Soft-computing methods in greenhouse environmental and crop modelling

Ferreira, P. M.; Ruano, Antonio

http://hdl.handle.net/10400.1/2270

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
utad-efita.pdf		675.48 KB	Adobe PDF	Download

Send Feedback

Authors

Ferreira, P. M.

Ruano, Antonio

Abstract(s)

This paper presents results regarding ongoing experimental research in a hydroponic greenhouse located at the University of Algarve in the South of Portugal. The work focuses on environmental predictive control and production optimisation for a tomato crop. Recent results on the application of Soft- Computing methods to external climate predictive models, and also on strategies for tomato growth modelling are presented. The climate and environmental quantities are modelled by using radial basis function neural networks whose input-output structure is selected by a multi-objective genetic algorithm. Image processing methods are applied to the extraction of plant features from pictures taken periodically.

Keywords

Greenhouse environmental modelling Crop growth modelling Soft computing methods

URI

http://hdl.handle.net/10400.1/2270

Citation

Ferreira, P. M.; Ruano, A. E. Soft-computing methods in greenhouse environmental and crop modelling. Trabalho apresentado em he 5th Conference of the European Federation for Information Technology in Agriculture, Food and Environment, and the 3th World Congress on Computers in Agriculture and Natural Resources, In Proceedings of the 5th Conference of the European Federation for Information Technology in Agriculture, Food and Environment, and the 3th World Congress on Computers in Agriculture and Natural Resources, Vila Real, 2005.