Measuring the Short-Term Plant Photosynthetic Response to Varying Light Quality Using Light Emitting Diodes (Leds)

Measuring the Short-term Plant Photosynthetic Response to Varying Light Quality Using Light Emitting Diodes (LEDs)

Michael A. Schwalb Department of Bioresource Engineering McGill University Montreal, Quebec, Canada

A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of Master of Science

December, 2013

Abstract

Light emitting diodes (LEDs) emit narrow bandwidth light and have the potential to increase the spectral efficiency of supplemental lighting in greenhouses by optimizing spectral output for plant growth and yields. At the moment of writing, data describing the plant response to varying light quality and quantity was limited. The objective of this research was to examine photosynthetic response of plants to varying light quality and quantity and to gather photosynthetic response data that could be used to design an optimal spectrum for a prototype LED array for plant growth experiments. The action spectrum of tomato (Solanum lycopersicum), lettuce (Lactuca sativa) and petunia (Petunia × hybrida) seedlings was measured at three irradiances (30, 60 and 120 µmol m-2 sec-1) using LED arrays with peak wavelengths from 405nm – 700nm and a bandwidth of 25nm (full width at half maximum). The action spectrums for all plant species at all three irradiances were characterized by localized blue and red action peaks within the range of 430 to 449 nm and 624 to 660 nm respectively. A peak also occurred at 595 nm for 30 µmol m-2 sec-1.The photosynthetic response of tomato, lettuce and petunia to varying red (660nm) and blue (430nm) wavelengths with and without background broadband radiation was also measured. For all three species tested, with and without background radiation, the optimum photosynthesis range occurred within the red to blue ratio (r:b) range of 5:1- 15:1 except for petunia without background radiation for which the maximum occurred at 50:1. These results suggest that the optimal red to blue ratio for photosynthetic activity for tomato, lettuce and petunia occurred between a red to blue ratio of 5:1-15:1.

Résumé

Les diodes électroluminescentes (DEL) émettent une lumière relativement monochromatique et pourraient accroître l’efficacité des lampes pour les serres commerciales en émettant des longueurs d’ondes optimisées pour le rendement des plantes. L’objectif de ce projet a consisté à examiner l’effet des longueurs d’ondes sur l’activité photosynthétique des plantes. L’activité photosynthétique des tomates (Solanum lycopersicum), laitues (Lactuca sativa) et pétunias (Petunia × hybrida) a été mesurée à trois puissances d’irradiation (30, 60 and 120 µmol m-2 sec-1) en utilisant des DELs avec une émission maximale entre 405 nm et 700 nm et une bande passante de 25 nm. La réponse photosynthétique maximale à chaque niveau d’irradiation se situait dans la portion bleu et rouge du spectre visible, soit respectivement entre 430 - 449 nm et 624 to 660 nm. Un maximum a aussi été observé à 595 nm à 30 µmol m-2 sec-1. L’effet de la proportion des longueurs d’onde bleue et rouge (émises par les DELs) sur l’activité photosynthétique des tomates, laitues et pétunias a aussi été mesuré avec et sans le rayonnement de fond. Pour chaque espèce, avec et sans le rayonnement de fond, la proportion optimale (en terme de rouge et bleu) pour l’activité photosynthétique se situait entre of 5:1- 15:1, sauf dans le cas du pétunia, pour lequel le maximum se situait à 50:1 sans rayonnement de fond. La proportion optimale pour l’activité photosynthétique a diminué avec le rayonnement de fond pour chaque espèce à chaque niveau d’irradiation.

Authorship and Manuscript

This thesis is written in a manuscript based format. The contribution of authors are as follows: (1) M. Schwalb – design of optimized light treatments for photosynthetic data collection, design and operation of experiments, as well as data collection, compilation, analysis and interpretation; (2) Dr. Lefsrud-provided guidance on experimental design, supervised experiments and reviewed thesis; (3) Tahera Naznin- helped develop methodology of experiments and helped collect and analyze photosynthetic data (4)- Julie Gagne- provided technical expertise with experimental instruments and helped collect and analyze data (5) Blake Bissonette- provided technical expertise with the operation and maintenance of experimental instrumentation.

Acknowledgements

I would like to thank my supervisor Dr. Lefsrud for providing generous support and invaluable guidance. I would also like to thank all of the co-authors for their technical expertise which made this project possible as well as the MITACS Accelerate program and General Electric Lighting Solutions for providing funding and facilitating a great experience as an intern in a corporate setting. This project would also not have been possible without the love and support of my wife Jaime, my dad, my mom and my sister. Finally, I would like to thank Pablo Gucciardo for his technical assistance with drafting a figure for the experimental setup.

Table of Contents

Abstract ...... 2 Résumé...... 3 Authorship and Manuscript ...... 4 Acknowledgements ...... 5 Table of Contents ...... 6 List of Figures ...... 10 List of Tables ...... 11 List of Equations ...... 12 1. General Introduction...... 13 1.1. Thesis Motivation ...... 13 1.2. Research Problem ...... 14 1.3. Objectives ...... 15 1.4. Hypothesis ...... 15 Abbreviations ...... 16 2. Literature Review ...... 17 2.1. Availability of Solar Irradiance ...... 17 2.2. Current Supplemental Lighting ...... 17 2.3. Light Emitting Diode Lighting ...... 19 2.4. LED Efficiency and Cost Evolution with Time ...... 21 2.5. Benefits of LEDs for Plant Growth ...... 22 2.6. Photosynthetic Reaction ...... 24 2.7. Pigments ...... 26 2.8. Photosynthetically Active Radiation ...... 29 2.9. Plant Response to Varying Light Quantity ...... 29 2.10. Light Quantification ...... 31 2.11. Action Spectrum ...... 31 2.12. Action Spectrum Measurements ...... 32 2.13. Photosynthetic Response to Varying Light Quality ...... 34

2.14. Plant Selection for Experimentation ...... 37 2.14.1. Tomato Greenhouse Crop Profile ...... 37 2.14.2. Lettuce Greenhouse Crop Profile ...... 38 2.14.3. Petunia Greenhouse Crop Profile ...... 38 References ...... 40 Connecting Statement to Chapter 3 ...... 45 Abstract ...... 46 Abbreviations ...... 47 3. Literature Review ...... 48 3.1. Introduction ...... 48 3.1.1. Action Spectrum ...... 48 3.1.2. Pigments ...... 50 3.1.3. Already Established Action Spectrum ...... 51 3.1.4. Current Supplemental Lighting Characteristics ...... 52 3.1.5. LED Lighting Characteristics ...... 52 3.1.6. Benefits of LEDs for Plant Growth ...... 53 3.1.7. Disadvantage of LED Lights for Plant Growth ...... 54 3.1.8. Research Problem ...... 55 3.1.9. Objectives ...... 56 3.2. Materials and Methods ...... 56 3.2.1. Plant Culture ...... 56 3.2.2. Plant Measurements ...... 57 3.2.3. Light Treatments ...... 57 3.2.4. Photosynthetic Measurements ...... 60 3.2.5. Statistical Analysis ...... 60 3.3. Action Spectrum Results ...... 61 3.3.1. Tomato Action Spectrum ...... 61 3.3.2. Lettuce Action Spectrum ...... 63 3.3.3. Petunia Action Spectrum...... 65

3.3.4. All Plants Action Spectrum ...... 67 3.3.5. Light Compensation ...... 68 3.4. Discussion ...... 70 3.4.1. Action Spectrum for Plant Species ...... 70 3.4.2. Action Spectrum for All Irradiances ...... 71 3.4.3. Light Compensation ...... 71 3.4.4. Green Peak at 595 nm ...... 72 3.4.5. Statistical Analysis ...... 72 3.4.6. Optimal Spectrum for a Supplemental Prototype LED Light for Plant Growth ...... 73 3.5. Conclusion ...... 73 References ...... 75 Connecting Statement to Chapter 4 ...... 80 Abstract ...... 81 Abbreviations ...... 82 4. Literature Review ...... 83 4.1. Introduction ...... 83 4.1.1. Benefits of LED Technology for Plant Growth ...... 84 4.1.2. Disadvantage of LED technology ...... 85 4.1.3. Red and Blue Light Effect on Photosynthesis and Photomorphogenesis ...... 85 4.1.4. Spectral Composition Optimization ...... 87 4.1.5. Experimental Objectives ...... 87 4.2. Materials and Methods ...... 88 4.2.1. Plant Culture ...... 88 4.2.2. Plant Measurements ...... 88 4.2.3. Light Treatments ...... 88 4.2.4. Photosynthetic Measurements ...... 90 4.2.5. Statistical Analysis ...... 90 4.3. Results ...... 92 4.3.1. Tomato without Background Radiation ...... 92

4.3.2. Tomato with HPS ...... 93 4.3.3. Tomato with Incandescent ...... 94 4.3.4. Lettuce without Background Radiation ...... 95 4.3.5. Lettuce with HPS ...... 96 4.3.6. Petunia without Background Radiation ...... 97 4.3.7. Petunia with HPS ...... 98 4.3.8. Statistical Analysis – All Plant Species Without Background Radiation ...... 99 4.3.9. Statistical Analysis – All Plant Species With Background HPS Radiation ...... 100 4.4. Discussion ...... 100 4.4.1. All plants summary ...... 100 4.4.2. Effect of Background Radiation ...... 101 4.4.3. Statistical Analysis ...... 101 4.4.4. Optimizing the R:B in LED lights ...... 102 4.5. Conclusion ...... 102 References ...... 104 5. Future Research ...... 109 5.1. Impact for Industry...... 109 5.2. Plant Parameters of Interest ...... 109 5.3. Lighting Parameters of Interest ...... 110 5.4. Interaction Effects ...... 110 5.5. Expanding on Thesis ...... 110 6. General Conclusion ...... 112 Appendix- Raw Data for Experiment Described in Chapter 4 ...... 113

List of Figures

Figure 2.1. Spectrum of 400 W HPS ...... 18 Figure 2.2. LED Diagram...... 20 Figure 2.3. Spectrum of Different Coloured LEDs...... 21 Figure 2.4. Schematic of the Photosynthetic Apparatus and the Chemical Reactions of Photosynthesis……………………………………………………………………………………………………………………….. 25 Figure 3.1. Absorption Spectrum of Tomato, Lettuce and Petunia...... 51 Figure 3.2. Experimental Setup ...... 59 Figure 3.3. Tomato Action Spectrum...... 61 Figure 3.4. Lettuce Action Spectrum...... 63 Figure 3.5. Petunia Action Spectrum...... 65 Figure 3.6. Light Compensation Points...... 68 Figure 4.1. Tomato Ratio Response without Background Radiation...... 92 Figure 4.2. Tomato Ratio Response with High Pressure Sodium...... 93 Figure 4.3. Tomato Ratio Response with Incandescent ...... 94 Figure 4.4. Lettuce Ratio Response without Background Radiation ...... 95 Figure 4.5. Lettuce Ratio Response with High Pressure Sodium ...... 96 Figure 4.6. Petunia Ratio Response without Background Radiation ...... 97 Figure 4.7. Petunia Ratio Response with High Pressure Sodium ...... 98

List of Tables

Table 3.1. Tomato Statistical Analysis...... 62 Table 3.2. Lettuce Statistical Analysis...... 64 Table 3.3. Petunia Statistical Analysis...... 66 Table 3.4. All Plants Statistical Analysis...... 67 Table 3.5. Light Compensation Data - Tomato and Lettuce...... 69 Table 3.6. Light Compensation Data - Petunia...... 70 Table 4.1. All Plant Species Statistical Analysis without Background Radiation...... 99 Table 4.2. All Plant Species Statistical Analysis with Background HPS Radiation...... 100 Table A.1.Tomato Ratio ...... 113 Table A.2. Tomato Ratio - High Pressure Sodium ...... 114 Table A.3. Tomato Ratio - Incandescent ...... 115 Table A.4. Lettuce Ratio ...... 116 Table A.5. Lettuce Ratio - High Pressure Sodium ...... 117 Table A.6. Petunia Ratio ...... 118 Table A.7. Petunia Ratio - High Pressure Sodium ...... 119

List of Equations

Equation 2.1. Photosynthesis ...... 24 Equation 2.2. Photosynthesis as a Function of Irradiance...... 30 Equation 2.3. Action Spectrum ...... 31 Equation 2.4. Quantum Yield ...... 31 Equation 2.5. Monochromator Throughput Losses ...... 33 Equation 3.1. Action Spectrum ...... 49

1. General Introduction

1.1. Thesis Motivation

As increasing global population and average standard of living continue to amplify the global demand for food, emerging methods to increase agricultural production are gaining considerable interest worldwide; field agriculture production is stagnating and under certain climate change scenarios, it is at risk of significantly decreasing due to a warmer average global temperature, the loss of fertile soil and the increase in extreme weather events (Bellows et al., 2003). Thus, the potential for increasing food production with traditional field agriculture is limited. Greenhouse production is an interesting alternative to traditional field agriculture as it increases agricultural productivity per unit area, increases the delivery efficiency of water and nutrients, reduces plant susceptibility to ambient environmental conditions (notably extreme weather events), increases the potential of local production in urban centers and/or in northern climates and does not require arable land (Jensen, 2002). In northern latitudes, commercial greenhouse production requires a significant amount of capital and energy to operate during winter months. However, light is typically one of the most expensive growth factor to provide artificially as currently used artificial lights are costly to operate and inefficient. This is largely due to the fact that these lights have wide bandwidth emissions and do not have a spectrum optimized for plant growth (Tamulaitis et al., 2005). High pressure sodium (HPS) lights for example, the most commonly used light in commercial greenhouses, have peak emissions in yellow waveband where photosynthetic utilization is relatively low when compared to red portion of the visible spectrum (McCree et al., 1972a; Balegh et al., 1970; Bulley et al., 1969). Unlike current supplemental lights, LEDs emit narrow bandwidth light which allows the color or spectrum of an LED array to be readily manipulated and optimized for plant growth (Massa et al., 2008; Morrow, 2008; Bula et al., 1991). With an optimized spectral output, the light utilization efficiency of LED light for plant growth has the potential to be significantly higher than alternative artificial lights such as HPS (Nelson et al., 2013; Massa et al., 2008; Bula et al., 1991). As a result, an optimized LED light has the potential to significantly reduce the operating

13 costs associated with artificial lighting in commercial greenhouses (Martineau et al., 2012; Bula et al., 1991) and increase yields and/or plant vigor (Massa et al., 2008; Bellows et al., 2001).

