The Effects of Wavelength Specific Light-Emitting Diode (LED) Lighting on Net Carbon Exchange Rate, Export, and Partitioning in Tomato

(Solanum lycopersicum)

By

Jason Lanoue

A Thesis

Presented to

The University Of Guelph

In partial fulfillment of requirements

for the degree of

Master of Science

in

Plant Agriculture

Guelph, Ontario, Canada

© Jason Lanoue, September, 2016

ABSTRACT

THE EFFECTS OF WAVELENGTH SPECIFIC LIGHT-EMITTING DIODE (LED) LIGHTING ON NET CARBON EXCHANGE RATE, EXPORT, AND

PARTITIONING IN TOMATO (Solanum lycopersicum)

Jason Lanoue Advisor: University of Guelph, 2016 Professor Bernard Grodzinski

This thesis is an investigation of the effects of wavelength specific lighting on tomato

growth and source leaf photosynthesis and export. Plants grown in a greenhouse during the

winter months under ambient or supplemental lighting showed little difference in whole

plant or leaf net carbon exchange rate nor carbon gain. However plants grown under

supplemental lighting produced statistically higher biomass and flower bud production.

Differences in transpiration rates and water use efficiency were determined when plants

were analyzed red-blue and red-white lighting treatments. An increase in daily export rates

was seen under red-blue and blue when compared to white or red light treatments of white

light grown plants. These increases in export rates indicate a direct effect on the export rates

solely based on spectral quality. Results from this thesis aim to increase the understanding

of wavelength specific lighting effects on tomatoes and help aid in optimizing the light

spectrum for greenhouse production.

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Acknowledgements

I would like to sincerely thank my advisor, Dr. Bernard Grodzinski, for all his support,

friendship and invaluable advice throughout my Masters. I would also like to thank my

advisory committee, Drs. Eric Lyons and Rong Cao for their questions and inquires which

helped improve my thesis and experimental design.

I would like to thank Dr. Evangelos Demosthenes Leonardos for his friendship and

immense help with the technical aspects during experimental set up. Naheed Rana for her

technical support in the lab with sample analysis as well as Ron Dutton for his assistance

with LED lighting and growth chambers.

I am grateful to my fellow graduate students for their friendship and advice

throughout my masters. I would like to thank my family and friends in both Guelph and

Windsor for their encouragement and support. My parents Anna and Rob, and my siblings

Dana and Melissa and their families.

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Table of Contents

Abstract……………………………………………………………………………………………………...ii

Acknowledgements……………………………………………………………………………………iii

Table of Contents………………………………………………………………………………………..iv

List of Tables……………………………………………………………………………………………..vii

List of Figures……………………………………………………………………………………………vii

List of Abbreviations and Definitions…………………………………………………………….x

Chapter 1: General Introduction………………………………………………………………...…1

1.1 Greenhouse Commercial Production and Supplemental Lighting………………………………….1 1.2 Light Spectral Quality……………………………………………………………………………………………...…4 1.2.1 Red Light……………………………………………………………………………………………………………..4 1.2.2 Blue Light…………………………………………………………………………………………………………….6 1.2.3 Green Light……………………………………………………………………………………………………….....8 1.3 Photosynthesis and Carbon Partitioning………………………………………………………………….....9 1.4 Carbon Export…………………………………………………………………………………………………………11 1.5 Hypothesis and Objectives……………………………………………………………………………………….14 1.6 Thesis Overview ……………………..………………………………………………………………………………15

Chapter 2: The Effect of HPS and Wavelength Specific LED Light on Whole Plant and Leaf CO2 and H2O Gas Exchange and Growth Parameters Under Long-term Acclimation of Solanum lycopersicum cv. ‘Bonny Best’………………………………….16 2.1 Introduction……………………………………………………………………………………………………………16 2.2 Material and Methods………………………………………………………………………………………………17 2.2.1 Plant Materials and Growth Conditions………………………………………………………………….17 2.2.2 Whole Plant Gas Exchange……………………………………………………………………………………..18 2.2.3 Leaf Gas Exchange…………………………………………………………………………………………………24 2.3 Results……………………………………………………………………………………………………………………25 2.4 Discussion……………………………………………………………………………………………………………….46 2.4.1 Effects of Supplemental Lighting on Whole Plant CO2 Gas Exchange………………………..46 2.4.2 Effects of Supplemental Lighting on Whole Plant H2O Gas Exchange………………………..48 2.4.3 Effects of Supplemental Lighting on Leaf CO2 Gas Exchange……………………………………..49 2.4.4 Effects of Supplemental Lighting on Leaf H2O Gas Exchange …………………………………..50

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Chapter 3: The Effect of HPS and Wavelength Specific LED Lights on Whole Plant and Leaf CO2 and H2O Gas Exchange and Growth Parameters Under Short-term Acclimation of Solanum lycopersicum cv. ‘Bonny Best’………………………….51 3.1 Introduction……………………………………………………………………………………………………………51 3.2 Material and Methods………………………………………………………………………………………………52 3.2.1 Plant Materials and Growth Conditions…………………………………………………………………..52 3.2.2 Daily Patterns of Whole Plant Gas Exchange……………………………………………………………53 3.2.3 Induction of Leaf Photosynthesis - Wake Up Experiments.………………………………….…....54 3.2.4 Responses to Wavelength Specific Lighting - Light Curves.……………………………………….55 3.3 Results……………………………………………………………………………………………………………………56 3.3.1 Whole Plant CO2 and H2O Gas Exchange at Saturating Light Level……………………………56 3.3.2 Whole Plant CO2 and H2O Gas Exchange at Sub-Saturating Light Level…………………….63 3.3.3 Wake Up……………………………………………………………………………………………………………….70 3.3.4 Leaf Light Curves…………………………………………………………………………………………………..71 3.4 Discussion……………………………………………………………………………………………………………….77 3.4.1 Comparison of Wavelength Specific Lighting and HPS Lighting on Whole Plant CO2 Gas Exchange...…………………………………………………………………………………………………………………....77 3.4.2 Comparison of Wavelength Specific Lighting on Leaf CO2 Gas Exchange……………………80 3.4.3 Effects of Wavelength Specific Lighting on Plant Wake Up………………………………………81 3.4.4 Effects of Wavelength Specific Lighting on H2O Gas Exchange………………………………….83

Chapter 4: Effects of Wavelength Specific Light on Carbon Fixation, Export and Partitioning in Solanum lycopersicum cv. ‘Bonny Best’…………………………………86 4.1 Introduction……………………………………………………………………………………………………………86 4.2 Materials and Methods………………………………………………………………………………………….....87 4.2.1 Plant Materials and Growth Conditions……………………………………………………………….....87 4.2.2 14C Export………………………………………………………………………………………………………….....88 4.2.2.1 Short Term 14C Feeding………………………………………………………………………………………88 4.2.2.2 Photoperiod Long Feed-Chase Export………………………………………………………………….90 4.2.3 14C Partitioning…………………………………………………………………………………………………......91 4.3 Results……………………………………………………………………………………………………………………96 4.4 Discussion……………………………………………………………………………………………………………..126 4.4.1 Effects of Wavelength Specific Lighting on H2O Gas Exchange………………………………..126 4.4.2 Effects of Wavelength Specific Lighting on Export During 3h Illumination………………126 4.4.3 Effects of Wavelength Specific Lighting on 14C Export and Partitioning During 15h Illumination and Subsequent 8h Dark Period……………………………………………………………….128

Chapter 5: Thesis Summary……………………………………………………………………...133 References……………………………………………………………………………………………...140 Appendix I: Chapter 2 Supplemental Tables………………………………………………152

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Appendix II: Chapter 3 Supplemental Tables……………………………………………..156 Appendix III: Supplemental Lighting Spectral Quality………………………………..164 Appendix IV: Statistical Analysis………………………………………………………………169

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List of Tables

Table 2.1: Physical growth measurements of greenhouse grown tomato plants under supplemental and ambient light conditions……………………………………………………………………28 Table 2.2: Whole plant daily average NCER and daily C-budgets on greenhouse grown tomato plants under supplemental and ambient lighting conditions………………………………..36 Table 2.3: Whole plant daily average transpiration rates and WUE of greenhouse grown tomato plants under supplemental and ambient lighting conditions………………………………..39 Table 3.1: Whole plant daily average NCER and C-budgets of tomato plants grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 1000±25µmol m-2 s-1…………62 Table 3.2: Whole plant daily average transpiration rates and WUE of tomato plants grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 1000±25µmol m-2 s-

1…………………………………………………………………………………………………………………………………...63 Table 3.3: Whole plant daily average NCER and C-budgets of tomato plants grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 350±10µmol m-2 s-1…………….69 Table 3.4: Whole plant daily average transpiration rates and WUE of tomato plants grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 350±10µmol m-2 s-

1…………………………………………………………………………………………………………………………………...70 Table 3.5: Effect of wavelength on wake up time of dark adapted tomato leaves………………71 Table 4.1: 15h and 23h daily average CO2 and H2O leaf gas exchange measurements for both high and low Pn rates under R, B, RB, or W light treatments……………………………………………105 Table 4.2: 15h and 23h of Pn, E, 14C partitioning, and 14C fate measurements under high Pn leaves illuminated with RB, W, R, or B light treatments…………………………………………………..122 Table 4.3: 15h and 23h of Pn, E, 14C partitioning, and 14C fate measurements under low Pn leaves illuminated with RB, W, R, or B light treatments…………………………………………………..124

List of Figures

Figure 2.1: Schematic of greenhouse light treatments and orientation…………………………….18 Figure 2.2: Overview of the whole plant gas exchange system and individual chambers lit with respective light treatments……………………………………………………………………………………21 Figure 2.3: Li-COR 6400 set up for greenhouse light curves with RB LED Li-COR standard chamber……………………………………………………………………………………………………………………….24

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Figure 2.4: Biomass production of greenhouse grown plants under supplemental and ambient light conditions………………………………………………………………………………………………..26 Figure 2.5: Whole plant NCER and C-budgets of greenhouse grown tomato plants grown under supplemental lighting………………………………………………………………………………………….30 Figure 2.6: Whole plant NCER and C-budgets of greenhouse grown tomato plants grown under ambient conditions……………………………………………………………………………………………...32 Figure 2.7: Whole plant transpiration rate and WUE of greenhouse grown tomato plants under both supplemental and ambient lighting conditions………………………………………………34 Figure 2.8: Light curves of greenhouse grown under both supplemental and ambient lighting conditions analyzed with a RB LED Li-COR standard….………………………………………42 Figure 2.9: Leaf transpiration rates, stomatal conductance, and internal CO2 concentration of greenhouse grown tomato plants under both supplemental and ambient lighting conditions analyzed with a RB LED Li-COR standard………………………………………………………44 Figure 3.1: Tomato leaf in a clear chamber of a Li-COR 6400…………………………………………..54 Figure 3.2: Whole plant NCER and C-budgets of W light grown tomato plants and analyzed under RB LED, RW LED, or HPS lighting at 1000±25µmol m-2 s-1 …………………………………….58 Figure 3.3: Whole plant transpiration rates and WUE of tomatoes grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 1000±25µmol m-2 s-1 ....……………………..60 Figure 3.4: Whole plant NCER and C-budgets of W light grown tomato plants and analyzed under RB LED, RW LED, or HPS lighting at 350±10µmol m-2 s-1 ……………………………………….65 Figure 3.5: Whole plant transpiration rates and WUE of tomatoes grown under W light and analyzed under RB LED, RW LED, or HPS lighting at 350±10µmol m-2 s-1....………………………..67 Figure 3.6: Wavelength specific lighting effect on leaf NCER……………………………………………73 Figure 3.7: Wavelength specific lighting effect on leaf stomatal conductance……………………74 Figure 3.8: Wavelength specific lighting effect on leaf transpiration rates……………………….75 Figure 3.9: Wavelength specific lighting effect on leaf internal CO2 concentration……………76 Figure 4.1: 14C leaf chamber setup…………………………………………………………………………………88 Figure 4.2: 14C leaf extraction process……………………………………………………………………………94

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Figure 4.3: 15h and 23h stomatal conductance for both high and low Pn rates under R, B, RB, or W light treatments……………………………………………………………………………………………….97 Figure 4.4: 15h and 23h transpiration rates for both high and low Pn rates under R, B, RB, or W light treatments……………………………………………………………………………………………………99 Figure 4.5: 15h WUE for both high and low Pn rates under R, B, RB, or W light treatments………………………………………………………………………………………………………………….101 Figure 4.6: 15h and 23h internal CO2 concentration for both high and low Pn rates under R, B, RB, and W light treatments………………………………………………………………………………………103 Figure 4.7: 3h 14C feeds of tomato leaves under R, B, RW, RB, W, and G light treatments…..108 Figure 4.8: 15h and 23h NCER, E, and % E relative to Pn of 14C feed leaves under high Pn from R, B, RB, or W light treatments…………………………………………………………………………...…112 Figure 4.9: 15h and 23h NCER, E, and % E relative to Pn of 14C feed leaves under low Pn from R, B, RB, and W light treatments……………………………………………………………………………………114 Figure 4.10: 15h and 23h 14C fraction recovery from both high and low Pn leaves illuminated with R, B, RB, or W light treatments………………………………………………………………………………116 Figure 4.11: 15h and 23h 14C fate from high Pn leaves illuminated with R, B, RB, or W light treatments………………………………………………………………………………………………………………….118 Figure 4.12: 15h and 23h 14C fate from low Pn leaves illuminated with R, B, RB, or W light treatments………………………………………………………………………………………………………………….120

x

List of Abbreviations and Definitions

ATP Adenosine triphosphate

AtSUC3 Sucrose transporter found in Arabidopsis

B Blue light treatment

Ba14CO3 Radioactive barium with radiolabelled 14C

BB Bonny Best; Tomato cultivar

14C Isotope of carbon; Radiolabelled carbon

14CO2 Carbon dioxide radiolabelled with 14C

CC Companion cell

Chl Chlorophyll

Ci Internal CO2 concentration measured in µmol of carbon m-2 s-1

CRY Cryptochrome

DAP Days after planting

DHAP Dihydroxyacetone phosphate

DLI Daily light integral

G Green light treatment

GA Gibberellin; Factor in seed germination

GGPP Geranylgeranyl pyrophosphate; Intermediate in the biosynthetic

pathway of carotenoids

G-3-P Glyceraldehyde 3-phosphate

H+ Proton

H+-ATPase An enzyme which catalyzes a dephosphorylation of ATP in order to

move H+ against it concentration gradient

HCl Hydrochloric acid

HID High-intensity discharge

HPS High pressure sodium

H2SO4 Sulfuric acid

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IC Intermediary cell

IRGA Infrared gas analyzer

LED Light emitting diode

LSC Liquid scintillation counter

MC Mesophyll cell

MH Metal halide

NADPH Nicotinamide adenine dinucleotide phosphate

NaH14CO3 Sodium bicarbonate radiolabelled with 14C

NCER Net carbon exchange rate; units of measure are µmol of carbon m-2 s-1

O Orange light treatment

PAR Photosynthetically active radiation

PHY Phytochrome

Pn Photosynthetic rate

PPC Phloem parenchyma cell

Ppm Parts per million

PSI Photosystem I

PSII Photosystem II

R Red light treatment

RB Red and blue light treatment

RBG Red, blue, and green light in a mixture

RFO Raffinose family oligosaccharide

Rubisco Ribulose-1,5-bisphosphate carboxylase oxygenase

RuBP Ribulose-1,5-bisphosphate

RW Red and white light treatment

QTL Quantitative trait locus

SPS Sucrose-phosphate synthase

SPS-PP Sucrose phosphate synthase – protein phosphatase

SUC Sucrose transporter; Also found in literature as SUT

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SWEET Sugars will eventually be exported transporter

TC Transfer cell

TP Triose phosphate

TPT Triose phosphate translocator

WP-NCER Whole plant net carbon exchange rate

WUE Water use efficiency; the rate of NCER to transpiration (µmol

CO2/mmol H2O)

3-PGA 3-phosphoglycerate

1

CHAPTER 1

General Introduction

1.1 Greenhouse Commercial Production and Supplemental Lighting

The tomato (Solanum lycopersicum) resides in the Solanaceae or nightshade family of

plants and is classified as a berry on the basis of molecular phylogeny (Knapp, 2002). Tomato

fruits vary in size drastically due to the expression of one quantitative trait locus (QTL),

fw2.2, and can range from 20 grams to over one kilogram (Frary et al. 2000). While tomatoes

are generally seen as red in colour, they can also be found as purple, yellow, orange, or green

which is again, controlled by various QTLs (Liu et al. 2003).

The commercialization of tomatoes has become of vast important as they are a staple in

many foods and provide a great nutritional profile. In 2013, upwards of 163 million tonnes

of tomatoes were produced worldwide (FAO United Nations, 2016). In 2016 there were 987

acres of greenhouses across Ontario dedicated to the production of tomatoes (Ontario

Greenhouse Vegetable Growers, 2016). Production of all vegetables, not only tomatoes, has

drastically improved in Canada and other northern countries with the implementation of

greenhouses and supplemental lighting which allow for year round growth and increased

yields (Ontario Greenhouse Vegetable Growers, 2016).

Currently, greenhouse lighting is comprised of high-intensity discharge (HID) lamps

such as Metal Halide (MH) or, mostly, high pressure sodium (HPS) lights. The addition of

lights as an alternative or supplement to ambient sunlight have seen a drastic increase in

production of greenhouse crops and ornamentals as it allows for the increase in the daily

light integral (DLI) (McAvoy & Janes, 1984; Oh et al., 2009). During the January months, the

2

addition of 150 µmol m-2 s-1 of light from HPS lamps was shown to increase fruit yield, weight

of tomatoes, and total biomass (McAvoy & Janes, 1984).

HPS lights have the added advantage of producing heat, which in the winter months can

aid in greenhouse temperature regulation (Brault et al., 1989). This excessive thermal waste

is able to provide 25-41% of the heating requirements a greenhouse may need in the cold

winter months in order to maintain optimal growing conditions (Brault et al., 1989).

However, HPS lights also have disadvantages to their use. The excessive thermal energy

can also cause damage to the plants when in close proximity (Cathey & Campbell, 1977). This

excessive heat and damage associated with it, perturbs the use of HPS lights in close

proximity to plant canopies. In recent studies the introduction of intracanopy lighting has

shown increases in fruit biomass, however an alternative to HPS lights will be needed for

this type of lighting (Gomez et al., 2013).

HPS lights are not the most photosynthetically activating lights as they lack high

percentages of red and blue and are stronger in the orange and green regions of

photosynthetically active radiation (PAR) (Nelson, 2012) (Appendix III). Light-emitting

diodes (LEDs) are a possible solution to the problems HPS lights have in greenhouses.

LEDs are a solid-state light source which have been increasingly thought of as a potential

supplement or replacement to HPS lights in greenhouses (Bula et al., 1991; Morrow, 2008).

LED lighting has an added advantage over HPS lighting in the fact that they are more energy

efficient (Bergh et al., 2001; Nelson & Bugbee, 2014). LED lighting systems have also grabbed

the attention of growers for their possible use as intracanopy lighting due to their cool face

emitting light source (Massa et al., 2008). This temperature regulation by the LED light

3

source allows them to be placed very close to the plant tissue without causing harm such as

burning which has been identified with HPS lights.

Unlike the broad spectrum properties of HPS lighting, LED lights are able to have either

broad spectrum light quality, or very narrow, wavelength specific spectral quality

(Nakamura et al., 1994; Goins et al., 1997; Nakamura, 1997) (Appendix III). Having the

capability to provide very narrow wavelengths to plants is one of the most useful properties

of LED lights as it is known photosynthesis is driven by certain colours better than others, as

described previously (Mackinney, 1940; Sæbø et al., 1995). Light quality and its effects of

plant function will be discussed in the sections below.

LED lighting systems have already been shown to be sufficient to grow plants in growth

chambers, greenhouses, and in tissue cultures (Hoenecke et al., 1992; Tanaka et al., 1998;

Jao et al., 2005). However, the way in which LED lights are best used, and their usefulness in

different crops is still undetermined. Some studies have found that the combination of LED

and HPS overhead lighting is most cost effective when taking into account heating cost, while

others say there is no effect of production while using overhead HPS lighting and intracanopy

LED lighting (Touwborst et al., 2010; Dueck et al., 2012).

Newer generations of LED lighting systems are being designed continuously. One of the

many attributes of LED light is its decreased energy consumption over the conventional HPS

lighting system. However, LED lighting fixtures are relatively expensive to purchase running

upwards of five times that of an HPS light (Nelson & Bugbee, 2014). This cost, however, is

seen to reduce due to three key factors of the LED lighting systems: 1) longevity, 2) energy

efficiency, and 3) light placement (Nelson & Bugbee, 2014). It is reported by Nelson & Bugbee

4

(2014), that LED lights can last a predicted life of up to 50,000 hours of operation while still

maintaining 70% of their original light output. HPS lighting on the other hand, are only

reported to last between 10,000 and 17,000 hours (Nelson & Bugbee, 2014).

1.2 Light Spectral Quality

Certain wavelengths of light have already been shown to preferentially activate

photosynthesis (Mackinney, 1940). Specific wavelengths of light have also been shown to

change morphologies, genetic response, and chemical compound formation in plants,

bacteria, and mammals (Liu et al., 2011b; Liu et al., 2012; Bellasio & Griffiths, 2014; Kim et

al., 2014; Deniz et al., 2015). In this section, the effects of the main LED wavelengths which

are currently being produced for plant growth, red, blue, and green, will be discussed.

1.2.1 Red Light

Red (R) light is the region of visible light between approximately 620-750nm and thus,

has the lowest energy associated with any colour of the visible spectrum. Red light is readily

absorbed by Chl a and Chl b (Mackinney, 1941). Red light has been used to study plant

growth on a wide variety of plants including peppers, lettuce, cucumber and tomatoes with

varying results (Brazaityte et al., 2010; Hogewoning et al., 2010; Lin et al., 2013; Gomez &

Mitchell, 2015). Grown under an all R light, cucumber plants showed a reduced

photosynthetic rate, stomatal conductance and internal leaf CO2 concentration compared to

plants subjected to R and blue (B) light treatments. Similar results were also found when

using rice and wheat when grown under solely red light (Goins et al., 1997; Matsuda et al.,

2004). These findings lead to the conclusion that growing plants solely under R light is not

an optimal light treatment (Hogewoning et al., 2010). However, a more recent study has

5

shown that ‘Komeett’ tomatoes seedlings grown in ambient conditions with R supplemental

lights, grew normally (Hernandez & Kubota, 2012).

Red light has also known to affect tomato morphology. It has been reported to increase

stem elongation but decrease overall plant biomass and leaf area from white (W) light

control tomato plants (Liu et al., 2011a; Liu et al., 2012). Leaf colour has also been noted to

change when under different lighting sources leaving R illuminated tomato leaves to be a

lighter green (G) colour as well as visibly different leaf anatomy. This lighter colour was likely

due to a decrease in both Chl a and Chl b content found in those leaves under certain light

treatments (Liu et al., 2012).

In addition to a change in overall leaf morphology and chlorophyll content, leaf antomy

was also changed by light. Red light produced statistically less stomata/mm2 than B, G, red-

blue (RB) and red-blue-green (RBG) light and produced roughly the same amount of stomata

as a dysprosium light control and orange (O) light grown plants (Liu et al., 2012). However,

the area covered by a stomata was statistically among the highest values determined under

all light treatments suggesting larger individual stomata (Stomatal area= π((length of

stomata)(width of stomata))/4) (Liu et al., 2011b). Plants grown under R light were also seen

to have among the thinnest leaves out of the possible light treatments and also have

significantly shorter palisade cells then all other light treatments tested (Liu et al., 2011b).

Studies using R light irradiated Arabidopsis seedlings have also shown changes in gene

transcription levels (Tepperman et al., 2004; Casal & Yanovsky, 2005). Tepperman et al.,

(2004) have done an extensive study on gene repression and induction in Arabidopsis. It was

determined that multiple genes coding for a range of cellular machinery from transcription

6

factors to chloroplast to cell defense are effected by R light (Tepperman et al., 2004). Not

only did they show that R light effected different families of genes differently, it was also

shown that genes within the same family are effected differently (Tepperman et al., 2004).

For example, it was shown that of genes transcribing for members of the cell defense family,

21 were induced by R light, while one was repressed (Tepperman et al., 2004). Time under

irradiance also effected transcriptions levels and it was found that of those same cell defense

genes increased to 43 induced and 27 repressed under longer irradiance times (Tepperman

et al., 2004).

