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Optimal Lighting for Plant Growth using LED and Laser Illuminations

Ryuta Udo1, Yusuke Yamashita1, Shozo Yamakami1, Yoshihiro Azuma1, Haruhiko Murase3, and Hirokazu Fukuda2*

1Department of Mechanical Engineering, School of Engineering, Osaka Prefecture University, Sakai 599-8531, Japan 2Department of Mechanical Engineering, Graduate School of Engineering, Osaka Prefecture University, Sakai 599-8531, Japan 3Research Organization for the 21st Century, Osaka Prefecture University, Sakai 599-8531, Japan *To whom correspondence should be addressed.Phone &Fax: +81-72-254-7916 E-mail: fukuda@me.osakafu-u.ac.jp

Keywords: Circadian clock, Laser, Plant factory, Sucrose metabolism.

Abstract Now that present agriculture has numerous problems, a plant factory will be

required in the future. However, plant factories have significant problems, particularly their high-cost. This study focused on cost-reduction in the lighting by taking consideration of the following four topics. (1) Correlation between the attributions of circadian clock and growth under LED illuminations. (2) Identification of the optimal photoperiod for plant growth by the relationship between circadian clock and sucrose metabolism. (3) Measurement of the phase responses of circadian rhythm for environmental signals using the stripe wave in plant root. (4) Low-cost illumination by an ultraviolet laser in the plant factory. (1) A transgenic lettuce (c.v. greenwave) was cultivated under continuous light. And then their bioluminescence which indicated the expression rate of a clock gene and their fresh weights were measured. After all, we investigated the correlation diagrams between the fresh weights and the circadian factors obtained from bioluminescence. (2) We analyzed numerically the metabolic cost of plants in various photoperiods by a model of sucrose and starch metabolism (Feugier and Satake, 2013). (3) To confirm the method of simplified determination of phase response curve, we have investigated the phase response of circadian rhythm in the root. And using phase oscillator model, we were subjected to analysis of dynamics with respect to the phase shift of the stripe pattern. (4) We used an ultraviolet laser which radiate ultraviolet rays (UV-A, B, C) of 253.7nm or above. And we irradiated the fluorescent screen suitable for each with one of them.

INTRODUCTION Present agricultural products have numerous problems, such as the necessity to meet

food safety standards under environmental pollution, and to increase food production efficiency under the increasing population. In order to solve these problems, a plant factory will be required in the future. Plant factory is define as following; a cultivation environment which is possible to product vegetables according to the year-around plan by carrying out advanced environmental control and plant growth prediction based upon monitoring of environment and vegetation.(Plant Factory WG, 2009)However there are some significant challenges to develop plant factory more, such as cost reduction, production expansion andimprovement of profitability.

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In order to solve these problems, in many cases, we divide a plant factory of a highly complicated productionsystem into two subsystems; “cultivation environment”and“plant”. As for “cultivation environment”, development of new light resource for cost reduction, or researches on environmental control methods have been performed. On the other hands, as for “plant”, researches focus on circadian clock of plant is being performed.

Circadian clock is ubiquitous to known forms of life forming autonomic rhythm which is about twenty-four-hour cycle. It is known that this function regulates a wide range scale of physiological metabolism ranging from individual to gene such as gene expression, phosphorylation of protein, chloroplast migration, stomatal behavior, photosynthesis, anthesis.(McClung, 2006) And because circadian clock regulates transport gene and consistency of nutritional component like vitamin C within plant, improvementof quality of vegetables by optimizing circadian clock is expected

In this study,we focused on cost reduction in the lighting by taking consideration of the following four topics. (1) Correlation between the attributions of circadian clock(e.g. period, amplitude, intensity of bioluminescence etc.) and growth under LED illuminations. (2) Identification of the optimal photoperiod for plant growth by the relationship between circadian clock and sucrose metabolism. (3) Measurement of the phase responses of circadian rhythm for environmental signals using the stripe wave in plant root. (4) Low-cost illumination by an ultraviolet laser in the plant factory. 1. To explore circadian clock factor which contribute to plant growth, we got

longitudinaldata of circadian clock of transgenic lettuce and its fresh weight. And then we try to find out the correlation between circadian clock factors and fresh weight.

