ABSTRACT 
 
 
 
 
Title of Thesis: The Plant Rhizosphere-Phyllosphere 
Connection: Analysis of root-associated 
Pseudomonas sp. -induced changes in Fruit 
Surface Phytochemical Profiles of Heirloom and 
Modern Tomato cultivars and effect on 
Salmonella enterica association 
  
 
Wesley Harrison Deaver, M.S., 2022 
  
Thesis directed by: Dr. Shirley Ann Micallef, Associate Professor, 
Department of Plant Science and Landscape 
Architecture  
 
 
Despite more rigorous food safety regulation for fruit and vegetable production, 
foodborne illnesses and massive food recalls have resulted from the enteropathogen 
Salmonella enterica on Solanum lycopersicum (tomato) fruits.  While some 
phytochemical profiles have been studied on modern cultivars in regards to minimizing 
Salmonella-plant association, little research has been done on heirloom varieties.  The 
interaction between the plant rhizosphere and phyllosphere remains understudied and the 
inoculation of plants with plant-growth promoting rhizobacteria (PGPR) can modify 
phyllosphere components of plants including fruit properties.  No research exists on 
whether PGPR colonization of tomato plant roots can alter the fruit?s phytochemical 
profile to affect Salmonella association.  Through several chemical and microbial 
analyses, I investigated the Salmonella association with fruit of modern and heirloom 
cultivars, as well as the impact of PGPR inoculation on this system.  In Chapter 3, I 
assessed fruit of modern and heirloom varieties, and explored possible associations 
between Salmonella growth in fruit soil amendments to a tomato field and profiling of 
  
surface washes and total sugar quantifications, citric acid and (for heirloom varieties) the 
fatty acid profiles.  Microbial counts differed from variety to variety and heirloom 
varieties demonstrated higher levels of sugars and citric acid compared to modern 
varieties.  Total sugar quantifications and citric acid were correlated with microbial 
counts in heirloom varieties, but not in modern varieties.  Chapter 4 focuses on the effects 
of inoculating the heirloom varieties with a PGPR in the genus Pseudomonas sp.on the 
fruit surface phytochemical profile and changes in microbial association.  Differing 
trends between the PGPR inoculated and non-inoculated groups were seen where citric 
acids were correlated with Salmonella association for the non-PGPR group, but not for 
the PGPR inoculated group.  For both the PGPR inoculated and non-inoculated groups, 
we measured a high degree of variation between the cultivars for the phytochemical 
profiles, and for both groups hexadecanoic acid was negatively correlated with microbial 
counts.  This study furthers the understanding of the relationship between tomato fruit 
phytochemistry and Salmonella association, as well as the effects of PGPR on modifying 
tomato fruit phytochemistry. These findings can help manage and improve the pre- and 
post-harvest food safety of tomato fruit. 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
The Plant Rhizosphere-Phyllosphere Connection: Analysis of root-associated 
Pseudomonas sp. -induced changes in Fruit Surface Phytochemical Profiles of 
Heirloom and Modern Tomato cultivars and effect on Salmonella enterica association 
 
 
 
by 
 
 
Wesley Harrison Deaver 
 
 
 
 
 
Thesis submitted to the Faculty of the Graduate School of the  
University of Maryland, College Park, in partial fulfillment 
of the requirements for the degree of 
Master?s of Science 
2022 
 
 
 
 
 
 
 
 
 
 
Advisory Committee: 
Dr. Shirley Micallef, Chair 
Dr. Wendy Peer 
Dr. Macarena Farcuh 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
? Copyright by 
Wesley Harrison Deaver 
2022 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
Acknowledgements 
 
I would like to extend my sincerest thanks and appreciation to my advisor, Dr. Shirley 
Micallef, who has been a source of unwavering encouragement and thoughtful critique 
throughout my graduate experience. I have always appreciated your honest and direct 
communication and your dedication to your students? success, and I look forward to 
many years of collaboration and friendship with you.  
 
I would also like to thank my Advisory Committee for their support: Dr. Wendy Peer and 
Dr. Macarena Farcuh. Both of you have helped me to grow as a scientist, providing me 
with many valuable opportunities and pieces of advice along the way.  
 
A special thank you to Dr. Yue Li from the Department of Chemistry whose expertise, 
encouragement, and support has been exceptionally important in my project. 
 