1.2.2 Blue Light

Blue light (450-500nm), like R light has been known for decades to be a highly absorbed

colour by Chl a and Chl b (Mackinney, 1940). The addition of B light to a light treatment has

shown an increase in carbon assimilation as well as stomatal conductance with even very

low B light input (Hogewoning et al., 2010; Lee et al., 2013). This increase was possibly due

to the increase in chlorophyll production by leaves under only B lights or in combination

with other colours such as R or G (Liu et al., 2012). This increase was also evident by a darker

G colour found in the leaf visually showing a higher chlorophyll content.

Morphologically, tomato plants grown strictly under B light, or in combination with B

light tend to be shorter than light treatments which are lacking B light (Liu et al., 2010; Liu

et al., 2012; Lee et al., 2013). However, these same plants showed significantly higher fresh

and dry weights than other light treatments (Takemiya et al., 2005; Liu et al., 2010; Liu et al.,

2012).

Blue light, whether in combination with other colours or by itself was also seen to

significantly increase leaf thickness and specifically increase the palisade cell length (Liu et

7

al., 2011b). However, it was noted by the authors that spongy mesophyll layers in the B and

RBG treatments were observed to be disorganized compared to other light treatments (Liu

et al., 2011b). Light intensity has been known to increase the number of palisade layers with

a high light intensity (360 µmol m-2 s-1) producing two or three levels and a low light intensity

(60 µmol m-2 s-1) only producing one (Yano & Terashima, 2001; Tsukaya, 2005). However, in

the study done by Liu et al., (2011b) light levels between the treatments were the same

(320±15 µmol m-2 s-1) so it is unlikely light intensity played a factor in palisade cell length.

Thus, there may have been a transcription induction which was causing longer palisade cells

to be produced. Also noted by Xiaoying et al. (2012), was the increased production and area

covered by stomata.

The addition of B light, even in minimal quantities is essential for normal plant growth

(Hogewoning et al., 2010). Some studies have shown that yield response in wheat,

Arabidopsis, spinach and lettuce plants, increased with even a 1% addition of B light (Goins

et al., 1998; Yorio et al., 1998). These results have also been seen in fruit producing crops

such as tomatoes and cucumbers (Menard et al., 2006). However, supplemental B light was

introduced via intra-canopy lighting and no statistical evidence was provided to prove that

increases in yield were produced due to the B light supplementation or due to the position

of lights (Menard et al., 2006).

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1.2.3 Green Light

Green light (500-570nm) and its use in plant systems has been debated for some time. It

has been known that it is among the least absorbed wavelength by plants and chlorophyll

and due to this reflectance, we perceive plants as green (Mackinney, 1941). However, recent

studies using G lighting have begun to challenge conventional thinking on what role it plays

in plant growth.

Plants do in fact have G light absorbing molecules. Phytochromes (Phy), Cryptochromes

(Cry), and Chl are mainly B and R light absorbing molecules but studies have also found they

are able to absorb G light (Steintiz et al., 1985; Banerjee et al., 2007). Tomato plants which

are grown solely under G light show evidence that it does not efficiently excite chlorophyll

by having an extremely low rate of photosynthesis (Liu et al., 2010; Liu et al., 2012).

However, both of these studies also show that when G light is in combination with R and B,

photosynthetic rates are at their highest, which in there lies the potential value of G light (Liu

et al., 2010; Liu et al., 2012).

Green light also produces the thinnest leaves when compared to other light treatments

(Liu et al., 2011b). However when mixed with R and B, this effect was negated and in fact,

the RBG treatment produced the thickest leaves (Liu et al., 2011b). On a stomatal basis,

tomato plants solely grown under G light produced the smallest stomata on an area basis

(Liu et al., 2011b). This feature was reflected in the stomatal conductance of plants grown

under G light as they have a drastically lower rate than all other treatments (Liu et al.,

2011b). A decrease in stomatal conductance was also seen in the RBG treatment when

9

compared to the RB treatment however there was no evidence of a decrease in

photosynthetic rate (Liu et al., 2011b).

Where G light has found its niche was when used as a supplemental source with R and B

light. When used in combination, G light has been shown to increase plant biomass and leaf

area in lettuce but this was not seen in young tomatoes plants (Kim et al., 2004a; Liu et al.,

2010; Liu et al., 2012). In the young tomato plants, the canopy was not very dense thus all

leaves may be illuminated by R or B light. However, the mature lettuce and tomato canopies

cause shading or ‘dark spots’ on the lettuce which will not be reached by R or B light. Since

G light was reflected more than other lights, it may be able to bounce around the canopy and

be absorbed by these ‘dark spots’ (Kim et al., 2004a; Liu et al., 2010).

Another theory deals with the transmission of light though multiple layer of cells or light

scattering and bouncing around within cells in a leaf. In spinach and alfalfa leaves, it was seen

that R and B light were absorbed in early stages of the leaf (<150µm) (Vogelmann et al., 1989;

Vogelmann, 1993; Sun et al., 1998). This allows G light to reach a whole other layer of

chloroplast which R and B light treatments are not able to adequately reach (Sun et al.,1998).

1.3 Photosynthesis and Carbon Partitioning

Photosynthesis is the process in which all plants and some bacteria are able to convert

light energy from the sun or an artificial light source into chemical energy, adenosine

triphosphate (ATP) and nicotinamide adenine dinucleotide phosphate (NADPH) with the

end goal of forming carbohydrates needed for plant growth. Leaves are usually thought of as

the only photosynthetically active tissue in a plant system however, it has been known for

quite some time that any chlorophyll containing tissue is able to photosynthesize (Steer &

10

Pearson, 1976). Although, leaves have been shown to provide approximately 80% of all

photosynthetic activity, stems, petioles, and even the fruits of some plants have been shown

to provide anywhere from 1-14% of photosynthetic activity depending on plant species

(Steer & Pearson, 1976; Chauhan & Pandey, 1984; Hetherington et al., 1998). In Arabidopsis

the inflorescence, or the non-leafy shoot area, has been shown to contribute approximately

70% of the photosynthetic activity when the plant is at a mature stage (Leonardos et al.,

2014) In tomatoes, about 15% of the total photosynthetic rate has been seen to be produced

by non-leaf structures (Hetherington et al., 1998).

In tomatoes specifically, the main components produced via carbon fixation are starch

and sucrose (Osorio et al., 2014). Along with the these main carbohydrates, tomato leaves

are also able to produce hexose sugars such as glucose and fructose, sugar alcohols such as

mannitol and inositol, as well as other simple sugars such as arabinose and mannose

(Schauer et al., 2005). Previous literature indicates carbon partitioning to be a highly

regulated process but it also varies wildly between species and even within species based on

environmental factors such as salinity, temperature, and nutrient availability (Balibrea et al.,

2000; Lemoine et al., 2013; Sung et al., 2013).

Light period has shown a significant effect in starch accumulation rate in tomato leaves

once beyond a 16h light period (Logendra et al., 1990). Once the tomato plants were

illuminated for 20h, the rate of starch accumulation was halved when compared to a 16h or

8h light period (Logendra et al., 1990). This drop in accumulation rate was not seen in hexose

or sucrose during these time periods with the exception of a slight drop in the hexose

accumulation rate from 8h to 16h (Logendra et al., 1990).

11

However, there is a lack of research comparing different light qualities (wavelengths)

and the partitioning rates of carbohydrates. One study using radish plants which were grown

under different light treatments with the addition of far-red light produced higher values of

sucrose, hexose and other soluble sugars when compared to plants grown under just white

light (Keiller & Smith, 1989). However, starch followed the opposite pattern and a higher

level of starch was seen in plants grown solely under W light which correlates with the total

dry weights of the plants which shows white light producing larger plants (Keiller & Smith,

1989). These results held true for both 14 days and 26 days after the treatment was started

(Keiller & Smith, 1989). There is a very clear knowledge gap in the literature about how

wavelength specific lighting is able to effect sugar partitioning in tomato leaves.

1.4 Carbon Export

Export of carbohydrates made from source tissue to growing sink tissue is a major factor

controlling plant development (Osorio et al., 2014). According to some studies, 80% of fixed

carbon can be exported by a mature leaf (Lemoine et al., 2013). This can happen via

immediate export of sucrose from the source leaf during the day, from the breakdown and

mobilization of starch under low irradiance or during the night period, or the mobilization

of sucrose fromm storage (Grange, 1985).

Sugar export was shown to not be consistent between species, however, evidence has

shown that tomatoes, cotton, and sugarbeet carbon export is closely correlated with the

source sucrose pools (Ho, 1976; Hendrix & Huber, 1986; Fondy et al., 1989). Export is able

to happen via two pathways: symplastic loading which does not need facilitator proteins and

apoplastic loading which does require enzymatic help. Several factors determine the method

of phloem loading which is used by a plant (i) the organization of cells surrounding the

12

phloem, (ii) the existence of transporter proteins, (iii) the existence of sucrose uptake

transporters in the phloem, (iv) and the existence of a concentration gradient between the

mesophyll cells (MCs) and the phloem itself (Zimmermann & Ziegler, 1975; Gamalei, 1989;

Sauer & Stolz, 1994; Nadwondnik & Lohaus, 2008).

Tomatoes have been determined to be apoplastic loaders via the use of invertase, an

enzyme which is able to hydrolyze sucrose, stopping the transport of sucrose into the phloem

(Dickinson et al., 1991). The absence of phloem loading while invertase was present was

determined to be due to the fact that the sucrose specific transporter involved was not able

to recognize the hydrolyzed sucrose and thus not able to transport it and thus determining

that tomatoes are apoplastic loaders (Dickinson et al., 1991).

During both apoplastic and symplastic loading, sucrose moves through plasmodesmata

from the MCs to the phloem parenchyma cells (PPCs) (Aoki et al., 2011). Until recently, the

mechanism of sucrose transport into the apoplast from the PPCs has been unknown (Aoki et

al., 2011). An enzyme from the family known as sugars will eventually be exported

transporters (SWEET) has been determined to be responsible for the transport of sucrose

from the PPCs to the apoplast (Chen et al., 2012). These SWEET proteins have been found in

tomatoes via a structurally conserved domain analysis of its genome which leads more

evidence to identify tomatoes as an apoplastic loading species (Feng et al., 2015).

Once sucrose has been moved into the apoplast by a SWEET enzyme, it has two routes

to enter the phloem. Both pathways involve a membrane bound sucrose transporter enzyme

(SUC; also found in literature as SUT) in order to pump sucrose against its concentration

gradient with the end goal being phloem loading. SUC was found to be ubiquitous in all

apoplastic loading plants (Sauer et al., 2004; Hackel et al., 2006; Sauer, 2007). Structurally,

13

SUC has been studied with the use of antibody detection, and hydrophobicity analysis to

show that it contains 12 hydrophobic regions which allows it to form a porin like structure

for sucrose to be moved through (Stolz et al., 1999). These SUC transporters can be found

either on the phloem allowing sucrose to directly enter, or be on a transfer cell (TC) where

sucrose then moves through plasmodesmata into the phloem (Aoki et al., 2011). Whichever

route was taken, sucrose will be pumped against its concentration gradient and was coupled

with the movement of a proton (H+) in a 1:1 stoichiometry (Boorer et al., 1996; Aoki et al.,

2011). In order to keep the H+ gradient higher in the apoplast, H+-ATPase was also found on

TC membrane and the phloem membrane which hydrolyze an ATP molecule in order to

transport H+ from the cytoplasm of the cell against its concentration gradient, making

apoplastic loading an energy consuming process (Sondergaard et al., 2004; Aoki et al., 2011).

Export rates have been shown to change in response to multiple factors. They have been

shown to follow a similar function as photosynthetic rates, that is, as photosynthetic rate

increases, as does export and vice versa (Jiao & Grodzinski, 1996; Leonardos et al., 1996).

Export rates have also been shown to fluctuate with temperature. At physiological conditions

(400 µmol m-2 s-1 and 21% O2) export was seen to decrease as temperature increased above

20°C and in a study involving Alstroemeria, export was virtually non-existent at

temperatures greater than 35°C (Jiao & Grodzinski, 1996; Leonardos et al., 1996). This

phenomena was likely due to the increase of the oxygenase activity of Rubisco due to the

lowering of the CO2/O2 specificity of the enzyme when temperatures increase (Stitt & Grosse,

1988). Cooling of plants also has an effect on export rates. Studies have shown that when

plants are transferred from a normal growth temperature of 20°C to a 12h period of 5°C,

export rates were drastically decreased from control plants which was mirrored by a drastic

14

decrease in photosynthetic rate (Jiao & Grodzinski, 1996; Leonardos et al., 1996; Leonardos

et al., 2003).

Multiple studies have also dealt with modifications or environmental factors which can

effect components within the apoplastic phloem loading pathway which was found in

tomatoes. Wounding of Arabidopsis plants has shown to produce an increased expression of

the sucrose transporter AtSUC3; while under water stress, spinach leaves showed an

increase in sucrose synthesis by activating sucrose-phosphate synthase (SPS) (Quick et al.,

1989; Meyer et al., 2004). However, neither study tries to identify whether these results lead

to a change in the export rate from either plant species. One notable gap in the literature is

the effect light quality has on carbon partitioning and export. Research which will be

discussed in this dissertation will try to elucidate this relationship.

1.5 Hypothesis and Objectives

The processes which happens during photosynthesis and phloem loading leading to

carbon export are well established. However, knowledge on how these processes are

affected by light quality is sparse, especially for carbon partitioning and export. My

hypothesis is that using wavelength specific LED lighting, photosynthesis and export can be

altered solely due to spectral quality and light intensity. The main objectives of my thesis

was to examine the response of young tomato seedlings on the basis of whole plant gas

exchange and water use when exposed to various LED treatments and a standard HPS light.

Also, to examine the effects wavelength specific lighting has on carbon export and

partitioning ratios within tomatoes. By accumulating knowledge on these topics, the effect

of spectral quality on greenhouse tomato production can be determined.

15

1.6 Thesis Overview

In order to test the effect of spectral quality on tomato production, whole plant gas

exchange was conducted which allowed for the diurnal patterns of whole tomatoes to be

determined when exposed to different spectral qualities of light. Also, 14C labelling studies

were performed on a sole source tomato leaf when illuminated with various wavelength

specific LEDs at a wide range of light intensities to determine carbon export as a function of

photosynthesis and carbon partitioning patterns.

In chapter 2, the objective was on whole plant net carbon exchange rate (NCER) and leaf

gas exchange measurements on greenhouse grown plants under supplemental or no

supplemental lighting during the winter months in Guelph, ON, Canada. Tomatoes were

grown under either 100±25 µmol m-2 s-1 of light from HPS, RB LED, or RW LED or an ambient

control. Whole plant and leaf gas exchange experiments helped to elucidate the effects of

different types of supplemental lighting on diurnal gas exchange. Leaf studies helped

determine the effects of the different types of supplemental lighting on the main

photosynthetic machinery of the plant.

In Chapter 3, whole plant and leaf parameters such as NCER, transpiration rate, stomatal

conductance, and internal CO2 concentration were examined. Plants which were grown

under W light were used at a vegetative stage and two different light levels during whole

plant experiments to determine direct effect of HPS, RW LED, and RB LED lights on non-

acclimated plants. Plants grown in the same way were subject to leaf light curves with

wavelength specific LEDs. Using various monochromatic and dichromatic LED lights allowed

16

for the determination of any differences between the aforementioned parameters under

short term illumination of the main photosynthetic machinery.

In Chapter 4, the objective was to elucidae the effect of spectral quality on carbon export

and carbon partitioning patterns. With plants grown under W light, the effects of wavelength

specific LEDs were tested with the help of 14C to trace sugar production. Individual leaves

were placed in a chamber which were then illuminated with an LED light, leaving the rest of

the plant in darkness to ensure that leaf was the sole source of carbohydrate pools for the

plant. By varying the light intensity and creating photosynthetic vs. export graphs any

differences in export over the full photosynthetic capability of the leaf can be examined.

Carbon partitioning patterns as light levels increase can also be determined to elucidate

whether carbon is preferentially partitioned into soluble sugars or starch by different

wavelengths or light intensities.

Chapter 2

The Effect of HPS and Wavelength Specific LED Lights on Whole Plant

and Leaf CO2 and H2O Gas Exchange and Growth Parameters Under Long-

term Acclimation of Solanum lycopersicum cv. ‘Bonney Best’

2.1 Introduction

Greenhouse supplementary lighting via HID lights such as HPS lighting has shown an

increase in crop productions in both vegetable and ornamental industries (McAvoy & Janes,

1984; Oh et al., 2009). During the cold winter months, the use of supplemental light allows

for the DLI to be increased as well as the heat added to the greenhouse have accounted for

17

an increase in yield (McAvoy & Janes, 1984). Although the current staple is HID lighting, there

is a strong push towards LED implementation of lighting systems in greenhouse production.

LED lights have the advantage of being low heat emitting as well as more energy efficient

(Nelson & Bugbee, 2014).

In this chapter, tomato plants grown in a greenhouse during the winter months in

Guelph, Ontario, Canada under various supplemental lighting regimes will be compared.

Both whole plant, and leaf growth parameters will be determined to see the effect of the

supplemental treatment has on plant growth and overall biomass production. The objective

was to determine if the use of wavelength specific LED lighting systems provides an

advantage during the winter growing season over conventional HPS lighting.

2.2 Materials and Methods

2.2.1 Plant Materials and Growth Conditions

Bonny Best (BB) cultivar of S. lycopersicum were purchased from William Dam Seeds

(Dundas, ON, Canada). Seeds were sown into 60 cavity potting trays (The HC Companies,

Middlefield, OH, USA) in Sungro professional growing mix #1 (Soba Beach, AB, Canada)

containing Canadian sphagnum peat moss, coarse perlite, dolomitic limestone, and a

fertilizer pre-charge on December 22nd, 2015 and March 3rd, 2016. Plants were transferred

to larger 1L pots (The HC Companies, Middlefield, OH, USA) with Sungro growing mix and

placed in the greenhouse at the University of Guelph (43° 31' 40.0584" N, 80° 13' 38.4996"

W) on January 21st, 2016 and March 23rd, 2016 respectively. 20 plants were arranged in a

complete randomized block design on growing tables under either Red-Blue LED (100±25

µmol m-2 s-1), Red-White LED (100±25 µmol m-2 s-1), or HPS (100±25 µmol m-2 s-1)

18

supplemental lighting and an ambient, no supplemental light control (Appendix III; Table

2.1). Supplemental lighting from LEDs were provided from 390W fixture made by The Light

Science Company (LSGC; Warwick, RI, USA) and HPS lighting from a 1000W HPS lights from

Philips (Markham, ON, Canada), Plants under supplemental lighting received light from 6am

to 10pm via a combination of sunlight and additional lighting whereas ambient conditions

received light only during the sunlight hours. Light reaching the plants never exceeded

500±50 µmol m-2 s-1 under ambient conditions. Temperatures were held to 20°C throughout

the day and night.

Ambient HPS RB HPS Ambient RW

RB Ambient RW RB RW HPS

Figure 2.1: Schematic showing light treatment placement for both greenhouse planting dates. RB= Red-blue, HPS= High pressure sodium, RW= Red-White.

Plants which were started on December 22nd, 2015 were grown until March 3rd, 2016 in

which they were destructively analyzed leaf area using a leaf area meter (LI-3100, LI-COR,

Lincoln, NE, USA). Roots were washed until dirt and particle free and were dried in an oven

at 70°C in order to determine dry biomass of roots, leaves, stems, and flowers. Plants which

were started on March 3rd, 2016 we subject to leaf and whole plant parameters described

below.

2.2.2 Whole Plant Gas Exchange

Whole plant growth experiments began on April 7th, 2016 and continued through April

25th, 2016 alternating between plants from treatments under supplemental night and those

under ambient conditions. Three plants were placed in each chamber on April 7th, two plants

19

were placed in each chamber on April 9th and 11th and only one plant was placed in the

chamber from the remainder of the experiments due to the growth of the plants.

A whole plant gas exchange system allows the monitoring of gas exchange and water use

of the whole plant system rather than just an individual leaf. The custom built system

resembles an earlier design used by Dutton et al., (1988). The system is controlled by

LabView 2009 (National Instruments Canada, Vaudreuil-Dorion, QC, Canada) and runs on a

Dell, Precision 490 (Dell Computers, Round Rock, TX, USA) computer. This systems allows

for the full control of CO2 concentration within the chambers, relative humidity control,

temperature control, and light intensity. The system employs six chamber made of clear

polycarbonate plant chambers which measure 32”x18”x18” with a glass top giving a total

chamber volume of 200L. During experiments with smaller plants, boxes of known volume

can be used to decrease chamber volumes which was needed to insure CO2 depletion is

within the systems limits. Two chambers are illuminated by 390W RW LED fixtures from

LSGC, two chambers are illuminated with 390W RB LED fixtures from LSGC, and two

chambers are illuminated with1000W HPS lights from Philips (Apendix III; Figure 2.2A). LED

lights have a dimmable setting which allows for the light intensity to be variable, HPS light

intensity can be varied by lifting the lights higher away from the chambers or by adding

shade clothes to the top of the chambers. Chambers which are illuminated by HPS lighting

have water baths placed between the light and the chamber in order to avoid overheating of

the chamber. All chambers were wrapped with aluminium foil on the outside to prevent light

from other lights from entering the chambers and to prevent light loss lower in the

chambers.

20

Light intensity was determined by placing Li-COR quantum sensors (LI-190SA, Li-COR

Inc. Lincoln, NE, USA) at the top of the plant canopy. Once light intensity was set, the

chambers are sealed with a clear polycarbonate door held on by 16 wing nut screws which

are tightened

21

to provide and air tight seal (Figure 2.2B). The system has two modes of use, an ‘open’ and

Figure 2.2: (A) Overview of the whole plant gas exchange system showing six individual chambers with various light treatments over them. Computer control (CU) system is shown as well as the climate control radiators (CCR) which is responsible for holding temperature and humidity within the chambers. (B) Individual chambers with tomato plants sealed inside.

A

CU

CCR

B

22

‘closed’ mode. Firstly, Compressed air generated by the University of Guelph was scrubbed

free on any CO2 by a purge gas generator (CO2 Adsorber, Puregas, Broomfield, CO, USA). CO2

was then added back into the system in the desired concentration in that particular

experiment. The mixed air was then pumped through a series of stainless steel piping and

solenoid valves (ASCO RedHat II, Florham Park, NJ, USA) to the chambers. CO2 and relative

humidity levels are checked every 20 seconds in sequential chambers (1 to 6) by an infrared

gas analyzer (IRGA; Li-COR CO2/H2O Gas analyzer 840, Lincoln, NE, USA) in the ‘open’ mode

meaning solenoid valves on the air inlet lines and outlet lines were in the open position

allowing for the determination of adjustment levels. In the ‘closed’ mode, the inlet and outlet

solenoid valves are set to the close position which isolates the CO2 within the chamber. The

chambers can then be sampled for the depletion of CO2 within the chamber by a second IRGA

(Li-COR CO2/H2O Gas analyzer 840, Lincoln, NE, USA). The sampling takes place for 90

seconds with the first 30 seconds being used to flush the line to prevent carry over from the

previous chamber. The next 60 seconds sampling period was used for the net carbon

exchange rate calculation (Equation 2.1) where Vol is the chamber volume (L); Ci is the initial

CO2 concentration during NCER measurement (µL L-1); Cf is the final CO2 concentration (µL

L-1); 0.0821 s the gas constant (L °K-1 mol-1); T is the temperature of the chamber air (°K);

and Δt is the elapse time during sampling (s) (Dutton et al., 1988).

Equation 2.1:

𝑁𝐶𝐸𝑅 =𝑉𝑜𝑙(𝐶𝑖−𝐶𝑓)

0.0821×𝑇×∆𝑡

23

Long term acclimation experiments using plants from the greenhouse were placed in

chambers with the same spectral quality they were grown under. Plants which were the

ambient light control treatment were subject to whole plant measurements under all three

lighting conditions used in the whole plant system. Plants were randomly selected from the

blocks for experimentation. The photoperiod was set to 16/8h with a light level of 500±10

µmol m-2 s-1 at canopy level. Relative humidity was held constant at 55±5% during the day

and night period and temperature was set to 22/18°C respectively. Plants were placed in

their respective chambers around 3pm and allowed to acclimate for the rest of the day and

night period. The following morning, lights would come on at 6am and shut off at 10pm

giving a 16h photoperiod. NCER would be recorded for that day and night and used in

analysis. The next morning, plants were taken out of the chambers and their leaf area would

be determined using a leaf area meter. The roots were then washed of the dirt and leaves,

stems, and roots were dried in an oven at 70°C for 48h. Samples were then weight and data

was normalized on a plant, dry weight, and leaf area basis.