1.2. Research Problem

To optimize the spectrum of a prototype LED array for plant growth, the spectral emissions should, hypothetically, correspond to peaks in action spectrum which describes the photosynthetic response of a plant to varying wavelengths (Morrow, 2008; Marcelis et al., 2002). However, at the moment of writing, such data was limited and was only available for a select number of plant species and limited irradiance levels, both of which can significantly affect the action spectrum (McCree et al., 1972a). To optimize the spectrum of an LED array for plant growth, action spectrum data is required for various plant species over a range of irradiances (Tamulaitis et al., 2005; Bula et al., 1991). Already established action spectrum was also limited since it was collected prior to the advent of high irradiance LEDs. Light treatments for these experiments were obtained by filtering high powered wide bandwidth lighting sources using either a filter or monochromator which result in significant irradiance loss and/or limited photon flux area (Symphotic Tii, 2002). This significantly reduces the plant photosynthetic response to light treatments (Brown et al., 1995) which can result in a reduced signal to noise ratio for photosynthetic observations. The limited photon flux area associated with filtering wide bandwidth light resulted in measurements that were made over a relatively small area using a cut leaf, rather than entire plants (McCree et al., 1972a; Bulley et al.,1970) which can reduce the signal to noise ratio further. This is due to the fact that cut leaf sections are subject to considerable physiological stress which can significantly affect the cut leaf’s angular reflectance patterns and other spectral properties with time (Lao et al., 2007). Conducting action spectrum measurements over a larger leaf area with an intact plant or seedling removes this effect entirely and this can be achieved with LEDs. Unlike wide bandwidth light sources, LEDs do not require filtering to achieve narrow bandwidth light and the plant response to varying wavelengths can hypothetically be measured at a higher irradiance and/or photon flux area. This can increase the signal to noise ratio of photosynthetic response measurements required to determine the action spectrum.

Once comprehensive action spectrum data sets are collected for various plant species and irradiance levels using high irradiance LEDs, further experimentation is required to determine the optimal ratio of wavebands where peaks in action spectrum occurred since this can significantly affect a plant’s photosynthetic response (Yorio et al., 2001; Brown et al., 1995; Bula et al., 1991). Such measurements would allow the optimal spectral composition for a prototype LED array (which is determined by both wavelengths and ratio of wavelengths) for photosynthetic activity to be estimated.

1.3. Objectives

The objectives of this research were developed, in conjunction with General Electric Lighting Solutions, with the ultimate goal of developing a prototype LED array for long term greenhouse experiments. As such, the main objectives of this research were:

 To collect comprehensive action spectrum data sets for multiple plant species and irradiance levels using high irradiance LEDs  Measure the photosynthetic response of multiple plant species to varying ratios of wavebands where peaks in action spectrum occurred  Estimate an optimum spectrum of a prototype LED array for tomato, lettuce and petunia that can be used for further experimentation

1.4. Hypothesis

The objectives of this research were based on the following hypotheses:

 LED arrays can result in optimized narrow bandwidth light treatments for plant photosynthetic observations  Action spectrum varies significantly according to plant species and irradiance levels  Photosynthetic response of plants varies according to the proportion wavelengths where peaks in action spectrum occurred

Abbreviations

A Amps AAFC Agriculture and Agri-Food Canada AlGaInP Aluminum gallium indium phosphide BF Blue fluorescent

CO2 Carbon dioxide CWF Cool white fluorescent ECE Electrical conversion efficiency GF Green fluorescent HID High intensity discharge HPS High pressure sodium InGaN Indium gallium nitride LE Luminous efficacy LED Light emitting diodes lm Lumens MJ Mega joules mmol Milli moles N junction Negative junction nm Nanometers

O2 Oxygen PAR Photosynthetically active radiation P junction Positive Junction r:b Ratio of red LED (660nm) to blue LED (442nm) flux, (in Watts m-2: Watts m-2) SCL Space charge layer µmol Micro moles V Volts QE Quantum efficiency W Watts

2. Literature Review

2.1. Availability of Solar Irradiance

Light is typically considered to be the single most limiting factor in photosynthesis and growth in greenhouses (Kania et al., 2002). The availability of solar radiation throughout the year is a critical consideration when determining the viability of greenhouses (Kania et al., 2002). The most significant sunlight parameter to be considered when evaluating the suitability of year- round solar irradiance of a given location is daily light integral which is the sum of irradiance throughout a day. This value varies according to latitude, climatic conditions, and time of year. In southern Quebec, the daily light integral for solar radiation ranges from 3.9 MJ m-2 to 21.0 MJ m- 2 depending on the season (Dorais, 2003). If the daily light integral is insufficient for plant growth, supplemental light is required for efficient crop cultivation. For a given spectrum of light, increases in irradiance (within a photoperiod and specific irradiance range) typically results in a proportional amount of increase in biomass yield (Dorais, 2003). The relationship between irradiance and photosynthesis is discussed in Section 2.9. In Quebec, between 10 to 45% of the total irradiance (depending on latitude and crop) is required from artificial lights during winter months (Dorais et al, 2002) although, it is estimated that artificial lighting provides an estimated 25-41 % of heating requirements (Dorais, 2003).

2.2. Current Supplemental Lighting

Traditional light sources used in greenhouses consist of gas discharge bulb technologies. The most efficient and utilized gas discharge light for greenhouses are high intensity discharge (HID) lights and the most efficient HID light is the high pressure sodium (HPS) light (Ieperen et al., 2008). The mechanisms that trigger electroluminescence in the HPS light (and HID lights), involve the relatively disordered (and poorly controlled) collision of electrons from ionized gas molecules or plasma (Lister et al., 2004). When the bulb is exposed to an electromagnetic potential, electrical discharge occurs within the plasma and electrons collide with neighboring electrons which results in a drop in electro-magnetic potential and photon emission.

The electroluminescent plasma mixture within HPS bulbs light consists of a sodium and mercury mixture. The sodium atoms result in peak emissions in the yellow waveband and are the main source of electron density (Lister et al., 2004). When conduction is triggered in the plasma mixture, the electrons released from sodium atoms collide with mercury atoms triggering electron transitions and releasing yellow waveband photons (Lister et al., 2004). Other phenomena, such as the perturbation caused by colliding atoms and the stark effect, are responsible for the broadening of the spectrum of HID bulb, including the HPS lamp (Lister et al., 2004). The HPS spectrum is illustrated in Figure 2.1.

Figure 2.1. Spectrum of 400 W HPS. Spectrum is expressed as relative intensity vs. wavelength (General Electric, 2012).

HID lights, including the HPS light, are characterized by high operating power (>200 °C), wide bandwidth emissions (HPS emission range from 390 nm to 800nm in addition to infrared radiation) as well as a spectral composition that is not readily controlled (Ieperen et al., 2008). Spectral composition can be controlled, albeit poorly, through the addition of different metal salts or gas compositions within the HID bulb or through the use of phosphor coatings (Lister et al., 2004).

2.3. Light Emitting Diode Lighting

Light emitting diodes (LEDs) have long been restricted to low wattage indicator lights found on electronic devices, however, due to technological developments, LEDs have become much more powerful, compact, robust, durable, efficient and powerful (Nelson et al., 2013; Morrow, 2008; Tsao et al., 2004). As a result, LEDs have the potential to replace incandescent lamps, fluorescent bulbs, and high intensity discharge lamps in many high wattage lighting applications including artificial lighting in commercial greenhouses (Nelson et al., 2013; Tsao et al., 2004). Unlike HPS (and HID) lights, LEDs have low (and variable) operating power, narrow bandwidth emissions, and a readily controllable spectral distribution (Brown et al., 1995). Narrow bandwidth emissions and readily controllable spectral composition are due to the nature of solid state lighting. An LED consists of a forward biased diode with a p and n junction and electroluminescence is achieved by adding chemical impurities within junctions (Kasap, 2001). The p junction is doped with elements (also called impurities) that have an abundance of valence electrons available for conduction while the n junction is doped with elements that have a shortage of electrons or holes (Kasap, 2001). Without externally applied voltage, an electromagnetic equilibrium is reached between the n-p junctions that is characterized by potential energy however, no net current discharge occurs as the diode is in a state of equilibrium. By contrast, when external voltage is applied, equilibrium no longer exists and holes and electrons flow from the p and n junction, respectively, to the depletion region located between junctions (Kasap, 2001). Once electrons and holes combine in the depletion region, electrons drop from the conduction band to the valance band which results in photon emission. The conduction band refers to the energy of free electrons that originate from the n junction while the valence band refers to the valance energy of the holes that originate from the p junction. Photons released from LEDs correspond to the energy difference of the conduction and valence bands, also called the band gap (Kasap, 2001). The band gap of an LED can be readily manipulated by altering the doping substances, (Kasap, 2001) and the dopant concentrations (Yufeng et al., 2007). When bonds are formed within solid substrate of the LED, delocalized molecular orbitals occur (Kasap, 2001). Varying the

19 chemical composition of the solid state lighting medium varies the energy levels associated with the delocalized orbtitals in the p and n junction and varies the band gap of the materials. A simplified diagram of the semi-conductor design and charge carrier concentration along the profile of an LED is illustrated in Figure 2.2.

Figure 2.2. LED Diagram. The carrier concentrations under forward bias excitation of an LED. Charge carrier concentrations for holes are denoted by ‘po’, and ‘no’ for electrons. SCL is the space charge layer, also known as the depletion region (Kasap, 2001).

LEDs can produce light from 350 nm to 940 nm (Steigerwald et al., 2002) and spectral composition control is greater with LEDs than any other commercial lighting technology (Morrow, 2008). The spectral composition of LEDs with peak wavelengths from 400 -700 nm is illustrated in Figure 2.3.

Figure 2.3. Spectrum of Different Coloured LEDs. Relative irradiance versus peak wavelength of 14 different LED arrays at 1.4 Amps. Relative irradiance was measured from a µmol m-2 sec-1 scale.

Electric conversion efficiency is a function of operating power, and, for a given peak wavelength, LEDs operating at high power typically have lower electric conversion efficiency than LEDs operating at low power. The electrical conversion efficiency loss as a function of operating power is referred to as Droop and, in part, is a result of polarizing fields which alters the dynamics of recombination processes of holes and electrons within the LED (Kim et al., 2007).

2.4. LED Efficiency and Cost Evolution with Time

While the initial capital investment for LED lights remains higher than HPS, the cost is drastically reducing with time (Martineau et al., 2012; Steigerwald et al., 2002). Increases in LEDs electric conversion efficiency with time have also been far greater than any gas discharge bulbs and these trends are expected to persist in the future (Haitz et al., 2002). The most aggressive advancements in LED technology have occurred in the red, blue and green parts of the spectrum due to the continual development of semiconductor alloy materials.