Without encouragement and inspiration from several dedicated science teachers and 
supervisors over the years, I would not be on this path. In particular, I would like to thank 
Dr. Angus Murphy who has pushed me to always think outside the box and reach beyond 
what work I had in front of me. 
 
I would also like to thank the Department of Plant Science and Landscape Architecture 
for making this all possible, along with the United States Department of Agriculture, who 
supported my research assistantship. For support with greenhouse and field studies, thank 
you to Meghan Holbert and Sydney Wallace in the UMD Research Greenhouse Complex 
staff and to Mike Newell of the Wye Research and Education Center. 
 
A big thank you to everyone in the Micallef lab who has helped me in my many 
experiments and lab work including Chris Bollinger, Sarinah Wahl, Xingchen Liu, Dr. 
Sultana Solaiman, Claire Hudson, Adam Hopper, Mary Theresa Callahan, and Dr. 
Angela Ferelli. 
 
And finally, thank you to my family for providing a wholesome upbringing and a 
nurturing environment to allow me to grow, to my best friend Roy for always bouncing 
mad scientist ideas off of, and to my heavenly wife for supporting me and putting up with 
my nonsense all the time. 
 
 
 
 ii  
Table of Contents 
 
Acknowledgements ........................................................................................................... ii 
Table of Contents ............................................................................................................. iii 
List of Figures .................................................................................................................... v 
Chapter 1: Introduction ................................................................................................... 1 
Chapter 2: Literature Review .......................................................................................... 4 
2.1. Foodborne illnesses due to fresh 
produce???????????????????????????????..?.....4 
2.2 Salmonella in the Plant Phyllosphere???????????????????....5 
2.3. Plant Defenses????????????????????????..???.?..6 
2.4. Salmonella and plant immunity..??????????????????????8 
2.5. Salmonella-plant pathogen-host plant interactions??????????????..9 
2.6. Plant-Growth Promoting Rhizomicrobes????????????????10 
2.7. Plant-Growth Promoting Rhizomicrobes and Human Pathogens on Plants???.11 
2.8 Fruit Ripening???????????????????????????.......12 
Chapter 3: Microbial and Phytochemical Analysis of fruit surfaces of Modern and 
Heirloom tomato cultivars ............................................................................................. 15 
1. Introduction??????????????????????????????.15 
2. Materials and Methods?????????????????????????...17 
2.1 Field and Greenhouse Design ............................................................................. 17 
2.2 Color and Texture Analysis ................................................................................ 18 
2.3 Microbial Measurements .................................................................................... 20 
2.4 Total Sugar Quantifications ................................................................................ 21 
2.5 Citric Acid Measurements???????..?????????????22 
2.6 Fatty Acids??????????????????????????...22 
2.7 Statistical Analysis??????????????????????..?.24 
3. Results?????????????????????????????????24 
3.1 Microbial Analysis .............................................................................................. 24 
3.2 Color and Texture Analysis ................................................................................ 26 
3.3 Sugar Analysis .................................................................................................... 28 
3.4 Citric Acid Analysis ............................................................................................ 30 
3.5 Fatty Acid Analysis???????????????????????.32 
3.6 Relationship between phytochemicals in fruit and Salmonella growth???..35 
4. Discussion???????????????????????????????..35 
Chapter 4: Inoculation of Solanum lycopersicum (tomato) plants with plant-growth 
promoting rhizobacteria Pseudomonas sp. S4????????????????...40 
1. Introduction??????????????????????????????..40 
2. Materials and Methods??????????????????????????41 
2.1 Greenhouse Design and PGPR Inoculation ........................................................ 41 
2.2 Plant Growth Promotion Analysis ...................................................................... 43 
 iii  
2.3 S Additional Methods and Materials Notes ........................................................ 43 
3. Results?????????????????????????????????43 
3.1 Fresh Weight Dry Weight Analysis .................................................................... 43 
3.2 Microbial Analysis .............................................................................................. 45 
3.3 Sugar Analysis .................................................................................................... 47 
3.4 Citric Acid Analysis ............................................................................................ 49 
3.5 Fatty Acid Analysis............................................................................................. 51 
3.6 Relationship between phytochemicals in fruit washes and Salmonella growth..56 
      3.7 Color Texture Analysis?????????????????????......56 
   3.8 Relationship between color/texture values in fruit washes and Salmonella 
growth????????????????????????????????60 
4. Discussion and Conclusions???????????????????????.?61 
4.1 Salmonella Association Discussion???????????????.?61 
 4.2 PGPR Growth Promotion, Color Texture Discussion????????.....61 
 4.3 Role of Sugars and Citric Acid in Salmonella-tomato interaction???..?63 
 4.4 Fatty Acids Discussion???????????????????..?..64 
 4.5 Conclusion????????????????????????..?.65 
Chapter 5: Conclusions and future directions ............................................................. 67 
Appendix 1: Supplementary tables ............................................................................... 70 
Bibliography .................................................................................................................... 72 
 