24

2.2.3 Leaf Gas Exchange

Leaf CO2 and H2O gas exchange studies began on April 14th, 2016 and continued through

April 17th, 2016. Freshly watered plants were taken away from their light treatment to a

neutral area for analysis. The 5th highest, most distal leaflet was used for analysis. The leaf

was placed in the chamber of a Li-COR 6400 portable unit (Lincoln, NE, USA) with a RB light

source from Li-COR (Figure 2.3.). The relative humidity was held steady at 65±5% by passing

the incoming air through a desiccant. The CO2 concentration was held steady at 415±10 µmol

m-2 s-1 by using Soda Lime. A light curve was produced by using the Li-COR 6400 auto curve

feature with a 120s minimum time and 240s maximum time starting from a high light

intensity and decreasing incrementally down to no light.

Figure 2.3: Li-COR 6400 portable unit set up for greenhouse leaf measurement with the red-blue light source on top of the chamber containing the leaf.

25

2.3 Results

Supplemental lighting proved to provide an increase in biomass production during the

winter months in tomato plants (Figure 2.4; Table 2.1). Plants grown under both RB and RW

LED supplemental provided an average increase of 10g and 4g in biomass production over

the HPS light treatment however this difference was not significant when analyzed with a

one-way ANOVA and a Tukey-Kramer adjustment (p<0.05). Supplemental lighting also

provided significant increases in both leaf area and flower bud numbers over the ambient

control (Table 2.1). Plants grown under the RB treatment showed the highest number of

flower buds on average and showed a 27% and 17% increase in number of buds formed

compared to HPS and RW treatments respectively. Again, these results were not statistically

significant (p<0.05) (Table 2.1).

Figure 2.4: Plant biomass measurements done on March 4th, 2016 of plants which were

planted on December 22nd, 2015 and subject to supplemental light treatments during the

winter months in Guelph, ON, Canada. RB= red-blue LED, HPS= high pressure sodium, RW=

red-white LED. Each supplemental light treatment provided 100±25 µmol m-2 s-1 of light.

Error bars represent ± the standard error of 6 replicates, 2 taken from each block.

Ambient RB HPS RW

Dry

Weig

ht (g

)

0

10

20

30

40

50

Stem

Ambient RB HPS RW

Root Leaf

Ambient RB HPS RW

Flower

Ambient RB HPS RW

Total

Ambient RB HPS RW

Table 2.1: Physical growth measurements taken from tomato plants grown under supplemental lighting in a greenhouse in Guelph, ON, Canada which were planted on December 22nd, 2015 and analyzed on March 4th, 2016. Each value represents the average of 6 different plants. Values in parentheses represent ± standard error and letter group (a, b) represents statistical differences within the row as determined by a one-way ANOVA and a Tukey-Kramer adjustment (p<0.05). Statistical analysis found in Appendix IV.

Figure 2.5A, C, and E show the diurnal gas exchange patterns of plants grown in a

greenhouse under supplemental lighting when analyzed under the same light in the whole

plant system. Plants grown under ambient conditions were analyzed under either RB LED,

RW LED, or HPS lighting (Figure 2.6). The ambient grown tomato plants which were placed

in the whole plant system under HPS lighting produced the highest average day time

photosynthetic rates under a dry weight basis of normalization (Table 2.2). Plants which

were grown under RW supplemental light in the greenhouse produced the lowest average

day time photosynthetic rates of all treatments (Table 2.2). No statistical difference of

respiration was determined from any treatment under any normalization (Table 2.2).

Light Treatments

Ambient Red-Blue HPS Red-White

Root Weight (g)

1.07(0.11)a 2.37(0.11)b 2.09(0.07)b 2.20(0.06)b

Stem Weight (g)

9.05(0.94)a 21.13(1.27)b 17.15(1.10)b 18.54(1.11)b

Leaf Weight (g)

10.63(1.07)a 25.26(1.71)b 20.21(1.24)b 22.57(1.29)b

Flower Weight (g)

0.15(0.02)a 0.51(0.04)b 0.42(0.07)b 0.40(0.06)b

Total Weight (g)

20.90(2.11)a 49.27(3.08)b 39.87(2.39)b 43.70(2.45)b

Leaf Area (m2) 0.49(0.03)a 0.80(0.03)b 0.78(0.03)b 0.77(0.04)b

# Flower Buds 36(5)a 127(6)b 100(5)b 118(11)b

29

Although statistical differences were determined for the average day time photosynthetic

rates between treatments, these did not translate into statistical differences in carbon

accumulation during the 16h light period or the whole 24h day period (Table 2.2).

When normalized on a per plant and leaf area basis, there was no statistical difference in

day time photosynthesis or night time respiration between plants under supplemental

lighting or ambient lighting when subject to the same lights during whole plant analysis

(Figure 2.5A and C; Figure 2.6A and C; Table 2.2). However, when normalized on a dry weight

basis, plants which were grown under the ambient control had statistically higher average

day time photosynthetic rates than their counterparts grown under supplemental lighting

when assessed under the same lights during whole plant analysis (Figure 2.5E; Figure 2.6E;

Table 2.2).

Plants grown under RB supplemental lighting provided statistically higher average day

time whole plant transpiration rates than did ambient grown plants which were analyzed

under HPS lighting (Table 2.3). This difference did not lead to a statistical difference in WUE

under any light treatment (Table 2.3).

30

Figure 2.5: Whole plant NCER (A, C, and E) and C-budget (B, D, and F) of tomato plants grown

in a greenhouse Guelph, ON, Canada from March 3rd, 2016 to April 25th, 2016 provided with

100±25 µmol m-2 s-1 of supplemental light from red-blue LED, HPS, or red-white LED lights.

Plants were place in the whole plant NCER system under the same lights they were grown

under with a light intensity of 500±10 µmol m-2 s-1 for 16h followed by an 8h dark period.

Whole plant NCER and C-budget are normalized on a plant basis (A and B), leaf area basis (C

and D), and a dry weight basis (E and F). Whole plant NCER points represent the hourly mean

values ± the standard error of 9 replicates and C-budget lines represent the mean of 9

replicates.

31

NC

ER

(µ

mo

l C

O2

pla

nt-1

s-1

)

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

C-b

ud

get

(C g

ain

-C l

oss

g C

pla

nt-

1)

0

1

2

3

4

5

NC

ER

(µ

mo

l C

m-2

s-1

)

-2

0

2

4

6

8

C-b

ud

get

(C g

ain

-C lo

ss g

C m

-2)

0

2

4

6

8

10

12

14

16

18

20

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

NC

ER

(µ

mo

l C

g-1

s-1

)

-0.05

0.00

0.05

0.10

0.15

0.20

Red-Blue

HPS

Red-White

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

C-b

ud

get

(C g

ain

-C l

oss

g C

g-1

)0.0

0.1

0.2

0.3

0.4

0.5

Red-Blue

HPS

Red-White

A B

C D

E F

32

Figure 2.6: Whole plant NCER (A, C, and E) and C-budget (B, D, and F) of tomato plants grown

in a greenhouse in Guelph, ON, Canada from March 3rd, 2016 to April 25th, 2016 under no

supplemental light. Plants were place in the whole plant NCER system under either red-blue

LED, HPS, or red-white LED lights with a light intensity of 500±10 µmol m-2 s-1 for 16h

followed by an 8h dark period. Whole plant NCER and C-budget are normalized on a plant

basis (A and B), leaf area basis (C and D), and a dry weight basis (E and F). Whole plant NCER

points represent the hourly mean values ± the standard error of 9 replicates and C-budget

lines represent the mean of 9 replicates.

33

NC

ER

(µ

mo

l C

O2

pla

nt-1

s-1

)

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

C-b

ud

ge

t (C

ga

in-C

lo

ss

g C

pla

nt-

1)

0

1

2

3

4

5

NC

ER

(µ

mo

l C

m-2

s-1

)

-2

0

2

4

6

8

C-b

ud

ge

t (C

ga

in-C

lo

ss g

C m

-2)

0

2

4

6

8

10

12

14

16

18

20

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

NC

ER

(µ

mo

l C

g-1

s-1

)

-0.05

0.00

0.05

0.10

0.15

Red-Blue

HPS

Red-White

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00C

-bu

dg

et

(C g

ain

-C l

oss

g C

g-1

)

0.0

0.1

0.2

0.3

0.4

Red-Blue

HPS

Red-White

A B

C D

E F

34

Figure 2.7: Whole plant transpiration (A and C) and WUE (B and D) of in a greenhouse

Guelph, ON, Canada from March 3rd, 2016 to April 25th, 2016 provided with 100±25 µmol m-

2 s-1 of supplemental light from red-blue LED, HPS, or red-white LED lights (A and B) or a no

supplemental light control (C and D). Plants were place in the whole plant NCER system

under either red-blue LED, HPS, or red-white LED lights with a light intensity of 500±10 µmol

m-2 s-1 for 16h followed by an 8h dark period. Plants which were grown under supplementary

light were placed under chambers which provided the same spectral quality of light.

Transpiration and WUE points represent the hourly mean values ± the standard error of 7

replicates for plants grown under red-blue supplemental lighting, 6 replicates for plants

grown under HPS, red-white supplemental lighting, and control plants placed under red-

white lighting during whole plant experiments, 4 replicates for control plants placed under

red-blue lighting during whole plant experiments, 3 replicates for control plants placed

under HPS lighting during whole plant experiments.

Tra

ns

pir

ati

on

(m

mo

l H

2O

·m-2

·s-1

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

WU

E (

µm

ol C

O2/m

mo

l H

2O

)

0

5

10

15

20

Red-Blue

White

Red-White

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Red-Blue

White

Red-White

A B

C D

Table 2.2: The effect on whole plant daily average NCER and daily C-budgets on greenhouse

grown tomato plants in Guelph, ON, Canada with 100±25 µmol m-2 s-1 of either red-blue, HPS,

or red-white supplemental light or a no light control. Plants were place in the whole plant

NCER system under either red-blue LED, HPS, or red-white LED lights with a light intensity

of 500±10 µmol m-2 s-1 for 16h followed by an 8h dark period. Plants which were grown

under supplementary light were placed under chambers which provided the same spectral

quality of light. Values represent the day and night means of each parameter. Values in

parentheses are ± the standard error of each mean and its respected replicates. Letters (a, b,

c, d) represent statistical significance within rows as determined by a one-way ANOVA with

a Tukey’s-Kramer adjustment (p<0.05). Statistical analysis can be found in Appendix IV.

CO2 Gas Exchange on a:

With Supplemental Light Ambient Control

Plant Basis Red-Blue HPS Red-White Red-Blue HPS Red-White Photosynthesis (µmol C plant-1 s-

1)

1.44(0.03)c 1.64(0.03)ab 1.46(0.03)c 1.52(0.04)bc 1.70(0.04)a 1.44(0.03)c

Respiration (µmol C plant-1 s-

1)

-0.32(0.01)a -0.33(0.02)a -0.33(0.02)a -0.34(0.02)a -0.34(0.02)a -0.34(0.02)a

C-Gain (g C plant-1)

3.66(0.43)a 4.15(0.50)a 3.70(0.45)a 3.84(0.42)a 4.30(0.58)a 3.65(0.40)a

C-Loss (g C plant-1)

0.40(0.05)a 0.42(0.05)a 0.41(0.05)a 0.42(0.05)a 0.43(0.07)a 0.43(0.06)a

Daily C-Gain (g C plant-1 day-1)

3.26(0.38)a 3.72(0.45)a 3.29(0.41)a 3.42(0.37)a 3.86(0.51)a 3.22(0.35)a

Leaf Area Basis

Photosynthesis (µmol C m-2 s-1)

6.81(0.14)ab 6.86(0.13)ab 6.40(0.12)bc 6.50(0.14)abc 7.01(0.14)a 6.03(0.13)c

Respiration (µmol C m-2 s-1)

-1.48(0.06)a -1.40(0.09)a -1.44(0.08)a -1.34(0.07)a -1.35(0.09)a -1.31(0.07)a

C-Gain (g C m-2) 17.25(0.94)a 17.39(0.61)a 16.22(0.63)a 16.48(1.33)a 17.76(1.20)a 15.29(1.41)a

C-Loss (g C m-2) 1.88(0.06)a 1.78(0.06)a 1.82(0.08)a 1.70(0.06)a 1.71(0.08)a 1.66(0.08)a

Daily C-Gain (g C m-2 day-1)

15.38(0.88)a 15.61(0.59)a 14.40(0.59)a 14.78(1.28)a 16.05(1.14)a 13.64(1.35)a

Dry Weight Basis

Photosynthesis (µmol C g-1 s-1)

0.13(0.003)cd 0.13(0.003)bc 0.12(0.002)d 0.15(0.003)ab 0.16(0.003)a 0.14(0.003)bc

Respiration (µmol C g-1 s-1)

-0.028(0.001)a -0.028(0.002)a -0.027(0.002)a -0.030(0.002)a -0.030(0.002)a -0.028(0.001)a

38

C-Gain (g C g-1) 0.32(0.02)a 0.34(0.02)a 0.31(0.02)a 0.37(0.04)a 0.40(0.04)a 0.34(0.04)a

C-Loss (g C g-1) 0.035(0.002)a 0.035(0.002)a 0.035(0.002)a 0.038(0.002)a 0.038(0.003)a 0.036(0.003)a

Daily C-Gain (g C g-1 day-1)

0.29(0.02)a 0.31(0.02)a 0.27(0.02)a 0.33(0.03)a 0.36(0.04)a 0.31(0.04)a

Table 2.3: The effect on whole plant daily average transpiration and WUE on greenhouse

grown tomato plants in Guelph, ON, Canada with 100±25 µmol m-2 s-1 of either red-blue, HPS,

or red-white supplemental light or a no light control. Plants were place in the whole plant

NCER system under either red-blue LED, HPS, or red-white LED lights with a light intensity

of 500±10 µmol m-2 s-1 for 16h followed by an 8h dark period. Plants which were grown

under supplementary light were placed under chambers which provided the same spectral

quality of light. Values represent the day and night means of each parameter. Values in

parentheses are ± the standard error of each mean and its respected replicates. Letters (a, b,

c, d) represent statistical significance within rows as determined by a one-way ANOVA with

a Tukey’s-Kramer adjustment (p<0.05). Statistical analysis can be found in Appendix IV.

H2O Gas Exchange

With Supplemental Lighting Ambient Control

Red-Blue HPS Red-White Red-Blue HPS Red-White Day Transpiration (mmol H2O m-2 s-1)

0.33(0.03)a 0.27(0.03)ab 0.29(0.02)ab 0.25(0.02)ab 0.22(0.02)b 0.28(0.02)ab

Night transpiration (mmol H2O m-2 s-1)

0.12(0.02)a 0.065(0.01)bc 0.10(0.01)ab 0.055(0.008)c 0.095(0.009)abc 0.058(0.008)bc

WUE(µmol CO2/mmol H2O)

5.37(1.87)a 7.96(2.97)a 7.13(2.31)a 6.57(2.50)a 7.66(2.05)a 6.38(2.17)a

Leaf measurements were performed on the second population of plants which were

seeded on March 3rd, 2016. Although there was an apparent difference between the tomato

plants which grew under supplemental lighting and those control plants on a photosynthetic

basis towards the higher light region of the graph, there is no statistical difference (Figure

2.8; Appendix I: Figure 2.1). No statistical difference was observed for stomatal conductance,

transpiration rates, or internal CO2 concentration with the exception of a statistical

difference in stomatal conductance between the tomato plants grown under the red-white

supplemental lighting and the no light control plants at a light level of 500 µmol m-2 s-1.

42

Figure 2.8: Light curves produced with the Li-COR 6400 portable unit and a red-blue

standard light provided by Li-COR. Plants were grown in a greenhouse in Guelph, ON, Canada

under 100±25 µmol m-2 s-1 of either red-blue, HPS, or red-white supplemental light or a no

light control. Light curves were started at 1500 µmol m-2s-1 and decreased incrementally to

0 µmol m-2s-1. Points represent the means of 6 different leaf replicates and ± standard errors

represent 6 separate leafs as replicates. Statistical analysis can be found in Appendix I.

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

NC

ER

(µ

mo

l m

-2 s

-1)

0

5

10

15

Ambient

Red-Blue

HPS

Red-White

44

Figure 2.9: Leaf transpiration rate, stomatal conductance, and internal CO2 concentration

curves produced with a Li-COR 6400 portable unit and a red-blue standard light provided by

Li-COR. Plants were grown in a greenhouse in Guelph, ON, Canada under 100±25 µmol m-2 s-

1 of either red-blue, HPS, or red-white supplemental light or an ambient control. Light curves

were started at 1500 µmol m-2s-1 and decreased incrementally to 0 µmol m-2s-1. Points

represent the means of 6 different leaf replicates and ± standard errors represent 6 separate

leafs as replicates. Statistical analysis can be found in Appendix I.

Sto

mata

l C

on

du

cta

nce (

mm

ol H

2O

·m-2

·s-1

)

0.0

0.1

0.2

0.3

0.4

0.5T

ran

sp

irati

on

(m

mo

l H

2O

·m-2

·s-1

)

0

1

2

3

4

5

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

Ci (

µm

ol m

ol-1

)

200

250

300

350

400

450

Ambient

Red-Blue

HPS

Red-White

A

B

C

46

2.4 Discussion

2.4.1 Effects of Supplemental Lighting on Whole Plant CO2 Gas Exchange

The addition of supplemental light during the winter months, regardless of spectral

quality, was shown to increase the average biomass production and flower production,

eventually leading to a higher yield, in tomato crops (Figure 2.4; Table 2.1) (McAvoy & Janes,

1984; Demers et al., 1998; Oh et al., 2009). The underlying properties of adding supplemental

light, namely the increase in DLI via an increase in light intensity during low light periods or

a lengthening of the photoperiod, may account for this change (Demers et al., 1998; Hao &

Papadopoulos, 1999). Increasing light intensity when ambient light levels are at a sub-

saturating level was able to increase photosynthetic rates due to the plants ability to use

additional light during this low light period which is known as quantum efficiency

(Trouwborst et al., 2010). Quantum efficiency is a measure of how much more CO2 can be

fixed for every additional photon of light added. During this low light period, the addition of

even small quantities of light were able to increase the CO2 fixation rate in a plant (Table 2.1).

For example, if you take a light level of 100 µmol m-2 s-1 from sunlight and add 100 µmol m-2

s-1 via supplemental light, the photosynthetic rate was seen to double, giving plants under

supplemental light a higher growth rate during identical ambient lighting conditions (Figure

2.8) (McAvoy & Janes, 1984; Demers et al., 1998; Hao & Papadopoulos, 1999; Oh et al., 2009;

Trouwborst et al., 2010). This phenomenon extrapolated over multiple days, weeks, and

even month will lead to the overall increase in biomass production of the plant which is seen

in table 2.1.

47

An increase in DLI is essentially increasing the amount of light which the plant sees

within a day. This can be done by either increase light intensity which was discussed above

or by lengthening the photoperiod. During the winter months, days in Guelph, ON, Canada

are relatively short and are not able to provide the optimal growing conditions.

Supplemental lighting allows for the extension of the photoperiod to more optimal levels.

This addition of light would also contribute to an increase in biomass production from the

plants which were exposed to supplemental lighting (Demers et al., 1998; Oh et al., 2009;

Currey & Erwin, 2011).

Whole plant gas exchange measurements allow for the analysis of how a plant works as

a whole organism, accounting for the small, but significant differences added by non-laminar

plant tissue (Steer & Pearson, 1976; Chauhan & Pandey, 1984; Hetherington et al., 1998;

Leonardos et al., 2014). Although both biomass production and leaf area are much less from

the ambient control plants, plants produced statistically equivalent values during whole

plant analysis to their supplemental light counterparts when analyzed under the same light

(Table 2.1; Table 2.2). Due to the mutual shading from the plants when they become larger

(ie. Plants grown under supplemental lighting) the differences which are seen by end of

production biomass do not translate into measureable difference with the whole plant

system.

Plants grown under different light intensity generally have a higher photosynthetic rate

at the light intensity they were grown at then plants which are grown under higher or lower

light intensity (Bjorkman et al., 1972). This was likely because plants which are grown under

higher light intensities usually have a higher abundance of RUBISCO than those grown under

48

low light conditions (Bjorkman et al., 1972). Although the light conditions for plants grown

under supplemental lighting were only approximately 100 µmol m-2 s-1 greater than plants

grown under the ambient control, these differences likely persist. For this reason it was

surprising to see no photosynthetic differences between the plants grown under

supplemental light and those grown under the ambient control (Figure2.5; Figure 2.6; Table

2.2). However, at such close grow light intensities the differences within the plant may be so

slight that the whole plant system isn’t sensitive enough to pick them up. Also the mutual

shading effect which was previously discussed may negate any variation due to growth

conditions.

2.4.2 Effects of Supplemental Lighting on Whole Plant H2O Gas Exchange

In both plants grown under supplemental lighting and ambient control conditions, there

was no difference in day transpiration rates with the exception of an increase in plants grown

under RB lighting when compared with ambient plants analyzed under HPS lighting (Table

2.3). At first glance, these results may seem to be counter intuitive, simply due to the high

heat emitting properties of the HPS light which should, in turn, increase stomatal opening

and transpiration rates in C3 plants as well as decrease WUE (Gajc-Wolska et al., 2013;

Kaminski et al., 2014). However, different spectral qualities such as R and B and the

combination have been known to increase stomatal density and stomatal opening which can

increase transpiration rates (Kana and Miller, 1977; Liu et al., 2011b; Liu et al., 2012). B light

has been determined to activate the plasma membrane K+-ATPase enzyme on the stomatal

guard cells via a phosphorylation event (Kinoshita and Shimazaki, 1999). This phenomenon

allows for the increase of ions, primarily K+, to enter the guard cells and increase the osmotic

49

pressure leading to an increase in stomatal opening (Kinoshita and Shimazaki, 1999). Red

light shows a similar relationship providing an increase in stomatal opening due to an

increase in ATP hydrolysis causing an increase in K+ and osmotic pressure (Lurie, 1978).

2.4.3 Effects of Supplemental Lighting on Leaf CO2 Gas Exchange

Leaf growth measurements gave an indication of what the main photosynthetic unit of

the plant is doing under difference conditions. Plants which were grown under supplemental

lighting all had slightly higher photosynthetic rates at the near-saturating and saturating

light levels, however no statistical significance was seen (Figure 2.8). These observations

give some confidence to previous observations made by Bjorkman et al., (1972) indicating

that plants grown under higher light intensities, in this instance the ones grown under

supplemental light, were seen to higher photosynthetic rates at higher light intensities.

Plants grown under RB and RW supplemental lighting showed similar or slightly higher

photosynthetic rates at higher light intensity which may be due to the increase in chlorophyll

content (Data not shown) (Bjorkman et al., 1972; Liu et al., 2011a; Liu et al., 2011b). An

increase in chlorophyll due to being grown under the lights would also allow them to absorb

more light during the leaf measurements leading to a higher photosynthetic rates (Figure

2.8). These subtle variations in plant morphology and anatomy are what would be negated

by mutual shading within the whole plant experiments and are better elucidated by the leaf

studies.

50

2.4.4 Effects of Supplemental Lighting on Leaf H2O Gas Exchange

Stomatal conductance, transpiration rates, and Ci within the leaf studies showed no

statistical variation between the light treatments (Figure 2.9). Although differences were

seen in the transpiration rates of the whole plant studies, those plants were analyzed under

different lights and not only grown under different lights. Plants which were subject to leaf

studies were grown under different light treatments but all analyzed under a RB light source

provided by Li-COR. Stomatal opening is known to have a relatively quick response, thus

doing the leaf experiment under the same light may alter the ion flux which controls stomatal

opening in a similar way under all growth conditions and negating differences between

growth treatments (Lurie, 1978; Grantz & Zeiger, 1986; Kinoshita and Shimazaki, 1999).

Also, since the stomatal density of tomato plants grown under RB and RW lightings have

shown to be similar, it was no surprise that those plants grown under those lights have close

stomatal conductance and transpiration rates (Liu et al., 2011b).