Since the 1990’s, the evolution of AlGaInP semiconductor alloy has spurred the development of red, yellow and orange LEDs with the peak efficiency at 650 nm. By contrast, the development of InGaN spurred the development of blue LEDs with peak efficiency at 441nm (Steigerwald et al., 2002). As a result of these developments, the blue and red LEDs have the highest electric conversion efficiency. Coincidentally, the blue and red portions of the spectrum are the most utilized by plant for photosynthesis. The photosynthetic utilization efficiency of different wavelengths is explored further in Section 2.11. The advancement of LED technology, in terms of cost reduction and increases in electric conversion efficiency, is (in part) driven by the reduction in the size of transistors predicted by Haitz’s law. Based on the same principle as Moore’s law, Haitz’s law predicts that the numbers of transistors in LED chips will double every 18-24 months. Moreover, Haitz’s law also predicts LED flux per package has doubled every 18-24 months for the past 30 years (Steigerwald et al., 2002). Moreover, LED prices have fallen by a factor of 10 while performance (based on total electric conversion efficiency) has increased by a factor of 20 per decade (Steigerwald et al., 2002). According to Haitz’s law, the flux and numbers of transistors per chip will continue to increase in the future. In addition to decreasing transistor size, progress in LED quantum efficiency can also be achieved through advancements in the materials used in LED semiconductor design.

2.5. Benefits of LEDs for Plant Growth

LEDs have numerous unique characteristics that are beneficial in many applications including commercial greenhouse production. These solid state lighting devices have the potential to increase the efficiency of supplemental lighting by optimizing spectral output and, due to continual technological improvements, eventually increasing electric conversion efficiency (Nelson et al., 2013; Tsao et al., 2010; Steigerwald et al., 2002). Red LEDs currently have an electric conversion efficiency comparable to HPS lamps and greater than incandescent and fluorescent bulbs although the efficiency of other coloured LEDs are rapidly increasing (Tsao et al., 2010). Nevertheless, LEDs can already result in significant energy savings when compared to HPS due to the potential to provide light that is more efficiently utilized by plants. Martineau

22 et al. (2012) reported that overhead LED lighting resulted in 34% less energy consumption when compared to overhead HPS to obtain a similar yield of lettuce. Gomez et al. (2013) reported that the average energy cost per tomato fruit of overhead HPS lighting is 403% higher than intracanopy LEDs with no significant difference in overall tomato fruit yield. In addition to the ability to optimize spectral composition for plant growth, LED lights also have the potential to maximizing light irradiance uniformity over a crop canopy and providing a relatively constant irradiance throughout a photoperiod (Matthieu et al., 2004). LEDs have greater potential to counter temporal variation in solar irradiance than traditional gas discharge supplemental lights as LEDs can be integrated readily into digital circuits and their output can be readily controlled (Tamulaitis et al., 2005). By contrast, current supplemental gas discharge lamps operate at a fixed voltage and wattage with no direct control over light output (Matthieu et al., 2004). As the sun angle changes within a day and between seasons, and as atmospheric constituents (clouds, water vapor and ozone concentration, etc.) undergo continuous movement and mixing, temporal variation in the quantity of solar irradiance occurs (Matthieu et al., 2004). To maintain a constant average irradiance, the output of an artificial light must be readily controlled to compensate for solar variation. For example, if solar irradiance decreases by X % of total irradiance (the sum of supplemental lighting output and solar irradiance) then supplemental lighting output must increase by X% of total irradiance to maintain constant average irradiance. However, such control (of light output) can only be achieved with LED (or incandescent) lights. For LEDs, output can be readily controlled by simply adjusting the current or voltage of their circuit (Tsao et al., 2010). While light output from HID lights can be controlled indirectly, typically through the use of shade control systems (Matthieu et al., 2004), significant energy loss occurs using this method. An additional benefit of LED lights is the potential to increase light uniformity (or minimize spatial irradiance variation) within crop canopies which is required to optimize crop yields (Ieperen et al., 2008). Reducing shaded areas can be more readily achieved with low powered lighting devices as opposed to high powered devices. The lower the output power, the lower the plant heat and light saturation restrictions and the lower the space constraints on the placement of lights. In essence, low powered devices can be placed closer to plant leaves

23 resulting in greater flexibility in their placement (Ieperen et al., 2008). Plants are characterized by heat and light restrictions and if these limits are surpassed, physiological damage can occur in leaf tissues which can be fatal to the plant. LEDs operate at relatively low power allowing placement within the crop canopies and, more effectively, increase light uniformity within crop canopies (Ieperen et al., 2008). HID typically operate at high power and due to heat and light saturation restrictions, these lights cannot be placed closer than 1 m from plant canopies to avoid leaf burn (Dorais, 2003). LEDs are also more durable and compact than traditional light sources (Steigerwald et al., 2002) and have an average rated life of 50 000 hours or greater while HID lamps have an average life span ranging from 15 000 – 35 000 hours (U.S. DOE., 2008).

2.6. Photosynthetic Reaction

Photosynthesis is a chemical process where the electromagnetic energy of photons are absorbed, transferred, and stored chemically in carbohydrate molecules through a complex array of oxidation/reduction reactions in photosynthetic organisms. Photosynthetic organisms, also referred to as photoautotrophic organisms, include bacteria, algae as well as plant species and together, are the source of energy for practically all life forms on Earth (Falkowski et al., 2007). The photosynthetic process can be described by the following simplified equation:

light + 6CO2 + 12H20  C6H12O6 + 6O2 + 6H20 (EQ 2.1)

In plants, photosynthesis takes place in the mesophyll or palisade layers of leaves which contain the chloroplast, the organelle responsible for photosynthesis. The internal constituents of the chloroplast are called the stroma and within the stroma are membrane structures called thylakoids. These thylakoids are stacked to form grana and photosynthesis takes place within the membranes of these thylakoid structures. The photosynthetic apparatus is illustrated in Figure 2.4.

Figure 2.4. Schematic of the Photosynthetic Apparatus and the Chemical Reactions of Photosynthesis (Falkowski et al., 2007).

There are two protein complexes that provide the structure and functionality required for the primary light reactions in photosynthesis: photosystem I and II. Both structures are equipped with a reaction center and an antennae complex capable of absorbing and transferring electro-magnetic energy to the reaction center. While both structures are fairly similar in function there are certain notable differences in their absorbance profiles: PS I has an absorption peak of 680 nm while PS II has an absorption peak of 700 nm (Falkowski et al., 2007). The photosynthetic process can be split into either light or dark reactions and, as implied by the name, the light reaction requires light and the dark reaction does not. Photosynthesis is triggered by the light reaction which starts with the absorption of photons by pigments present in the antennae complex and/or the reaction center of photosystem II (Falkowski et al., 2007). Once the electro-magnetic energy is absorbed and transferred to the reaction center, energized electrons are transported via plastiquinone and cytochrome bf6 molecules to the reaction center of photosystem I (Falkowski et al., 2007).

In the initial light reaction in photosystem II, water is electrolyzed and O2 is formed and released from the leaf through the stomata. As photosystem I accepts electrons transported by the cytochrome bf6 complex from photosystem II, its antenna simultaneously absorbs and

25 transfers electro-magnetic energy of incident photons to its reaction center, which, similarly to photosystem II, serves to further decrease the redox potential of molecules within the reaction center (Falkowski et al., 2007). In essence, two decreases in the redox potential occur through photon absorption: one in photosystem II and another in photosystem I. After the second redox potential decrease in photosystem I, the resulting energy is then stored through the reduction of nicotinamide adenine dinucleotide phosphate (NADP) to nicotinamide adenine dinucleotide phosphate-oxidase (NAPH) and, ultimately, adenosine diphosphate to adenosine triphosphate. The resulting ATP and NADPH are then transported and used in the carbon reactions pathway or Calvin cycle pathway (Falkowski et al., 2007). NADP is a coenzyme that stores electromagnetic energy in the form of decreased redox potential when reduced to NADPH (Pollack et al., 2007). This redox potential is used in anabolic reactions of metabolic activities including lipid and nucleic acid synthesis and CO2 assimilation through reduction (Pollack et al., 2007). ADP is a molecule used to store and transfer energy in various metabolic processes in the cell when oxidized to ATP (Falkowski et al., 2007).

2.7. Pigments

The two main categories of light harvesting pigments in higher plants are chlorophyll, which is green in appearance and caratenoids (notably lutein and B-carotene) which are typically red, orange or yellow in color (Lockstein et al., 2007). The perceived color of an object is determined by absorption, transmission and reflection processes but since pigments have strong absorption in the visible waveband, their appearance is largely dominated by their absorption characteristics. For example, chlorophylls have a greenish color due to its inherent strong absorption in the red and blue portion of the visible spectrum. Chlorophyll molecules are non-covalently bound to proteins in chloroplast to form a protein chlorophyll complex while carotenoids are hydrophobic and must be anchored in the membranes of thylakoids (Lockstein et al., 2007). In essence, these pigments are assembled to form a complex antennae network within the thylakoid membrane capable of resonant energy transfer to the reaction center of the photosystems (Lockstein et al., 2007).

The most dominant pigment in higher plants is chlorophyll and there are three main categories of chlorophyll: chlorophyll a, b and c (Lockstein et al., 2007). Chlorophyll a and b can be found in plants and algae while chlorophyll c can only be found in members of the Chromista family. In higher plants, chlorophyll a and b are the most prevalent pigments in the photosynthetic process, but it is only chlorophyll a that is the primary electron donor in both photosystem I and photosystem II (Lockstein et al., 2007). By extension, all pigments other than chlorophyll a are considered to be accessory pigments and, in addition to chlorophyll a, form the antennae complex of the photosystems. Absorbance spectra of photosynthetic pigments across the PAR spectrum are presented in Figure 2.5.

Figure 2.5. Quantum Yield Curve and Pigment Absorption Spectra. The quantum yield curve averaged from 22 species measured by McCree et al. (1972a) denoted by PAR curve, along with the absorbance of the main photosynthetic pigments expressed as % absorbed wavebands from Taiz and Zeiger (2010) (Gagne et al., 2012).

Pigments are able to absorb electro-magnetic energy due to the inherent properties of their molecular structures. Chlorophyll molecules contain a porphyrin ring while carotenoids contain a carbon ring, both of which form highly conjugated systems capable of absorbing and transferring the energy of photons (Wozniak et al., 2007). The double bonds in these molecules are relatively unstable which are characterized by a magnetic moment that readily allows electron transition (Wozniak et al., 2007). The electron transition phenomena allows for electro-

27 magnetic energy to be transferred when electrons are subject to an electro-magnetic force as a result of photon absorption. The transfer of electro-magnetic energy between pigment molecules is achieved through fluorescent resonance energy transfer, which occurs through dipole to dipole interactions (Cohen et al., 2002). Due to the inherent properties of atomic resonance, certain wavelengths or frequencies allow for greater resonance and energy transfer than others (Cohen et al., 2002). This phenomenon explains, in part, the photosynthetic utilization efficiency of different wavelengths across the PAR spectrum. A leaf’s absorption spectrum is not only affected by the absorption profiles of pigments but on other factors as well such as internal and external optical properties that influence the reflection, dispersion and refraction characteristics of a leaf (McCree et al., 1972a). The absorption of tomato, lettuce and petunia is presented in Figure 2.6.

Figure 2.6. Absorption Spectrum of Tomato, Lettuce and Petunia. Absorbtion spectrum of sunlight by greenhouse tomato (Solanum lycopersicum L.), field lettuce (Lactuca sativa L.) and field petunia (Petunia × hybrida) plants as measured with a spectroradiometer (StellarNet Black Comet CXR SR-50 Spectroradiometer, Apogee instruments)(Gagne et al., 2012).

2.8. Photosynthetically Active Radiation

While solar radiation is broadband and spans from short wave to long wave (radio waves), the most important radiation for photosynthesis is within the photosynthetically active radiation (PAR). The PAR spectrum consists of radiation that triggers direct photosynthesis response in photosynthetic organisms and ranges from 400-700 nm (McCree et al. 1976). After atmospheric filtering, roughly half of the radiation that penetrates the atmosphere and reaches the earth’s surface is within the visible or PAR range. While not directly involved in photosynthesis, wavelengths outside the PAR spectrum notably UV and far red radiation, affect plant morphological and biochemical characteristics which can indirectly affect photosynthesis. For example, Halliday et al. (1994) reported that increasing amounts of far red radiation (expressed as a ratio to red light) can increase internode length and trigger earlier flowering processes. Kasperbauer (1988) observed increasing internode length with increasing far red radiation in addition to changing chlorophyll a/b contents and (as an indirect result) changing CO2 fixation and/or photosynthetic rates. UV-B can influence chlorophyll b content (Taiz and Zeiger, 1998) and thus, can also affect photosynthesis indirectly. Nevertheless, the focus of this thesis is to examine the photosynthetic response of wavelengths that trigger significant direct photosynthesis response, notably the PAR wavelengths. Plants respond to both the quantity and quality of solar radiation (Terashima et al., 2009), supplemental lighting is currently only designed to compensate for the variation in the quantity of solar radiation and not its quality. Compensation for varying light quality is possible however, its mechanisms, effects on plants, and advantages are beyond the scope of current knowledge. Due to increased spectral control, the potential for compensating for light quality is much greater with LEDs than any other current lighting technology (Tamulaitis et al., 2005).

