Introduction
Year-round cut roses are greatest cut flowers in the global flower market. The cut roses were grown in greenhouses influenced by microclimate conditions such as temperature, light, and CO2. Thus, predicting the growth of cut roses affected by environmental conditions is important for maximizing cropping efficiency (Lenzt 1998; Dayan et al. 2002;Lee et al. 2003). Especially, because temperature and light not only affects growth of cut roses and photosynthesis of leaves but also shoot development, they are important environmental condition (Pasian and Lieth 1994).
In general, reasonable temperature for cultivation of cut roses in greenhouses is reported as 24-27℃ in the day and 15-18℃ at night. Growth of roses stops when the temperature below 5℃, and starts dormancy when temperature below 0℃ (Boodley and Seeley 1960;De Vries et al. 1982). Temperature can also affects development rate, photosynthesis and physiological characteristics of cut roses, such as bent neck, blind and bullhead etc. (Sarkka 2004;Soe 2013). The net photosynthetic rate of roses increases with increasing temperature between 18 and 30℃. But, the net photosynthetic rate decreased sharply when above 37℃. The number of days from bud break to harvest decreased with increasing temperature. On the other hand, the number of days from cutting to bud break was not affected by temperature (Lieth and Pasian 1993).
Moderately high temperature accelerates development from bud break to harvest, photosynthesis rate and assimilation rate. However, high temperature cause irreversible damage to quality of cut roses that plant growth as stem length, flower size, leaf area and flower weight and development. Continuous high temperature stress decreased flower dry weight and increased flower abscission in Rosa L. ‘Belinda’s Dream (BD) and the Knock Out rose ‘RADrazz’ (KO) at the visible stage (Greyvenstein et al. 2014). Maximum mean leaf area, dry and fresh weight of flower was decreased in high temperature than control temperature (Shin et al. 2001). Anthocyanin accumulation in flower was inhibited by heat treatment at development stage in ‘Jaguar’ rose flowers. The anthocyanin accumulation was affected on transcript levels, it explained to continued inhibition of anthocyanin accumulation after heat treatment finished (Dela et al. 2003).
Under climate of Korea, maintaining consistent year-round production of cut roses in the greenhouses is difficult due to high temperature in summer. Therefore, it is important to determine the optimal growing condition by analyzing the effect of seasonal environment changes in the greenhouses on the growth of cut roses. Growers can use plant growth model that is an analysis of plant response to major environmental factors which affect plant growth such as temperature, light and humidity (Greyvenstein et al. 2014).
The plant growth models are useful tools for understanding interaction between environmental conditions and plant growth and determining how controlling plant growth (Lentz 1998;Marcelis et al. 1998;Lee et al. 2003). Also, the models can support to making cultural decisions that can be increasing productivity and quality using basic data for the automatic environmental control system in greenhouses (Challa 2002;Fourcaud et al. 2008). Thus, in this study, a model for rose shoot growth developed by the previous study (Kim and Lieth 2012) was validated and modified with the purpose of predicting the changes in the growth of cut roses under high temperature.
Materials and Methods
Plant materials and growth environment
This experiment was performed in environmentallycontrolled growth chambers (HB-301SP, Hanbaek Scientific Co., Korea) of Environment Floriculture Lab in the University of Seoul. ‘Antique Curl’ and ‘Beast’ were materialized after transplanting using peatmoss : perlite (1:1 v:v) media in plastic pots.
Each plant was irrigated with nutrient solution by 1,000 mL a day in EC of 1.6 dS·m-1`and pH level of 6.0. High temperature treatment was set at 32/28℃, comparing the control of 24/20℃, day and night.
Photoperiod was 16-h which consisted of 130 μmol·m-2·s-1 provided by LED white light and 200 μmol·m-2·s-1 provided by high-pressure sodium lamps and relative humidity was fixed at 60%. Environmental data were measured every hour by data logger (HOBO® Relative Humidity/Temperature/ Light/External Data Logger, Onset Computer Corp., USA).
Measurements
Plant growth
To measure the growth of 2 cut rose cultivars during a flowering cycle, flowering shoots of 2 cultivars labeled after cutting at the same height (above 2 five-leaflet leaves) before putting into the chambers. The shoots sprouting from the terminal buds of the labeled branches were used for measurement. Harvested shoots were separated as stems, leaves, or flowers. Then, shoot length and leaf number was measured. Total leaf area was measured with the LI-3100C Area Meter (LI-COR Biosciences, USA) and dry weight of a stem, leaves, or a flower was measured after drying in a dry oven (HSD-38RM, vision scientific Co. Ltd, Korea) at 75℃ for 72 hours.