In summary, plant biomass production and flower bud formation was increased with

the addition of supplemental lighting. Plants grown under ambient treatments showed

higher daily Pn rates when normalized on a dry weight basis when compared to plants grown

under supplemental lighting which is likely due to the increase in mutual shading of the

larger plants from the supplemental light treatments (Figure 2.1). An increase in the whole

plant daily average transpiration rates was seen from the plants grown under RB lighting

when compared to the ambient grown plants which were analyzed under HPS lighting. No

statistical differences were seen between other treatments.

51

Chapter 3

The Effect of HPS and Wavelength Specific LED Lights on Whole Plant

and Leaf Growth Parameters Under Short-term Acclimation of Solanum

lycopersicum cv. ‘Bonney Best’

3.1 Introduction

In Chapter 2, supplemental lighting from any source provided an increase in biomass

production of greenhouse grown tomatoes during the winter months. However, when

comparing plants grown under different lighting conditions, morphological changes which

have come about due to the lights effectively make them different plants which doesn’t allow

for the comparison of what wavelength specific lighting effects in the short term (Liu et al.,

2012).

The use of wavelength specific LED lighting has been well documented and was shown

to cause morphological and anatomical changes to plants when used as a sole or

supplemental lighting source during plant growth (Liu et al.,, 2011b; Hernandez & Kubota,

2012; Lee et al., 2013). The study of such plants was extensive and have provided both CO2

and H2O gas exchange differences however the differences seen may be due to the changes

enacted by long term exposure to the lights and not the lights themselves (Liu et al., 2010;

Hernandez & Kubota, 2012; Liu et al., 2012; Lee et al., 2013). For this reason, it was important

to study plants which have been grown under a broad spectrum W light then placed under

wavelength specific lighting to determine if there was any direct effect from the light on

sister plants.

52

In this chapter, a comparison of whole plant NCER and water use efficiency (WUE) will

occur between HPS lighting, which is currently the standard for greenhouse supplementary

lights, and two commercially available wavelength specific LED lights. Leaf growth

parameters will also be studied on plants which have been grown in a broad spectrum W

light then exposure to a variety of wavelength specific LEDs. The objective was to determine

if wavelength specific lighting has a direct effect on whole plant or leaf growth parameters

under short-term irradiance on plants which were identical.

3.2 Materials and Methods

3.2.1 Plant Materials and Growth Conditions

Bonny Best (BB) cultivar of S. lycopersicum were purchased from William Dam Seeds

(Dundas, ON, Canada). Seeds were sown into 60 cavity potting trays (The HC Companies,

Middlefield, OH, USA) in Sungro professional growing mix #1 (Soba Beach, AB, Canada)

containing Canadian sphagnum peat moss, coarse perlite, dolomitic limestone, and a

fertilizer pre-charge. Germination took place in a growth chamber (GC-20 Bigfoot series,

Biochambers, Winnipeg, MB, Canada) with a temperature setting of 22/18°C with a 16/8h

photoperiod under a clear plastic lid (The HC Companies, Middlefield, OH, USA) to aid in

maintaining a high relative humidity (~85%). Plants were provided with 200±50 µmol m-2

s-1 PAR at the pot level. Once germinated, the plastic lid was removed and the relative

humidity within the growth chambers was maintained 65±10%, ambient CO2 and a light

level of 300±50 µmol m-2 s-1 PAR at canopy level. For the first 2 weeks after germination,

plants were watered with raw water as needed and fertilized every 3rd day with Miracle-Gro

All-purpose 24-8-16 with micronutrients (Scotts Canada Ltd., Mississauga, ON, Canada).

53

Plants were repotted into 2”x2” pots (The HC Companies, Middlefield, OH, USA) in

Sungro professional growing mix #1, 2-3 weeks after germination and kept in the growth

chamber at the same conditions stated as above. Plants were fertilized as needed with

Miracle-Gro All-purpose 24-8-16 with micronutrients. Plants were grown until the 31 day

after planting (DAP) or the 50 DAP and were used for whole plant and leaf experimentation.

3.2.2 Daily Patterns of Whole Plant Gas Exchange

Whole plant system design is identical to that states in chapter 2.3.2.

Two short term acclimation experiments using plants which were grown in growth

chambers under W light, plants were randomly selected from a larger population. For the

first experiment, four plants which were 31 DAP were put into each chamber. The

photoperiod was set to 16/8h with a light level of 1000±25 µmol m-2 s-1 from either a HPS

light, RB LED, or RW LED at canopy level (Appendix III). Relative humidity was held constant

at 55±5% during the day and night period and temperature was set to 22/18°C. For the

second experiment two plants which were 51 DAP. The photoperiod, relative humidity, and

temperature were the same as the first experiment, however the light level was changed to

350±10 µmol m-2 s-1 1 from either a HPS light, RB LED, or RW LED which was the light

intensity at the top of the canopy in the growth chambers at the beginning of the experiment

(Appendix III). Plants were placed in their respective chambers around 3pm and allowed to

acclimate for the rest of the day and night period. The following morning, lights would come

on at 6am and shut off at 10pm giving a 16h photoperiod. NCER would be recorded for that

day and night and used in analysis. The next morning, plants would be taken out of the

chambers and their leaf area would be determined using a leaf area meter. The roots were

54

then washed of the dirt and leaves, stems, and roots were dried in an oven at 70°C for 48h.

Samples were then weight and data was normalized on a dry weight and leaf area basis.

3.2.3 Induction of Leaf Photosynthesis - Wake Up Experiment

Once plants reached the 40 DAP mark, wake up studies began. Plants were switched to

an identical schedule as their growth schedule but the night period in the growth chamber

was set to happen from 8am to 6pm. This was done to allow for plants to be in darkness

during the time of day they were being used.

Based on the knowledge from the whole plant experiments, it was known that

respiration stayed constant throughout the whole night cycle so plants could be used

throughout the night. However, the first hour of the night cycle was excluded and plants were

not used during this period. Plants which were selected were taken out of the dark growth

chamber and immediately had the most distal leaflet on the 5th leaf from the top placed in

the chamber of a Li-COR 6400 portable unit. The chamber head was equipped with a clear

top which allowed for light to travel through it to the leaf. The air which was drawn into the

machine is scrubbed free on CO2 by a purge gas generator. A set concentration of CO2 was

Figure 3.1: Li-COR 6400 with a tomato leaf inside the chamber being illuminated by green light.

55

then pumped back into the air stream using liquefied CO2. The leaf temperature within the

chamber was held at 22°C with a relative humidity of 50-60% and a CO2 level of 400 µmol m-

2 s-1 (Figure 3.1). w

Lights which were used were PAR38 LED flood lights provided by LSGC and consisted of

R, B, W, and a RB mixture (Appendix III). Lights were standardized with a Li-COR quantum

sensor since the sensor which was in the Li-COR 6400 is a gallium arsenide sensor and lack

the ability to detect all colours equally. With this knowledge, lights were set to a 1000 µmol

m-2 s-1 light level which was deemed to be around the saturation point of each light. Leaves

were left in the chamber until they reached their maximum photosynthetic rate at that light

level. This experiment was repeated five time, each time using a new leaf and rotating

through the different light colours.

3.2.4 Responses to Wavelength Specific Lighting - Light Curves

Once plants reached the 31-35 DAP stage, the generation of light curves begun. All plants

were woken up in the growth chambers under a broad spectrum W light in order to fully

prime the photosystems. Plants were then taken out of the growth chamber and placed into

the leaf chamber of the Li-COR 6400. Again, the most distal leaf on the fifth leaf from the top

was used for measurements. The chamber was set to the same parameters as that in section

3.3.2. Wake Up Study.

Each leaf will then go through a light curve under one single light without the chamber

being opened. Light curves started at a 1500 µmol m-2 s-1 light level with the exception of the

G light and O light (Appendix III), which due to technical issue could only reach a maximum

light level of 800 µmol m-2 s-1 and 600 µmol m-2 s-1 respectively. This was done following the

56

protocol established for the automatic light curves in the Li-COR 6400 manual as well as

those laid out by Evans & Santiago (2014). The light level was then decreased incrementally

until the light was turned off. Readings were taken every 15 seconds and at each decreased

light level, the leaf was allowed to acclimate to the light level until a steady photosynthetic

level was achieved. At this time, the readings of approximately two minutes where averaged

and taken as the photosynthetic level for that light level. These light curves were performed

with three leaves for each of the different light colours (Appendix III), were averaged and

those averages were used to create the light curves.

3.3 Results

3.3.1 Whole Plant CO2 and H2O Gas Exchange at Saturating Light Level

Figure 3.2 shows the diurnal whole plant net carbon exchange rates (Panels A, C, and E)

and C-budgets (Panels B, D, and F) of tomato plants which were grown under identical W

light conditions in a growth cabinet then subjected to a consecutive day/night period under

either a 1000±25 µmol m-2 s-1 of RB LED, RW LED, or HPS light treatments in whole plant gas

exchange chambers. This light level was deemed to be a saturating level via Figure 3.6. No

significant differences were observed in the photosynthetic, respiration, or C-budgets

between light treatments when the data was normalized on a plant, leaf area, or plant weight

basis (Table 3.1). However, under all light treatments, a decrease in photosynthesis was seen

to start around 4pm which provided a decrease of approximately 25% of the maximum

hourly photosynthetic rate by the end of the light period (Figure 3.2A, C, and E).

The average whole plant transpiration rate during the day of the RB light treatment was

significantly higher than the other two treatments at a 1000±25 µmol m-2 s-1 light level

57

(Table 3.2). However, RB produced a significantly lower transpiration rate (35%) than the

HPS treatment during the subsequent night period (Table 3.2). However, the average day

time WUE was not significantly different between the treatments even though the RB

treatment exhibits a 15% decrease from the other treatments (Table 3.2). Whole plant

transpiration patterns follow that of photosynthesis during the day and exhibit a decreases

around the 4pm mark as whole plant WUE shows the opposite trend and increases at that

point in time as it is a function of the photosynthesis and transpiration (Figure 3.3).

58

Figure 3.2: Whole plant NCER (A, C, and E) and C-budget (B, D, and F) of tomato plants grown

under W light and analyzed under RB, HPS, and RW light treatments with a light level of

1000±25 µmol m-2 s-1 respectively. Whole plant NCER and C-budget are normalized on a

plant basis (A and B), leaf area basis (C and D), and a dry weight basis (E and F). Whole plant

NCER points represent the hourly mean values ± the standard error of 4 replicates and C-

budget lines represent the mean of 4 replicates.

59

N

CE

R (

µm

ol

C p

lan

t-1 s

-1)

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

NC

ER

(µ

mo

l C

m-2

s-1

)

-5

0

5

10

15

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

NC

ER

(µ

mo

l C

g-1

s-1

)

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

Red-Blue

HPS

Red-White

C-b

ud

get

(C g

ain

-C l

os

s g

C p

lan

t-1)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

C-b

ud

get

(C g

ain

-C lo

ss g

C m

-2)

0

5

10

15

20

25

30

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

C-b

ud

get

(C g

ain

-C l

os

s g

C g

-1)

0.0

0.1

0.2

0.3

0.4

0.5

Red-Blue

HPS

Red-White

A B

C D

E F

Figure 3.3: Whole plant transpiration (A) and WUE (B) of tomato plants grown under white

light then subject to a 16h light period under either RB, HPS, or RW light treatment with a

light level of 1000±25 µmol m-2 s-1 respectively followed by an 8h dark period. Each RW point

represents the hourly mean of 4 replicates ± the standard error. Each HPS and RB point

represents the hourly mean of 2 replicates ± the standard error.

61

Tra

ns

pir

ati

on

(m

mo

l H

2O

·m-2

·s-1

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

WU

E (

µm

ol C

O2/m

mo

l H

2O

)

4

6

8

10

12

14

Red-Blue

HPS

Red-White

A

B

62

Table 3.1: The effect of RB, HPS, and RW lighting at a light level of 1000±25 µmol m-2 s-1 respectively on whole plant NCER daily averages and daily C-budgets of tomatoes grown under white light. Each value for photosynthesis, respiration, and C-budget represent the mean of 4 values. Each value for transpiration and WUE represent the mean of 2 values. Values in parentheses represent ± the standard error for each mean. Letters (a, b) indicate a statistical difference (α=0.05) for the whole plant parameters within a row. Statistical analysis can be found in Appendix II.

CO2 Gas Exchange on a:

Light Treatment

Plant Basis Red-White HPS Red-Blue

Photosynthesis (µmol C plant-1 s-1)

0.63(0.03)a 0.64(0.02)a 0.61(0.02)a

Respiration (µmol C plant-1 s-1)

-0.081(0.005)a -0.085(0.006)a -0.081(0.002)a

C-Gain (g C plant-1) 1.60(0.13)a 1.62(0.16)a 1.55(0.16)a

C-Loss (g C plant-1) 0.10(0.006)a 0.10(0.004)a 0.10(0.01)a

Daily C-Gain (g C plant-1 day-1)

1.49(0.12)a 1.51(0.15)a 1.45(0.14)a

Leaf Area Basis

Photosynthesis (µmol C m-2 s-1)

10.84(0.4)a 10.81(0.4)a 10.19(0.4)a

Respiration (µmol C m-2 s-1)

-1.41(0.08)a -1.46(0.09)a -1.35(0.04)a

C-Gain (g C m-2) 27.47(1.9)a 27.42(1.9)a 25.78(1.6)a

C-Loss (g C m-2) 1.76(0.2)a 1.82(0.2)a 1.68(0.2)a

Daily C-Gain (g C m-2 day-1)

25.69(1.7)a 25.56(1.8)a 24.11(1.4)a

Dry Weight Basis

Photosynthesis (µmol C g-1 s-1)

0.16(0.007)a 0.17(0.006)a 0.17(0.006)a

Respiration (µmol C g-1 s-1)

-0.021(0.001)a -0.024(0.001)a -0.022(0.001)a

C-Gain (g C g-1) 0.41(0.03)a 0.44(0.03)a 0.42(0.03)a

C-Loss (g C g-1) 0.026(0.002)a 0.030(0.004)a 0.027(0.003)a

Daily C-Gain (g C g-1 day-1)

0.38(0.03)a 0.41(0.03)a 0.39(0.03)a

63

Table 3.2: The effect of RB, HPS, and RW lighting at a light level of 1000±25 µmol m-2 s-1 respectively on whole plant daily average transpiration rate and WUE of tomatoes grown under white light. Each value for photosynthesis, respiration, and C-budget represent the mean of 4 values. Each value for transpiration and WUE represent the mean of 2 values. Values in parentheses represent ± the standard error for each mean. Letters (a, b) indicate a statistical difference (α=0.05) for the whole plant parameters within a row. Statistical analysis can be found in Appendix II.

H2O Gas Exchange Light Treatment Red-Blue HPS Red-White

Day Transpiration (mmol H2O·m-2·s-1)

0.42(0.03)a 0.32(0.02)b 0.32(0.02)b

Night transpiration (mmol H2O·m-2·s-1)

0.042(0.006)b 0.065(0.004)a 0.054(0.005)ab

WUE(µmol CO2/mmol H2O)

6.89(0.4)a 8.13(0.3)a 8.12(0.4)a

3.3.2 Whole Plant CO2 and H2O Gas Exchange at Sub-Saturating Light Level

A similar experiment was done with larger plants and a lower, sub-saturating light level

(350±10 µmol m-2 s-1) in order to see if these observations from the above experiment held

true under different conditions. Again, there was no statistical difference between NCER

rates between the RB, HPS, and RW light treatments when normalized on a plant basis or a

leaf area basis (Table 3.3). A significant difference was observed between the RW and RB

treatments when normalized on a dry weight basis (Table 3.3). However, this difference was

not seen to follow through into the C-gain throughout the day (Table 3.3). Figure 3.4A, C, and

E again show a decrease in the hourly average photosynthetic rate starting around 4pm

which results in approximately a 15% decrease by the end of the light period.

Transpiration rates and WUE patterns follow closely with those observed in the

experiment with a light level of 1000±25 µmol m-2 s-1(Figure 3.4A and B). However, in the

lower light level, the RW also produced a statistically higher transpiration rate and provides

64

a higher daily average transpiration rate than RB and HPS and was 18% and 27% higher

respectively at the maximum transpiration rate (Table 3.4). Unlike the higher light intensity

experiment, there is no significant difference in the night time transpiration rates (Table 3.4).

WUE is observed to be statistically lower under both RB and RW LED treatments when

compared to the HPS (Table 3.4). These difference accounted for a 35% and 38% decrease

in daily average WUE respectively under those light treatments.

65

Figure 3.4: Whole plant NCER (A, C, and E) and C-budget (B, D, and F) of tomato plants grown

under W light and analyzed under RB, HPS, and RW light treatments with a light level of

350±10 µmol m-2 s-1 respectively. Whole plant NCER and C-budget are normalized on a plant

basis (A and B), leaf area basis (C and D), and a dry weight basis (E and F). Whole plant NCER

points represent the hourly mean values ± the standard error of 6 replicates and C-budget

lines represent the mean of 6 replicates.

NC

ER

(µ

mo

l C

pla

nt-

1 s

-1)

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

NC

ER

(µ

mo

l C

m-2

s-1

)

-2

-1

0

1

2

3

4

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

NC

ER

(µ

mo

l C

g-1

s-1

)

-0.01

0.00

0.01

0.02

0.03

Red-White

HPS

Red-Blue

C-b

ud

get

(C g

ain

-C lo

ss g

C p

lan

t-1)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

C-b

ud

ge

t (C

ga

in-C

lo

ss g

C m

-2)

0

2

4

6

8

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

C-b

ud

get

(C g

ain

-C lo

ss g

C g

-1)

0.00

0.02

0.04

0.06

Red-White

HPS

Red-Blue

A B

C D

E F

Figure 3.5: Whole plant transpiration (A) and WUE (B) of tomato plants grown under white

light then subject to a 16h light period under either RB, HPS, or RW light treatment with a

light level of 350±10 µmol m-2 s-1 respectively followed by an 8h dark period. Each RB point

represents the hourly mean of 6 replicates ± the standard error. Each HPS and RB point

represents the hourly mean of 3 replicates ± the standard error.

68

Tra

ns

pir

ati

on

(m

mo

l H

2O

·m-2

·s-1

)

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Time (hh:mm:ss)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

WU

E (

µm

ol C

O2/m

mo

l H

2O

)

0

2

4

6

8

10

12

Red-White

HPS

Red-Blue

A

B

69

Table 3.3: The effect of RB, HPS, and RW lighting at a light level of 350±10 µmol m-2 s-1 respectively on whole plant daily average NCER and daily C-budgets of tomatoes grown under white light. Each value for photosynthesis, respiration, and C-budget represent the mean of 4 values. Each value for transpiration and WUE represent the mean of 2 values. Values in parentheses represent ± the standard error for each mean. Letters (a, b) indicate a statistical difference (α=0.05) for the whole plant parameters within a row. Statistical analysis can be found in Appendix II.

CO2 Gas Exchange on a:

Light Treatment

Plant Basis Red-White HPS Red-Blue

Photosynthesis (µmol C plant-1 s-1)

0.67(0.01)a 0.70(0.01)a 0.68(0.02)a

Respiration (µmol C plant-1 s-1)

-0.17(0.006)a -0.17(0.009)a -0.16(0.007)a

C-Gain (g C plant-1) 1.77(0.04)a 1.77(0.06)a 1.73(0.05)a

C-Loss (g C plant-1) 0.21(0.03)a 0.21(0.03)a 0.21(0.03)a

Daily C-Gain (g C plant-1 day-1)

1.56(0.04)a 1.56(0.06)a 1.56(0.04)a

Leaf Area Basis

Photosynthesis (µmol C m-2 s-1)

3.01(0.07)a 3.13(0.06)a 3.04(0.07)a

Respiration (µmol C m-2 s-1)

-0.77(0.02)a -0.74(0.04)a -0.71(0.03)a

C-Gain (g C m-2) 7.91(0.4)a 7.96(0.6)a 7.77(0.4)a

C-Loss (g C m-2) 0.90(0.09)a 0.94(0.1)a 0.90(0.09)a

Daily C-Gain (g C m-2 day-1)

7.00(0.4)a 7.02(0.6)a 6.99(0.4)a

Dry Weight Basis

Photosynthesis (µmol C g-1 s-1)

0.025(0.0006)a 0.024(0.0004)ab 0.023(0.0005)b

Respiration (µmol C g-1 s-1)

-0.0063(0.0003)a -0.0055(0.0002)a -0.0056(0.0002)a

C-Gain (g C g-1) 0.061(0.004)a 0.059(0.004)a 0.061(0.004)a

C-Loss (g C g-1) 0.0069(0.0006)a 0.0066(0.0007)a 0.0069(0.0006)a

Daily C-Gain (g C g-1 day-1)

0.054(0.004)a 0.053(0.005)a 0.054(0.004)a

70

Table 3.4: The effect of RB, HPS, and RW lighting at a light level of 350±10 µmol m-2 s-1 respectively on whole plant diurnal NCER and daily C-budgets of tomatoes grown under white light. Each value for photosynthesis, respiration, and C-budget represent the mean of 4 values. Each value for transpiration and WUE represent the mean of 2 values. Values in parentheses represent ± the standard error for each mean. Letters (a, b) indicate a statistical difference (α=0.05) for the whole plant parameters within a row. Statistical analysis can be found in Appendix II.

H2O Gas Exchange Light Treatment Red-White HPS Red-Blue

Day Transpiration (mmol H2O·m-2·s-1)

0.23(0.01)a 0.16(0.01)b 0.21(0.009)a

Night transpiration (mmol H2O·m-2·s-1)

0.075(0.004)a 0.058(0.004)a 0.066(0.007)a

WUE(µmol CO2/mmol H2O)

3.27(0.2)b 5.26(0.5)a 3.41(0.1)b

3.3.3 Wake Up

Time to maximum photosynthesis under a set light level (1000 µmol m-2 s-1) varies

based on the spectral quality of the light the leaf is illuminated with after a darkened period

(Table 3.5). Lights containing any amount of R light were seen to cause the plants to ‘wake

up’ and reach their maximum photosynthetic rate in a short period of time than those lacking

light in the R spectrum. White light provided the quickest time to maximum photosynthesis

as the B treatment provided statistically the slowest time to maximum photosynthesis (Table

3.5).

71

Table 3.5: The effect of various wavelengths on the time to maximum photosynthesis. Tomato plants were grown at 22°C/18°C and were taken from a dark chamber. Each value represents 5 replicates. The values in parentheses represents the standard error (±) for each mean and the letters (a, b) indicate statistical differences (α=0.05) between the different light treatments via a means comparison with a Tukey-Kramer adjustment. Statistical analysis in appendix II.

Treatment Time to Maximum Photosynthesis (min:sec)

White 10:12 (1:22)b

Blue 21:09 (2:13)a

Red 15:45 (3:20)ab

Red-Blue 13:48 (1:53)ab

3.3.4 Leaf Light Curves

The photosynthetic rates at set light levels were higher in leaf studies when lights which

exhibit a large quantity of R in the treatment (Figure 3.6). The R and RB treatments

consistently provided the highest photosynthetic rate at a given PAR level for most of the

light curve (Appendix II: Table 3.1). At the upper saturating light levels (Greater than 800

µmol m-2 s-1) the RB treatment produced the highest photosynthetic rate and had an average

photosynthetic rate approximately 6% higher than the R treatment and 17% higher than the

B treatment. The B treatment provided one of the lowest photosynthetic rates of any

treatments throughout most of the light levels (Appendix II: Table 3.1). Surprisingly, G and

O provided statistically among the highest photosynthetic rates. The RW treatment also

72

produced the lowest photosynthetic rates during the lower PAR regions (Less than200 µmol

m-2 s-1).

Stomatal conductance and transpiration rate varied in parallel with each other based as

a function of wavelength (Figures 3.6 and 3.7). Through the various light intensities, from

saturating light to no light at all, there was very little statistically significant difference in

both parameters between the different light treatments (Appendix II: Table 3.1). However,

during the 800 and 600 µmol m-2 s-1 region, the O light treatment produced the highest

stomatal conductance of any treatment and was still significantly different then the G

treatment until the 400 µmol m-2 s-1 light level. Transpiration rates followed nearly identical

patterns and a significant difference was seen between B and G light treatments at 800 µmol

m-2 s-1 and G and O light treatments at 600 and 400 µmol m-2 s-1 (Appendix II: Table 3.2). No

significant difference was seen in either parameter at any other light levels.

The amount of CO2 within the leaf tissue is known as the internal CO2 concentration (Ci).

This value was calculated as a function of stomatal conductance, external CO2 concentration,

and carbon fixation rates. As an overall pattern, as the light intensity and photosynthetic

rates decreases under each light treatment, the Ci increased due to less of the internal CO2

being fixed (Figure 3.7).

