A Model For Predictingrowthdynamic Of Cut Lilium In Greenhouse

A model for predicting growth dynamic of cut lilium in greenhouse was developed based on the effects of temperature and radiation on the growth of cut lilium. Experiments of cut lilium(Lilium spp. cv. Sorbonne and Siberia), with different planting dates and densities, were conducted in a solar greenhouse located at Lianyungang, JiangSu (34°42'N, 119°30'E). Based on the quantitative analysis of the experimental data, a photo-thermal index(PTI) based model for predicting canopy leaf area index (LAI) and a PTI based model for predicting dry matter partitioning index (PI) of greenhouse cut lilium were developed. These two models were then integrated with the general photosynthetic driven crop growth model SUCROS to develop a model for predicting the growth dynamic of cut lilium grown in greenhouses. Independent experimental data were used to validate the model. The main results of this study are summarized as follows:(1) Based on the experimental data, a photo-thermal index(PTI) based model for predicting greenhouse cut lilium leaf area was developed. Independent experimental data were used to validate the model. The results show that the model can give predictions of the leaf area index (LAI) of greenhouse cut lilium satisfactorily. The result showed that the coefficient of determination (r2) between the predicted and measured results were, respectively,0.92 for cv. Siberia and 0.9 for cv. Sorbonne; and the root mean square error (RMSE) between the predicted and measured results were, respectively,0.67 for cv. Siberia and 0.31 for cv. Sorbonne. The prediction accuracy was 10%and 27%, respectively higher than that using the Growth Degree Days (GDD) based and specific leaf area (SLA) based leaf area model for cv. Siberia. The prediction accuracy was 11%and 29%, respectively higher than that using the Growth Degree Days (GDD) based and specific leaf area (SLA) based leaf area model for cv. Sorbonne.(2) Based on the experimental data, a photo-thermal index(PTI) based model for predicting dry matter partitioning index was developed. This model and the PTI based LAI model were then integrated with the generic crop growth model SUCROS to develop a model for predicting the growth dynamic of cut lilium grown in greenhouses. Independent experimental data were used to validate the model. The results show that the model can give good predictions of the dry matter production of cut lilium. The result showed that the coefficient of determination (r2) between the predicted and measured results were, respectively,0.9 for the total dry weight of cv.Siberia and 0.89 for the total dry weight of cv. Sorbonne; and the root mean square error (RMSE) between the predicted and measured results were, respectively,1.47g-prl-1 for the total dry weight of cv. Siberia and 1.5g-pl-1 for the total dry weight of cv. Sorbonne. The prediction accuracy was 29% and 28%, respectively higher than that using the specific leaf area (SLA) based model for predicting the total dry weight of cv. Sorbonne and cv. Siberia. The result showed that the coefficient of determination (r2) between the predicted and measured results were, respectively,0.91, 0.9,0.9,0.85 for the stem dry weight, leaf dry weight, flower dry weight and bulb dry weight of cv. Siberia and 0.89,0.89,0.89,0.85 for the stem dry weight, leaf dry weight, flower dry weight and bulb dry weight of cv. Sorbonne; and the root mean square error (RMSE) between the predicted and measured results were, respectively, 0.42g-pl-1,0.38g-pl-1,0.25g-pl-1,0.6 g-pl-1 for the stem dry weight, leaf dry weight, flower dry weight and bulb dry weight of cv. Sorbonne and 0.51g-pl-1,0.37g-pl-1,0.24g-pl-1,0.52g-pl-1 for the stem dry weight, leaf dry weight, flower dry weight and bulb dry weight of cv. Sorbonne.The model developed in this study can predict the growth dynamic of cut lilium grown in greenhouses with such input as hourly data of radiation and temperature inside greenhouse and planting density, hence, can be used for the optimisation of planting date and density for greenhouse cut lilium production.