University of Tabriz Journal of Agricultural Science and Sustainable Production 2476-4310 29 4 2019 12 22 Estimation of Flower Stem Length in Greenhouse Roses Using Richard’s Growth Model Estimation of Flower Stem Length in Greenhouse Roses Using Richard’s Growth Model 205 215 9792 FA Sajad Hosseini Mansour Matloobi Adel Dabbagh Mohammadi Nassab Journal Article 2019 02 17 Flower stem length is highly important in cut roses. One of the Richard’s function application is estimating growth behavior of plants. Four cultivars of cut roses have been selected in a commercial greenhouse then were subjected to stem length measurement upon producing a new node. Data was first fitted to the nearest form of curve, i.e., quadratic model. Coefficient of determination was calculated between 0.95 and 0.98 for this model. Thereafter, data transformation was done by dividing each value by the maximum value in the measured data. Richard’s function was then fitted to the data which gave rise to R² value of more than 0.99 for most cultivars. To estimate model parameters for all curves of cultivars in two seasons we used nonlinear least square regression. The cultivar ‘Black Magic’ showed the highest rate of curve slope in inflection point, however the curve slope for spring season was appeared to be more than the summer slope. First derivative of the Richard’s function was used to calculate the relative stem growth rate. Results indicated higher rate of relative growth rate for spring stems rather than summer stems. Spring stems showed their highest relative growth rate in eighth and ninth node while this happened for summer stems in nodes of five and six. Estimation of stem final length was done by 10 cm difference from the measured value in fourth node onwards and about 5 cm difference in nodes followed by node 8.     Flower stem length is highly important in cut roses. One of the Richard’s function application is estimating growth behavior of plants. Four cultivars of cut roses have been selected in a commercial greenhouse then were subjected to stem length measurement upon producing a new node. Data was first fitted to the nearest form of curve, i.e., quadratic model. Coefficient of determination was calculated between 0.95 and 0.98 for this model. Thereafter, data transformation was done by dividing each value by the maximum value in the measured data. Richard’s function was then fitted to the data which gave rise to R² value of more than 0.99 for most cultivars. To estimate model parameters for all curves of cultivars in two seasons we used nonlinear least square regression. The cultivar ‘Black Magic’ showed the highest rate of curve slope in inflection point, however the curve slope for spring season was appeared to be more than the summer slope. First derivative of the Richard’s function was used to calculate the relative stem growth rate. Results indicated higher rate of relative growth rate for spring stems rather than summer stems. Spring stems showed their highest relative growth rate in eighth and ninth node while this happened for summer stems in nodes of five and six. Estimation of stem final length was done by 10 cm difference from the measured value in fourth node onwards and about 5 cm difference in nodes followed by node 8.     https://sustainagriculture.tabrizu.ac.ir/article_9792_e2f6ba57b22b2c255192d007026cd9cf.pdf