Simulation Model On Development, Growth And Quality For Cut Tulip In Solar Greenhouse

Tulip (Tulip gesneriana) is one of the famous top grade cut flowers around the world and it becomes the main festival cut flower in China. Presently, tulip is cultivated in the solar greenhouse to meet market demand at lowest cost at north drainage area of the Huai river. Crop growth simulation model is a very useful tool for the optimization of climate management on greenhouse crop. In order to solve the problem such as low quality and untidy florescence during production of cut tulip in solar greenhouse, we developed a simulation model on development, growth and quality for cut tulip cultivated in solar greenhouse, which can assistant planting management and environment optimization, improve flower quality and economy benefit. For this purpose, three experiments with different planting dates and planting densities were conducted in a solar greenhouse located at Lianyungang, Jiangsu (34°42'N,119°30'E) from Nov.2007 and Feb.2008. Based on the physiological and ecological process on growth, development and quality formation of cut tulip and the quantitative analysis on the data of environment and plant, a photo-thermal index (PTI) which means intercepted product of thermal effectiveness and PAR per plant was used to develop a simulation model on development, growth and quality for cut tulip that includes three sub-model:simulation model on development stages and florescence, simulation model on the dry matter production and dry matter partitioning, simulation model on external quality of cut tulip. The main research contents are as follows:1. A model for development simulation and flower date prediction of cut tulip in solar greenhouseBased on the effects of temperature and photo-synthetically active radiation on tulip development, the index of intercepted product of thermal effectiveness and PAR per plant (PTI) was used to predict cut tulip development stages and harvest date. Data from the first planting experiment were used to develop the model and determine the PTI required at every development stages of cut tulip, and 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 cut tulip satisfactorily. Based on the 1:1 line, the determination coefficient (R2) between the predicted and observed development stages is 0.95; and the root mean squared errors (RMSE) between the predicted and observed days of sprouting stage, leaf unfolding stage, bud visible stage and harvesting stage are 0.7,1.3,2.9 and 1 days, respectively. Compared with the model based on the Growth Degree Days(GDD), the prediction accuracy of the model developed is significantly higher than that of the GDD-based model(RMSE are 0.7,7.5,5.2 and 1.7 days, respectively).2. The growth dynamics simulation model of cut tulip in solar greenhouse(1) The leaf area index prediction model of cut tulip in solar greenhouseBased on the response of number and growth of unfolding leaf to temperature and light, a relationship between the unfolding leaf number (n) and PTI after sprouting was developed firstly as following equation:n=4x(1-exp(-anxPTI/4))In the equation,4 is the total leaf number, an is the cultivar parameter. Then, the relationship between the leaf length and PTI after leaf unfolding was expressed as followings:Kn=(K1-K4)+K1xexp(-n/rn)ΔPTInj=PTIj-PTInWhere Kn is the elongating rate of leaf (mm·(MJ·pl-1)-1), APTInj is the PTI accumulated from leaf unfolding to the day j (MJ·pl-1), LL0(=80mm) is the original length as leaf unfolding (mm); LLmax,n is the maximum length of leaf. K1 and K4 are the elongating rate of the 1st and 4th leaf (mm·(MJ·pl-1)-1), respectively. rn is the factor which affects the leaf elongating rate. PTIj is the PTI accumulated from sprouting to the day j (MJ·pl-1), PTIn is the PTI accumulated from sprouting to the leaf n unfolding (MJ·pl-1).According to the data about leaf area, leaf length and width from the first experiment, the relationship between leaf area (LA) and product of leaf length (LLn) and leaf width (LWn), and between the leaf length (LLn) and leaf width (LWn).LAn=axLLnxLWn LWn=bxLLnWhere a is the leaf area coefficient and b is the cultivar parameter. The daily leaf area index was calculated as following:LAI=LAxpThe simulation model of leaf area index was validated with independent experiment data. Based on the 1:1 line, the determination coefficient (R2) and the root mean squared error (RMSE) between the predicted and the measured leaf area index are 0.98 and 0.09, respectively.