73

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

NC

ER

(µ

mol m

-2 s

-1)

-5

0

5

10

15

20

25

Red

Blue

Red-White

Red-Blue

Green

Orange

White

Figure 3.6: Light curves generated with the Li-COR 6400 from white light grown tomato leaves when analyzed under various colours of LED lights. Each point represent 3 replicates each done with separate leaves without removing the leaves from the chamber between light levels. Statistics found in Appendix II.

74

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

Sto

ma

tal C

on

du

cta

nce

(m

mo

l H

2O

·m-2

·s-1

)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Red

Blue

Red-White

Red-Blue

Green

Orange

White

Figure 3.7: The effects of various wavelengths and light intensity on the stomatal conductance of white light grown tomato leaves. Each point represents 3 replicates of difference leaves where the chamber was not opened between light intensities. Statistical found in Appendix II.

75

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

Tra

nspiration (

mm

ol H

2O

·m-2

·s-1

)

0

1

2

3

4

5

6

Red

Blue

Red-White

Red-Blue

Green

Orange

White

Figure 3.8: Effects of various wavelengths and light intensity on the transpiration rates of white light grown tomato leaves. Each point represents 3 replicates of different leaves where the chamber was not opened between light intensities. Statistics found in Appendix II.

76

PAR (µmol m-2

s-1

)

0 200 400 600 800 1000 1200 1400 1600

Ci (

µm

ol m

ol-1

)

200

250

300

350

400

450

500

Red

Blue

Red-White

Red-Blue

Green

Orange

White

Figure 3.9: Effects of various wavelengths and light intensity on the Ci of white light grown tomato leaves. Each point represents 3 replicates of different leaves where the chamber was not opened between light intensities. Statistics found in Appendix II.

3.4 Discussion

3.4.1 Comparison of Wavelength Specific LED Lighting and HPS Lighting

on Whole Plant CO2 Gas Exchange

As expected, a lower light level caused a lower photosynthetic rate independent of light

treatments when normalized on a leaf area and plant dry weight basis for whole plant

analysis and leaf studies (Figure 3.2; Figure 3.4; Figure 3.6) (Liu et al., 2011b). This decrease

lead to less carbon being accumulated within the plant under lower light levels (Table 3.1;

Table 3.3). However, on a plant basis, there was no difference in the photosynthetic rates

between the two light levels which was likely due to the size and canopy architecture of

plants used in each experiment. The more complex leaf canopy of the plants used in the low

light experiment makes it harder for light to travel to the lower leaves which was causing the

average photosynthetic rate on a leaf area basis to be decreased. This mutual shading was

again an example why the use of leaf photosynthetic measurements cannot be used to

interpret the trends of a whole plant as a system.

Tepperman et al. (2004) provided evidence that gene expression could be altered in a

little as one hour by illuminated white grown plants with an R and far R light. Thus, it is quite

possible that gene expression may be altered within the plants during the experiment

analyzed under RB and RW treatments. However, the benefits or downfalls of such genetic

control were not observed in this short term, whole plant experiments but were evidence in

the end biomass production from the greenhouse experiments (Table 2.1) (Tepperman et

al., 2004). These long term acclimated plants provided similar results to current literature

providing evidence which indicates that long term exposure may provide advantages during

78

production (Goins et al., 1997; Matsuda et al., 2004; Hogewoning et al., 2010; Liu et al.,

2011b).

Unlike previous studies, there was no effect on photosynthesis and carbon gain provided

by the different light treatments when compared within the same light intensity (Goins et al.,

1997; Matsuda et al., 2004; Hogewoning et al., 2010; Liu et al., 2011b). However, previous

literature only accounted for differences in leaf photosynthetic rates that did show some

differences in photosynthetic rates mainly in the RB treatment (Figure 3.6). In previous

experiments, researchers have used plants which were grown solely under a specific colour

of light which has the ability to change the morphological and anatomical structure of the

plant as evident in studies performed by Liu et al. (2011b and 2012). In the studies described

in chapter 3, all plants were grown under a broad spectrum white light in a growth chamber

making the plants effectively sister plants before they are subject to the different light

treatments. Doing so allowed for the direct effect of the lights on plants, which have no

morphological or anatomical advantage brought about by long term exposure to different

light treatments, to be determined. Under these conditions no differences were determined

for the whole plant NCER studies (Figure 3.2; Figure 3.4; Table 3.1; Table 3.3). However

during leaf experiments, RB light provided statistically higher leaf photosynthetic rates than

B light alone (Figure 3.6; Appendix II: Table 3.1).

Also observed was the decrease in the photosynthetic rate which was found to be

ubiquitous under all light treatments during the late afternoon period which accounted for

a 25% and 15% in the 1000±25 µmol m-2 s-1 and 350±10 µmol m-2 s-1 treatments respectively

(Figure 3.2 and Figure 3.4). Transcription patterns of phytochrome (PHY) and cryptochrome

79

(CRY) which are light absorbing molecules have been observed to follow a circadian rhythm

which exhibits a decrease approximately 12 hours after being exposed to light (Facella et al.,

2008). If these molecules have a decreased transcription rate as well as a decreased

abundance within the leaf, this may cause a lower rate of light absorption (Facella et al.,

2008). While these molecules are not the main light absorbing molecules within the leaf, they

still contribute by transferring energy to Chl a helping to drive photosynthesis (Goedheer,

1969; Cogdell et al., 1981; Cogdell 1985).

The decrease in photosynthesis may also be due to a feedback inhibition of RUBISCO

activity by sucrose (Roh and Choi, 2004; Kasai, 2008). In soybeans, it was observed that as

sucrose levels increased, there was a linear decrease in the photosynthetic rate of the leaf

(Kasai, 2008). This decrease in photosynthesis was attributed to the sucrose having a

negative correlation with RUBISCO as well as having a positive correlation with RuBP which

both lead to a decrease in the photosynthetic rate (Brooks and Portis, 1988; Kasai, 2008). A

similar phenomenon was observed in tobacco leaves which are in the same family,

Solanaceae, as tomatoes. It was determined that an increase of sucrose increased the

activation of RUBISCO, however at higher levels of sucrose (<4%), RUBISCO activation

started to fall off which would lead to a lower photosynthetic rate. Although neither

mechanism has been determined to effect tomato photosynthetic rates, Figure 3.2 and Figure

3.4 provide evidence that there is a change in the photosynthetic rate of young tomato plants

during the latter hours of the afternoon.

80

3.4.2 Comparison of Wavelength Specific Lighting on Leaf CO2 Gas

Exchange

Although B light is readily absorbed by Chl a and b, previous finding have determined

that B light alone was not adequate for driving a high rate of photosynthesis (Mackinney,

1940; Hogewoning et al., 2010). A slight decrease was also seen in the pure R light treatment

(Figure 3.6; Appendix II: Table 3.1). This leads to the idea proposed by Hogewoning et al.,

(2010) of spectral deficiency syndrome. This theory states that a sole wavelength alone will

not generate a high photosynthetic rate within plants (Hogewoning et al., 2010). Data

presented in Figure 3.6 supports this idea. It was clear that the addition of a more complex

light treatment (R + B or some combination) was able to increase photosynthetic rates

without increasing the light intensity of the treatment. This was also seen in plant

morphology with a complex light treatment providing healthier and more ‘natural’ looking

plants as seen in Liu et al., (2012).

During leaf experiments, unlike reports from Liu et al., (2012), the O and G lights used in

our experiments were able to produce high photosynthetic rates. The O light used in these

experiments had a wavelength maximum of approximately 600nm which falls within the

absorbance spectrum of Chl a and Chl b as well as some carotenoids and other light

harvesting molecules (Mackinney, 1941; Andersson et al., 1991). Thus it is not unlikely that

an O light on its own would be able to produce a high rate of photosynthesis. It is also fairly

close in wavelength to the R light treatment which was used in experimentations adding

further verification. Also of note, in an experimentation where R and B light were the most

dominant lights in a light treatment, the addition of an O light of close wavelength to the one

81

used in this experimentation allowed for an increase in photosynthetic rates compared to

treatments lacking the orange light (Brazaityte et al., 2010).

Green light had been dismissed with respect to driving photosynthesis when used as a

sole illumination source. However, G light is able to penetrate leaf tissue and proceed to

travel further than any other visible light which allows for a different set of chloroplast to

absorb light and in turn drive photosynthesis (Sun et al., 1998; Terashima et al., 2009).

However, when used as a sole light source, G light changes the morphology of the whole plant

producing elongated stems and causes a poor health index (Liu et al., 2012). Because G light

was able to penetrate the leaf and reach a different level of chloroplast, as well as be able to

bounce around the canopy of plants and drive photosynthesis, it may be useful in

combination with other lights (Figure 3.2) (Sun et al., 1998; Terashima et al., 2009).

3.4.3 Effects of Wavelength Specific Lighting on Plant Wake Up

Chloroplast avoidance is a phenomenon where under high light intensities chloroplast

actually move away from the light source (Inoue & Shibata, 1973; Zurzycki, 1980; Banas et

al., 2012). Under the strong light which is used in this experiment (1000 µmol m-2 s-1)

phototropins 1 and 2 (phot1 and phot2) are stimulated, but it is phot2 which enacts the

avoidance response by enacting chloroplast movement via myosin and actin filaments

(Banas et al., 2012).

The way chloroplast avoidance has been measured in the past was by a decrease in light

absorption by the leaf or cell (Zurzycki, 1980). Photosynthetic rate is increased by light

absorption which may indicated that the slower time to maximum photosynthetic rate seen

under the B light is really a chloroplast avoidance response to the high light reducing light

82

absorption (Inoue & Shibata, 1973; Zurzycki, 1980; Banas et al., 2012). Although this process

is usually associated with single cells, it can be imagined to happen in multiple cells within a

leaf causing a bunching effect and effectively causing mutual shading between chloroplast.

The leaf will then slowly acclimatize to the high light level and the chloroplast avoidance

begins to weaken allowing more chloroplast to absorb light and in turn increasing

photosynthetic rates. This phenomenon has not been seen with any other wavelength of light

and even under low B light intensity is not a factor (Inoue & Shibata, 1973). In fact, R light

has shown to inhibit the avoidance response of chloroplast and cause a faster rate of

reappearance in chloroplast post B light illumination (Ichikawa et al., 2011). It does so by

being absorbed by phot1 which caused an antagonistic reaction to the actin movement of

chloroplast effectively stopping the process all together and allowing for chloroplast to stay

in the illuminated area (Ichikawa et al., 2011).

Chloroplast ‘leakiness’ may also be an explanation for the slow time to reach maximum

Pn rate under B light. Triose phosphate translocator is the enzyme responsible for the export

of triose phosphate (TP) and 3-PGA from the chloroplast to the cytosol for sucrose synthesis

(Walters et al., 2004). If TP was exported from the chloroplast too quickly, the intermediates

needed for the Calvin cycle will be depleted (Walters et al., 2004). Although there is no

literature tying B light to an increase in TP efflux, it is worth noting that if B light was able to

effect this rate and cause a decrease in Calvin cycle intermediates, it may results in a slow

priming of the leaf which could be seen as a slower rate to reach maximum Pn (Walters et

al., 2004). This theory will be revisited in chapter 4.

83

Evolutionarily speaking, plants may have evolved over millions of years to adapt to the

high amount of R light in the atmosphere during the morning hours. During the morning

hours B light, which is in the shorter wavelength region of the visible spectrum, is scattered

before it’s able to reach the ground via air particles and other particulate which is known as

Rayleigh scattering (Bates, 1984). This scattering is the reason we perceive the sky as blue

and as the day continues, more of the short wavelength B light is able to reach the ground

(Bates, 1984). Thus, longer wavelength R light is able to reach the Earth during the morning

hours and over millions of years plants could adapt to use this to their advantage.

The result showing W light as being significantly quicker to enact maximum

photosynthesis followed by RB light combination then the sole R light indicates that a

broader spectrum was needed to wake up the plants. This again reinforces the need for more

than a wavelength specific lighting due to the spectral deficiency syndrome (Hogewoning et

al., 2010).

3.4.4 Effects of Wavelength Specific Lighting on H2O Gas Exchange

Statistical differences were observed between RB and HPS transpiration rates during the

high light whole plant experiment and in the low light whole plant experiment RB and RW

show statistically higher transpiration rates than the HPS treatment for whole plant

experiments (Table 3.2; Table 3.4). During the low light experiment, differences in

transpiration rates translated to lower WUE which proved to be a significant (Table 3.4).

These results may seem to be counter intuitive, simply due to the high heat emitting

properties of the HPS light which should, in turn, increase stomatal opening and

transpiration rates in C3 plants as well as decrease WUE (Gajc-Wolska et al., 2013; Kaminski

84

et al., 2014). However, different spectral qualities such as R and B light and the combination

have been known to increase stomatal opening which can increase transpiration rates (Kana

and Miller, 1977; Liu et al., 2012). When looking at leaf stomatal conductance, there was an

increase under the B and R lights (Figure 3.7). This increase in stomatal conductance results

in generally higher transpiration rates under these lights as well (Figure 3.8). Thus during

the whole plant experiments which these differences are magnified by the amount of leaf

area in the chambers (Figure 3.3; Figure 3.5). As the light level decreases the difference in

stomatal conductance and transpiration rate due to a higher amount of B light in the RB light

treatment seems to diminish which was why at the low light level whole plant study, no

difference were seen between the RB and RW light treatments (Table 3.4). As discussed in

sections 2.5, the increase in stomatal conductance and opening was due to the influx of K+

ions into the guard cells (Lurie, 1978; Kinoshita and Shimazaki, 1999). Unlike experiments

in chapter 2, plants in this experiment were grown under white light allowing the increase

in stomatal conductance and connected transpiration rates to be seen as a direct function of

the lights the plants and leaves were illuminated with.

Due to this stomatal opening, B light, R light and mixtures including those invoke higher

Ci values from the leaf studies then those with do not contain either such as G and W to some

extent. Green light has been shown to antagonize the effects B light has on plants such as

increase stomatal conductance and opening (Frechilla et al., 2000; Kim et al., 2004b;

Hogewoning et al., 2010). Pulses of B light were able to increase stomatal opening where as

a pulse of a high intensity G light caused no response in stomatal opening (Frechilla et al.,

2000). Also, when G light was added to a B and R light mixture, stomatal opening decreases

(Frechilla et al., 2000). It has been proposed that the accumulation of zeaxanthin in guard

85

cells can decrease stomatal opening by blocking the influx of K+ into the cell (Frechilla et al.,

1999). Thus, it was possible that in treatments containing either pure G light, or G light in

any amount, that stomatal conductance would decrease effecting the transpiration rates and

Ci of the leaves.

In summary, plants grown under the same conditions then analyzed under RB LED, RW

LED, or HPS lighting provided no difference in whole plant NCER under saturating or sub-

saturating light levels. Slight differences were seen at the leaf leave with the RB light

treatment providing the highest Pn rate at a light level of 1500 µmol m-2 s-1. Statistical

increases in transpiration rates were seen when plants were analyzed under RB and RW LED

during sub-saturating light level whole plant experiments. Statistical increases in

transpiration rates were also seen under the RB light treatment at saturating light level.

These differences were mirrored in the WUE at each light level. This chapter provides

evidence of the short term effects of wavelength specific lighting on plants and leaves grown

under identical conditions (sister plants). This evidence allows for a better understanding of

the effects of short term wavelengths specific illumination which is needed for the sizing and

timing of the experimental design needed to preform experiments in Chapter 4.

86

Chapter 4

Effects of Wavelength Specific Light on Carbon Fixation, Export and

Partitioning in Source Leaves of Solanum lycopersicum cv. ‘Bonney Best’

4.1 Introduction

Chapters 2 and 3 dealt with the carbon fixation under different light conditions of the

whole plant and source tissue. However, this is only half of the story when it comes to carbon

metabolism or plant growth (Osorio et al., 2014). CO2 drawn into the leaf from the air is

quickly turned into the essential building blocks which enable plant growth via a series of

chemical reactions. The partitioning of carbon into the various building blocks of plants is a

highly regulated process within a plant, however it varies greatly between species (Balibrea

et al., 2000; Lemoine et al., 2013; Sung et al., 2013). For tomato, the main carbohydrates are

well known and are sucrose and starch (Osorio et al., 2014).

Sucrose, which is made in the source leaf, is immediately exported via apoplastic phloem

loading to the growing sink tissue. This is achieved via a pair of transporter proteins allowing

it to pass through cell membranes. Once made in the MC, sucrose is moved through

plasmodesmata into the PPC where it encounters SWEET enzymes which are responsible for

the movement of sucrose into the apoplast (Chen et al., 2012; Feng et al., 2015). Once in the

apoplast, the sucrose is either ushered into TCs where it can passively diffuse into the

phloem or move directly into the phloem. Both processes are facilitated by SUC (Sauer et al.,

2004; Hackel et al., 2006; Sauer, 2007; Aoki et al., 2011).

87

Certain factors are known to effect export such as temperature (Jiao & Grodzinski, 1996;

Leonardos et al., 1996; Leonardos et al., 2003). Others have shown an increase in enzymes

either involved in sucrose synthesis or apoplastic phloem loading, however neither study

attempted to measure if export itself was actually effected (Quick et al., 1989; Meyer et al.,

2004). In this chapter, the effect of light quality on the sugar partitioning ratios and carbon

export rates will be elucidated during short term and photoperiod long illumination at

various light intensities.

4.2 Materials and Methods

4.2.1 Plant Materials and Growth Conditions

Plants were grown in the identical fashion to the above section 3.3.1 Plant Materials and

Growth Conditions. However, three days before the experiment was set to start, the

photoperiod was changed from 16h/8h to 12h/12h. This was done in order to deplete the

sucrose pools within the leaves to insure isotopic equilibrium would be reached during the

shorter feed experiments. These conditions were determined by Gibon et al. (2004) due to

the depletion of sucrose and other soluble sugars during a 12h/12h photoperiod of

Arabidopsis without harming the photosynthetic capability. A portion of the plants were also

put to a delayed morning, being in the light from 11:30am-11:30pm. This was done to allow

for two experiments per day when doing short term feeds, both being done with plants which

had recently been woken up.

88

4.2.2 14C Export

Radioactive CO2 (14CO2) was generated in a large gas tight syringe (Hamilton Co., Reno, NV,

USA) by reacting either radioactive sodium bicarbonate (NaH14CO3; MP Biomedical, Sanata

Ana, CA, USA) with 30% Sulfuric acid (H2SO4; Fisher Scientific, Ottawa, ON, Canada) or

radioactive barium carbonate (Ba14CO3; NEC) with 30% hydrochloric acid (HCl; Fisher

Scientific, Ottawa, ON, Canada). In order to pump the 14CO2 into the leaf export system, it was

drawn into a 60mL syringe and loaded onto a pump (PHD 2000 Infusion, Harvard Apparatus,

Holliston, MA, USA) which then gets injected into the air stream at a set rate allowing it to

get into the leaf chambers.

4.2.2.1 Short Term 14C Feeding

After three days under the 12h/12h photoperiod, plants were taken out of the growth

chamber and the most distal leaflet on the 5th leaf from the top was placed in a specially

designed leaf chamber for gas exchange and export measurements. Leaf chambers were

sealed with vacuum grease (Dow Corning, High Vacuum Grease, Auburn MI, USA) in order to

provide an air tight seal to prevent radioactivity from leaking out of the chambers. Chambers

Figure 4.1: 14C leaf chamber with a tomato leaf sealed inside illuminated by a red-white PAR38 with the water jackets circulating for temperature control.

89

were identical to that used in Leonardos et al., (2003) which included a circulating water

jacket for temperature regulation, a glass window on the top to allow light to pass through,

and a Geiger-Muller (GM) detector (model 7231, LND Inc., Oceanside, NY, USA) for

radioactivity monitoring (Leonardos et al., 2003). Flowrate within each chamber was held

steady at 500cc m-1 with a CO2 concentration of 405±10 µmol m-2 s-1 (Figure 4.1). Only the

leaf inside the chamber was illuminated by the light. This was done in order to see the effects

of wavelength specific lighting on a strong source leaf.

Lights used were identical PAR38’s as that use for the leaf photosynthetic measurements

done with the Li-COR 6400 (Appendix III). Light levels were varied between experiments in

order to produce a photosynthetic vs. export relationship. This was done in order to

elucidate not only the effects wavelength specific lighting had but also to determine if light

intensity played a role in export. Once the leaf was set in the chamber the light level was

established by placing a Li-COR quantum sensor on top of the chamber and using a correction

factor to determine the light level inside the chamber.

Once the light level has been selected and the photosynthetic rate of each leaf has shown

to be steady, 14CO2 is pumped into the air stream and drawn into the leaf chamber. This

radioactive feed will last for approximately three hours under steady light, CO2 and humidity

conditions. The accumulation of 14C by the leaf is monitored by the GM at the base of the

chamber. The carbon export rate was calculated by using the difference between the

photosynthetic rate (Pn) which is measure by an IRGA and the 14C retention which is

measured by the GM (CGM) (Equation 4.1). This CGM value is then corrected for the leaf size,

the radioactivity used in that experiment, and the GM efficiency from each chamber.

90

Equation 4.1:

𝐸𝑥𝑝𝑜𝑟𝑡 = 𝑃𝑛 − 𝐶𝐺𝑀

4.2.2.2 Photoperiod Long Feed-Chase Export

Plants were grown identical to those above in section 4.3.2.1 Short Term 14C experiment.

This experiment evaluated the photoperiod long (15h) day time export rates of plants as well

as the night time (8h) export rates. In order to do so, two photosynthetic levels were chosen,

12 µmol m-2 s-1 and 6 µmol m-2 s-1. Plants were illuminated with the appropriate light level to

achieve such photosynthetic rates with either R, B, RB mixture or W LED lights, again only

illuminating one leaf.

Plants were woken up under white light in the growth chamber in order to prime the

photosystems then transferred to the leaf chambers. Once the photosynthetic rate was

established, 14CO2 was pumped into the air stream and allowed to enter the leaf chamber.

Plants were either left in the chamber for 15h or a full light and dark period lasting 15h and

8h respectively. During the 15h feeds, 14CO2 was being constantly pumped into the chamber

which contained the leaves and were set to a temperature of 22°C, relative humidity of 50-

60%, and a CO2 concentration of 405±10 µmol m-2 s-1.

During 23h experiments, plants were under the same parameters as the 15h feeds for

the day time period but at night were lowered down to 18°C with a flow rate of 150cc m-1.

During the night period the lights were shut off but leaves remained inside the leaf chambers.

The respired air was collected in a 40mL 20% KOH (Sigma-Aldrich, St. Louis, MO, USA) traps

and was used to correct for the loss of 14C by respiration in order to get the night time export

91

rates. Daytime export rates are calculated using equation 4.1 and night time rates are

calculated using equation 4.2 where Rd is the respiration rate determined using the KOH

traps and CGM.

Equation 4.2:

𝐸𝑥𝑝𝑜𝑟𝑡 = 𝑅𝑑 − 𝐶𝐺𝑀

4.2.3 14C Partitioning

Once the runs were done, leaves were immediately taken out of the chamber and cut to

the appropriate chamber size (ie, cutting off regions which contained vacuum grease)

(Figure 4.2A). Pictures were taken in order to determine the leaf size by using ImageJ

(University of Wisconsin-Madison). Leaves were then cut into small pieces and extracted

three times using boiling 80% ethanol for 20-30 minutes each time, leaving a soluble fraction

and extracted leaf tissue (Figure 4.2B and 4.2G).

From this point on, soluble and extracted tissue fractions were processed separately.

Tissue fractions were dried in an oven at 70°C for 24 hours. Once dried, they were placed in

a 2mL flat bottom microfuge tube with two 3mm stainless steel balls. The samples were put

into a grinder (Mixer Mill MM 400, Retsch, Haan, Germany). Samples were dry ground twice

for 5 minutes each at 30Hz. One mL of 80% ethanol was then added to the microfuge tubes

and the samples were ground again at 30Hz for 2 minutes in order to mix the ethanol with

the ground tissue. The stainless steel balls were removed and washed with 80% ethanol,

then the microfuge tubes were topped up to a final volume of 1.75mL (Figure 4.2H). Three

50µL subsamples were taken from each sample and placed in individual scintillation vials

92

with 2.8mL of scintillation cocktail (MP Biomedicals, LLC. Solon, OH, USA) and counted in a

liquid scintillation counter (LSC; model LS-6800, Beckman Instruments Inc., San Ramon, CA,

USA) (Figure 4.2I).

