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Economic Analysis of Weed Management Options in Rice Production in the Philippines
The study deals with the development of decision support system (DSS) for weeds in rice crops. This model will integrate the biological, agronomic, and economic components of Philippine rice farming system. The DSS that will be developed for rice will be distinct from those DSSs constructed to investigate profitable integrated weed management (IWM) strategies in other important crops in global agriculture. One difference is the focus on rice systems. Another is the inclusion of different establishment options for rice crops in the model such as transplanted and direct-seeded rice. Moreover, the simulation model that will be constructed in the study will be optimised using a new method developed for simulation-optimisation. The simulated annealing technique will be used to consider decision problems that are simultaneously constrained and stochastic. This will be the first application of this simulated annealing algorithm outside of computer science. Lastly, this study will incorporate an analysis of the trends and factors affecting herbicide use by rice farmers.
In an effort to avoid high use of herbicides while still getting good yields and preventing more environmental damage in the future, rice farmers are encouraged to use IWM strategies. However, evaluating possible IWM strategies is complex and difficult for farmers and scientists. Bio-economic simulation models can help farmers make long-term understanding about weed management. But it appears that no DSS exists for weed management in rice, despite this crop being the most important commodity in the Philippines and Asia. Thus, this study aims to develop the first DSS for weeds in rice crops. This decision tool will provide information for farmers about the long-term effects of different weed management strategies. It can also be useful for weed researchers in dealing with other weed problems.