Model description
Kim and Lieth (2012) reported shoot growth model of cut roses. This model was composed of 3 sub-models: shoot growth, root growth, and nutrient uptake models.
Light use efficiency (LUE) is the ratio of dry mass and daily intercepted light (I) by plant canopy (Q) (Eq. 1 and 1.a) (Monteith 1994). The extinction coefficient (k) was given at 0.65 (Goudriaan 1994).
Values of the parameter LUEmax,0 and ‘a’ in Eq. 4 were given at 0.0203 and 0.1151 g (DM·MJ-1) (Kim and Lee 2002). Then, the function of temperature which was used to calculate relative rose growth ratio in the range of temperature of 5℃ to 40℃. Thus, daily shoot growth rate can be expressed as in Eq. 4.
LAI (m2) = Maximum potential leaf area (shoot DM – theological shoot DM)/[3.63+(shoot DM – theological shoot DM)] (Eq. 5)
Leaf area index (LAI) in Eq.1 was calculated by (Eq. 5) (Kim and Lieth 2012). Maximal potential leaf area per shoot was 0.1211 m2 and theological shoot DM was 0.1232 g when the first leaf began to be unfolded in ‘Kardinal’ rose cultivar. Maximal potential leaf area per shoot was modified 0.1008 m2 in ‘Antique Curl’ by previous study (data not shown).
Model validation
The predicted shoot growth was calculated by the shoot growth model, which uses daily mean temperature, accumulative light and predicted leaf area as in Eq. 5 during experiment period. The model was validated by regression analyzing between measured shoot growth per week and predicted shoot growth.
Statistical analysis
SAS (Statistical Analysis System) version 9.4 (SAS Institute Inc., Cary, NC, USA) was used to analyze the experimental data for multiple comparisons by analysis of variance (ANOVA) and to calculate correlation efficient between measured and estimated data. Differences between means of treatments were assessed with Duncan’s New Multiple Range Test (p < 0.05).
Results and Discussion
Growth of cut roses under control and high temperature
The rose shoot growth under control and high temperature treatment were measured once a week (Fig. 1 and 2). The number of flowering days was about 42 days in both cultivars under control condition. However, the number of flowering days decreased under high temperature. Also, the number of days from cutting to bud break decreased at high temperature. The previous study also showed a similar result in increasing development from bud break to harvest (Pasian and Lieth 1996) and development from cutting to bud break (Van den Berg 1987) with increasing temperature.
Under high temperature, shoot length, total leaf number, leaf area, total dry mass decreased compared to those grown under control (24/20℃). In early growth stage, there was no difference of plant growth. At 14th day, dry mass of ‘Antique Curl’ grown under high temperature condition was higher than control, result from fast leaf area expansion caused by accelerated development rate (Fig. 1D). However, in the case of ‘Beast’, all plant growth tended to show lower results than control from bud break to harvest. When over 21 days, shoot length, leaf area, dry mass decreased significantly in both cultivars.
As results of statistical analysis at harvest, In the case of ‘Antique Curl’, shoot length, total leaf number, leaf area and dry mass decreased significantly, 50%, 13%, 65%, and 55%, respectively (Table 1). In the case of ‘Beast’, shoot length, total leaf number, leaf are and dry mass decreased significantly 67%, 43%, 81%, and 80%, respectively. Higher temperature accelerates respiration and dark respiration, resulting in the increase in carbohydrate consumption. Short length, decrease in leaf area, flower size, and the number of flowering days were also observed under high temperature in ‘Kardinal’ rose (Shin et al. 2001). In this study, total leaf number was significantly decreased, it is similar from the result of the previous study that the number of leaf primordial in axillary buds before the bud break was not affected of temperature, but total leaf number was decreased by increasing temperature (Marcelis-van Acker 1995).
Plant growth of ‘Beast’ decreased more than ‘Antique Curl’. In addition to this, bud break after harvesting also decreased more than ‘Antique Curl’. Therefore, ‘Beast’ might be considered to be a weak cultivar to high temperature than ‘Antique Curl’.
