A Model for Predicting the Flowering Date and External Quality of Lily Grown in Traditional Chinese Solar Greenhouse
|School||Nanjing Agricultural College|
|Course||Ornamental Plants and Horticulture|
|Keywords||Lily Development Model Flowering date PTI External quality|
Crop growth and development model is a useful tool for the optimization of greenhouse crop and climate management. As one of the most popular cut flowers in the world, lily is favored by the Chinese people. In order to optimize the climate management for cut lily (Lilium spp.) grown in a greenhouse, a cut lily development and external quality simulation model was developed. Experiments with different planting dates and densities were conducted in a solar greenhouse in Lianyungang (34°42′N,119°30’E) from August,2008 to February,2009. The photo-thermal effects on the development and external quality of lily were quantitatively analyzed using the experimental data. Based on the quantitative analysis, a model for predicting the development stages, flowering date and external quality of lily was developed using an integrated photo-thermal index (Physiological Product of Thermal Effectiveness and PAR, PTI). Independent experimental data were used to validate the model.(1) In the sub-model for predicting the development stages and flowering date of lily, the effect of temperature and solar radiation on the development of lily was quantitatively analyzed. An integrated photo-thermal index of physiological product of thermal effectiveness and PAR (PTI) was used to predict the development stages and flowering date of lily. Independent experimental data were used to validate the model. The results show that the model can give predictions of the development stages and flowering date of lily crops satisfactorily. Based on the 1:1 line, the determination coefficient between the predicted and observed development stages is 0.97; and the root mean squared errors (RMSE) between the predicted and observed days from shoot emergence to leaf unfolding, visible bud and harvesting date are, respectively,3.8,4.2 and 7.3 days. The model developed in this study gives more accurate predictions than the GDD (Growing Degree Days) based model (with RMSE of 5.6,9.0 and 13.1 days, respectively, between the predicted and observed days from shoot emergence to leaf unfolding, visible bud and harvesting date). (2) In the sub-model for predicting the external quality of lily in solar greenhouse, the effect of temperature and solar radiation on the external quality of lily was quantitatively analyzed. Based on these quantitative relationships, a model for predicting the effects of PAR and temperature on the external quality indices of cut lily was developed.The relationship between plant height, number of leaves per plant and PTI was express with the negative exponent equation. The relationship between bud length, bud diameter and PTI was express with the exponential-liner equation. The results show that the model gives satisfactory predictions of the external quality indices of the cut lily grown under different plant dates and plant densities. The coefficient of determination (r2) and the root mean square error (RMSE) between the predicted and measured results were, respectively, 0.94 and 0.07m for plant height,0.91 and 4.3 for leaves number per plant,0.86 and 8.0mm, 0.85 and 8.5mm,0.87 and 6.8mm,0.89 and 6.0mm,0.88 and 5.8mm for bud length of one flower bud, two flower buds, three flower buds, four flower buds and five flower buds, 0.85 and 2.4mm,0.86 and 2.3mm,0.87 and 2.0mm,0.87 and 2.0mm,0.87 and 1.7mm for bud diameter of one flower bud, two flower buds, three flower buds, four flower buds and five flower buds.(3) In the sub-model for predicting the relative yield of lily in solar greenhouse, according to the data captured at harvesting, the relationship between the photo-thermal index accumulated through the total growth process and relative yield of cut lily was express with the liner equation. Independent experiment data were used to validate the model. Based on the 1:1 line, the coefficient of determination (r2) between the predicted and measured values for the relative yield of Rank first, second and third are 0.87,0.83 and 0.89, respectively; the root mean squared error (RMSE) are 6.6%,4.9%and 6.0%, respectively.Using the planting date, planting density, air temperature at 1.5m above ground and PAR above canopy inside the greenhouse as input, our model can give satisfactory predictions of the development, flowering date and external quality of cut lily in solar greenhouse. Hence, our model can be used for decision making for precision management of PAR and temperature in greenhouse lily production.