2.9. Plant Response to Varying Light Quantity

When all other growth factors are adequately supplied, light is the most limiting factor in plant growth (Kania et al., 2002). In such conditions, plant growth and photosynthesis increases with increasing photosynthetic photon flux assuming the irradiance provided is above light

29 compensation point and below light saturation. The light compensation point is the irradiance at which an equal amount of carbon dioxide production occurs from respiration processes as oxygen production from photosynthetic processes while light saturation point is the irradiance at which maximum photosynthesis rates occur. The relationship between photosynthesis and irradiance levels (for a given spectrum) is reportedly hyperbolic in nature within the boundaries of light compensation and light saturation points (McCree et al., 1976). The exact hyperbolic relationship between photosynthetic activity and irradiance levels varies according to plant species and the quality of light. The hyperbolic relationship defined by McCree et al. (1972a) can be described by the following equation:

P= -bI / (1+aI) (EQ 2.2)

Where P is photosynthetic action, I is irradiance, a and b are parameters that include a plant and quality effect on photosynthetic action. I, a and b together, determine the tangential slopes and shape of the hyperbola.

The relationship described by Equation 2.2 implies that for a given wavelength and plant, increasing irradiance results in increasing photosynthetic rates (and ultimately yields) until light saturation point is reached which, by definition, is the irradiance at which light is no longer a limiting factor in photosynthesis. Supplemental lighting ideally should supplement solar irradiance to achieve irradiance levels just below the saturation point at an optimal irradiance where increased photosynthesis and biomass yields offset increased energy costs associated with operating lights. As stated by Equation 2.2, photosynthetic activity varies according to the wavelength and irradiance of incident light and as such, the action spectrum of plant may vary according to irradiance. The action spectrum is defined in Section 2.11. If variation caused by irradiance is significant, experiments that have observed the action spectrum of plants at low irradiances are not representative of the action spectrum at higher irradiances.

2.10. Light Quantification

Electromagnetic radiation can be quantified in radiometric units as J m-2 and W m-2 or quantum units as µmol m-2 sec-1 (McCree et al., 1972a). The distinction between both units of measure is that radiometric units are a measure of energy per unit area while quanta units are a measure of the number of photons per unit area (expressed as µmol or mole per m-2). The energy of a photon is inversely proportional to its wavelengths and equals the Plank constant, h, times the photon’s frequency. The conversion of quanta to radiometric units is dependent on the wavelength of light being measured. From a plant’s perspective, it is convenient to quantify irradiance in quanta terms as opposed to radiometric as the photosynthetic response (measured as action spectrum) is more strongly related to number of photons per unit area rather than the energy of photons per unit area (McCree et al., 1972a).

2.11. Action Spectrum

Plants only utilize wavelengths of light for photosynthesis within the visible range of the electro-magnetic spectrum (which ranges from 400-700 nm) and this spectrum is referred to as photosynthetically active radiation (McCree et al., 1972a). Within the PAR, wavelengths of light are utilized with different photosynthetic efficiencies and the action spectrum describes the photosynthetic utilization efficiency, expressed as relative photosynthetic activity across the PAR spectrum (McCree et al., 1972a).

Action = (Plight – Pdark)/ irradiance (EQ 2.3)

-2 -1 Where Plight is net photosynthesis under light is expressed in mmol CO2 m sec , Pdark is net -2 -1 -2 -1 photosynthesis in dark expressed in mmol CO2 m sec and irradiance is expressed in µmol m s .

Quantum yield also describes photosynthetic utilization efficiency (also expressed as relative photosynthetic activity at a given irradiance), although, after photon absorption by leaf pigments (McCree et al., 1972a). Quantum yield is calculated using Equation 2.4.

Quantum Yield = Action/ (Wavelength x Absorption) (EQ 2.4)

Where wavelength is the irradiance of a given wavelength and absorptance is the absorption of wavelength expressed in %.

Since absorption must be accounted for when designing the optimum spectral composition of LED lights, describing photosynthetic utilization efficiency in action spectrum is preferred from the perspective of spectral design. The principles of LED array design for plant growth are explored in Chapter 3 and 4. McCree et al.(1972a) observed increasing action spectrum peaks from 450, 500 and 675 nm when the action spectrum of 22 plant species were averaged to obtain a single action spectrum (Figure 2.1). The 450 nm and 675 nm in the averaged action spectrum corresponded strongly with the absorbance of chlorophyll a and b (the two most dominant pigments in plant leaves) and also with previous action spectrum experiments. Bulley et al. (1969) observed a local peak at 440 nm and a maximum at 660 nm for both corn and radish leaves. Balegh et al. (1970) observed a local peak at 437 nm and a maximum at 670 nm for red kidney beans. Hoover et al. (1937) observed a local peak at 435 and a maximum at 677nm for wheat. The bandwidths that were measured for the light treatments in the experiments described above were 25 nm or greater therefore, the wavelength shift of peaks (17 nm) between experiments was not significant.

2.12. Action Spectrum Measurements

Prior to the development of high irradiance LEDs, photosynthetic action spectrum was measured by filtering wide bandwidth lighting sources using either a monochromator or filters which results in significant irradiance loss and/or limited photon flux area (Symphotic Tii, 2002). A reduced photosynthetic response can result in a reduced signal to noise ratio for photosynthetic observations. A monochromator is an optical device that uses constructive interference (or amplification) by manipulating the path length of photons with high precision and accuracy through the rotation of diffractive gratings or dispersive prisms to amplify and/or filter out certain wavelengths (Palmer et al., 2005). A photon with a given wavelength undergoes positive

32 interference after reflection of the reflective diffraction grating or refraction from a dispersive prism for a given path length. Monochromators are characterized by high throughput losses as a result of the nature of filtering wavebands, the constraining nature of the field stops (the monochromator aperture is small and only accepts relatively collimated rays within the solid angle of acceptance θ) as well as grating (or prism) and reflection losses (Symphotic Tii, 2002). Monochromator throughput losses are summarized in Equation 2.5. (Symphotic Tii, 2002).

n P0 = PiVFEmR (EQ 2.5)

Where P0 is output power in mW, Pi is power incident to entrance slit plane, V is vignetting factor as a result of source image being larger than aperture of monochromator, F = (F/#illumination)2/(F/#monochromator)2 and represents losses due to F-stop mismatching between

n monochromator and light source, Em is grating efficiency, and R are total reflection losses from n mirrors. F-stop is defined as Focal length/Aperture and is a unitless number. F = 1 if (F/#illumination) > (F/#monochromator).

For a given monochromator, throughput losses depend on the bandwidth (controlled from slit width) and the photon flux incident to the entrance slit aperture within solid angle of acceptance θ measured from the slit plane. The smaller the bandwidth, the smaller the photon flux within solid angle of acceptance and the greater the throughput losses. For LED arrays used in the experiments presented in Chapter 3 and 4, throughput losses for an Oriel Cornerstone 260 1/4 m (Newport Corp. Irvine, CA) were greater than 95% for a maximum output bandwidth of 25 nm. The most comprehensive action spectrum data to date was measured by McCree et al.(1972a) who obtained light treatments by filtering a high powered xenon light source using a Bausch and Lomb high intensity monochromator. The light treatments had a 25 nm bandwidth over a 20 +/- 1 mm photon flux area across the PAR spectrum with an average irradiance of 30 W m-2. Balegh et al. (1970) obtained light treatments at an irradiance of roughly 5.9 W m-2 at a bandwidth of 25 nm although the leaf area exposed to light treatments was not specified. Bulley et al. (1969) used narrow bandwidth light treatments obtained using Balzer Filtraflex B-40 and

Schott Deptal interference filters and had an exposed leaf area of 9 cm2, with a bandwidth of 11 nm and 17 nm respectively and a constant irradiance of 40 W m-2. With LEDs, filters are not required to obtain narrow bandwidth light and photon flux losses as a result of filtering can be avoided (Fan et al., 2012).

2.13. Photosynthetic Response to Varying Light Quality

Plants respond to varying light quality through a multitude of dynamic and complex pathways. Wavelengths (directly and indirectly) trigger various morphological and biochemical reactions in plants that are vital to its health. The phytochrome system responds to light within 350-800nm and is responsible for regulating metabolic activities and photomorphological responses such as stem length, leaf shape and thickness (Dorais, 2003). Red light is important in the development of the photosystem complex and various photomorphogenetic characteristics including stem length while blue light has been identified as affecting chlorophyll concentrations, stomatal openings and other photomorphogenetic responses (Urbonaviciut et al., 2007). A combination of blue and red can result in higher photosynthetic activity and better photomorphogenesis characteristics than red or blue alone. Urbonaviciut et al. (2007) exposed lettuce plants to red LEDs (peak wavelength of 640 nm) supplemented with short wavelengths of LEDs (365, 460, 500 nm) and compared the plant response to fluorescent lamps. The treatment that included red supplementation with 500 nm resulted in significantly higher hypocotyls growth than all other treatments. The treatment that included supplementation with 365 nm light resulted in generally unhealthy plants that exhibited strange morphological changes such as spindling and slightness. Other biometric measurements including biomass accumulation, number of leaves and leaf area were not statistically significant while net photosynthesis was not statistically different for any of the treatments although, the fluorescent light treatment resulted in slightly higher photosynthesis rate. Chlorophyll a, b and carotenoid leaf concentrations exhibited no statistical difference between treatments except for chlorophyll a which had statistically higher concentration under fluorescent light than all the other treatments. Carbohydrate content was significantly higher for red LED supplemented with 465 nm blue light than for any other treatment. The results from

34 this experiment suggest that for optimal growth, red supplementation with 465 nm is much preferable to either 365 nm or 500 nm. However, the shortwave supplementation for each light treatment represented a different fraction of total photosynthetic photonic flux (PPF); as a result each LED treatment had a distinct shortwave to red ratio. The ratio of shortwave (or more notably blue) to red has a significant impact on plant photosynthesis and morphology (Urbonaviciut et al., 2007). A variation in the response amongst treatments is not attributed solely to varying wavelengths but to varying shortwave to red ratios as well. Nevertheless, since the ratios ranged from 8-12% (and were fairly similar to each other), the expected effect of changing shortwave to red ratios was on photosynthetic response was deemed to be minimal. Yorio et al. (2001) exposed radish, lettuce, and spinach to red LED light, red +blue (10%) light and cool white fluorescents (CWF); stomatal conductance, leaf photosynthetic rates, and dry mass accumulation were measured 21 days after seeding. Plants exposed to LEDs exhibited a statistically significantly lower net photosynthetis and stomatal conductance than plants exposed to CWF. Dry mass accumulation for all the treatments were all statistically different (except lettuce CWF and red+blue) with CWF resulting in the highest and red LEDs (without blue supplementation) resulting in the lowest. While both LED treatment resulted in significantly lower dry mass accumulation than CWF, mixing blue and red resulted in higher dry mass accumulation than red light alone. This experiment confirms that adding blue light to red light is more beneficial for dry mass accumulation than blue or red alone. The peak wavelength of the red LED was 660 nm and the blue fluorescents emitted wavelengths within the portion of blue of the PAR spectrum (400-500nm) while the CWF emitted wavelengths within the range from 300 – 1000 nm. While the distribution of intensity vs. wavelength for the LED resembled a normal distribution, the wavelength distribution for the cool daylight fluorescents was discontinuous (spiky in nature) and spanned a wider range of wavelengths. As such, it is difficult to attribute any plant responses from CWF treatments with any specific wavelengths. Goins et al. (1997) exposed wheat plants to red LEDs, red LEDs supplemented with blue fluorescent lamps (BF) (1% and 10%), and daylight cool fluorescent lamps. While wheat plants were able to complete a life-cycle under red light alone, certain notable morphological differences occurred when compared to the daylight cool fluorescent bulb treatments. Under