Application of the Shoot growth model of cut roses grown under high temperature
To apply the validated shoot growth model for cut roses grown under high temperature, the shoot growth model as in Eq. 4 was used to simulate the shoot growth process by inputting environment data (daily mean temperature and daily accumulated light) in the growth chamber, and estimated leaf area using Eq. 5. The simulated patterns of shoot growth of ‘Antique Curl’ and ‘Beast’ were compared with measured data from harvest every week (Fig. 3).
As the result of comparison between measured shoot growth and estimated shoot growth, the model showed a reasonable estimation of changes in growth of the rose shoots under control and high temperature, giving high coefficients of determination (R2 = 0.90 and 0.82 under control condition and R2 = 0.80 and 0.62 under high temperature condition). However, in ‘Beast’ under high temperature, a somewhat low prediction was presented (Fig. 3). Also, in the case of ‘Antique Curl’, both control and high temperature showed an overestimation.
To discern the predictability of shoot growth model with the decreasing shoot growth under high temperature, the mean of shoot growth of 2 cultivars at control and high temperature was compared with estimated shoot growth using linear regression analysis. Although overestimation was observed both control and high temperature in ‘Antique Curl’, the correlation between measured mean shoot growth and estimated shoot growth showed a high coefficient of determination (R2 = 0.82, 0.91, respectively) regardless of cultivar. Thus, the decrease in shoot growth under high temperature was estimated well by the shoot growth model regardless of cultivars.
As the result of the application of the shoot growth model in cut roses grown under high temperature, the model showed a good performance in both cultivars. However, at harvest stage, the model overestimated the growth of ‘Antique Curl’ cultivar in both control and treatment. Thus, modified leaf area model in experiment 1 was applied to improve the accuracy of the model at harvest stage. Re-experimentation showed that the improved predicting of the shoot growth at harvest stage while maintaining a high coefficient of determination both control and treatment in ‘Antique Curl’ (Fig. 4). This result indicates that the shoot growth model using modified leaf area can apply to improve accuracy of the model under high temperature.
Validation of the shoot growth using modified model
In this study, under high temperature, rose shoot growth decreased above about 50%, which was the result of the increased carbohydrate consumption by the respiration and dark respiration (Shin 2001; Buck-sorlin et al. 2011). Also, high temperature accelerates development from bud break to harvest in both cultivars. This result was identical from the result of the previous study that the number of days from bud break to harvest decreased with increasing temperature (Van de Berg 1987; Pasian and Lieth 1996).
As result of the application of the shoot growth model under high temperature, the model estimated significantly well the decreasing in shoot growth. During experiment, because light intensity was fixed in both control and treatment in the growth chambers, it is thought that the estimation of decreasing shoot growth is result by the function of temperature in the previous study (Shin et al. 2001). The model predicted the decreased shoot growth rate was about 53% at harvest under high temperature. Because shoot growth of ‘Antique Curl’ decreased about 50% and shoot growth of ‘Beast’ was decreased ‘80% at harvest stage, this model showed a better prediction in ‘Antique Curl’ (R2 = 0.90) at high temperature than in ‘Beast’ (R2 = 0.62). This result is thought to be because of the vulnerable characteristic under high temperature of ‘Beast’ cultivar, result in abnormal growth by high temperature i.e. bud break after harvesting and bud development extremely decreased.
Generally, the shoot growth model showed a reasonable prediction about shoot growth at control and decreasing shoot growth under high temperature in 2 cultivars (R2 = 0.90, 0.82, 0.80, and 0.62). The results of the previous study presented similar decreasing pattern with increased temperature in summer (Kim and Lieth 2012). However, at harvest stage, the shoot growth model overperformed for the cultivar ‘Antique curl’ both control and high temperature (Fig. 3A and C). In order to resolve this problem, modified leaf area model of experiment 1 in ‘Antique Curl’ was applied to the shoot growth model. The model using modified model showed a more accurate estimation at harvest stage than the existed model while maintaining a high coefficient of determination (Fig. 4). Therefore, the shoot growth model and modified model can be applied to predict the shoot growth of cut roses grown under high temperature.
Conclusion
In the domestic cultivation of cut roses, the high temperature in summer negatively affects productivity and quality of cut roses i.e. reduce flower size, shoot length, number of petal and leaf area etc (Moe and Kristoffersen 1968;Shin et al. 2001). Thus, growers use equipment for screening to create shade for plants. But, the shade of screening can reduce radiation and then, negatively affects rose production. Because this model is not only able to estimate the decrease in shoot growth at high temperature but also the effects caused by light, it can support the growers in deciding which environmental control strategy can provide the optimal environment for high quality and high productivity.