Numerical Prediction of Rose Growth

Abstract A new mathematical model is presented for the prediction of rose growth in a greenhouse. Given the measured ambient environmental conditions, the model consist of a local photosynthesis model, predicting the photosynthesis per unit leaf area, coupled to a global greenhouse model, which predicts the mass production of the rose crop per unit area of greenhouse in time. The numerical implementation of this mathematical rose model is validated against harvest data of the rose variety “Red Berlin” from January 1st 2001 through to January 20th 2002. Global trends are predicted reasonably well, and larger deviations between model and data in certain weeks are due to actual pest and fertigation mismatches not present in the model. We hypothesize that further improvements in the relation between the change in the crop’s mass and the total photosynthesis, the dependence of the sprouting sites on the total photosynthesis and the parameter fitting can strengthen the leading-order model considered.