35 red LEDs (regardless of the level of blue supplementation), wheat plants generally exhibited lower stem development at both 15 and 25 days after planting (DAP), however, at 70 DAP a longer stem was observed. As BF supplementation was increased from 0% to 10%, greater shoot matter and higher net photosynthesis rates at for the plants at 15, 25, and 40 DAP, supported by Yorio et al. (2001). At 15 and 40 DAP, net leaf photosynthesis rate for the red LEDs supplemented with 10% BF was not statistically different from white daylight fluorescent. In addition, the final stem length and spike dry matter at 70 DAP for red LED supplemented with 10% was not statistically different than from white daylight fluorescent light. The peak wavelength for the red LEDs was 650 nm and the blue fluorescent lights had a bandwidth of 200 nm ranging from 350-550 and was broader than the BF used in Yorio et al. (2001). The emissions of the blue fluorescent light used in this experiment included wavelengths that are not considered blue. The variability in plant response between treatments could not be attributed solely to the variation in the blue portion but the variation of the entire spectrum of light when varying the blue fluorescents provided by the light treatments. Brown et al. (1995) exposed Hungarian Wax pepper (Capsicum annum L.) to red light, red light supplemented with far red radiation, red light supplemented with blue light (1% of PPF) and broad spectrum metal halide lights. Pepper plants that received the metal halide treatment resulted in significantly higher biomass yields than all of the other LED treatments. However, the LED treatment that included blue supplementation (1% of total PPF) resulted in significantly higher leaf, root and overall plant biomass. This result is similar to those attained by Goins et al. (1997) and Yorio et al. (2001). Both the red and far red light treatments consisted of LEDs with a spectral output of 660 nm and 730 nm, respectively. The blue wavelength supplementation was obtained using blue fluorescent bulbs (providing 1% of total PPF in blue region) while a broad spectrum metal halide lamp was used for the broadband light source. All light treatments consisted of a 300 µmol m-2 sec-1 at canopy level and the height of lights were raised throughout the experiment to maintain constant irradiance at canopy level. Yagani et al. (1996) exposed lettuce plants to blue LEDs, red LEDs, and fluorescent lights for plant growth (50% blue, 50% red) at two distinct irradiance levels of 172 and 84 µmol m-2 sec- 1. The results demonstrated that lettuce plants can complete a full growth cycle under only red

36 or only blue light, however, in both cases, notable morphological deformities were observed. Under red light alone, stem elongation was abnormally large and leaves underwent considerable curling. Lettuce plants exposed to only blue light exhibited abnormally short stems and round leaves. The difference between light quality treatments for dry biomass accumulation was not statistically significant. However, the higher irradiances results in significantly higher biomass yields for all light treatments. For all of the experiments described above, the light treatment did not include solar supplementation. It is important to note that in greenhouse applications, lighting is typically supplemented with broadband solar irradiance. To extrapolate the results of the above experiments to scenarios where solar supplementation occurs it is difficult but nevertheless certain inferences can be made. If solar supplementation (to a constant total PPF level) occurs, then the spectral quality between treatments diminishes. As such, the variation in plant response between treatments is expected to be lower in a scenario where there is background solar irradiance.

2.14. Plant Selection for Experimentation

Tomato, lettuce and petunia were selected as the higher plant species for action spectrum experimentation in this project. Tomato is the most cultivated crops in greenhouses, lettuce is the most cultivated leafy green vegetative crops in greenhouses (Stats Can.2011), and petunia is a significant crop in global greenhouse production and, similarly to tomato is a member of the nightshade family (Solanaceae). Selecting two species within the same family allows for the variation in photosynthetic response between species within the same family to be observed while selecting lettuce allows for the variation in photosynthetic response between species of different higher plant families to be observed.

2.14.1. Tomato Greenhouse Crop Profile

Tomato is the most significant greenhouse crop in terms of total tonnage production and value added per year in Canada. In 2011, it was estimated that tomato greenhouse production in

Canada was valued at $496 million for a total production of 268 502 tonnes and a total production area of 540 ha (AAFC, 2011a). In Quebec, typical supplemental lighting installations provide 120 W m-2 at canopy level with a 400 W HPS lights, although, this requirement depends on solar light availability (Dorais, 2003). Increasing the photoperiod from 12 hrs to 18 hrs increased the dry mass of tomatoes by 30% at 120 µmol m-2 sec-1 from a 400 HPS light although no statistically significant differences in fruit yield (measured as fruit mass) were observed (Dorais, 1996). Increasing the photoperiod from 18 to 24 hrs resulted in statistical higher stem and leaf dry mass, although there were no statistically significant observable difference in total fresh mass fruit yield, leaf area (Dorais, 1996).

2.14.2. Lettuce Greenhouse Crop Profile

Lettuce is one of the most cultivated vegetative crop in Canadian greenhouses with an estimated total farm gate value of $ 27.6 million from a total production area of 32 ha (AAFC, 2011b). Depending on lettuce variety, roughly 10-12 weeks is required between seeding and harvest and a greenhouse will typically produce 8-10 cycles per year (AAFC, 2006). The lighting requirements for lettuce are roughly 20 W m-2 or 100 µmol m-2 sec-1 from an HPS light over a 24hr photoperiod for seedlings. Typically, an 18 hr photoperiod is used in commercial greenhouse production (AAFC, 2006). Nevertheless, increasing the photoperiod from 16 hrs to 24 hrs at 50 and 100 µmol m-2 sec-1 increased lettuce fresh mass by up to a factor 1.4 and 1.3 respectively (Gaudreau et al., 1994).

2.14.3. Petunia Greenhouse Crop Profile

Petunias are a member of the nightshade family, and are amongst the most popular bedding plants in Canada, due to their versatility, varieties, and various flower colors. In Canada, 8.121 million potted plants were produced in 2011 (Stats Can, 2011). Petunias are considered long day plants and having a photoperiod greater than 11 hrs typically promotes early flowering (Baloch et al., 2009). Increasing the photoperiod from 8 to 17 hrs reduced the days to flowering by 16 days when day extension (after 8hrs) was achieved with 7 µmol m-2 sec-1 of artificial light (Baloch et al., 2009).

Irradiance required by petunias can range from 100- 200 µmol m-2 sec-1 with a photoperiod of 18 hrs. Increasing artificial light levels from 100 to 200 µmol m-2 sec-1 reduced days to flowering by up to 23 days at 30 °C (Kaczperski et al., 1991). At lower temperatures, the effect of irradiance on days to flowering is even greater (Kaczperski et al., 1991). Increasing the irradiance from 175 to 375 µmol m-2 sec-1 with a 16 hr photoperiod resulted in 60% increased seedling dry mass by 25% at 21 °C (Graper et al., 1992).

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Connecting Statement to Chapter 3

Action spectrum data for plants is integral to optimize the spectrum of supplemental greenhouse LED lights. Short term photosynthetic observations measured as action spectrum can be used to examine the plant photosynthetic response to wavelengths and determine which wavelengths trigger the greatest photosynthetic response. Chapter 3 describes the methodology, results and discussion of action spectrum observations for tomato (Solanum lycopersicum), lettuce (Lactuca sativa) and petunia (Petunia × hybrida) using light emitting diodes (LEDs) for light treatments.

Abstract

Light emitting diodes (LEDs) have the potential to optimize the spectrum of supplements greenhouse lights by providing wavelengths that maximize photosynthesis. The objective of this experiment is to collect action spectrum data that can be used to optimize the spectrum of LED lights. In this experiment, the action spectrum of tomato (Solanum lycopersicum), lettuce (Lactuca sativa) and petunia (Petunia × hybrida) seedlings were measured using a portable LICOR (Licor, Lincoln, NE) LI-6400XT portable photosynthesis system and LED light treatments with a 25 nm bandwidth (full width at half maximum). Photosynthetic measurements were taken from 405 nm to 700 nm. The action spectrum for all plant species were characterized by localized blue and red action peaks within the range of 430 to 449 nm and 624 to 660 nm respectively. A maximum in action spectrum also occurred at 595 nm at 30 µmol m-2 sec-1 for tomato and lettuce. The blue and red peaks were consistent with experiments conducted by Belegh et al. (1970) for corn and radish, Bulley et al. (1970) for red kidney beans, Hoover (1937) for wheat and McCree et al. (1972a) for an average action spectrum of 22 species (including tomato and lettuce). The blue and red peaks in action spectrum also corresponded well with the absorption spectrum of chlorophyll a and b and with the absorption spectrum of the plant’s leaves.

Abbreviations

A Amps BF Blue fluorescent

CO2 Carbon dioxide CWF Cool white fluorescent GF Green fluorescent HID High intensity discharge HPS High pressure sodium LED Light emitting diodes lm Lumens mmol Milli moles m Meters nm Nanometers

O2 Oxygen PAR Photosynthetically active radiation StatsCan Statistics Canada µmol Micro moles W Watts

3. Literature Review

3.1. Introduction

3.1.1. Action Spectrum

An optimized spectrum for plant growth must include wavelengths within the peak photosynthetic range as described by the action spectrum of plants (Morrow, 2008; Marcelis et al., 2002). The action spectrum describes the plant photosynthetic utilization efficiency across a range of wavelengths. Plants only utilize wavelengths within PAR for photosynthesis which ranges from 400-700 nm and photosynthetic utilization is not equal amongst PAR wavelengths (McCree et al., 1972a).

The plant action spectrum is calculated using the following equation (McCree et al., 1972a):

Action = (Plight – Pdark)/ irradiance (EQ 3.1)

-2 -1 Where Plight is net photosynthesis under lights expressed in mmol CO2 m sec , Pdark is net photosynthesis -2 -1 -2 -1 in dark expressed in mmol CO2 m sec and irradiance is expressed in µmol m sec . Plight and Pdark are normalized with leaf area.

The action spectrum of plants is affected by plant species and irradiance level amongst other factors (McCree et al., 1972a). The effect of plant species on the action spectrum is in part due to the difference between absorption spectra of leaves for different plant species. Absorption spectrum depends on the concentrations and absorption spectra of leaf pigments as well as a leaf’s internal and external structure amongst other factors (McCree et al., 1972a). Action spectrum is also affected by irradiance (McCree et al., 1972a). The effect of irradiance on action spectrum is evidenced by the fact that the relationship between irradiance and photosynthetic activity is hyperobolic and depends on wavelength (McCree et al., 1972a). This implies that the distribution of the action spectrum curve is also dependent on irradiance. This assumption supports more recent research that suggests the shifting of peak wavelength response is possible as irradiance levels increase (Hopkins et al., 2004; Köst, 1988; Heber et al., 2005). For acetone, peak absorption in a plant can shift up to 38 nm and is dependent on the specific environment surrounding the chloroplasts (Heber and Shuvalov, 2005). For the spectral design of lights, it is more convenient to express and analyze photosynthetic activity or action spectrum as opposed to quantum yield. Quantum yield is the action spectrum normalized with the absorbed irradiance for a given waveband (McCree et al., 1972a). Since the absorption spectrum of leaves affects the efficiency of lights, the action spectrum provides a better indication of which wavelengths are the most efficient for plant growth (Bugbee, 2004).

3.1.2. Pigments

The absorption spectra of photosynthetic pigments influence the action spectrum of plants as photosynthetic activity is triggered when photons are absorbed by leaf pigments (Lockstein et al., 2007). The two main categories of light harvesting pigments in higher plants are chlorophyll, which are green in appearance and carotenoids (notably lutein and β-carotene) which are typically red, orange or yellow in color (Lockstein et al., 2007). The most dominant pigment in higher plants is chlorophyll and there are three main categories of chlorophyll: chlorophyll a, b and c (chlorophyll c is only found in marine algae). The most prevalent chlorophyll pigments in higher plants are chlorophyll a and b. Chl a is characterized by a local peak at 430 nm and a maximum at 663 nm while Chl b peaks at 453 nm and 642 nm (Taiz and Zeiger, 1998). The β-carotene and lutein pigments in acetone absorb strongly in the blue region of light with a maximum peak occurring at 454 and 448 nm, respectively (Hopkins and Huner, 2004; Köst, 1988; Taiz and Zeiger, 1998). These pigments have local absorption peaks with β-carotene having a second absorption peak at 477 nm, and lutein having two local peaks at 422 and 474 nm. A leaf’s absorption spectrum is a result of the all the pigments present within the leaf as well as other internal and external optical properties which result in photon reflection, dispersion and refraction (McCree et al., 1972a). The absorption profiles of tomato, lettuce and petunia is illustrated in Figure 3.1.

Figure 3.1. Absorption Spectrum of Tomato, Lettuce and Petunia. Absorbtion spectrum of sunlight by greenhouse tomato (Solanum lycopersicum L.), field lettuce (Lactuca sativa L.) and field petunia (Petunia × hybrida) plants as measured with a spectroradiometer (StellarNet Black Comet CXR SR-50 Spectroradiometer, Apogee instruments)(Gagne et al., 2012).

