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Updated: Nov 20, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Data for spatio-temporal modelling and optimisation of multi-product rice value chains
Stephen S Doliente1,2, Sheila Samsatli1
1Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
Abstract:
A current and fully-referenced dataset of resources and technologies for rice provision system is presented in this paper. These data served as model input data for the first multi-objective spatio-temporal optimisation of Philippine rice value chains. Data on available farmland area and their characteristics, such as paddy rice yield, rice farming costs and GHG emissions, are reported. As scenarios were developed for optimal rice value chains of integrated food and non-food production, estimates on the spatio-temporal demands on food, energy, fuels and chemical are presented. Data on sale prices and GHG emission factors of the raw materials and products are also compiled. Processing and transporting technologies involved in the modelling have their economic and operating parameters presented in this paper. This dataset has been collated through academic journals, technical papers and government agencies; all of which have been properly referenced. These data are valuable to various stakeholders of the rice industry across the globe aiming to understand rice value chains optimisation studies and to conduct further scenario development under different conditions and assumptions.
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