(2) The simulation model on biomass production and dry matter partitioning of cut tulipThe biomass production and dry matter partitioning is the foundation of growth and formation of external quality. Based on the response of tulip growth to temperature and photo-synthetically active radiation, PTI was used as an index to develop a model for predicting biomass production and dry matter partitioning. The relationship between the total dry weight per plant (W) and PTI was expressed with a liner equation:W=W0+b×PTIWhere W0 is the bub dry weight before planting (g·pl-1), b is the increasing rate of total dry weight per plant (g·MJ-1).The dry matter partitioning model can be expressed as follows:PIS=PISo+(PISh-PISo)×[1-exp(-cxPTI/(PISh-PISo))]PIR=1-PISPIST=PISTo+(PISTh-PISTo)/(1+exp(-(PTI-e)x102))PIL=PILh+PILo/(1+exp((PTI-d)/d))PIF=1-PIL-PISTFWS=gxDWSWhere PIS, PIR, PIST, PIL and PIF are the dry matter partitioning index of shoot, root, stem, leaf, and flower, respectively. PISo, PISTo and PILo are the dry matter partitioning index of shoot, stem and leaf as sprouting, respectively. PISTh and PILh are the dry matter partitioning index of stem and leaf as harvesting, respectively. FWS and DWS is shoot fresh weight and dry weight respectively, d, e and g are all the coefficient related to the variety. Independent experiment data were used to validate the model. Based on the 1:1 line, the determination coefficient (R2) between the predicted and the measured value for total dry weight per plant, stem dry weight per plant, leaf dry weight per plant, flower dry weight per plant and shoot fresh weight per plant are 0.98,0.98,0.98,0.97,0.98, respectively; the root mean squared error (RMSE) are 0.19 g·pl-1,0.07 g·pl-1,0.08 g·pl-1,0.03 g·pl-1, 2.08g·pl-1, respectively.3. The simulation model on external quality of cut tulip in solar greenhouseBased on the response of quality of cut tulip to temperature and light, the model for predicting the plant height (H), the basilar stem (length and diameter), the flower neck (length and diameter), the bud (length and diameter) and internodes length was developed.The relationship between plant height (H) and PTI was expressed with an exponential-liner equation:H=(cm/rm)ln[1+exp(rm(PTI-PTIb))]Where cm is the increasing rate of plant height (mm·(MJ·pl-1)-1), rm is the relative increasing rate of plant height (mm·mm-1·(MJ·pl-1)-1), PTIb is the PTI accumulated from sprouting to the canopy covering ground (MJ·pl-1).The relationship between the basilar stem (length and diameter), the flower neck (length and diameter), the bud (length and diameter) and PTI was expressed with the negative exponent equation:Y=Ymaxx(1-exp(-rxPTI/Ymax))+Y0Where Y is the value of quality indices as cutting, Ymax is the maximum increasing value of above mentioned indices, r the increasing rate (mm·MJ·pl-1)-1), Y0 is the original value of the quality indice before measured.The simulation of internodes length begins with developing the relationship of maximum increasing value (LImax,i), increasing rate (ri) of each inter-node and maximum increasing value (LImax,1), increasing rate (ri,1) of the first inter-node length, which was expressed as follows:LI=LImax,i×(1-exp(-rixPTI/LImax,i))+LI0LImax,i=LImax, 1×(1-Kmax,i×(i-1))ri=r1,i×(1-Kr;i×(i-1))Where LI is the length value of inter-node as cutting, LI0 (=20 mm) is the original value of internodes before measured, i is the internodes order, Kmax,i and Kr,i is the factor affects the maximum increasing value (LImax,i) and increasing rate (ri), respectively.Independent experiment data were used to validate the model. Based on the 1:1 line, the determination coefficient (R2) between the predicted and the measured value for plant height, length of basilar stem, diameter of basilar stem, length of flower neck, diameter of flower neck, bud length, bud diameter and internodes length are 0.97,0.98,0.98,0.98,0.97, 0.98,0.97 and 0.96, respectively; the root mean squared error (RMSE) are 30.8mm,3.5mm, 0.1mm,5.5mm,0.1mm,1.2mm,0.4mm and 1.8mm, respectively. 4. Simulation of the relative yieldAccording to the data captured at harvesting, a relationship between the photo-thermal index accumulated through the total growth process and relative yield of cut tulip was developed as follows:RA=Ro+V1xPTIRb=Ro+V2xPTIRc=Rf-RA-RBWhere the RA, RB, and RC are the relative yield of Rank A, B and C respectively, R0 is the original relative yield of cut tulip before measured (R0=16.7%), V1 and V2 are all the coefficient related to the variety, Rf is the flowering rate (%). Independent experiment data were used to validate the model. Based on the 1:1 line, the determination coefficient (R2) between the predicted and the measured value for the relative yield of Rank A, B and C are 0.95,0.97,0.96, respectively; the root mean squared error (RMSE) are 1.0%.0.5%,1.4%, respectively.The model developed in this study can give satisfactory predictions of the different development stages, dry matter production, and dry weight of each organ, main quality indices and relative yield of cut tulip by inputting the data of average air temperature, photo-synthetically active radiation in the solar greenhouse and the cultivar parameter. It has fewer parameters could be captured easily and can be used for control of light and temperature for cut tulip production to realize high quality and raise yield by optimizing planting date and planting density in solar greenhouses.