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This paper details the development and verification of ROSESIM, a computer simulation model of the growth of 'Royalty' roses ( Rosa hybrida L.) based on experimentally observed growth responses from pinch until flowering under 15 combinations of constant photosynthetic photon flux (PPF), day temperature (DT), and night temperature (NT). Selected according to a rotatable central composite design, these treatment combinations represent commercial greenhouse conditions during the winter and spring in the midwestern United States; each selected condition was maintained in an environmental growth chamber having 12-hour photoperiods. ROSESIM incorporates regression models of four flower development characteristics (days from pinch to visible bud, first color, sepal reflex, and flowering) that are full quadratic polynomials in PPF, DT, and NT. ROSESIM also incorporates mathematical models of nine plant growth characteristics (stem length and the following fresh and dry weights: stem, leaf, flower, and total) based on data recorded every 10 days and at flowering. At each design point, a cubic regression in time (days from pinch) estimated the plant growth characteristics on intermediate days; then difference equations were developed to predict the resulting daily growth increments as third-degree polynomial functions of days from pinch, PPF, DT, and NT. ROSESIM was verified by plotting against time each simulated plant growth characteristic and the associated experimental observations for the eight factorial design points defining the region of interest. Moreover, one-way analysis of variance procedures were applied to the differences between ROSESIM predictions and the corresponding observed means for all 15 treatment combinations. At 20 days from pinch, significant differences ( P < 0.05) were observed for all nine plant growth characteristics. At 30 and 40 days from pinch, only flower fresh and dry weights yielded significant differences; at flowering, none of the 13 selected responses yielded significant differences. These graphical and statistical comparisons provide good evidence of ROSESIM's ability to predict the growth response of 'Royalty' roses over a wide range of constant environmental conditions. changing plant response to constantly changing greenhouse condi- tions. By comparing growth observed at a time early in develop- ment with model predictions based on the measured environmen- tal conditions, and then by predicting growth from that time until flower in response to expected environmental conditions, such a model could anticipate early in development how flowering shoot size and quality would be affected at flowering. Many studies have illustrated the importance of photosynthetic photon flux (PPF) for promoting rose growth and flowering, whether it is received naturally (Mattson and Widmer, 1971) or applied supplementally (Armitage and Tsujita, 1979; Carpenter and Anderson, 1972; Cockshull, 1975; Moe, 1972; White and Richter, 1973). Net photosynthetic rate curves and the PPF satura- tion point have been determined for young leaves (Aiken and Hanan, 1975). PPF response functions have been determined to predict net photosynthesis for leaves 10 to 40 days old from 10 to 37C (Lieth and Pasian, 1990; Pasian and Lieth, 1989). Understand- ing these environmental effects on basic plant photosynthesis and partitioning to vegetative and reproductive tissues allows one to predict rose growth more accurately than by predicting photosyn- thesis alone. More empirical approaches to plant growth modeling have used response surface techniques based on central composite experi- mental designs. Armitage et al. (1981) quantified flowering time response and general plant morphology of Tagetes patula L. to PPF, day temperature (DT), and night temperature (NT). Karlsson Functions relating plant growth characteristics to several envi- ronmental factors have successfully predicted plant response over set time intervals (Hammer and Langhans, 1976) or at flowering (Hopper and Hammer, 1991; Karlsson and Heins, 1986). Another approach to plant growth modeling consisted of developing linear or quadratic polynomials of time to depict responses over time of relative growth rate, net assimilation rate, and leaf area ratio for various cultivars (Fernandez and Miller, 1987) or to illustrate changes in stem length (SL) for cultivars grown under various environments (Hammer and Hopper, 1989). One study dynami- cally simulated plant growth in response to the complex energy balance of the greenhouse environment (Takakura et al., 1971). However, considerably more attention was directed toward ther- mal environmental relationships than to representing plant growth accurately. A dynamic representation of plant growth response to several environmental factors over time is desirable for predicting

A Simulation Model of Rosa hybrida Growth Response to Constant Irradiance and Day and Night Temperatures