Ethanol soluble fractions were vacuum dried (Model Sc210A, SpeedVac Plus, Savant)

(Figure 4.2C). Samples were then suspended in a mixture of water and 99% chloroform (3:2

v/v) and thoroughly agitated. Samples were separated by centrifugation at 11,000 RPM

(Figure 4.2D). Two 50µL subsamples were taken from each of the water and chloroform

layers of each sample and counted in a LSC (Figures 4.2E and 4.2F). Determination of carbon

partitioning within samples are calculated using equations 4.3, 4.4, and 4.5 which represent

the %14C recovered from each portion of the leaf. In equation 4.3, the radioactivity as

determined by the LSC in the ethanol insoluble faction (dpminsol) is divided by the total

radioactivity in the sample (dpmtot) multiplied by 100. Equations 4.4 and 4.5 are identical

with the exception of the fractions being sampled. In equation 4.4 which is to determine

radioactivity in the water soluble fraction, radioactivity in that fraction is represented by

‘dpmH20’ and in equation 4.5, radioactivity determined in the chloroform fraction is

represented by ‘dpmChl’.

Equation 4.3:

𝑝𝐶14𝑖𝑛𝑠𝑜𝑙 = (𝑑𝑝𝑚𝑖𝑛𝑠𝑜𝑙

𝑑𝑝𝑚𝑡𝑜𝑡) ∗ 100

Equation 4.4:

𝑝𝐶14𝐻2𝑂 = (𝑑𝑝𝑚𝐻2𝑂

𝑑𝑝𝑚𝑡𝑜𝑡) ∗ 100

93

Equation 4.5:

𝑝𝐶14𝐶ℎ𝑙 = (𝑑𝑝𝑚𝐶ℎ𝑙

𝑑𝑝𝑚𝑡𝑜𝑡) ∗ 100

94

Figure 4.2: Extraction process of leaves which were used for export and partitioning

experiments. (A) Leaf which has been cut to the size of the chamber for extraction. (B)

Ethanol soluble fraction of triple extracted leaf. (C) Dried ethanol soluble fraction. (D)

Suspended soluble leaf fraction after it has been separated by centrifugation showing the

water layer on the top and chloroform layer as the green bottom layer. (E) Subsample of the

water fraction in a scintillation vial. (F) Subsample of the chloroform fraction in a

scintillation vial. (G) Ethanol insoluble leaf fraction after being triple extracted. (H) Insoluble

fraction after it had been dry ground and suspended in ethanol. (I) Subsample of insoluble

fraction in a scintillation vial.

95

A B

C D

E F

G

H

I

96

4.3 Results

Stomatal conductance, transpiration rates, WUE and Ci show similar results from

15h/23h 14C feeds as do both leaf and whole plant experiments from chapter 2 and 3. Again,

lights containing blue show the highest stomatal conductance among all light treatments

(Figure 4.3; Table 4.1). With this increase in stomatal conductance, an increase in

transpiration and Ci are also seen (Figure 4.4; Figure 4.6). Increases in WUE are seen under

the W light treatment showing an increase in CO2 fixation for every mmol of H2O being used.

These results were seen in both the high Pn and low Pn experiments provide more proof to

the results in chapter 2 and 3.

97

Figure 4.3: 15 hour and 23 hour (pooled) stomatal conductance of plants grown and woken

up under white light then transferred to either RB, W, R, or B lighting with a Pn rate of

approximately 12 µmol m-2 s-1 (A) and 6 µmol m-2 s-1 (B) for the start of the 15h 14C feed

period and an 8h dark chase period. Each point and standard error bars during the day time

period (0h to 15h) represents the hourly average of 10 replicates for R, 9 replicates for B, 11

replicates for RB, and 9 replicates for W. Each point and standard error bars during the night

period (15h to 23h) represents the hourly average of 5 replicates for R, 5 replicates for B, 5

replicates for RB, and 3 replicates for W. Each replicates represents and independent leaf.

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Sto

ma

tal C

on

du

cta

nc

e (

um

ol C

O2·m

-2·s

-1 )

0

20

40

60

80

100

120

140

Red

Blue

Red-Blue

White

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

A B

Figure 4.4: 15 hour and 23 hour (pooled) Transpiration rates of plants grown and woken

up under white light were then transferred to either RB, W, R, or B lighting with PAR adjusted

to achieve Pn rate of approximately 12 µmol m-2 s-1 (A) and 6 µmol m-2 s-1 (B) for the start of

the 15h 14C feed period and an 8h dark chase period. Each point and standard error bars

during the day time period (0h to 15h) represents the hourly average of 10 replicates for R,

9 replicates for B, 11 replicates for RB, and 9 replicates for W. Each point and standard error

bars during the night period (15h to 23h) represents the hourly average of 5 replicates for

R, 5 replicates for B, 5 replicates for RB, and 3 replicates for W. Each replicates represents

and independent leaf.

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Tra

nsp

irati

on

(m

mo

l H

2O

·m-2

·s-1

)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Red

Blue

Red-Blue

White

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

A B

Figure 4.5: 15 hour WUE of plants grown and woken up under white light then transferred

to either RB, W, R, or B lighting with a Pn rate of approximately 12 µmol m-2 s-1 (A) and 6

µmol m-2 s-1 (B) for the start of the 15h 14C feed period and an 8h dark chase period. Each

point and standard error bars during the day time period (0h to 15h) represents the hourly

average of 10 replicates for R, 9 replicates for B, 11 replicates for RB, and 9 replicates for W.

Each replicate represents and independent leaf.

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

WU

E (

µm

ol C

O2/m

mo

l H

2O

)

0

2

4

6

8

10

12

Red

Blue

Red-Blue

White

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

A B

Figure 4.6: 15 hour and 24 hour (pooled) Ci of plants grown and woken up under white light

then transferred to either RB, W, R, or B lighting with a Pn rate of approximately 12 µmol m-

2 s-1 (A) and 6 µmol m-2 s-1 (B) for the start of the 15h 14C feed period and an 8h dark chase

period. Each point and standard error bars during the day time period (0h to 15h) represents

the hourly average of 10 replicates for R, 9 replicates for B, 11 replicates for RB, and 9

replicates for W. Each point and standard error bars during the night period (15h to 23h)

represents the hourly average of 5 replicates for R, 5 replicates for B, 5 replicates for RB, and

3 replicates for W. Each replicates represents and independent leaf.

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Ci (

µm

ol m

ol-1

)

200

300

400

500

600

700

800

Red

Blue

Red-Blue

White

Time(h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

A B

Table 4.1: 15 hour and 23 hour (pooled) CO2 and H2O gas exchange measurements of plants

grown and woken up under white light then transferred to either RB, W, R, or B lighting with

a high Pn rate of approximately 12 µmol m-2 s-1 and a low Pn rate of 6 µmol m-2 s-1 for the

start of the 15h 14C feed period and an 8h dark chase period. For high Pn, Each point and

standard error bars during the day time period (07:00:00 to 22:00:00) represents the hourly

average of 11 replicates for R, 7 replicates for B, 11 replicates for RB, and 11 replicates for

W. Each point and standard error bars during the night period (22:00:00 to 06:00:00)

represents the hourly average of 6 replicates for R, 4 replicates for B, 5 replicates for RB, and

6 replicates for W. For low Pn each point and standard error bars during the day time period

(0h to 15h) represents the hourly average of 10 replicates for R, 9 replicates for B, 11

replicates for RB, and 9 replicates for W. Each point and standard error bars during the night

period (15h to 23h) represents the hourly average of 5 replicates for R, 5 replicates for B, 5

replicates for RB, and 3 replicates for W. Each replicates represents and independent leaf.

Statistical analysis found in Appendix IV.

106

CO2 and H2O Gas Exchange

Light Treatments

High Photosynthetic Rate

Red-Blue White Red Blue

Day Time Stomatal Conductance (µmol CO2 m-2 s-1)

89.24(3.97)ab 78.37(2.41)bc 69.40(4.10)c 96.92(5.60)a

Night Time Stomatal Conductance (µmol CO2 m-2 s-1)

15.21(0.34)a 6.06(0.49)c 14.1(1.06)a 9.90(0.24)b

Day Time Transpiration Rate (mmol H2O m-2 s-1)

1.76(0.06)a 1.27(0.03)b 1.39(0.06)b 1.82(0.09)a

Night time Transpiration Rate (mmol H2O m-2 s-1)

0.15(0.002)a 0.022(0.003)c 0.16(0.01)c 0.10(0.001)b

WUE (µmol CO2/mmol H2O)

6.56(0.09)c 9.99(0.08)a 7.93(0.09)b 6.15(0.06)d

Day Time Ci (µmol mol-1)

251.62(2.14)b 218.43(2.36)c 223.75(2.72)c 261.99(2.06)a

Night Time Ci (µmol mol-1)

468.80(2.11)b 515.88(12.37)a 518.43(6.02)a 515.01(11.19)a

Low Photosynthetic Rate

Day Time Stomatal Conductance (µmol CO2 m-2 s-1)

59.92(2.48)ab 51.47(2.25)bc 46.99(2.23)c 61.82(3.60)a

Night Time Stomatal Conductance (µmol CO2 m-2 s-1)

9.58(0.52)a 5.94(0.43)c 9.83(0.75)a 9.33(0.74)a

Day Time Transpiration Rate (mmol H2O m-2 s-1)

0.93(0.03)b 0.85(0.03)b 0.81(0.03)b 1.31(0.08)a

Night time Transpiration Rate (mmol H2O m-2 s-1)

0.078(0.005)b 0.021(0.002)c 0.12(0.009)a 0.070(0.004)b

WUE (µmol CO2/mmol H2O)

7.95(0.18)b 9.14(0.20)a 8.75(0.11)a 5.42(0.08)c

Day Time Ci (µmol mol-1)

267.21(4.16)a 243.81(4.67)b 246.45(2.71)b 272.08(1.71)a

Night Time Ci (µmol mol-1)

488.51(8.69)a 493.20(11.12)a 467.89(8.47)a 511.59(26.29)a

107

Three hour feeds with 14C of tomato plants offers the first evidence showing proof that

export rates of sugars made in a source leaf can be altered not only by light intensity but also

short term exposure to wavelength specific lighting (Figure 4.7). As indicated in the caption

for Figure 4.7 a regression line was created for each type of light treatment. The number of

separate plant experiments providing each regression line varied between 28 and 35

separate leaves. In, so far as these regression lines show a pattern of the relationship

between Pn and E driven by each spectral quality. It is worth noting that regression lines

(E=yo+mx where E is the export rate (µmol m-2 s-1); yo is the E value at a 0 Pn rate; m is the

slope; x is the Pn rate) produced from the set of wavelength specific data are: ER=-

0.4812+0.4384x, EB=0.2558+0.3973x, ERW=0.1260+0.371x, ERB=-1.1593+0.4952x,

EW=0.4978+0.3270x, and EG=0.3961+0.2809x for R, B, RW, RB, W, and G light treatments

respectively. In summary, these regression lines need further statistical validation in longer

then 3h feeds, however, they allow for the sizing of experiments described in section 4.2.2.2.

Red-blue and R light treatments show the lowest levels of export in the lower

photosynthetic regions as indicated by the yo value of their regression line equations above

(Figure 4.7). At the high end of the photosynthetic range, G light produces the lowest rate of

export followed by the W light which is indicated by a having the lowest slope values in

regression lines (Figure 4.7). Red-blue, R, and B light treatments produce the highest export

rates at a high Pn which is also indicated by the slope value in their respective regression

lines being the highest indicated the largest increase of E for every increase in Pn (Figure

4.7).

108

Figure 4.7: 3 hour export values from tomato plants grown under white light conditions,

woken up in white like then transferred to wavelength specific LED lighting. Each point

represents the average export rate determined by the difference between Pn and CGM

throughout the isotopic period of the experiment and is representative of one leaf.

Regression lines are a function of 35, 34, 28, 30, 35, and 33 separate leaf data from R, B, RW,

RB, W, and G light treatments respectively.

109

NCER (µmol C m-2

s-1

)

0 5 10 15 20 25

Ex

po

rt (

µm

ol C

m-2

s-1

)

0

2

4

6

8

10

12

14

Red

Blue

Red-White

Red-Blue

White

Green

Red Regression

Blue Regression

Red-White Regression

Red-Blue Regression

White Regression

Green Regression

110

15h 14C feeds and 23h 14C feed/chase experiments allowed for the elucidation of whole

day leaf export rates. Like the whole plant experiments in chapter 2 and 3, there was a drop

in the Pn rates during both the high Pn experiments and the low Pn experiments (Figure

4.8A; Figure 4.9A). During the high Pn experiments the W light treatment produced the

highest Pn rates and the highest E rates amount light treatments (Figure 4.8A; Figure 4.8C).

However, when expressed as a ratio of E as a percentage of Pn, all light treatments produced

statistically the same values throughout the day and as daily averages (Figure 4.8E; Figure

4.8F; Table 4.2). Figure 4.10A and Figure 4.10C show the amount of 14C recovered in the

ethanol insoluble fraction, water soluble fraction, and chloroform fraction. The water soluble

fraction, which contains sugars such as sucrose, is the portion of 14C which was able to be

immediately mobilized and exported out of the leaf. In Figure 4.10A and Figure 4.10C, there

is no difference in the amount of 14C recovered between the light treatments which indicates

the exportable fractions were the same size within all the light treatments (Table 4.2). Figure

4.11 shows similar data showing the amount of total fixed C which was exported during the

day and night which again represents no difference between the treatments (Table 4.2).

During the low Pn experiments, again all the light treatments produced statistically the

same Pn rates. However, during the low light experiments, the RB treatment produced

higher export rates throughout the day as well as a higher daily average than other

treatments and produced a statistically high daily average export than the W and R light

treatments (Figure 4.9B; Figure 4.9C; Table 4.3). The B light treatment alone also produced

a high daily average export which was seen to be not significantly different than the RB, W,

or R treatments (Table 4.3). These difference in E holds true when normalized to E as a

percentage of Pn (Table 4.3). The higher E rate is also seen by a significantly higher 14C

111

recovered in the water soluble fraction from the RB light treatment than any other light

treatment (Figure 4.10B). The increased E rate of the B light treatment however does not

show a statistically higher 14C recovery in the soluble fraction (Figure 4.10B; Table 4.3). Day

time export is seen to be statistically higher in the low Pn RB treatment which again lends

more proof and validation to the increase in E from the RB light treatment (Figure 4.12A;

Figure 4.12C; Table 4.3).

These changes in export were only seen during the day time periods when leaves were

illuminated with their respective light treatments (Figure 4.8C; Figure 4.8D; Figure 4.9C;

Figure 4.9D; Figure 4.11; Figure 4.12; Table 4.2; Table 4.3). The increase in E rate from the

RB light and to a lesser extent the B light treatments during the low Pn, sub-saturating light

levels, of plants which were grown and woken up under a broad spectrum white light

indicate the first evidence that whole day carbon export/partitioning patterns can be alter

based on light quality. These results also indicate that plants which were effectively sister

plants with no anatomical or morphological differences due to the spectral quality can be

effected by a short term irradiance with different spectral qualities and thus indicating a

direct effect from the lights on export rates and partitioning ratios.

112

Figure 4.8: 15 hour and 23 hour (pooled) NCER (Panels A and B), E (Panels C and D), and %

E relative to Pn (Panels E and F) of plants grown and woken up under white light then

transferred to either RB (A, C, and E), W (A, C, and E), R (B, D, and F), or B (B, D, and F) lighting

with a Pn rate of approximately 12 µmol m-2 s-1 for the start of the 15h 14C feed period and

an 8h dark chase period. Each point and standard error bars during the day time period (0h

to 15h) represents the hourly average of 11 replicates for R, 7 replicates for B, 11 replicates

for RB, and 11 replicates for W. Each point and standard error bars during the night period

(15h to 23h) represents the hourly average of 6 replicates for R, 4 replicates for B, 5

replicates for RB, and 6 replicates for W. Each replicates represents and independent leaf.

113

Red

Blue

Ph

oto

syn

thesis

(µ

mo

l C

O2 m

-2 s

-1)

-2

0

2

4

6

8

10

12

14

16

Red-Blue

White

Exp

ort

(µ

mo

l C

O2 m

- 2 m

-2 s

-1)

0

2

4

6

8

10

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

% E

xp

ort

rela

tive t

o P

ho

tosyn

thets

is

0.2

0.4

0.6

0.8

1.0

A B

C D

E F

114

Figure 4.9: 15 hour and 24 hour (pooled) Pn (Panels A and B), E (Panels C and D), and % E

relative to Pn (Panels E and F) of plants grown and woken up under white light then

transferred to either RB (A, C, and E), W (A, C, and E), R (B, D, and F), or B (B, D, and F) lighting

with a Pn rate of approximately 6 µmol m-2 s-1 for the start of the 15h 14C feed period and an

8h dark chase period. Each point and standard error bars during the day time period (0h to

15h) represents the hourly average of 10 replicates for R, 9 replicates for B, 11 replicates for

RB, and 9 replicates for W. Each point and standard error bars during the night period (15h

to 23h) represents the hourly average of 5 replicates for R, 5 replicates for B, 5 replicates for

RB, and 3 replicates for W. Each replicates represents and independent leaf.

115

Red

Blue

Ph

oto

syn

the

sis

(µ

mo

l C

O2 m

-2 s

-1)

-2

0

2

4

6

8

10

Red-Blue

White

Ex

po

rt (

µm

ol

CO

2 m

- 2 m

-2 s

-1)

0

2

4

6

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

Time (h)

06:00:00 10:00:00 14:00:00 18:00:00 22:00:00 02:00:00 06:00:00

% E

xp

ort

re

lati

ve

to

Ph

oto

syn

the

tsis

0.0

0.2

0.4

0.6

0.8

1.0

A B

C D

E F

116

Figure 4.10: 15 hour (A and B) 23 hour (C and D) 14C fraction recovery from plants grown

and woken up under white light then transferred to either RB, W, R, or B lighting with a Pn

rate of approximately 12 µmol m-2 s-1 (A and C) and 6 µmol m-2 s-1 (B and D) for the end of

the 15h 14C feed period and 23h feed/chase period. Column and standard error bars

represents the averages of 11 replicates for R, 7 replicates for B, 11 replicates for RB, and 11

replicates for W (A). Column and standard error bars represents the averages of 10

replicates for R, 9 replicates for B, 11 replicates for RB, and 9 replicates for W (B). Column

and standard error bars represents the averages of 6 replicates for R, 4 replicates for B, 5

replicates for RB, and 6 replicates for W (C). Column and standard error bars represents the

averages of 5 replicates for R, 5 replicates for B, 5 replicates for RB, and 3 replicates for W

(D). Each replicates represents and independent leaf. Each replicates represents and

independent leaf.

% 1

4C

Fra

cti

on

Re

co

ve

ry

0

20

40

60

80

Light Treatments

Red Blue Red-Blue White

% 1

4C

Fra

cti

on

Re

co

ve

ry

0

20

40

60

80

Ethanol Insoluble Fraction

Water Soluble Fraction

Chloroform Fraction

Light Treatments

Red Blue Red-Blue White

A

C

B

D

Figure 4.11: 15 hour and 24 hour (pooled) of 14C fate of plants grown and woken up under

white light then transferred to either RB (A and C), W (A and C), R (B and D), or B (B and D)

lighting with a Pn rate of approximately 12 µmol m-2 s-1 for the start of the 15h 14C feed period

and an 8h dark chase period. Panels C and D represent the % 14C of the total fixed 14C devoted

to each fraction. Column and standard error bars represents the averages of 17 replicates for

the total 14C fixed, 11 for day export and remaining 14C at the end 15h, 6 for night export,

respiration, and remaining 14C at the end of 23h for R, 11 replicates for the total 14C fixed and

7 for day export and remaining 14C at the end 15h, 4 for night export, respiration, and

remaining 14C at the end of 23h for B, 16 replicates for the total 14C fixed and 11 for day

export and remaining 14C at the end 15h, 5 for night export, respiration, and remaining 14C

at the end of 23h for RB, and 17 replicates for the total 14C fixed and 11 for day export and

remaining 14C at the end 15h, 5 for night export, respiration, and remaining 14C at the end of

23h for W. Each replicates represents and independent leaf.

Total fixed

Day export

Remaining after 15h

Night export

Respiration

Remaining after 23h

14C

assim

ilate

d (

mm

ol

C m

-2)

0

200

400

600

800

Red BlueRed-blue White

% 1

4C

of

To

tal

14C

Fix

ed

0

20

40

60

80

A

C

B

D

Figure 4.12: 15 hour and 24 hour (pooled) of 14C fate of plants grown and woken up under

white light then transferred to either RB (A and C), W (A and C), R (B and D), or B (B and D)

lighting with a Pn rate of approximately 6 µmol m-2 s-1 for the start of the 15h 14C feed period

and an 8h dark chase period. Panels C and D is the % 14C of the total fixed 14C devoted to each

fraction. Column and standard error bars represents the averages of 15 replicates for the

total 14C fixed, 10 for day export and remaining 14C at the end 15h, 5 for night export,

respiration, and remaining 14C at the end of 23h for R, 14 replicates for the total 14C fixed and

9 for day export and remaining 14C at the end 15h, 5 for night export, respiration, and

remaining 14C at the end of 23h for B, 16 replicates for the total 14C fixed and 11 for day

export and remaining 14C at the end 15h, 5 for night export, respiration, and remaining 14C

at the end of 23h for RB, and 12 replicates for the total 14C fixed and 9 for day export and

remaining 14C at the end 15h, 3 for night export, respiration, and remaining 14C at the end of

23h for W. Each replicates represents and independent leaf.

Total fixed

Day export

Remaining after 15h

Night export

Respiration

Remaining after 23h

14C

assim

ilate

d (

mm

ol

C m

-2)

0

100

200

300

400

500

Red BlueRed-blue White

% 1

4C

of

To

tal

14C

Fix

ed

0

20

40

60

80

A

C

B

D

Table 4.2: 15 hour and 23 hour (pooled) Pn, E, 14C partitioning, and 14C fate measurements

of plants grown and woken up under white light then transferred to either RB, W, R, or B

lighting with a high Pn rate of approximately 12 µmol m-2 s-1 for the start of the 15h 14C feed

period and an 8h dark chase period. For high Pn, Each point and standard error bars during

the day time period (07:00:00 to 22:00:00) represents the hourly average of 11 replicates

for R, 7 replicates for B, 11 replicates for RB, and 11 replicates for W. Each point and standard

error bars during the night period (22:00:00 to 06:00:00) represents the hourly average of

6 replicates for R, 4 replicates for B, 5 replicates for RB, and 6 replicates for W. Statistical

analysis found in Appendix IV.

Light Treatments Red-Blue White Red Blue

Gas Exchange Photosynthesis (µmol C m-2 s-1)

11.36(0.41)ab 12.51(0.21)a 10.82(0.49)b 10.80(0.54)b

Respiration (µmol C m-2 s-1)

-0.57(0.004)a -0.57(0.01)a -0.85(0.02)b -0.62(0.01)a

Export Day Export (µmol C m-2 s-1)

7.45(0.21)a 8.37(0.38)a 7.28(0.25)a 7.34(0.35)a

Night Export (µmol C m-2 s-1)

1.29(0.08)a 1.37(0.26)a 1.13(0.21)a 0.77(0.04)a

% Export of Photosynthesis

0.67(0.03)a 0.67(0.03)a 0.69(0.03)a 0.71(0.04)a

14C Partitioning (% 14C)

Ethanol Insoluble (15h)

55.90(3.85)a 65.31(2.36)a 55.13(6.05)a 48.85(7.64)a

Water Soluble (15h)

37.90(3.36)a 30.72(2.22)a 37.74(4.47)a 42.80(7.09)a

Chloroform (15h) 5.96(0.66)ab 3.97(0.44)b 7.12(1.73)ab 8.35(0.67)a

Insoluble (23h) 64.76(3.08)a 58.84(6.40)a 57.67(3.71)a 63.84(3.28)a

Soluble (23h) 25.37(3.50)a 34.48(3.63)a 33.33(3.16)a 28.17(2.39)a

Chloroform (23h) 9.87(0.42)a 6.68(2.77)a 9.01(0.66)a 7.99(0.89)a

14C Fate (mmol C m-2)

Total Fixed 607.50(28.48)a 602.82(29.17)a 589.08(19.70)a 589.60(42.93)a

Day Export 400.72(24.59)a 447.35(25.32)a 409.82(19.52)a 399.38(31.67)a

Remaining at the end of 15h

203.48(17.30)a 225.47(21.28)a 179.27(11.76)a 190.22(23.64)a

Night Export 51.25(8.02)a 61.81(10.38)a 49.17(4.47)a 26.52(9.82)a

Respiration 2.57(0.35)a 4.79(0.85)a 4.53(0.94)a 3.40(1.17)a

Remaining at the end of 23h

166.39(10.86)a 130.31(21.33)a 137.03(6.00)a 119.43(24.07)a

% 14C of Total Fixed

Day Export 65.89(2.24)a 66.60(2.76)a 69.42(1.98)a 67.91(3.40)a

Remaining at the end of 15h

34.11(2.24)a 33.40(2.76)a 30.58(1.98)a 32.09(3.40)a

Night Export 8.39(1.03)a 9.68(1.49)a 8.82(0.76)a 4.86(1.66)a

Respiration 0.44(0.08)a 0.78(0.17)a 0.84(0.19)a 0.66(0.25)a

Remaining at the end of 23h

26.58(0.92)a 20.25(2.92)a 24.69(1.19)a 22.21(3.64)a

Table 4.3: 15 hour and 23 hour (pooled) Pn, E, 14C partitioning, and 14C fate measurements

of plants grown and woken up under white light then transferred to either RB, W, R, or B

lighting with a low Pn rate of approximately 6 µmol m-2 s-1 for the start of the 15h 14C feed

period and an 8h dark chase period. For high Pn, Each point and standard error bars during

the day time period (0h to 15h) represents the hourly average of 10 replicates for R, 9

replicates for B, 11 replicates for RB, and 9 replicates for W. Each point and standard error

bars during the night period (15h to 23h) represents the hourly average of 5 replicates for

R, 5 replicates for B, 5 replicates for RB, and 3 replicates for W. Each replicates represents

and independent leaf. Statistical analysis found in Appendix IV.

