. For strategic weed management decisions, preventive measures and the identification of new opportunities for weed control, quantitative insight into the dynamics and spatial patterns of weed populations is also required. The complexity of the process and the long-term character of weed population dynamics make the use of models necessary. Different modelling approaches have been developed and are described briefly. Opportunities to use the available knowledge and models to improve weed management are discussed. Weeds occur in patches and their sensitivity to herbicides changes strongly with developmental stage, making precision techniques for herbicide application in time and space an option for reducing herbicide use. Limitations related to insight in biological processes as well as the state of technological development are discussed.
Kropff
M J
MJ
Department of Theoretical Production Ecology, Wageningen Agricultural University, The Netherlands.
Wallinga
J
J
Lotz
L A
LA
D000383:Agriculture / Q000379:methods*; D018556:Crops, Agricultural / Q000254:growth & development*; D017753:Ecosystem; D008954:Models, Biological; D015233:Models, Statistical; D006109:Poaceae