2. To analyze C metabolism in plant under artificial light condition, we analyzed numerically the metabolic cost of plants in various photoperiods by a model of sucrose and starch metabolism(Feugier and Satake, 2013).

3. To confirm the methodology of simplified determination of the PRC, we have investigated the phase response of circadian clock in roots to perturbation by temperature pulse in continuous. In continuous condition, roots included overall phase at the same time, and we could observed the phase shift of overall. And using computer simulation of a phase oscillator model, we calculated the PRC and evaluated for their characteristics.

4. To develop the fluorescent light resource using ultraviolet laser,we calculated power which ultraviolet laser needs to obtain as much quantity of light as fluorescent light.

Materials and Methods 1. Transgenic Greenwave lettuces carrying the CCA1::LUC construct were disseminatedin

40-mm dish treated with 500 µl of fertilizer (Otsuka House 1st; N : P2O5 : K2O : CaO : MgO = 10 : 8 : 27 : 0 : 4, and Otsuka House 2nd; N : P2O5 : K2O : CaO : MgO = 11 : 0 : 0 : 23 : 0, Otsuka Chemistry)and 500 µl of luciferin (1mM) dissolved in water and grown under continuous light condition (80 µmol m−2 s−1of Red LED and 20 µmol m−2 s−1 of Blue LED,) at 26°C for 14 days.As for fertilizer, its pH and EC were adjusted to pH6.0 and EC2.0. All the while bioluminescence assaywere carried out with a monitoring system (Fig.1)known asKondotron, developed by Kondo, Strayer, Kulkarni, Taylor, Ishiura,1993.This system enables that the bioluminescence was detectedby a photomultiplier tube (PMT) (Hamamatsu H7360-01MOD; Hamamatsu Photonics KK, Japan) enclosed in a light-tight box. Each dish was on a turntable, which was located under the PMT and rotated sequentially every 20 min under the control of a computer.Measured bioluminescence data were stored in the computer. After finishing

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two weeks measurement, fresh weights above-part of the lettuces were measured as index of plant growth.

2. We analyzed the cost to plants in variousphotoperiods by Runge-Kutta method, evaluated the stress to plants, and identified the optimal photoperiod. We estimated thequantity of daily average sucrose starvationby the model of sucrose and starch metabolism and regarded this quantity as the stress to plants. Figure 2a shows the flow chart of the mechanistic model for sucrose and starch regulation in plant photosynthetic leaves. Rates γ(t), β(t), and η(t) represent the oscillation of thethree processes, carbon partitioning, starch degradation, and sucrose export. During light period a fraction γ(t) of carbon assimilated by photosynthesis is partitioned into starch and a fraction 1-γ(t) is partitioned into sucrose. No partitioning occurs at night as there is no photosynthesis. Starch is degraded into sucrose with rate β(t) which is the only source of sucrose at night to support leaf respiration and growth. Sucrose is exported with rate η(t) to non-photosynthetic tissues such as roots and immature leaves via the phloem. Figure 2b represents the scheme of feedback system in sucrose metabolismby sucrose starvation.Sucrose starvation occurs when sucrose concentration goes below the threshold S*.Starvation will induce a shift in time in the oscillation of thethree processes, carbon partitioning γ(t), starch degradation β(t), and sucrose export η(t).

3. To investigate the phase response of plant roots, we develop the phase oscillator model of circadian clock in roots (Fukuda,Ukai,Oyama, 2012). We assumed the system of circadian rhythm of root cells respond in accordance with the function of 1 hour Dark-pulse perturbations. Phase response curve of the 1 hour Dark-pulse has been revealed in previous studies (Fukuda,Murase,Tokuda, 2008). 푍(∅) = −0.093 + 0.327 sin(∅ − 1.64) + 0.079 sin(2∅ − 2.19) (1) We evaluated the difference between PRC obtained from global rhythm of root cells and obtained from Local rhythm of cell by using a phase oscillator model.

