Cultivating single-node cutting (SNC) is appropriate for a plant factory system, since a massive quantity of uniform quality of cut flower roses per unit area can be produced over a short period of time. To cultivate factory-type SNC roses based on pr ...

Cultivating single-node cutting (SNC) is appropriate for a plant factory system, since a massive quantity of uniform quality of cut flower roses per unit area can be produced over a short period of time. To cultivate factory-type SNC roses based on production planning year round, variations of growth has to be analyzed according to growth period and environmental conditions. This study was conducted to determine the optimal plant density and nutrient control technology, and to develop growth models for SNC roses by investigating factors affecting factory-type production systems.
Plant density had a significant effect on the growth and quality of SNC roses. Flower shoot length, stem diameter and number of petals decreased as plant density increased. In addition, fresh and dry weight per plant decreased with increasing plant density, while yield per area increased except for the plant density of 133 plants/m2 (7.5X10 cm2) and 107 plants/m2 (7.5X12.5 cm2). The highest productivity was shown in the treatment of 89 plants/m2 (7.5X15 cm2) where the highest marketable yield per area was represented.
The concentrations of nutrients in root environment were maintained within the target ranges in the treatment of macroelement control (M) and macro and microelement control (MM), which showed a higher yield and product quality than the other treatments. The supply of mineral nutrients and the uptake by SNC was shown to be the highest in the treatment of nutrient solution supplement (S) during the growth period. Water supply and uptake of 'Red Velvet' were shown to be 20.9~21.6 and 19.4~20.8% lower in the M and MM treatments, respectively, than in the treatment of EC control (EC). The photosynthesis of SNC roses 'Vital' and 'Red velvet' was higher in the M and MM than that of other control systems. Both varieties showed lower Fo and high Fm and Fv/Fo values in the M and MM control treatments than in the EC, S and NPK control treatments.
The base temperature (Tb), optimum (Topt), and maximum temperatures (Tmax) were estimated by regression of the rate of shoot development against the average temperature gradient. The estimated Tb value, 5.56？H？H, was used in thermal unit computations for rose shoot development. The number of leaves, leaf area, and leaf fresh weight showed the sigmoid curve regardless of the cutting time. The leaf area model was described as sigmoidal function using growing degree-day (GDD). Leaf area was y=578.7 [1+(GDD/956.1)^-8.54]^-1. Estimated average thermal units and standard deviation for phases CT-TP (from cutting to transplant) and TP-HV (from transplant to harvest) were 426？H}42？H？H∙d and 783？H}24？H？H∙d, respectively.
GDD improved the accuracy of the model and gave a better estimate of growth parameters compared with time or incident PAR integral. Top fresh and dry mass per m2 were well fitted by the expolinear equations using GDD parameter. The growth parameters of maximum crop growth rate (Cm), maximum relative growth rate (Rm), and the lost time (tb) for expolinear growth function were obtained by fitting dry mass production measurements of SNCs at three plant densities. Crop growth model of SNC roses was described as the expolinear growth function using GDD and plant density. Parameters Cm and tb showed a curvilinear relationship with plant density over three experiments and were fitted to the quadratic function. The Cm was [-0.0005∙PD^2+0.097∙PD+3.25], and tb was [-0.2∙PD^2+35.6∙PD+591.4]. The estimated and measured top dry mass per m2 showed a reasonably good fit with 1.142 (R2=0.988) using GDD and plant density as input data.
As the results of this study, the optimum environments for SNCs and presented modeling approach may serve as a simple tool to understanding crop growth and planning cropping systems under seasonal climate conditions and as a reference in the field of crowth model for SNC roses.

GDD변수로 SNC의 생육예측을 할 경우, 시간이나 적산일사량 변수 보다 모델의 정&# ...

GDD변수로 SNC의 생육예측을 할 경우, 시간이나 적산일사량 변수 보다 모델의 정확성을 향상시켰고, 보다 나은 생육요인 예측이 가능했다. 단위 면적당 지상부 생체중과 건물중은 GDD변수를 사용하여 expolinear함수로 나타낼 수 있었다. 3수준의 재식밀도에 따른 expolinear함수의 생육요인인 최대작물생장률(Cm), 최대상대생장률(Rm), 및 lost time (tb)이 예측되었다. 따라서 SNC의 작물생장모델은 expolinear 생육함수를 재식밀도와 GDD에 대한 함수로 표기하였다. Cm과 tb는 재식밀도와 curvilinear관계를 보였고, 2차함수로 나타낼 수 있었다. GDD와 재식밀도를 사용하여 예측된 값과 실제 측정된 값을 비교한 결과, 신뢰구간 1%내에서 높은 정의상관을 보였다.
장미식물공장에서 single-stemmed 장미를 생산할 경우, 정식 후 수확까지 소요일수가 년 평균 35일이 소요되어 년간 10회 수확이 가능하다. 정식간격이 10x10cm일 때, 1회에 면적당 100 plants/m2를 생산하여, 년간 10,250,000송이/ha를, 정식간격이 10x20cm일 때 1회 면적당 생산량은 50송이/m2를 생산하여 년간 5,130,000 plants /ha를 생산한다. 아울러 년평균 가격을 80원을 적용하면 년간 조수익은 10x10cm로 정식할 경우 1ha당 10,250,000 plants 를 생산하여 소득이 820,000,000원이 되며, 소득률을 40%로 정하면 328,000,000원의 소득을 올릴 수 있다. 장미 식물공장 생산을 통해 생산성을 증대시키고, 연중 계획 생산과 규격화된 상품 생산이 가능하며 수익을 극대화 시킬 수 있다.