Suratanee A., Siripant Suchada, Lursinsap Chidchanok.
2004. Modeling the soybean growth in different amount of nitrogen, phosphorus and potassium using neural network.
In : Proceedings of the 4th International workshop on functional-structural plant models (FSPM), abstracts of papers and posters, 7-11 June 2004, Montpellier, France. Godin Christophe (ed.), Hanan Jim (ed.), Kurth Winfried (ed.), Lacointe André (ed.), Takenaka Akio (ed.), Prusinkiewicz Przemyslaw (ed.), Dejong Thedore M. (ed.), Beveridge Christine (ed.). CIRAD-AMIS-UMR AMAP
Résumé : This paper proposed a simulation model of soybean growth which is effected by major nutrient factors, nitrogen, phosphorus and potassium. A feedforward neural network is used as a basis of the modelling. The combination of different percentage of nitrogen, phosphorus, potassium, time steps and the collected height data of the soybean are used as inputs. The model can predict the height at designated time intervals, whereby the result can be visualized with L-systems.
Mots-clés Agrovoc : modèle de simulation, Glycine max, croissance, azote, phosphore, potassium
Classification Agris : U10 - Informatique, mathématiques et statistiques
F61 - Physiologie végétale - Nutrition
Auteurs et affiliations
- Suratanee A., AVIC (THA)
- Siripant Suchada, AVIC (THA)
- Lursinsap Chidchanok, AVIC (THA)
Autres liens de la publication
Source : Cirad - Agritrop (https://agritrop.cirad.fr/523875/)
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