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

Abstract

<jats:p>This paper details the development and verification of ROSESIM, a computer simulation model of the growth of `Royalty' roses (<jats:italic>Rosa hybrida</jats:italic> 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 (<jats:italic>P</jats:italic> &lt; 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.</jats:p>

Rose bush leaf and internode expansion dynamics: analysis and development of a model capturing interplant variability

“…Several models describing architectural variables have been developed for cut-flower roses. A first group of models predicts variables at the level of the whole shoot, such as total stem length and basal stem diameter (Hopper et al, 1994; Costa and Heuvelink, 2003; Oki et al, 2006) or morphological quality classes (Morisot, 1996). Structural descriptions have been refined further in more mechanistic models (Lieth and Pasian, 1991; Dayan et al, 2004), mostly with a view to predicting the harvest of rose flowers more accurately.…”

Prediction and calculation of morphological characteristics and distribution of assimilates in the ROSGRO model

“…Morisot [14,15] and Kool and de Koning [19] give the substitution between average length and number of cut flowers, but not the distribution of canopy architecture on whose basis shoot processes can be calculated. Statistical correlative models predict growth and flower development characteristics, but are limited to a single variety, to a defined growth period, and to a specific range of tested environmental conditions [1]. The more mechanistic models of Lieth and Pasian [17,18] suggest a possible determination of processes on leaf and on shoots, but they are derived from measurements on a single leaf or typical shoots, and not from an organized canopy development sequence as found in L-systems [2].…”

“…those of Morisot (PP. rose) [14], Hopper et al (ROSESIM) [1], Kool and de Konig [45], and even the more mechanistic models of Lieth and Pasian [18] have been better validated and are probably much more suitable for applications as guides to growers. However, ROSGRO is developed and can be used for other purposes: as a mechanistic model it is an analytical instrument for achieving better understanding of the rose crop growth and flower quality, by sorting out the complex biological interactions leading to the development of the canopy.…”

“…Depending on market requirements, a grower will adjust the nature and timing of his interventions to achieve the target number and quality of flowers [1]. Whereas vegetable crop models seek to increase biomass, yield and number of fruits, in the case of flowers and ornamentals, morphology and geometry are also targets, and a predictive capability is needed in practical applications [2].…”

“…Hopper et al [1] developed a correlative model (ROSESIM) of the development of a flowering rose shoot as affected by air temperature; the model expressed rose shoot growth rate from pinching date till flowering as a polynomial function of constant photosynthetic photon flux and differing day and night temperatures. Kool [13] developed a model for the prediction of rose productivity during the second year of cultivation from past stem size, while Morisot [14,15] predicted biomass and some parameters of rose quality on the basis of the energy intercepted by the rose canopy.…”