SIMULATION OF GREENHOUSE CUCUMBER LEAF AREA BASED ON RADIATION AND THERMAL EFFECTIVENESS

Abstract

Background and Aims Leaf area index (LAI) is one of the most important crop parameters in photosynthesis driven crop growth simulation models. Temperature and radiation are important climate factors affecting crop leaf growth. The aim of this study is to quantitatively investigate the effects of both temperature and photosynthetically active radiation (PAR) on the leaf growth of greenhouse cucumber (Cucumis sativus). Methods Experiments with different cultivars and sowing dates were conducted in greenhouses of Shanghai Academy of Agricultural Sciences during August,2003 and July,2004. We used the following quantitative relationships based on experimental data to model the relationship between the product of thermal effectiveness and PAR (TEP): accumulated TEP to the number of unfolding leaves per plant and the number of old leaves removed per plant,leaf position relative to the rate of increase in leaf length and the maximum leaf length; and the ratio of leaf area to leaf length. Based on these quantitative relationships,a leaf area simulation model for greenhouse cucumber was developed. Independent experimental data were used to validate the model. The simulated results of the model developed in this study were compared with those of the traditional GDD based model (which predict leaf area based on growing degree days) and SLA based model (which predict leaf area based on the specific leaf area and leaf dry weight). Key Results The coefficient of determination (R2) and the root mean squared error (RMSE) between the simulated and the measured leaf area index (LAI) based on the 1∶1 line are 0.879 2 and 0.398 0,respectively. The prediction accuracy of this model is 37% and 74% higher,respectively,than that of the traditional GDD and SLA based models. Conclusions The model developed in this study can predict LAI satisfactorily using air temperature,radiation,date of the first leaf unfolding and planting density. The simple model input makes the model user friendly and more applicable in greenhouse crop and climate management practices.