푑∅( , )

푑푡= 휔( , ) + 퐾 sin ∅( , ) − ∅( , )

( , , )

+ 훿 퐶 sin π− ∅( , )

+ 푃(푡)푍 ∅( , ) (2) We considered a cellular system composed of 푁 × 푁 cells (section size) ×푁 cells (root length).∅( , )and 휔( , )represent the phase andcircadian frequency of the cell located at position (푚,푛) ofsection 푗 along the root.Elongation rate of the root tip is 푗∗ = [(푣 푡 − 푥 )]. In the meristem, we suppose that daughter cells inherit thephases of their parental cells with stochastic noise ∅ ∗

( , ) = ∅ ∗( , ) + ϵ, where ϵ is a random

phase-copying error, which is distributed normally with mean ⟨ϵ⟩ = 0 0 and standard deviation 휎∅.The natural frequency of the 푗th cell ω( , )is distributed normally with average 휔 and standard deviation 휎 . The second term in Eq. (2) is the coupling between cellular oscillators, where <l, p, q>means the position of nearest neighbors of the cell in the position (푚,푛)atsection 푗. The third term 훿 퐶 sin 휋 − ∅( , ) represents the force of phase resetting, 퐶 is the strength of the phase resetting, and 훿 is Kronecker’s delta. This term operates only in the root tip. In addition, the fourth term 푃(푡)푍 ∅( , ) represents the force of phase response curve. (푍(∅) = −0.093 + 0.327 sin(∅ −1.64+0.079sin2∅−2.19)

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There are four parameters that are involved in the global rhythm of root. We investigated the changes in the PRC characteristic obtained from global rhythm of root cells by changing four parameters (K, C, 휎 , 휎∅.)

4. We thought of using an ultraviolet laser which radiates ultraviolet rays of 253.7nm and irradiating the fluorescent screen with that like Fig 3. When fluorescent screen is irradiated with Ultraviolet lays, it emits light uniformly.To evaluate the power consumption of UV laser, equation (3) was derived. E = 퐸 (3) Power of laserEUV calculated from amount of energy of UV in fluorescent light Ef as follows: 퐸 = 0.6퐸 (4) Here, Efshowed the power consumption of fluorescent light. Area which irradiated by laser beam A’ and area size of cross section of fluorescent light A were defined as follows: A′ = (5) A = 휋푑퐿 (6) We calculated the power consumption of UV laser usingdifferent Ef. Set of parameters, d andL, for each Efwere introduced same as the fluorescent light in the marketplace.

RESULTS AND DISCUSSION 1. An example of longitudinal data of bioluminescence is shown in Figure 4a. Initial rise of

bioluminescence describes that a lettuce germinates is about 48 hours from starting measurement, and after that bioluminescence showed huge waves over a 24 hours cycle. From this data, we extracted average period of circadian rhythm as an index to evaluate each sample.We accessed the correlation between average period for two weeks and fresh weight of the lettuces and the correlation diagram is shown in Figure 4b. As a result, we found the coefficient of correlation about 0.57. This means that the shorter the circadian clock period is the more lettuce will grow. Based on this data, it might be indicating that there is a possibility to predict the growth of vegetables by monitoring their circadian clock.

2. Figure 5 shows starvation cost profiles in each photoperiod. The condition of photoperiod changes from 8h light/8h dark to 16h light/16h dark. Each photoperiodswere changed after 10 cycles of 12h light/12h dark to integrate each sucrose concentration. Cost profiles use the value in the 11th cycle. By ranking the cost, we obtained the most appropriateLD cycle.

3. We could evaluate the difference between PRC obtained from cell population rhythm of root and obtained from single cell rhythm of root by using a phase oscillator model(Fig. 1(a) and 1(c)). In these results, it was suggested that it is possible to investigate the difference of PRC between cell population and single cell, and construct the method for estimating the PRC from the stripe wave in plant root.