125

Light Treatments Red-Blue White Red Blue

Gas Exchange Photosynthesis (µmol C m-2 s-1)

7.16(0.09)a 7.25(0.09)a 6.97(0.19)a 6.90(0.32)a

Respiration (µmol C m-2 s-1)

-0.46(0.005)c -0.44(0.005)bc -0.38(0.01)a -0.42(0.01)b

Day Export (µmol C m-2 s-1)

5.43(0.12)a 4.61(0.24)b 4.61(0.10)b 4.90(0.13)ab

Night Export (µmol C m-2 s-1)

0.46(0.11)a 0.89(0.20)a 0.91(0.15)a 0.74(0.18)a

% Export of Photosynthesis

0.76(0.02)a 0.63(0.03)b 0.64(0.02)b 0.71(0.02)ab

14C Partitioning (% 14C)

Ethanol Insoluble (15h)

46.53(3.02)b 62.36(2.59)a 63.14(2.04)a 62.58(3.80)a

Water Soluble (15h)

46.57(2.22)a 30.98(2.26)b 32.25(2.27)b 31.12(3.03)b

Chloroform (15h) 6.90(0.82)a 6.66(0.61)a 4.62(0.84)a 6.31(0.80)a

Insoluble (23h) 51.03(8.59)a 51.40(4.42)a 51.22(2.23)a 49.84(2.12)a

Soluble (23h) 40.78(6.18)a 40.57(2.50)a 41.18(3.76)a 41.21(2.26)a

Chloroform (23h) 8.19(2.56)a 8.03(1.92)a 4.60(1.53)a 8.95(0.28)a

14C Fate (mmol C m-2)

Total Fixed 388.42(12.66)a 391.38(27.08)a 371.43(26.14)a 364.42(34.78)a

Day Export 292.57(11.25)a 231.99(27.27)a 240.94(20.29)a 262.24(23.99)a

Remaining at the end of 15h

95.84(9.04)b 159.38(17.51)a 130.49(13.88)ab 102.17(13.33)b

Night Export 22.48(3.09)a 50.09(17.72)a 33.70(10.48)a 40.50(13.36)a

Respiration 4.15(0.68)a 3.98(1.40)a 5.21(1.14)a 4.29(0.95)a

Remaining at the end of 23h

50.53(6.65)a 69.41(14.86)a 89.98(13.48)a 74.07(31.30)a

% 14C of Total Fixed

Day Export 75.40(2.00)a 58.67(4.45)b 64.67(2.74)ab 72.31(2.15)a

Remaining at the end of 15h

24.60(2.00)b 41.33(4.45)a 35.33(2.74)ab 27.69(2.15)b

Night Export 5.89(0.89)a 16.11(4.87)a 8.75(2.27)a 9.49(2.90)a

Respiration 1.11(0.24)a 1.25(0.40)a 1.49(0.26)a 1.36(0.52)a

Remaining at the end of 23h

13.05(1.54)a 23.27(6.03)a 26.00(3.34)a 27.11(6.67)a

126

4.4 Discussion

4.4.1 Effects of Wavelength Specific Lighting on H2O Gas Exchange

Stomatal conductance, transpiration rates, WUE, and Ci results all show similar results

to those seen in chapters 2 and 3. The increases in stomatal conductance, transpiration rates,

and Ci were seen in treatments which have a high amount of B and R light which are again

due to the influx of K+ ions into the guard cells around the stomata (Lurie, 1978; Kinoshita

and Shimazaki, 1999). The G light provided by the W light treatment acts as an antagonist to

the B and RB light effects and counteracts the stomatal opening leading to the lower stomatal

conductance, transpiration rates, and Ci as well as the higher WUE (Figure4.3; Figure 4.4;

Figure 4.5; Figure 4.6; Table 4.1) (Frechilla et al., 2000; Kim et al., 2004b; Hogewoning et al.,

2010). These effects were generated by an accumulation of zeaxanthin in the stomatal guard

cells which stops the influx in K+ ions (Frechilla et al., 2000). These light dependent results

were seen to be ubiquitous among all experiments presented in the thesis and thus indicate

plants were acting similarly, independent of the systems being used during experimentation

as.

4.4.2 Effects of Wavelength Specific Lighting on Export During 3h

Illumination

Three hour feeds of tomato leaves with 14C under various wavelengths specific LED

lighting provided the first evidence of a difference in export rates based on light intensity

and more importantly spectral quality (Figure 4.7). However, at a low light intensity or a low

Pn it was unclear if the pools within the source leaf have reached isotopic, steady state

127

equilibrium which is a perquisite for making accurate E measurements (Figure 4.7). At a low

Pn rate, the existing pools of unlabelled compounds may be getting exported while the 14C

labelling was still taking place and thus E from the leaf will be underestimated (Geiger and

Fonday, 1979). These results were also shown in previous experiments by Geiger and Fondy,

(1979). At a higher light intensity enacting a higher Pn, the pools may be able to be labelled

and begin to E at isotopic equilibrium before the end of the experiment allowing for accurate

determination of E (Figure 4.7) (Geiger and Fondy, 1979).

When looking at results from 15h/23h feed chase experiments, at the high Pn level, all

light treatments are producing identical E rates which was generally what was seen in Figure

4.7 which leads more confidence to accurate E measurements during high Pn and high light

intensity during the shorter 3h feeds (Figure 4.8). Alternatively, the results seen in Figure

4.9 do not match up with those in Figure 4.7 which further defends the idea of not being at

isotopic equilibrium during the low Pn and light intensity 3h feed experiments (Geiger and

Fondy, 1976). Also of note, during the beginning hours (06:00:00 to approximately

11:00:00) of the 15h/23h experiments there was a rapid increase in E rates which does not

change in parallel with the Pn rate (Figure 4.8C; Figure 4.9C). After this initial period, E rates

fluctuate with respect to the Pn rates until the later part of the day. These results again

indicate a lack of isotopic equilibrium in during the beginning of the experiments providing

less confidence in the 3h results, especially during the low light conditions.

128

4.4.3 Effects of Wavelength Specific Lighting on 14C Export and

Partitioning During 15h Illumination and Subsequent 8h Dark Period

15h feed and 8h chase periods allow for a better ‘real world’ observation of what

happens to E throughout the day of a strong source leaf from a tomato plant (Figure 4.8;

Figure 4.9). During the high Pn and consequently a relatively saturating light level, no

difference in export nor 14C partitioning was determined (Figure 4.8; Figure 4.10A). This

result indicates that at a saturating or near saturating light level, all systems, such as C

fixation and C partitioning, as well as components of export, such as sucrose phosphate

synthase (SPS), phloem loading mechanism, and facilitator enzyme like SWEET and SUC are

working at the same rate independent of the quality of light which the leaf was illuminated

with.

However, during the low Pn experiments in which the plants were provided with sub-

saturating light levels, E was determined to be different between light treatments (Figure

4.9; Table 4.3). The RB light treatment show significant increases in E rates when compared

to R and W light treatments, while the sole B light treatment showed no significant difference

from any light treatment on a daily average E rate (Figure 4.9; Table 4.3).

Extractions from the leaves from the 15h 14C feed under a low Pn inducing RB light

showed significantly larger recovery of 14C in the soluble fraction than any other light

treatment (Table 4.3). Sucrose phosphate synthase (SPS) and sucrose synthase (SuSy) are

the two major sucrose producing enzyme within plants, however due to downstream

movement of sucrose-6-phosphate, it is generally accepted that SPS is the major component

of sucrose biosynthesis while SuSy is plays a large role in sucrose degradation (Stitt et al.,

129

1987). The production of sucrose from SPS happens when SPS is in the active state which is

regulated by the phosphorylation and dephosphorylation of the enzyme by SPS-kinase and

SPS-protein phosphatase (SPS-PP) respectively (Huber & Huber, 1990a; Huber & Huber,

1990b). SPS is active and making sucrose when it is in the dephosphorylated phase and the

dephosphorylation reaction is facilitated by SPS-PP (Huber & Huber, 1990a). SPS-PP is

known to be activated by light and thus dephosphorylating SPS allowing for sucrose to be

produced during high light periods (Weiner et al., 1992). Currently, there is no literature on

the effects spectral quality has on the activation of SPS-PP and its ability to dephosphorylate

SPS. However, results in Figure 4.10B and Table 4.3 show an increased 14C recovery in the

water soluble fraction which, due to tomatoes being apoplastic loaders, it was thought to be

sucrose. Thus, it was plausible that the RB light treatment at a sub-saturating light level and

low Pn level was able to increase the activation of SPS-PP and thus the activation of SPS to

cause more sucrose (Huber & Huber, 1990a; Weiner et al., 1992). It was also possible that

the RB light treatment decreases the activation of SPS-kinase and thus decreasing the rate of

phosphorylation of SPS enacting the same results (Huber & Huber, 1990a; Huber & Huber,

1990b).

Interestingly, Jones & Ort (1997) determined that SPS activity in tomato leaves followed

a circadian pattern which decrease during the early night hours. This decrease in SPS activity

during these early night hours could explain why leaves that were sampled at 23h (After the

8h dark period) under all conditions showed similar insoluble and soluble recovery of 14C

and no difference was seen in night time export during high or low Pn experiments (Figure

4.10A; Figure 4.10B; Table 4.2; Table 4.3) (Weiner et al., 1992).

130

As stated in chapter 2, TPT catalyzes the transfer of TP from the chloroplast to the

cytosol where this event takes place (Walters et al., 2004). TPT functions as an anti-port

enzyme which works in a 1:1 stoichiometry exporting TP and importing inorganic phosphate

(Pi) from the cytosol for ATP production within the chloroplast. As stated before, the

increased export of TP (Chloroplast leakiness) may not be a good thing when trying to prime

dark adapted leaves but would consequently allow for a higher export rate due to an increase

of TP available for sucrose synthesis via SPS (Walters et al., 2004). Thus it is not

unreasonable to predict that the slow priming seen in dark adapted leaf when exposed to B

light may be also supporting the higher E rate from treatments containing B light.

However, an increase in TPT or SPS activity may not be the sole explanation for the

increase in E seen in the RB and B light treatments. Since tomatoes are apoplastic loaders,

they must use facilitator proteins in order to transport the sucrose from the MC to the

phloem during phloem loading (Zimmermann & Ziegler, 1975; Gamalei, 1989; Sauer & Stolz,

1994; Nadwondnik & Lohaus, 2008). The main facilitator proteins involved in this pathway

are SUC and SWEET enzymes (Sauer et al., 2004; Hackel et al., 2006; Sauer, 2007; Feng et al.,

2015). Although there is no current literature tying these enzymes with a kinetic rate change

due to illumination with different spectral qualities of light, it must not be ruled out as a

cause for an increased E rate.

Like the phosphorylation and dephosphorylation events which control SPS via a light

effect on another protein, SPS-PP or SPS-kinase, there may be other proteins or co-factors

with can cause such an event in either SUC, SWEET or both leading to a higher E rate (Huber

& Huber, 1990a; Huber & Huber, 1990b). An increase in enzymatic rate or a conformational

131

change causing changes in the enzyme itself could cause a higher affinity for sucrose

increasing the rate of transfer from MC to the phloem instead of storage which is seen under

the RB and B light treatments (Table 4.3).

Blue light, present in both lighting treatments which caused a higher rate of export is

also readily absorbed by CRY (Somers et al., 1998; Liu et al., 2011c). CRY plays an important

role in plant circadian clocks and photoperiod effects and can alter things such as flowering

time and gene expression (Somers et al., 1998; Liu et al., 2011c). Due to Rayleigh scattering,

it is known that during the afternoon hours of the day, the B light component is at its

strongest which is coincidentally when the light level is the highest (Bates, 1984). Thus, CRY

is absorbing most of its light during the afternoon, or high light hours. When placing leaves

under B or RB treatments for experimentation, there was possibly an activation of CRY which

could be translating to the plant causing it to think it was under high light conditions (Bate,

1984; Somers et al.¸1998; Liu et al., 2011c). From previous studies and results in this section,

E rate was increased with light intensity (Jiao & Grodzinski, 1996; Leonardos et al., 1996).

Under the low Pn, RB and B light treatments, the absorption of high amounts of B light via

CRY may trick the plant to thinking it was under a high light condition and trigger the higher

E rate which was seen (Figure 4.9C and E; Table 4.3). At the high Pn, that increase in E due

to CRY absorption of B light could have been nullified because all systems are already

saturated with light leading to already maximal E rates.

Although there is currently little research done of the effects of wavelength specific LED

lighting on the E rates and the components which make up the E pathway in a whole, results

show an increase in E rates from the RB light treatment during sub-saturating light

132

conditions (Figure 4.9C; Table 4.3). The modes of action described above provide possible

explanation for the increase in E seen in both RB and B light treatments. However, further

experimentation is needed in order to provide concrete evidence to confirm these

explanations.

In summary, this chapter provides the first evidence that carbon export can be altered

solely by spectral quality. At a higher, near saturating light intensity, spectral quality did not

alter carbon E or partitioning ratios within a source leaf. However, under a sub-saturating

light level, RB increased E rates when compared to R and W light treatments while B light

provided statistically the same E rate as RB, R, and W light treatments. Because the plants

used in this experiment were sister plants, the increase in E due to the RB light treatment

can be said to be direct effects of the spectral quality.

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Chapter 5

Thesis Summary

The main objective of this thesis was to examine the effects wavelength specific LED and

HPS lighting on tomato growth as it pertains to greenhouse production. Previous studies

have established an increase in the stomatal opening as well as transpiration rate when

plants were exposed to B and R lighting (Kana and Miller, 1977; Liu et al., 2011b; Liu et al.,

2012). Both B and R lights have been shown to increase K+ ion influx into the guard cells

surrounding the stomata leading to an increase in osmotic pressure and stomatal opening

bringing about a higher stomatal conductance and transpiration rate (Lurie, 1978; Kinoshita

and Shimazaki, 1999; Liu et al., 2012). All plants which were used in these studies were

grown under wavelength specific lighting which caused anatomical and morphological

differences within the plants as a results (Kana and Miller, 1977; Lurie, 1978; Kinoshita and

Shimazaki, 1999; Liu et al., 2011b; Liu et al., 2012).

Results in chapters 2, 3, and 4 indicate similar results to previous literature when done

using whole plant and leaf experimentation when done with plants grown under wavelength

specific light and W light when exposed to specific wavelengths in short term. In chapter 2,

plants were grown in a greenhouse during the winter months with supplemental lighting

provided by either HPS, RB LED, or RW LED (100±25 µmol m-2 s-1) or an ambient control.

Plants were then transferred to a custom whole plant chamber and analyzed under either

HPS, RB LED, or RW LED (500±10 µmol m-2 s-1). During these experiments, both plants which

were grown under RB or RW supplemental light and those which were grown under the

ambient conditions but placed under the RW or RB LED lights translated to a higher

134

transpiration rate. These results can be attributed to a difference in anatomical and

morphological differences for plants which were grown under supplemental lighting as well

as response to short term illumination with wavelength specific lighting (Liu et al., 2011b).

However, plants which were grown under the ambient conditions would have been

effectively the same before the start of the whole plant experimentation thus those

differences were direct effects from the lights. These results which were seen in the whole

plant system were mimicked, although to a lesser extent, in leaf studies which were done

under a standard RB LED light source from Li-COR with greenhouse grown plants.

In chapters 3 and 4, plants were all grown under a broad spectrum W light and thus

were effectively sister plants during experimentation. In both whole plant studies in chapter

3 and leaf studies in both chapter 3 and 4, similar results were obtained as in chapter 2 and

previous literature (Kana and Miller, 1977; Lurie, 1978; Kinoshita and Shimazaki, 1999; Liu

et al., 2011b; Liu et al., 2012). Thus, like plants in the greenhouse experiments which were

grown under the ambient control conditions, it can be concluded that results seen in an

increase in transpiration rate, stomatal conductance and Ci as well as a decrease in WUE from

plants analyzed under R light, B light or a combination of both are direct effects from the

lights.

During whole plant experiments, an HPS light was used to compare to the RB and RW

LED lights, however, during leaf experimentation a W LED light was used for technical

reasons. Although both lights contain R and B light in them, the presence of a high amount of

G light is able to diminish the effects of R and B light (Frechilla et al., 2000; Kim et al., 2004b;

Hogewoning et al., 2010). Previous literature has determined that this phenomenon was due

135

to an increase in zeaxanthin within the guard cells of the stomata which does not allow for a

large influx of K+ and thus negating the stomatal opening effect and causing a lower

transpiration rate and higher WUE then RW and RB LEDs (Frechilla et al., 2000).

Whole plant gas exchange analysis was needed to understand how the plant as a whole

were effected by various conditions including light as it has been determined that leaves are

not the only major tissue to contribute to NCER (Steer & Pearson, 1976; Chauhan & Pandey,

1984; Hetherington et al., 1998; Leonardos et al., 2014). Mutual shading also reduces the

light getting through the canopy thus effecting the photosynthetic rates of leaves lower in

the canopy. Whole plant gas exchange analysis measured the effect on NCER and well as the

aforementioned transpiration rate and WUE under HPS, RB LED, and RW LED under

different light intensities. Plants in chapter 2 which were grown under supplemental lighting

or ambient control produced subtle differences between the average day time NCER rates

with plants grown under ambient control conditions producing higher rates than those

grown under supplemental light when analyzed under the same lighting on a dry weight

basis. These subtle differences did not translate into a higher daily carbon gain measured by

the whole plant system. Differences in NCER between ambient grown plants and plants

grown under supplemental lighting can be attributed to a higher degree of mutual shading

in the bigger plants coming from the supplemental light treatments. Whole plant gas

exchange experiments preformed in chapter 3 with plants grown under a broad spectrum

white light showed similar results with no significant difference between light treatments.

However, subtle differences were seen during leaf experiments in both chapters. These

results indicated that a combination RB light treatment produced the highest photosynthetic

136

rate during leaf experiments which has also been recorded in a number of previous studies,

but were not detectable during whole plant analysis (Goins et al., 1998; Yorio et al., 1998;

Liu et al., 2012). It was likely that due to mutual shading within the plant canopy, these

results from the leaf experiment were nullified. However, as results indicate in chapter 2,

plants which are grown under supplemental RB light were seen to have the highest biomass

which confirms results from previous studies (Goins et al., 1998; Yorio et al., 1998; Takemiya

et al., 2005; Liu et al., 2010; Liu et al., 2012). Results indicate that although no differences in

gas exchange were seen, plants grown under RB lighting during the winter months caused

the highest biomass (Goins et al., 1998; Yorio et al., 1998; Takemiya et al., 2005; Liu et al.,

2010; Liu et al., 2012).

An interesting result, which was also seen in Chrysanthemums but not previously

recorded in literature was the increased time it took for leaves which have been dark

adapted to reach maximum photosynthesis when solely illuminated with B light. Plants in

chapter 3 were grown under a broad spectrum W light, therefore results are again deemed

to be a direct effect of the light itself. Although not previously recorded, these results could

stem from chloroplast leaking due to the B light. If too much TP was exported out of the

chloroplast too quickly, the chloroplast would not be able to accumulate the intermediates

needed for the Calvin cycle to preform properly (Walters et al., 2004). This decrease in

accumulation in Calvin cycle intermediates can result in a decreased Pn rate. Thus, if B light

causes chloroplast leaking via too much TP being exported, the rate of Pn increase to a

maximum rate would be slowed leading to the results seen in chapter 3. These result may

also be an evolutionary adaption from the low B light conditions during the morning via

Rayleigh scattering which causes less B light to reach the plants (Bates, 1984). Thus plants

137

may have better adapted to wake up to a higher amount of R light or a more broad spectrum

light which are indicated by results in chapter 3.

Export of sugar is a major factor in plant growth. Previous research on E was limited to

the effects of light intensity and temperature (Leonardos et al., 1996; Leonardos et al., 2003).

Currently, no previous research has been done to try and elucidate the effects of wavelength

specific lighting on export. Evidence from the 3h feed experiments allowed for the first

indication that wavelength specific LED lighting was able to alter E rates. However, during

later experimentation it was determined that isotopic equilibrium of the sugar pools may

have not been achieved. Thus, only the 15h/23h feed chase experiments provide reliable

results.

During high Pn experiments, no difference in E or carbon partitioning ratios was

determined. However, during the low Pn experiments, RB light treatment induced a higher

E rate from illuminated source leaves than did R and W light treatments and there was no

statistical difference when comparing RB light with the B light. Under low Pn RB illumination,

after the 13h feed period, a higher 14C recovery was achieved for the soluble sugar fraction

than any other light treatment. These results could be due to an increase activity in SPS or

an increase activity in TPT exporting TP out of the chloroplast into the cytosol for sucrose

synthesis (Huber & Huber, 1990a; Weiner et al., 1992). SPS itself is not regulated by light but

is instead regulated by phosphorylation or more specifically, activated by dephosphorylation

which happens via SPS-PP which is activated by light, however it is currently unknown if a

particular wavelength does so more efficiently (Huber & Huber, 1990a; Weiner et al., 1992).

Thus the increase in dephosphorylation of SPS via the excitation of SPS-PP when exposed to

138

RB light in any amount could be causing the increase in E due to the higher sucrose

production.

However, the B light treatment does not show an increase in 14C recovery of the water

soluble sugar fraction when compared to the R or W light treatments but still causes a

statistically equivalent E rate at the same Pn level as the RB light treatment. Therefore, there

must be another mode of action which is driving E. Tomatoes, being apoplastic loaders, must

use facilitator proteins like SWEET and SUC to move sucrose from the MC to the phloem for

transport to the rest of the plant (Sauer et al., 2004; Hackel et al., 2006; Sauer, 2007; Feng et

al., 2015). Although there is currently no literature stating a light response of these

transporters which could increase E, based on the effect light has on SPS via SPS-PP

dephosphorylation, the possibility of a similar mechanism effecting SWEET or SUC enzymes

which must not be ignored.

Cryptochrome is a B light absorbing molecule which is known to influence many plant

related functions such as flowering and circadian rhythm (Somers et al., 1998; Liu et al.,

2011c). Due to the Rayleigh scattering effect of lighting, it is known that more B light is

available at the ground level during the later parts of the day (Bates, 1984). Thus it plausible

to conclude that under B or RB light illumination, plants are tricked into thinking they are

under a high light environment. This may be a signal that energy needed for some processes

like export was abundant which causing the plants to export at a faster rate.