3.1.3. Already Established Action Spectrum

McCree et al. (1972a) observed increasing action spectrum peaks from 450, 500 and 675 nm when the action spectrum of 22 plant species were averaged to obtain a single action spectrum. The 450 nm and 675 nm in the averaged action spectrum corresponded strongly with the absorbance of chlorophyll a and b (the two most dominant pigments in plant leaves) and also with previous action spectrum experiments. Bulley et al. (1969) observed a local peak at 440 nm and a maximum at 660 nm for both corn and radish leaves. Balegh et al. (1970) observed a local peak at 437 nm and a maximum at 670 nm for red kidney beans. Hoover et al. (1937) observed a local peak at 435 and a maximum at 677nm for wheat. The bandwidths that were measured for the light treatments in the experiments described above were 25 nm or greater therefore, the wavelength shift of peaks (17 nm) between experiments was not significant.

3.1.4. Current Supplemental Lighting Characteristics

The most commonly used artificial lights in greenhouses are high intensity discharge (HID) bulbs (Tamulaitis et al., 2005). The most utilized and efficient HID supplemental light in greenhouses is the high pressure sodium (HPS) light (Ieperen et al., 2008). Spectral emissions of HPS bulbs do not correspond to peaks in action spectrum and the spectral efficiency of HPS bulbs for plant growth is relatively limited (Morrow, 2008). Photosynthetic activity is relatively low from 540 to 620 nm where peak emissions from HPS bulbs occur (Morrow, 2008; McCree et al., 1972a). The spectrum of an HPS bulb can be controlled, albeit poorly, through the use of phosphor coatings (Tamulaitis et al., 2005). The mechanisms that trigger photon emissions in the HPS light (and HID lights), involve the disordered collision of electrons between ionized gas molecules or plasma (Lister et al., 2004). Electron collisions involving sodium atoms release yellow waveband photons and results in the peak at 589 nm. Perturbation caused by colliding atoms and external electrical fields (known as the Stark Effect) is responsible for the broad spectrum of the HPS bulb (Lister et al., 2004). In addition to poor spectral control, HPS bulbs (and all HID bulbs) are characterized by high operating power (400-600 W) and temperature (>200 °C). The implications of the HPS lighting characteristics from the perspective of plant growth are explored in Section 3.1.6.

3.1.5. LED Lighting Characteristics

LEDs are a form of solid state lighting and the principles of photon emissions are inherently different than for HPS bulbs. Photon emission in LEDs (also referred to as electroluminescence) is achieved by adding chemical impurities or dopants within the solid state diode (Kasap, 2001). The colour of an LED can be readily manipulated by altering the doping substances, (Kasap, 2001) and the dopant concentrations (Yufeng et al., 2007). Due to the wide availability of dopants, spectral composition control with LEDs is greater than any other commercial lighting technology (Morrow, 2008). AlGaInP is a semiconductor material commonly used to produce peak wavelengths within the range of 590 nm – 940 nm (Bula et al., 1991) while

InGaN is a common used material to produce peak wavelengths ranging from 350 nm – 500 nm (Steigerwald et al., 2002). Red and blue LEDs have the highest electric conversion efficiency.

Unlike HID lights, LEDs are characterized by a high degree of spectral composition control, low heat production as well as variable and low operating power which have the potential to increase the light delivery and spectral efficiency of supplemental lighting in greenhouses (Steigerwald et al., 2002).

3.1.6. Benefits of LEDs for Plant Growth

LEDs of various colors can be combined in supplemental LED array to maximize spectral efficiency and optimize plant growth (Tamulaitis et al., 2005). The spectrum of HPS bulbs cannot readily be manipulated and optimized for plant growth (Tamulaitis et al., 2005). For example, HPS lights have relatively low blue and red waveband emissions (Tamulaitis et al., 2005). Blue light has been identified as affecting chlorophyll concentrations, metabolic processes, stomatal openings and other photomorphogenic responses (Urbonaviciut et al., 2007). Red light is important in the development of the photosystem complex and various photomorphogenetic characteristics including stem length while blue light has been identified as affecting chlorophyll concentrations, stomatal openings and other photomorphogenetic responses (Urbonaviciut et al., 2007). An LED array can readily provide red and blue emissions although to fully optimize its spectrum, research is required to determine the wavelengths (or range of wavelengths) of light that optimize plant photosynthetic, photomorphogenic, phototrophic and metabolic processes (Tamulaitis et al., 2005; Hyeon-Him et al., 2004). Variable operating power allows for the optical power output from a supplemental LED light to be readily controlled depending on solar irradiance, the light required by plant species, or any other factors that affect the amount of optical output required (Matthieu et al., 2004). HPS and other HID lamps operate at a fix voltage and wattage with no direct control over light output (Matthieu et al., 2004). With supplemental LED lights, a constant and optimal irradiance below light saturation point and above light compensation point can readily be provided (Matthieu et al., 2004; Ieperen et al., 2008). The light compensation point is the point where the level of light irradiance provided to the plant results in an equal amount of carbon dioxide

53 production from respiration and oxygen production from photosynthesis. Light saturation point is the point at which light is no longer a limiting factor in photosynthesis. LEDs can provide an ideal irradiance that is below light saturation point and reduce disorders and efficiency losses associated with excess irradiance (Matthieu et al., 2004). LEDs can also reduce the amount of leaves within the canopy that are exposed to irradiance below light saturation point and this can increase photosynthetic activity and yields (Ieperen et al., 2008). Low operating power allows for greater flexibility in lighting placement as low powered devices can be placed closer to plant leaves (Ieperen et al., 2008). Plants are characterized by heat and light restrictions and if these limits are surpassed, physiological damage can occur in leaf tissues which can be fatal to the plant (Dorais, 2003). Since LEDs operate at relatively low power and are of small size, they can be placed within crop canopies and, more effectively, increase irradiance levels throughout crop canopies (Ieperen et al., 2008). HID (and HPS lights) operate at high power and due to heat and light saturation restrictions, they cannot be placed closer than 1 m from plant canopies to avoid leaf burn (Dorais, 2003).

3.1.7. Disadvantage of LED Lights for Plant Growth

Currently, the main disadvantages of LED lights are that they are relatively costly when compared to traditional commercial lights. Nelson et al. (2013) estimated that initial capital investment for LEDs are 5 to 10 times higher than conventional HPS. The electric conversion efficiency however is significantly increasing with time while cost of LEDs lights is decreasing (Nelson et al., 2013; Tamulaitis et al., 2005). The advancement of LED technology, in terms of both cost reduction and increases in electric conversion efficiency, is (in part) driven by the reduction in the size of transistors predicted by Haitz law. Based on the same principle as Moore’s law, Haitz’s law predicts that the numbers of transistors in LED chips will double every 18-24 months which will likely result in a decrease in the cost of LEDs in the near future. LED prices have fallen by a factor of 10 while performance (based on total electric conversion efficiency) has increased by a factor of 20 per decade (Tamulaitis et al., 2005). Even though the initial capital investment of an LED lights for plant growth is currently higher than for HPS lights, this will likely not be the case in the near future (Morrow et al., 2008).

3.1.8. Research Problem

Already established action spectrum data for plants is limited and observations were obtained with a photon flux over a relatively small area which can trigger a relatively low photosynthetic response from plant leaves. A reduced photosynthetic response can result in a reduced signal to noise ratio for photosynthetic observations. Prior to the development of high irradiance LEDs, narrow bandwidth light treatments used to determine the plant response to varying wavelengths were obtained by filtering broadband light sources with an interference filter and/or monochromators both of which result in significant irradiance loss (Carnie et al., 2012). For LED arrays used during this research, photon flux losses for an Oriel Cornerstone monochromator (260 1/4 m; Newport Corp. Irvine, CA) were greater than 95% for a maximum output bandwidth of 25 nm. McCree et al. (1972a) and Balegh et al. (1970) filtered a high powered xenon light source using a high intensity monochromator (Bausch and Lomb) to obtain light treatments. McCree et al. (1972a) obtained light treatment with a bandwidth at an irradiance of 30 W m-2 and a bandwidth of 25 nm over an exposed leaf area of 3.14 cm2. Balegh et al. (1970) obtained light treatments at an irradiance of roughly 5.9 W m-2 at a bandwidth of 25 nm although the leaf area exposed to light treatments was not specified. Bulley et al. (1969) used narrow bandwidth light treatments obtained using Balzer Filtraflex B-40 and Schott Deptal interference filters and had an exposed leaf area of 9 cm2, with a bandwidth of 11 nm and 17 nm respectively and a constant irradiance of 40 W m-2. With LEDs, filters are not required to obtain narrow bandwidth light and photon flux losses as a result of filtering can be avoided (Fan et al., 2012). Hypothetically, with LEDs as opposed to broadband light sources, action spectrum can be observed at a higher photon flux and/or over a greater leaf area which can result in a greater photosynthetic rate and a reduced signal to noise ratio. Measuring the action spectrum of multiple plant species can help estimate the effect of species on photosynthetic activity and action spectrum. Tomato, lettuce, and petunia were selected as the species for the action spectrum experiments as these plants are representative

55 of greenhouse crops. This selection allows for a full range of horticultural crops including a fruiting crop (tomato), a leafy vegetable crop (lettuce) and a flowering crop (petunia). Tomato is the most cultivated crops in commercial greenhouse production while lettuce is the most cultivated leafy green vegetative crops in commercial greenhouses (Stats Can., 2011). Petunia is a significant commercial greenhouse crop production and, similarly to tomatoes is a member of the nightshade family (Solanaceae). Selecting two species within the same family allows for the variation in photosynthetic response between species within the same family to be observed while selecting lettuce allows for the variation in photosynthetic response between species of different higher plant families to be observed.

3.1.9. Objectives

The objectives of this experiment were:

 Measure the action spectrum of various plant species at different irradiances using light treatments obtained with LED lights.

 Determine the impact irradiance and plant species has on photosynthetic activity and action spectrum.

 Compare action spectrum results with established action spectrum data.

3.2. Materials and Methods

3.2.1. Plant Culture

Seeds of tomato ( ‘Beefsteak’, lot A1, OSC, Ontario, Canada), lettuce ( ‘Buttercrunch’, lot A1, OSC, Ontario, Canada) and petunia (‘Purple Wave’, Dec 2009 lot, Stokes, Ontario, Canada) were sown into rockwool growing cubes (Grodan A/S, Dk-2640, Hedehusene, Denmark) and germinated in a growth chamber (E15, Conviron, Winnipeg, Canada) under fluorescent and incandescent bulbs (150 µmol m-2 sec-1) . The plants were provided with a half strength Hoagland nutrient solution described by Lefsrud et al. (2006) and exposed to a day/night temperature of 23 °C and 21°C +/- 1°C, respectively with a photoperiod of 16 hrs. The plants selected for experimentation were tested 2

56 weeks after germination and had the emergence of the 4th true leaf to allow for a relatively reproducible symmetrical leaf and plant distribution for testing. Plants were selected to be consistent in size, age, and outliers in appearance were not selected for experimentation.

3.2.2. Plant Measurements

Whole plant photosynthetic measurements were made using the LI-6400 photosynthesis system (LI-COR Inc., Lincoln, NE, USA) equipped with a 6400 -17 Whole Plant Arabidopsis chamber (LI-COR Inc., Lincoln, NE, USA). The LI-6400 provided a controlled plant environment and real time measurement of photosynthesis rates simultaneously. Whole seedlings rooted in wet rockwool were placed in the LI-6400 and parafilm was placed on top of the rockwool cube to ensure moisture retention within the root zone.

The LI-6400 controlled relative humidity (75% +/-3.5%), CO2 concentration (400 ppm +/- 10 ppm) and temperature (21°C +/- 1°C). The LI-6400 unit determined net photosynthesis by measuring carbon utilization by calculating the difference in CO2 concentration of incoming and outgoing air (to the plant chamber) using an infrared gas analyzers with a precision of 0.09 % at 350 CO2 ppm.

3.2.3. Light Treatments

The light treatments were provided with 14 distinct LED arrays each with a distinct color and peak wavelength. The 14 prototype arrays consisted of the following peak wavelengths: 405 (LedEngin, USA), 417 (Norlux, USA), 430 (Marubeni, Japan), 449, 470, 501, 520 (Phillips-Lumileds, USA), 575 (Marubeni, Japan), 595, 624, 633 (Phillips-Lumileds, USA), 662 (LedEngin, USA), 680 and 700 nm (Marubeni, Japan).