4. We calculated power of laser by substituting some values of fluorescent light suppose that laser beam diameter d’ was 5mm. According to Table 1, power which laser needs is about 5mW.This is much smaller than any other Ef in Table 1. Therefore, it was suggested that the fluorescent illumination device which is driven by ultraviolet laser can substantially reduce quantity of electricity.

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CONCLUSION From these studies, we got following four conclusions.

1. We suggested that there is a correlation between the attribution of circadian clock and growth of plant. This result could be the first step to prediction of plant growth.

2. As a result of numerical simulation in various conditions of photoperiods, we obtained the lowest cost value around 12h light/12h dark condition.

3. We could suggest that it is possible to calculate PRC from phase response of stripe wave and construct the method for estimating the PRC from the stripe wave in plant root.

4. The fluorescent illumination device which is driven by ultraviolet laser can obtain as much quantity of light as fluorescent light by using ultraviolet laser whose power is about5mW, in theoretically.

Literature Cited Feugier,F. G., Satake,A. 2013. Dynamical feedback between circadian clock and sucrose

availability explains adaptive response of starch metabolism to various photoperiods. Frontiers in Plant Science 305(3): 1-11.

Fukuda, H., Murase, H., Tokuda, I. 2013.Controlling Circadian Rhythms by Dark-Pulse Perturbations in Arabidopsis thaliana. Sci. Rep. 3, 1533

Fukuda, H., Ukai, K., Oyama, T. 2012. Self-arrangement of Cellular Circadian Rhythms Through Phase Resetting in Plant Roots, Phys. Rev. E86, 4, 041917

Kondo, T., Strayer, A. C., Kulkarni, D. R., Taylor, W.,Ishiura, M., Golden, S. S., & Johnson, H. C.1993. Circadian rhythms in prokaryotes: luciferase as a reporter of circadian gene expression in cyanobacteria. Proc. Natl. Acad. Sci. USA 90, 5672–6

McClung CR. 2006. Plant circadian rhythms. Plant Cell18: 792-803 Nakamichi, N., Ito, S., Oyama, T., Yamashino, T., Kondo, T., & Mizuno, T. 2004.

Characterization of plant circadian rhythms by employing Arabidopsis cultured cells with bioluminescence reporters.Plant Cell Physiol. 45,57–67

Plant Factory WG, 2009, Plant factory WG report: Ministry of Agriculture, Japan

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Tables:

Table 1. Relationship between power consumption of fluorescent light and power of laser

Ef [W] d [mm] L [mm] E [W]

10 25.5 330 4.46×10-3 15 25.5 436 5.06×10-3 20 28.0 580 4.62×10-3 30 32.5 630 5.49×10-3 35 32.5 1000 4.04×10-3 40 28.0 1198 4.47×10-3

(d : glass tube diameter of fluorescent light, L : length of fluorescent light)

Figures

Figure 1.Kondotron system a) A general view. b)

Figure 2. a) Flow chart of the model.

(a)

Figure 1.Kondotron system a) A general view. b) System configuration diagram

Flow chart of the model. b) Scheme of feedback system in sucrose metabolism.

(b)

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ystem configuration diagram.

b) Scheme of feedback system in sucrose metabolism.

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Figure 3. Schematic design of UV

Figure 4. a) Longitudinal data of bioluminescence. b) Correlation diagram of average period for two weeks and fresh weight of the lettuces.

(a)

Schematic design of UV-driven fluorescent equipment.

a) Longitudinal data of bioluminescence. b) Correlation diagram of average

two weeks and fresh weight of the lettuces.

(b)

a) Longitudinal data of bioluminescence. b) Correlation diagram of average

Figure

Figure 6. (a)Stripe wave obtained by simulation using the phase oscillator model.(b)response curve2.19 (c) Phase response curve (

(a)

Figure 5. Starvation cost profiles in each photoperiod.

(a)Stripe wave obtained by simulation using the phase oscillator model.(b)response curve

Phase response curve ( K=0.002,C=0.8, =0.07, ∅=0.07

(a)

(b)

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(a)Stripe wave obtained by simulation using the phase oscillator model.(b)Phase

=0.07)

(c)

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