In chapter 1, my hypothesis was that photosynthesis and export can be altered solely

due to spectral quality and light intensity of the light treatment. Based on the result provided

in this thesis, my hypothesis would be accepted. Although whole plant experiments saw very

139

little or no effect on whole plant NCER, leaf studies provided subtle differences between light

treatments on plants which were grown under a broad spectrum W light and did not have

any morphological or anatomical differences due to the light, like previous literature,

establishing light direct effect on plant growth and metabolism (Figure 3.6) (Goins et al.,

1998; Yorio et al., 1998; Liu et al., 2012). Interestingly, transpiration rate, stomatal

conductance, and Ci were all increased under the R, B, RB, and RW light treatments and WUE

was decreased when compared to a W light control which mirrors the results in current

literature (Kana and Miller, 1977; Lurie, 1978; Kinoshita and Shimazaki, 1999; Liu et al.,

2011b; Liu et al., 2012). Again, plants were grown under broad spectrum W light and results

can be deemed to be a result of solely spectral quality.

Novel results showing an increase in E rates under RB and B light treatments when

compared to W and R light treatments also indicates a difference in growth due to

wavelength specific LED lighting (Table 4.3). Further research is needed to elucidate the

underlying causes of the E increases seen in RB and B light treatments. Results displayed in

this thesis will help increase the understanding of spectral plant needs during growth and

help implement a spectrum optimized lighting treatments in greenhouse tomato production

via both conventional and intracanopy lighting.

140

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APPENDIX I

Chapter 2 Supplemental Tables

Table 2.1: Effects Supplemental lighting on the leaf NCER (µmol m-2 s-1) values of greenhouse grown tomato plants in Guelph, ON, Canada during the winter months. Plants were subject to 100±25 µmol m-2 s-1 of either red-blue, HPS, or red-white supplemental light or a no light control and analyzed with a Li-COR standard red-blue LED light. Each value represents 6 replicates each replicate was done on a different leaf. The values in parentheses represents the standard error (±) for each mean and letter values (a) indicates statistical differences (α=0.05) between light treatments within a light level via a means comparison and a Tukey-Kramer adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Ambient Red-Blue HPS Red-White

1500 12.33(0.91)a 15.53(0.72)a 14.5(0.90)a 15.17(1.13)a

1000 12.14(0.66)a 14.98(0.67)a 13.92(1.02)a 15.13(0.83)a

750 11.28(0.44 a 14.02(0.45)a 13.13(1.12)a 14.03(0.75)a

500 10.39(0.62)a 12.63(0.32)a 11.93(1.05)a 12.63(0.70)a

250 8.44(0.62)a 9.78(0.21)a 9.56(0.62)a 10.09(0.42)a

125 6.65(0.30)a 6.86(0.31)a 6.82(0.27)a 7.13(0.20)a

100 5.18(0.11)a 5.16(0.15)a 5.50(0.15)a 5.46(0.14)a

75 4.01(0.17)a 3.94(0.16)a 4.15(0.17)a 4.25(0.17)a

50 2.56(0.13)a 2.53(0.20)a 2.63(0.08)a 2.43(0.23)a

25 0.72(0.10)a 0.67(0.16)a 0.75(0.13)a 0.69(0.17)a

10 -0.26(0.16)a -0.36(0.12)a -0.23(0.09)a -0.31(0.12)a

0 -1.19(0.13)a -1.22(0.13)a -1.15(0.12)a -1.05(0.12)a

Table 2.2: Effects Supplemental lighting on the leaf stomatal conductance (mmol H2O m-2 s-

1) values of greenhouse grown tomato plants in Guelph, ON, Canada during the winter months. Plants were subject to 100±25 µmol m-2 s-1 of either red-blue, HPS, or red-white supplemental light or a no light control and analyzed with a Li-COR standard red-blue LED light. Each value represents 6 replicates each replicate was done on a different leaf. The values in parentheses represents the standard error (±) for each mean and letter values (a, b) indicates statistical differences (α=0.05) between light treatments within a light level via a means comparison and a Tukey-Kramer adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Ambient Red-Blue HPS Red-White

1500 0.25(0.06)a 0.39(0.06)a 0.30(0.06)a 0.32(0.07)a

1000 0.20(0.04)a 0.29(0.04)a 0.29(0.03)a 0.31(0.04)a

750 0.16(0.01)a 0.22(0.02)a 0.17(0.03)a 0.23(0.02)a

500 0.12(0.009)b 0.19(0.02)ab 0.15(0.02)ab 0.20(0.02)a

250 0.11(0.006)a 0.16(0.01)a 0.17(0.03)a 0.17(0.02)a

125 0.094(0.009)a 0.31(0.03)a 0.11(0.02)a 0.15(0.02)a

100 0.092(0.01)a 0.14(0.02)a 0.11(0.02)a 0.15(0.02)a

75 0.082(0.009)a 0.16(0.02)a 0.080(0.02)a 0.13(0.02)a

50 0.082(0.008)a 0.20(0.04)a 0.069(0.02)a 0.13(0.02)a

25 0.059(0.01)a 0.16(0.04)a 0.090(0.02)a 0.11(0.02)a

10 0.060(0.007)a 0.10(0.01)a 0.052(0.03)a 0.087(0.02)a

0 0.051(0.005)a 0.084(0.02)a 0.090(0.01)a 0.083(0.01)a

Table 2.3: Effects Supplemental lighting on the leaf transpiration rates (mmol H2O m-2 s-1) of greenhouse grown tomato plants in Guelph, ON, Canada during the winter months. Plants were subject to 100±25 µmol m-2 s-1 of either red-blue, HPS, or red-white supplemental light or a no light control and analyzed with a Li-COR standard red-blue LED light. Each value represents 6 replicates each replicate was done on a different leaf. The values in parentheses represents the standard error (±) for each mean and letter values (a) indicates statistical differences (α=0.05) between light treatments within a light level via a means comparison and a Tukey-Kramer adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Ambient Red-Blue HPS Red-White

1500 2.30(0.57)a 2.85(0.32)a 2.24(0.33)a 2.47(0.39)a

1000 2.05(0.41)a 2.36(0.28)a 2.25(0.20)a 2.51(0.24)a

750 1.77(0.21)a 1.87(0.22)a 1.40(0.24)a 2.02(0.14)a

500 1.39(0.11)a 1.68(0.13)a 1.22(0.22)a 1.72(0.17)a

250 1.21(0.09)a 1.52(0.15)a 1.47(0.28)a 1.64(0.21)a

125 1.11(0.13)a 1.37(0.13)a 1.03(0.15)a 1.43(0.20)a

100 1.06(0.13)a 1.30(0.25)a 1.18(0.23)a 1.45(0.22)a

75 0.97(0.14)a 1.28(0.27)a 0.88(0.19)a 1.33(0.24)a

50 0.99(0.15)a 1.17(0.17)a 0.71(0.16)a 1.31(0.15)a

25 0.75(0.22)a 1.08(0.18)a 0.99(0.19)a 1.18(0.20)a

10 0.77(0.14)a 1.06(0.15)a 0.57(0.27)a 0.95(0.19)a

0 0.63(0.11)a 0.88(0.16)a 0.95(0.12)a 0.87(0.12)a

Table 2.4: Effects Supplemental lighting on the leaf internal CO2 concentration (µmol CO2 mol air-1) of greenhouse grown tomato plants in Guelph, ON, Canada during the winter months. Plants were subject to 100±25 µmol m-2 s-1 of either red-blue, HPS, or red-white supplemental light or a no light control and analyzed with a Li-COR standard red-blue LED light. Each value represents 6 replicates each replicate was done on a different leaf. The values in parentheses represents the standard error (±) for each mean and letter values (a) indicates statistical differences (α=0.05) between light treatments within a light level via a means comparison and a Tukey-Kramer adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Ambient Red-Blue HPS Red-White

1500 288.00(19.3)a 291.67(17.0)a 311.83(20.8)a 300.50(11.3)a

1000 273.17(23.4)a 276.67(18.1)a 321.17(10.8)a 301.50(9.0)a

750 266.00(11.5)a 265.50(17.6)a 284.00(24.2)a 287.83(11.7)a

500 247.17(11.6)a 260.17(7.6)a 283.67(23.9)a 282.83(13.0)a

250 261.50(10.2)a 278.83(11.3)a 299.67(27.8)a 293.33(14.2)a

125 274.17(11.2)a 309.67(8.6)a 303.17(25.8)a 305.50(21.8)a

100 300.83(7.3)a 303.00(30.7)a 319.50(21.5)a 321.33(19.1)a

75 314.67(7.0)a 322.83(21.3)a 318.83(23.1)a 330.50(15.7)a

50 347.17(5.9)a 359.4(11.8)a 337.83(19.5)a 359.67(6.6)a

25 381.33(6.9)a 388.33(7.5)a 386.50(9.1)a 377.83(8.1)a

10 414.17(9.2)a 405.67(8.7)a 398.33(5.4)a 397.50(4.0)a

0 445.00(7.9)a 426.20(6.8)a 419.25(7.3)a 419.6(5.7)a

APENDIX II

Chapter 3 Supplemental Tables

Table 3.1: Effects of various wavelengths of LED lights and light intensity on the

photosynthetic rate (µmol m-2 s-1) at set light levels tomato leaves which were grown at

22°C/18°C under a broad spectrum white light. Each value represents 3 replicates each

replicate was done on a different leaf. The values in parentheses represents the standard

error (±) for each mean and letter values (a,b,c,d) indicates statistical differences (α=0.05)

between light treatments within a light level via a means comparison and a Tukey-Kramer

adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Light Treatment

Red Blue Red-White Red-Blue Green Orange White

1500 17.92(0.23)ab 15.81(0.52)b 17.39(0.31)ab 19.15(0.64)a N/A N/A 17.67(0.78)ab

1000 16.88(0.14)ab 13.95(0.49)c 16.82(0.23)ab 18.37(0.63)a N/A N/A 16.12(0.20)b

800 16.34(0.04)ab 12.98(0.43)b 16.28(0.22)ab 17.87(0.66)a 13.63(1.74)b N/A 15.06(0.55)ab

600 15.57(0.10)a 11.75(0.52)b 15.00(0.13)ab 16.72(0.56)a 13.25(1.50)ab 16.89(0.35)a 14.24(0.67)ab

400 13.66(0.23)a 9.58(0.70)b 12.14(0.12)ab 14.11(0.43)a 11.68(1.02)ab 13.90(0.30)a 12.62(0.62)a

300 11.63(0.21)a 7.81(0.71)b 9.75(0.10)ab 11.70(0.38)a 9.75(0.74)ab 11.40(0.30)a 10.82(0.50)a

200 8.67(0.20)a 5.26(0.66)c 6.55(0.16)bc 8.44(0.16)a 6.86(0.60)abc 7.89(0.06)ab 7.86(0.34)ab

100 4.64(0.09)a 2.17(0.51)c 2.58(0.12)bc 4.09(0.14)a 3.33(0.42)abc 3.68(0.12)ab 3.45(0.19)abc

75 3.31(0.10)a 1.04(0.51)c 1.54(0.09)bc 2.95(0.08)a 2.36(0.27)ab 2.57(0.16)ab 2.28(0.18)ab

50 1.93(0.04)a 0.26(0.52)b 0.26(0.15)b 1.53(0.13)a 1.45(0.28)a 1.54(0.02)a 1.03(0.16)ab

40 1.32(0.01)a 0.04(0.58)bc -0.22(0.11)c 1.02(0.10)ab 0.89(0.22)ab 1.05(0.05)ab 0.48(0.10)abc

30 0.71(0.02)a -0.64(0.83)c -0.60(0.18)bc 0.42(0.07)ab 0.34(0.10)abc 0.63(0.05)a -0.17(0.20)abc

20 0.17(0.04)a -0.72(0.53)abc -1.31(0.04)c -0.08(0.08)ab -0.17(0.08)a 0.08(0.08)a -0.81(0.16)bc

10 -0.54(0.01)a -1.29(0.04)b -1.80(0.04)b -0.79(0.10)a -0.64(0.06)a -0.40(0.05)a -1.04(0.20)b

0 -1.16(0.05)ab -1.99(0.64)bcd -2.42(0.16)d -1.34(0.05)abc -1.17(0.01)ab -1.01(0.02)a -2.01(0.16)cd

Table 3.2: Effects of various wavelengths of LED lights and light intensity on the stomatal

conductance (mmol H2O m-2 s-1) at set light levels of tomato leaves which were grown at

22°C/18°C under a broad spectrum white light. Each value represents 3 replicates each

replicate was done on a different leaf. The values in parentheses represents the standard

error (±) for each mean and letter values (a,b,c,d) indicates statistical differences (α=0.05)

between light treatments within a light level via a means comparison and a Tukey-Kramer

adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Light Treatment

Red Blue Red-White Red-Blue Green Orange White

1500 0.81(0.21)a 0.91(0.23)a 0.47(0.07)a 0.60(0.14)a N/A N/A 0.50(0.10)a

1000 0.45(0.06)a 0.63(0.14)a 0.40(0.04)a 0.52(0.12)a N/A N/A 0.30(0.02)a

800 0.39(0.05)a 0.46(0.05)a 0.38(0.03)a 0.44(0.10)a 0.21(0.07)a N/A 0.27(0.03)a

600 0.36(0.06)b 0.37(0.03)b 0.36(0.02)b 0.41(0.09)b 0.21(0.07)b 0.91(0.14)a 0.26(0.02)b

400 0.32(0.06)b 0.33(0.02)b 0.33(0.02)b 0.37(0.08)b 0.21(0.06)b 0.77(0.17)a 0.24(0.01)b

300 0.30(0.06)ab 0.31(0.02)ab 0.31(0.03)ab 0.33(0.07)ab 0.21(0.06)b 0.52(0.13)a 0.21(0.01)ab

200 0.29(0.06)a 0.29(0.01)a 0.28(0.02)a 0.29(0.06)a 0.19(0.05)a 0.29(0.05)a 0.17(0.01)a

100 0.28(0.06)a 0.27(0.01)a 0.25(0.02)a 0.25(0.06)a 0.17(0.04)a 0.19(0.02)a 0.13(0.004)a

75 0.27(0.06)a 0.26(0.01)a 0.23(0.02)a 0.23(0.06)a 0.15(0.04)a 0.15(0.02)a 0.11(0.003)a

50 0.26(0.06)a 0.25(0.01)a 0.23(0.02)a 0.22(0.05)a 0.14(0.04)a 0.14(0.03)a 0.10(0.0008)a

40 0.25(0.06)a 0.23(0.01)a 0.22(0.02)a 0.21(0.05)a 0.13(0.03)a 0.14(0.04)a 0.09(0.002)a

30 0.25(0.06)a 0.23(0.01)a 0.23(0.0004)a 0.20(0.05)a 0.12(0.03)a 0.13(0.02)a 0.09(0.003)a

20 0.25(0.06)a 0.22(0.003)a 0.23(0.004)a 0.19(0.05)a 0.12(0.03)a 0.13(0.03)a 0.09(0.004)a

10 0.24(0.06)a 0.22(0.001)a 0.20(0.02)a 0.19(0.05)a 0.11(0.03)a 0.13(0.03)a 0.09(0.005)a

0 0.23(0.06)a 0.22(0.008)a 0.20(0.02)a 0.18(0.05)a 0.11(0.03)a 0.13(0.03)a 0.08(0.009)a

Table 3.3: Effects of various wavelengths of LED lights and light intensity on the

transpiration rate (mmol H2O m-2 s-1) at set light levels of tomato leaves which were grown

at 22°C/18°C under a broad spectrum white light. Each value represents 3 replicates each

replicate was done on a different leaf. The values in parentheses represents the standard

error (±) for each mean and letter values (a,b,c,d) indicates statistical differences (α=0.05)

between light treatments within a light level via a means comparison and a Tukey-Kramer

adjustment. Statistical analysis can be found in Appendix IV.

PAR (µmol m-2 s-1)

Light Treatment

Red Blue Red-White Red-Blue Green Orange White

1500 4.07(0.70)a 4.78(0.51)a 3.01(0.24)a 3.68(0.45)a N/A N/A 3.32(0.59)a

1000 3.13(0.35)a 4.02(0.46)a 2.71(0.17)a 3.38(0.45)a N/A N/A 2.38(0.01)a

800 2.84(0.33)ab 3.45(0.24)a 2.63(0.11)ab 3.17(0.40)ab 1.76(0.39)b N/A 2.41(0.29)ab

600 2.71(0.32)ab 3.00(0.11)ab 2.57(0.10)ab 3.03(0.40)ab 1.80(0.38)b 3.60(0.20)a 2.38(0.24)ab

400 2.60(0.32)ab 2.76(0.08)ab 2.44(0.09)ab 2.84(0.40)ab 1.82(0.32)b 3.48(0.34)a 2.26(0.15)ab

300 2.53(0.40)a 2.66(0.07)a 2.31(0.13)a 2.67(0.41)a 1.79(0.31)a 2.87(0.44)a 2.05(0.11)a

200 2.44(0.42)a 2.51(0.09)a 2.17(0.13)a 2.45(0.36)a 1.70(0.27)a 2.00(0.27)a 1.79(0.10)a

100 2.37(0.44)a 2.37(0.11)a 2.00(0.14)a 2.22(0.38)a 1.56(0.23)a 1.46(0.13)a 1.46(0.09)a

75 2.32(0.46)a 2.27(0.09)a 1.91(0.15)a 2.08(0.41)a 1.43(0.23)a 1.23(0.13)a 1.26(0.09)a

50 2.28(0.48)a 2.21(0.09)a 1.86(0.15)a 1.97(0.41)a 1.34(0.22)a 1.15(0.16)a 1.16(0.09)a

40 2.23(0.49)a 2.14(0.11)a 1.82(0.16)a 1.91(0.43)a 1.28(0.22)a 1.12(0.17)a 1.08(0.10)a

30 2.18(0.49)a 2.09(0.06)a 1.93(0.03)a 1.86(0.43)a 1.22(0.21)a 1.10(0.18)a 1.02(0.10)a

20 2.15(0.49)a 2.04(0.07)a 1.88(0.005)a 1.82(0.44)a 1.19(0.21)a 1.09(0.18)a 1.00(0.10)a

10 2.12(0.49)a 2.04(0.04)a 1.67(0.15)a 1.79(0.43)a 1.15(0.21)a 1.08(0.18)a 0.96(0.11)a

0 2.09(0.47)a 1.99(0.03)a 1.74(0.13)a 1.75(0.42)a 1.10(0.21)a 1.09(0.19)a 0.89(0.12)a

162

Table 3.4: Effects of various wavelengths of LED lights and light intensity on the Ci (µmol

CO2 mol air-1) at set light levels of tomato leaves which were grown at 22°C/18°C under a

broad spectrum white light. Each value represents 3 replicates each replicate was done on

a different leaf. The values in parentheses represents the standard error (±) for each mean

and letter values (a,b,c,d) indicates statistical differences (α=0.05) between light treatments

within a light level via a means comparison and a Tukey-Kramer adjustment. Statistical

analysis can be found in Appendix IV.

163

PAR (µmol m-2 s-1)

Light Treatment

Red Blue Red-White Red-Blue Green Orange White

1500 320.31(13.99)a 335.19(4.81)a 302.37(7.71)a 302.81(14.62)a N/A N/A 304.63(8.08)a

1000 301.87(9.86)a 330.41(5.86)a 295.86(6.48)a 297.79(15.34)a N/A N/A 278.44(6.94)a

800 295.44(9.34)ab 324.43(5.86)a 296.04(4.70)ab 292.52(13.8)ab 252.23(18.58)b N/A 278.39(10.74)ab

600 293.85(10.92)ab 320.84(6.80)a 300.47(4.30)ab 293.39(14.45)ab 257.60(18.77)b 335.09(6.14)a 280.62(7.43)ab

400 301.28(10.55)abc 329.32(6.81)ab 313.51(3.08)abc 302.28(14.50)abc 276.66(15.13)c 338.80(6.74)a 287.41(4.32)bc

300 311.90(10.22)ab 338.94(6.11)a 325.04(3.93)ab 311.13(13.84)ab 292.92(13.12)ab 334.09(11.19)ab 291.84(3.61)b

200 329.36(8.23)ab 354.86(5.12)b 343.75(2.46)ab 327.94(11.78)ab 319.49(7.58)ab 333.55(10.13)ab 307.20(4.13)a

100 356.97(5.67)abc 375.89(3.97)a 372.00(0.61)ab 357.08(7.54)abc 354.59(2.84)bc 355.61(3.27)abc 345.23(0.90)c

75 366.36(4.23)abc 384.23(4.03)a 379.73(0.44)ab 364.44(7.30)bc 362.79(3.44)bc 362.13(2.65)bc 356.48(1.93)c

50 376.76(3.21)ab 390.38(4.31)a 390.66(1.32)a 377.67(3.44)ab 373.31(3.45)b 373.02(2.79)b 374.28(1.75)b

40 381.64(2.00)bc 392.10(5.05)ab 394.89(1.32)a 382.38(2.37)bc 380.51(2.59)bc 379.29(1.86)c 383.17(1.13)bc

30 386.71(1.29)ab 397.75(4.28)a 397.82(1.86)a 388.53(1.24)ab 388.07(1.43)ab 385.11(0.80)b 395.68(2.98)ab

20 391.53(0.66)c 399.39(4.81)abc 403.35(0.61)ab 394.46(1.06)bc 396.08(1.40)bc 393.18(0.80)bc 408.90(2.41)a

10 398.11(1.44)b 402.73(2.94)b 410.80(1.28)ab 402.60(2.96)b 404.41(2.77)b 400.16(1.43)b 420.69(2.49)a

0 404.14(2.99)b 410.15(3.43)b 416.37(3.66)b 409.85(5.22)b 414.02(3.88)b 409.17(2.63)b 439.62(2.12)a

Appendix III

Wavelength Specific Lighting

Determination of wavelength spectrum of lights used in Chapters 2, 3, and 4 were

determined using a spectrometer (Flame Spectrometer, Ocean Optics, Dunedin, FL, USA).

Figure 1.1: Wavelength spectrum of a red LED PAR38 floodlight from LSGC.

Figure 1.2: Wavelength spectrum of a blue LED PAR38 floodlight from LSGC.

-10000

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400 450 500 550 600 650 700 750

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165

Figure 1.3: Wavelength spectrum of a green LED PAR38 floodlight from LSGC.

Figure 1.4: Wavelength spectrum of an orange LED PAR38 floodlight from LSGC.

-5000

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166

Figure 1.5: Wavelength spectrum of a white LED PAR38 floodlight from LSGC

Figure 1.6: Wavelength spectrum of a red-blue LED PAR38 floodlight from LSGC.

-2000

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167

Figure 1.7: Wavelength spectrum of a red-white LED PAR38 floodlight from LSGC.

Figure 1.8: Wavelength spectrum of a red-blue large LED luminary from LSGC.

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168

Figure 1.9: Wavelength spectrum of a red-white large LED luminary from LSGC.

Figure 1.10: Wavelength spectrum of an HPS from Philips lighting.

169

Appendix IV

Statistical analysis

A one-way analysis of variance (one-way ANOVA) and a means comparison via a Tukey-

Kramer test we conducted on for all tables in chapters 2, 3, and 4 and a general example of

the output is presented. The probability of a type I error was set to 0.05% for all analyses.

Table 1.1: One-way ANOVA for whole plants greenhouse grown tomato plant daily average photosynthesis values normalized on a dry weight basis (µmol C g-1 s-1) grown under and exposed to different lighting conditions (Table 2.2).

One-way ANOVA Dependent variable: Photosynthesis (µmol C g-1 s-1) Fixed Effect Num DF Den DF F value Pr>F Light Treatment 5 90 20.11 <0.0001

Table 1.2: Means comparison for whole plants greenhouse grown tomato plant daily average photosynthesis values normalized on a dry weight basis (µmol C g-1 s-1) grown under and exposed to different lighting conditions via a Tukey-Kramer test (α=0.05) (Table 2.2).

Treatment Mean Standard Error Letter Group Ambient – HPS 0.1563 0.002746 A Ambient – Red-Blue 0.1452 0.002746 AB Ambient – Red-White 0.1355 0.002746 BC HPS 0.1346 0.002746 BC Red-Blue 0.1278 0.002746 CD Red-White 0.1220 0.002746 D

170

Figure 1.1: Studentized Residual analysis for whole plants greenhouse grown tomato plant daily average photosynthesis values normalized on a dry weight basis (µmol C g-1 s-1) grown under and exposed to different lighting conditions (Table 2.2).

Studentized Residuals for pnlevel

BIC -540

AICC -537.9

AIC -538

Objective -540

Fit Statistics

Std Dev 1.0052

M aximum 1.4278

M ean 49E-16

M inimum -3.266

Observations 96

Residual Statistics

-2 -1 0 1 2

Quantile

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idual

-3 -1.8 -0.6 0.6 1.8 3

Residual

0

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30

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cent

0.12 0.13 0.14 0.15

Predicted Mean

-3

-2

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idual