Each LED wavelength exhibited similar (full width at half maximum) bandwidth but different electric conversion efficiency and irradiance level for a given amperage. Specific wavelengths of LEDs were chosen based on the unit array design, LED availability and pigment absorption spectra. The number of LEDs per array were chosen to compensate for varying electric conversion efficiencies; the lower the electric conversion efficiency for a given

57 wavelength, the greater the number of LED point sources required to achieve a given average irradiance. Measurement of PAR for each wavelength as well as wavelength distribution was determined using a spectroradiometer (PS-300, Apogee Instruments, Logan, UT, USA) equipped with a converging lens at optical fiber aperture to minimize sampling error due to critical angle losses. The LED array was controlled (current controlled) using a single channel controller to produce uniform irradiance of specific wavelengths of light over the PAR spectrum. Specifications of the controller is a 24 VDC, 2.0 A maximum, 48 W unit with current selected and displayed (0-1.92 ADC), with automatic voltage control. Maximum power output of the LED arrays was at 28 W with optical power ranging from 0.4 to 5.5 W and PAR from 60 to 500 µmol m-2 sec-1, wavelength dependent. Each LED array was tested at three distinct irradiance levels consisting of 30, 60, and 120 µmol m-2sec-1 except for 575 and 595 nm arrays for which irradiances of 60 and 120 µmol m-2sec- 1 were not attainable due to limited electric conversion efficiency at those wavelengths. The irradiances were chosen to provide irradiances below and above light compensation point with the 120 µmol m-2sec-1 corresponding to the maximum irradiance achieved by all arrays except for 575 and 595 nm. The Arabidopsis chamber was covered with a transparent plastic film which was characterized by an average transmission of 80% (average tested value across wavelengths) across the visible spectrum and calculations were made to account for reflection and absorption losses. The experimental setup is illustrated in Figure 3.2. The light from the LED arrays was converged using a Fresnel lens (with a focal length of 17.8 cm) and reflected perpendicular to the LICOR aperture with a flat circular mirror (diameter of 7 cm) orientated at a 45 degree tilt with respect to the LED array.

Figure 3.2. Experimental Setup. The output of LED arrays was converged using a Fresnel lens (with a focal length of 17.8 cm) and reflected to the perpendicular to LICOR aperture with a flat circular mirror (with a diameter of 7cm) with a 45 degree tilt with respect of the LED array. The position of LED array, circular mirror and LICOR aperture was fixed, however, the Fresnel lens position was variable according to LED color. The distance between LED array to Fresnel lens, labeled as ‘X1’, and Fresnel to mirror distance, labeled as X2, was also variable according to the color of LED array.

The distance from the LED array to Fresnel lens, labeled as X1 and the distance between Fresnel lens to the mirror, labeled as X2, was varied according to the color of LED array. The distance between LED array and Fresnel lens, denoted by x, resulted in optimum light homogeneity. Each color of LED array employed distinct design, optical properties, lens covers and spatial distribution for the individual LED point sources (placed on a circuit board array) and each array resulted in a unique light distribution pattern. Light maps at the LICOR Arabidopsis chamber aperture were made after every three measurements for each array run to quantify irradiance spatial variation and ensure temporal stability. Eight sampling locations were selected to cover the whole variability of the LICOR aperture and were consistently used throughout the experiment. A single location was selected as an average representative of the eight sampling locations and used to set irradiance values for light treatments. With maximum light homogeneity over the LICOR aperture, the irradiance varied from 10-15% (LED array dependent) from the mean irradiance of the 8 sampling points at the maximum irradiance of 120 µmol m-2 sec-1 within the Arabidopsis test chamber.

3.2.4. Photosynthetic Measurements

The LI-6400 environment was stabilized for at least 5 min and test plants were placed inside the Arabidopsis chamber in the dark for 10 min to collect baseline photosynthesis measurements. Irradiance levels were set at one of the three levels and the plant was exposed to the LED array light for 3 min while carbon dioxide utilization rates were measured. Photosynthetic stabilization often occurred after 2 min of light treatment exposure however even after stabilization, the coefficient of variation for the net photosynthesis ranged from 0.01 to 0.7. Irradiance, peak wavelengths and bandwidth for each LED array were measured before and after photosynthetic measurements to ensure irradiance and wavelength temporal stability. Between photosynthetic measurements, plants were placed in the dark for 2 min to allow for dark respiration and to eliminate carry over effects from previous wavelengths. At least 3 replicates were obtained per plant species for each wavelength and the order of wavelengths tested was randomized to minimize the potential of interaction effects between wavelengths. Leaf area was determined by taking a digital image of leaves and using Image J software (Bethesda, MD, USA) to determine leaf area.

3.2.5. Statistical Analysis

The data was analyzed by SAS (Cary, NC, USA) using proc Mixed at a significance level of p=0.05 with Tukey adjusted pairwise comparisons for the means. Significance of random effect parameters was determined by running proc Mixed with and without the random effect parameters and comparing the Bayesian Information Criterion (BIC). If the BIC criterion for the model without the random effect parameter was less than or equal to the BIC criterion for the model with the random effect parameter, the random effect parameter was considered not statistically significant. Regression analysis was conducted using the GLM (generalized linear model) procedure of SPSS (Chicago, IL). The relationship between experimental dependent variables and treatments was estimated by regression analysis to determine light compensation point. Orthogonal polynomials were used to study changes associated with treatments by partitioning the sums of squares into components associated with linear and quadratic terms.

3.3. Action Spectrum Results

3.3.1. Tomato Action Spectrum

3 A

)

1 2 ABC - ABC ABC ABC BC ABC

sec ABC ABC

2 C

- 1 C

2 0 A

ABC AB -1 ABCD ABCD PAR 30 ABCD ABCD A AB ABCD BCD CD BCD PAR 60 -2 BCD D BC CD PAR 120 CDE CDE -3 CDE DE CDE CDE DE E CDE

Photosynthesis (mm (mm CO Photosynthesis -4

-5 400 450 500 550 600 650 700 750 Wavelength (nm)

Figure 3.3. Tomato Action Spectrum. Average relative photosynthesis response of tomato (Solanum lycopersicum) seedlings verse peak wavelength from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm peak wavelengths) at three irradiance levels (30, 60 and 120 μmol m-2 sec-1). Each data point was replicated three times with different plants, with averages plotted and bars for standard error of the mean. For each irradiation level, the means were grouped according to the Tukey method with a significance level of 0.05. The lack of data points at 575 and 595nm is due to a lack of LED arrays capable of reaching this irradiance level.

The action spectrum for tomato at 30 µmol m-2 sec-1 was characterized by a maximum in action spectrum at 595 nm which was statistically different than all wavelengths except 633 nm. The red peak at 633 nm was statistically different than photosynthetic activity at all other red wavelengths except 624 nm, while the photosynthetic response of the blue peak at 405 nm was not statistically different than any of the other blue wavelengths tested. At 60 µmol m-2 sec-1, a maximum in action spectrum occurred at 624 nm which was not statistically different than any of the other red wavelengths except 680 nm. The blue peak occurred at 430 nm and it was not statistically different than any other blue wavelengths.

At 120 µmol m-2 sec-1, a maximum in action spectrum occurred at 633 nm although it was not statistically different than any other red wavelengths. A blue peak occurred at 430 nm although it was not statistically different than any other blue wavelengths except 405 nm. For tomato at all three irradiance levels, a blue peak occurred at either 405 nm, 430 nm or 449 nm. The red peak occurred at either 624 nm or 633 nm.

Effect Pr>F

Irradiance <0.0001

Wavelength <0.0001

Irradiance x Wavelength <0.0268

Table 3.1. Tomato Statistical Analysis. Data was analyzed in SAS using proc Mixed at a significance of 0.05. Significance of random effect parameters was determined by running proc Mixed with and without the random effect parameters and comparing the Bayesian information criterion (BIC) criterion. If the BIC criterion for the model without the random effect parameter was less than or equal to the BIC criterion for the model with the random effect parameter, then the random effect parameter was considered not statistically significant.

When the data was analyzed in proc Mixed in SAS (Table 3.1), wavelength, irradiance and wavelength x irradiance interaction effects were all statistically significant for tomatoes. The plant effect or replication effect was not statistically significant.

3.3.2. Lettuce Action Spectrum

3.5 A

)

1 3

- AB sec

2.5 AB 2 - ABC ABC m ABC ABC ABC 2 2 2 ABC BC BC 1.5 PAR 30 PAR 60 1 C PAR 120 0.5

Photosynthesis (mm (mm CO Photosynthesis -0.5

-1 400 450 500 550 600 650 700 750 Wavelength (nm)

Figure 3.4. Lettuce Action Spectrum. Average relative photosynthesis response of lettuce (Lactuca sativa) seedlings verse peak wavelength from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm peak wavelengths) at three irradiance levels (30, 60 and 120 μmol m-2sec- 1). Each data point was replicated four times with different plants, with average plotted with bars for the standard error of the mean. For each irradiation level, the means were grouped according to the Tukey method with a significance level of 0.05. Data points for PAR 30 and PAR 60 were not statistically different. The lack of data points at 575 and 595nm is due to a lack of LED arrays capable of reaching this irradiance level.

The action spectrum for lettuce at 30 µmol m-2 sec-1 was characterized by a maximum at 595 nm although none of the data points were statistically different. The blue or red peaks occurred at 430 nm and 633 nm respectively. At 60 µmol m-2 sec-1, a maximum in action spectrum occurred at 624 nm and a blue peak occurred at 430 nm. None of the data points were statistically different. At 120 µmol m-2 sec-1, the red peak in action spectrum was also the maximum and occurred at 633 nm. This maximum was not statistically different than any of the other red data points. The blue peak occurred at 430 nm however, it was not statistically different than any other blue wavelengths except 405 nm. 63

The action spectrum for lettuce at all three irradiance levels was characterized by peaks in the red and blue wavebands in addition to a maximum at 595 nm at 30 µmol m-2 sec-1.

Effect Pr>F

Irradiance <0.0001

Wavelength <0.0268

Irradiance x Wavelength <0.0001

Table 3.2. Lettuce Statistical Analysis. Data was analyzed in SAS using proc Mixed at a significance of 0.05. Significance of random effect parameters was determined by running proc Mixed with and without the random effect parameters and comparing the Bayesian information criterion (BIC) criterion. If the BIC criterion for the model without the random effect parameter was less than or equal to the BIC criterion for the model with the random effect parameter, then the random effect parameter was considered not statistically significant.

As specified in Table 3.2, irradiance, wavelength and an irradiance x wavelength interaction were all statistically significant for lettuce. The random plant or replicate effect was also statistically significant and remained the statistical model.

3.3.3. Petunia Action Spectrum

3.2

2.7 A AB ABC

2.2

) ABC

1 ABC -

s ABCD ABCD

2 1.7

- BCD BCD BCD m

CD 2 1.2 A A AB D 0.7 AB AB PAR 30 ABC ABC ABC ABC 0.2 ABC PAR 60 PAR 120 -0.3 BC C -0.8

Photosynthesis(mmolCO -1.3

-1.8 400 450 500 550 600 650 700 750 Wavelength (nm)

Figure 3.5. Petunia Action Spectrum. Average relative photosynthesis response of petunia (Petunia × hybrida) seedlings versus light from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm) at three irradiance levels (30, 60 and 120 μmol m-2 sec-1). Each data point was replicated five times with different plants, with average plotted and bars for the standard error of the mean. For each irradiation level, the means were grouped according to the Tukey method with a significance level of 0.05. Data points for PAR 30 were not statistically different. The lack of data points at 575 and 595nm is due to a lack of LED arrays capable of reaching this irradiance level.

The action spectrum for petunia at 30 µmol m-2 sec-1 was characterized by a maximum at 633 nm although none of the data points were statistically different. Secondary peaks occurred at 595 nm and in the blue region at 449 nm. At 60 µmol m-2 sec-1, a maximum in action spectrum occurred at 624 nm however, it was not statistically different than any other red wavelength or the blue peak which occurred at 430 nm. The 430 nm peak did not have statistically different photosynthetic response than any other blue wavelengths except 417 nm. At 120 µmol m-2 sec-1, a maximum in action spectrum occurred at 633 nm although it was not statistically different than photosynthetic activity at any other red wavelengths or the blue peak which occurred at 430 nm. The 430 nm peak was only statistically different than 405 nm.

For all irradiances, the blue peak for petunia occurred at either 430 nm or 449 nm. The red peak occurred at either 624 nm or 633 nm.

Effect Pr>F

Irradiance <0.0001

Wavelength <0.0001

Irradiance x Wavelength <0.0928

Table 3.3. Petunia Statistical Analysis. Data was analyzed in SAS using proc Mixed at a significance of 0.05. Significance of random effect parameters was determined by running proc Mixed with and without the random effect parameters and comparing the Bayesian information criterion (BIC) criterion. If the BIC criterion for the model without the random effect parameter was less than or equal to the BIC criterion for the model with the random effect parameter, then the random effect parameter was considered not statistically significant.

