A neural network experiment on the site-specific simulation of potato tuber growth in Eastern Canada

The objective of this work was to optimize a neural network (NN) for modelling potato tuber growth and its in-field variations in eastern Canada. In addition to climatic inputs, the cumulative and maximal leaf area index (LAI) were incorporated to account for in-field scale variability. Soil and gen...

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Veröffentlicht in:	Computers and electronics in agriculture 2010-08, Vol.73 (2), p.126-132
Hauptverfasser:	Fortin, Jérôme G., Anctil, François, Parent, Léon-Étienne, Bolinder, Martin A.
Format:	Artikel
Sprache:	eng
Schlagworte:	accuracy Agricultural Science Agronomy. Soil science and plant productions Biological and medical sciences climatic factors Computer Science Computer simulation Crop growth model crop models Datavetenskap (datalogi) Electronics Errors Failure Fundamental and applied biological sciences. Psychology Jordbruksvetenskap Leaf area index Mathematical analysis Mathematical models model validation Neural network Neural networks Nonlinearity on-farm research potatoes rain Regression simulation models Solanum tuberosum Solar radiation spatial variation SUBSTOR temporal variation tubers
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