As specified in Table 3.3, irradiance and wavelength were all statistically significant, however, a wavelength x irradiance interaction effects was not statistically significant for petunias. The individual plant or replicate effect was not statistically significant and was removed from the statistical model.

3.3.4. All Plants Action Spectrum

For all three plants at all three irradiances, blue and red peaks in action spectrum occurred in the range of 417 nm – 449 nm and 624 nm to 660 nm.

Effect Pr>F

Irradiance <0.0001

Species <0.0001

Wavelength <0.0001

Species x Wavelength <0.0001

Species x Irradiance <0.0001

Wavelength x Irradiance <0.0001

Table 3.4. All Plants Statistical Analysis. Data was analyzed in SAS using proc Mixed at a significance of 0.05. Significance of random effect parameters was determined by running proc Mixed with and without the random effect parameters and comparing the Bayesian information criterion (BIC) criterion. If the BIC criterion for the model without the random effect parameter was less than or equal to the BIC criterion for the model with the random effect parameter, then the random effect parameter was considered not statistically significant.

When the data sets for all plants were combined (Table 3.4), species, plant, irradiance, wavelength, species, species x wavelength, species x irradiance, and irradiance x wavelength interaction effects were all statistically significant.

3.3.5. Light Compensation

120 110 100

)

2 80 - 70 60 Tomato 50 Petunia

40 Lettuce Irradiance (umol m (umol Irradiance 30 20 10 0 400 450 500 550 600 650 700 Wavelength (nm)

Figure 3.6. Light Compensation Points. Light compensation point for three plant species calculated (linear regression) from average relative photosynthesis response of tomato (Solanum lycopersicum), lettuce (Lactuca sativa), and petunia (Petunia × hybrida) seedlings at three irradiance levels (30, 60 and 120 μmol m-2sec-1) light from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm). The lack of data points at 575 and 595nm is due to a lack of LED arrays capable of reaching this irradiance level. Each data point was replicated at least three times with different plants, with average plotted with standard deviation bars. Lines are placed to estimate possible curve fitting and by no means have been scientifically proven.

From regression analysis (linear) the light compensation point was determined for each wavelength (Figure 3.6). The average light compensation point for tomato was 94.4 ± 10.9 μmol m-2 sec-1, for lettuce was 36.4 ± 7.7 μmol m-2 sec-1, and for petunia was 66.1 ± 12.4 μmol m-2 sec- 1. The linear equation and resulting R2 (between 0.68 and 0.95) for each equation is provided in Table 3.5 and 3.6.

Tomato Lettuce Compensation Compensation Wavelength R2 Constant b1 point R2 Constant b1 point 405 0.963 -3.56 0.03 104.9 0.209 -0.24 0.01 32.4 417 0.972 -5.70 0.06 97.4 0.678 -1.11 0.02 46.3 430 0.958 -4.30 0.05 85.9 0.725 -0.78 0.02 34.1 449 0.951 -4.75 0.05 93.2 0.878 -0.70 0.02 33.1 470 0.912 -5.19 0.05 101.7 0.654 -1.02 0.02 48.4 501 0.987 -5.71 0.05 107.7 0.578 -0.77 0.02 42.5 520 0.945 -5.49 0.05 103.6 0.709 -0.86 0.02 45.5 575 595 624 0.958 -4.01 0.05 77.0 0.835 -0.84 0.03 26.1 633 0.930 -3.20 0.04 72.6 0.899 -0.89 0.03 27.8 662 0.926 -4.31 0.05 93.6 0.769 -0.67 0.02 27.9 680 0.988 -5.46 0.06 99.3 0.669 -0.85 0.02 38.6 700 0.966 -5.23 0.05 96.8 0.636 -0.75 0.02 33.9 Average 0.955 94.5 0.687 36.4 St. dev. 10.9 7.7

Table 3.5. Light Compensation Data - Tomato and Lettuce. Light compensation point calculated (linear regression) from average relative photosynthesis response of tomato (Solanum lycopersicum) and lettuce (Lactuca sativa) seedlings at three irradiance levels (30, 60 and 120 μmol m-2sec-1) light from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm). The lack of data points at 575 and 595 nm is due to a lack of LED arrays capable of reaching this irradiance level. Each data point was replicated at least five times with different plants.

Petunia Wavelength R2 Constant b1 Compensation point 405 0.946 -1.80 0.02 91.3 417 0.883 -2.48 0.03 77.6 430 0.911 -1.47 0.03 54.5 449 0.859 -1.38 0.03 55.2 470 0.793 -1.82 0.03 67.3 501 0.807 -2.03 0.03 75.3 520 0.804 -2.10 0.03 72.6 575 595 624 0.807 -2.07 0.04 55.9 633 0.849 -1.74 0.04 49.7 662 0.774 -1.62 0.03 54.1 680 0.830 -2.21 0.03 71.4 700 0.898 -2.25 0.03 68.1 Average 0.847 66.1 St. dev. 12.4

Table 3.6. Light Compensation Data - Petunia. Light compensation point calculated (linear regression) from average relative photosynthesis response of petunia (Petunia × hybrida) seedlings at three irradiance levels (30, 60 and 120 μmol m-2 sec-1) light from 14 LED arrays (405, 417, 430, 449, 470, 501, 520, 575, 595, 624, 633, 662, 680 and 700 nm). The lack of data points at 575 and 595nm is due to a lack of LED arrays capable of reaching this irradiance level. Each data point was replicated at least five times with different plants.

3.4. Discussion

3.4.1. Action Spectrum for Plant Species

The action spectrum for all plant species were characterized by localized blue and red action peaks within the range of 430 to 449 nm and 624 to 660 nm respectively. These peaks were consistent with experiments conducted by Belegh et al. (1970) for corn and radish, Bulley et al. (1970) for red kidney beans, Hoover (1937) for wheat and McCree et al. (1972a) for an action spectrum averaged for 22 species (including tomato and lettuce). All of the blue and red peaks in these experiments also occurred within 430 to 449 nm and 624 to 660 nm range respectively. The blue peaks in action spectrum also corresponded well with the absorption spectrum photosynthetic pigments notably chlorophyll a and b, lutein, β-carotene, zeaxanthin, and lycopene. The red peaks in action spectrum corresponded well with the absorption spectrum of chlorophyll a and b as well as zeaxanthin. The red and blue peaks were also 70 consistent with the measured absorption spectrum of tomato, lettuce and petunia where peak absorption occurred. Notable differences in the tomato and lettuce action spectrum occurred in the yellow waveband. Lettuce had a higher relative response from 470 nm to 575 nm when compared to tomato. This difference could be due to the shade plant characteristics of the lettuce plant verses the sun plant characteristics of the tomato plant (Taiz and Zeiger, 2010; Terashima et al., 2009; Vogelmann, 1993). Shade plants do not receive as much blue and red light as the sun plants and this shift in photosynthetic efficiency at low irradiance levels could be due to this response (Taiz and Zeiger, 2010; Terashima et al., 2009; Vogelmann, 1993).

3.4.2. Action Spectrum for All Irradiances

There were observable differences between action spectrums for a given species at different irradiances. Most notably, the red and blue peaks shifted slightly however this shift was never greater than 25 nm or to the next LED array colour available for testing. Similar shifts were observed in experiments conducted by Heber and Shuvalov (2005) who observed that acetone can shift its absorbance by as high as 38 nm. The observed shifts in blue and red peaks as irradiance increased however were not consistently positive or negative, and there were no observable patterns in these shifts. The observed 25 nm (or less) shifts in blue and red peaks may be a result of noise considering the bandwidth of the LED light treatments was also 25 nm (full width at half maximum). This is further supported by the wavelength dependent hyperbolic relationship between irradiance and photosynthetic activities estimated by McCree et al. (1972a) which predicts a consistent positive or negative shift in action spectrum peaks as irradiance increases.

3.4.3. Light Compensation

The light compensation data supports the premise that light compensation and light saturation points depends on wavelength. The dependence of light compensation and saturation points supports the theory that the (non-linear) relationship between irradiance and photosynthetic activity depends on wavelength which was reported by McCree et al. (1972a). These results also suggest that the distribution of action spectrum varies as irradiance changes.

3.4.4. Green Peak at 595 nm

The peak at 595 nm was not consistent with action spectrum observations made by McCree et al. (1972a), Balegh et al. (1970) and Bulley et al. (1970), which only observed a shoulder at 600 nm. The 595 nm peak was also not consistent with the absorption profiles for all plant species (Figure 3.1) as all plants had relatively low absorption at 595 nm when compared to the absorption with 417 to 449 nm and 624 to 660 nm ranges. Hyeon-Hye et al. (2004) reported that yellow and green light, including 595 nm, (obtained with GF lights with emissions ranging from 500 to 600 nm) can be more photosynthetically efficient than any other wavelength when added to background red and blue LEDs at 150 µmol m-2 sec-1. However, Hyeon-Hye et al’s (2004) results do not explain the 595 nm peak in action spectrum peak that was observed without background radiation.

3.4.5. Statistical Analysis

The 595 nm peaks were not statistically significant and observations made at an irradiance of 30 µmol m-2 sec-1 had the highest estimated signal to noise ratio (measured as the reciprocal of the coefficient of variation) when compared to 60 and 120 µmol m-2 sec-1. This is expected to be a result of the lower photosynthetic response and signal at 30 µmol m-2 sec-1 as opposed to 60 or 120 µmol m-2 sec-1. Since none of the 595 nm peaks were statistically significant and/or corresponded with previously observed action spectrums or absorption profiles of plant species, further research is required to validate these peaks at 595 nm. As illustrated in Figure 3.4, lettuce exhibited a greater variation between replicates and, unlike tomato and lettuce, the plant effect was statistically significant. A plant effect in the statistical model presented above will not restrict any effects originating from the plant and could include any noise effects generated by the measuring devices, the LICOR controlled environment, or the external environment. Since petunia and tomato did not exhibit a significant plant effect (on photosynthetic activity), it is likely that this effect originated from differences between individual lettuce plants. This suggests that a greater range of wavelengths may be optimal for lettuce photosynthesis, which allows for greater freedom when trying to select the optimal spectrum for lettuce growth.

When data for all species were combined and analyzed statistically using proc Mixed in SAS (Table 3.4), species x wavelength and irradiance x wavelength both had a statistically significant on photosynthetic activity. However, the statistical significance of these interaction effects had little effect on the peaks in photosynthetic activity since the blue and red peaks for all three species at all three irradiances occurred within the range of 417 to 449 nm and 624 to 660 nm respectively.

3.4.6. Optimal Spectrum for a Supplemental Prototype LED Light for Plant Growth

A combination of blue and red can result in higher photosynthetic activity and better photomorphogenic characteristics than red or blue alone. Red light is important in the development of the photosystem complex and various photomorphogenetic characteristics including stem length while blue light has been identified as affecting chlorophyll concentrations, stomatal openings and other photomorphogenetic responses (Urbonaviciut et al., 2007). A combination of red and blue light may be optimal for a prototype supplemental LED array used for further long term experiments.

3.5. Conclusion

The 449 nm and 660 nm wavelengths may be optimal for supplemental LED lights since they were in peak photosynthetic range and these LEDs have the greatest electric conversion efficiency in the blue and red wavebands respectively. From the perspective of selecting an optimum spectrum for a supplemental LED light for plant growth, the peak in photosynthetic activity at 595 nm at 30 µmol m-2 sec-1 currently has little impact; these LEDs are the least efficient of all the visible wavelengths (Hyeon-Hym et al., 2004) and their use in supplemental LED array is currently not economically feasible. With the progression of LED technology and expected increase in electric conversion efficiency, the use of 595 nm in a supplemental LED array might be economically viable in the future. Both 660 nm and 449 nm are within the optimal range for photosynthetic activity as described by action spectrum although the ratio of these wavelengths to optimize photosynthetic activity is still unknown. To optimize the spectrum of a supplemental LED light,

73 further research is required to observe the plant photosynthetic and morphological effect of combining these wavelengths at different proportions. It has already been evidenced that the plant photosynthetic response is dependent on the proportion or ratio of wavelengths (Goins et al., 2004). The photosynthetic response to combined wavebands is also not equal to the sum of the individual wavebands (Govindjee., et al., 1964). Additional plant observations are therefore required to estimate the optimal proportion of blue and red wavelengths for an LED array in order to optimize photosynthetic rates and yields.

References

Agriculture and Agri-Food Canada. 2006. Crop Profile of Greenhouse Lettuce in Canada. Ottawa, Ontario.