  
 iv  
List of Figures 
 
Chapter 2 
 
Figure 1. CIELAB color scale (L= light vs dark, a=red vs green, b=yellow/blue, c=bright 
vs dark, h=angular position around a central or neutral point). 
Chapter 3 
 
Figure 2. Analysis of Salmonella growth on exudate washes of Heirloom and Modern 
varieties. Error bars indicate stnd error. Asterisk indicates significant differences. 
(p=0.06) 
Figure 3. Analysis of Salmonella growth on fruit surface washes within Heirloom and 
Modern varieties. Error bars indicate stnd error. Letters denote significant differences. 
(p<0.05) 
Figure 4. Analysis of color scale values by cultivar for Heirloom varieties. Error bars 
indicate stnd error.  Letters indicate significant differences. (p<0.05) 
Figure 5. Analysis of texture values by cultivar within Heirloom varieties. Error bars 
indicate stnd error.  Letters indicate significant differences. (p<0.05) 
Figure 6. Analysis of total sugar quantification between Heirloom and Modern varieties. 
Error bars indicate stnd error. Asterisk indicates significant difference. (p<0.05) 
Figure 7. Analysis of total sugar quantification within cultivars. Error bars indicate stnd 
error.  Asterisks indicate significant differences. (p<0.05) 
Figure 8. Analysis of citric acid across heirloom and modern varieties. Error bars indicate 
stnd error. Asterisk indicates significant difference. (p=0.098) 
Figure 9. Analysis of citric acid within cultivars. Error bars indicate stnd error. Asterisks 
indicate significant differences. (p<0.05) 
 v  
Figure 10. Analysis of saturated fatty acids.  Error bars indicate stnd error.  Asterisks 
indicate significant differences. (p<0.05) 
Figure 11. Analysis of unsaturated fatty acids.  Error bars indicate stnd error.  Letters 
indicate significant differences. (p<0.05)  
Figure 12. Analysis of monounsaturated fatty acids.  Error bars indicate stnd error.  
Asterisks indicate significant differences. (p<0.05)  
Chapter 4 
 
Figure 13.  Average fresh weight and dry weight of heirloom plants inoculated (PGPR+) 
and uninoculated (PGPR-) with PGPR Pseudomonas sp. at 6 weeks post-germination.  
Error bars indicate stnd error.  Asterisks indicates significant difference. (p</=0.0857) 
Figure 14. Average fresh weight and dry weight of both PGPR+ and PGPR- heirloom 
tomato plants by cultivar at 6 weeks.  Error bars indicate standard error.  Asterisk 
indicates significant difference (p<0.05). 
Figure 15. Analysis of Salmonella growth on exudate washes of Heirloom varieties with 
and without PGPR. Error bars indicates stnd error.  Asterisk indicates significant 
differences. (p<0.05). 
Figure 16.  Analysis of Salmonella growth on exudate washes within Heirloom varieties 
PGPR+/-. Error bars indicate stnd error.  Asterisks indicate significant differences. 
(p</=0.05)  
Figure 17. Analysis of Sugar analysis within Heirloom varieties for both PGPR +/-. Error 
bars indicate stnd error.  Asterisk indicates significant differences. (p<0.05) 
Figure 18. Analysis of Sugar analysis within Heirloom varieties for both PGPR +/-. Error 
bars indicate stnd error.  Asterisks indicate significant differences. (p<0.05) 
 vi  
Figure 19. Average citric acid of fruit surface washes for PGPR+ and PGPR- treated 
heirloom tomato plants.  Error bars indicate standard error.  Asterisk indicates significant 
difference (p<0.05). 
Figure 20. Average citric acid of fruit surface washes for PGPR+ and PGPR- treated 
heirloom tomato plants across cultivars.  Error bars indicate standard error.  Asterisk 
indicates significant difference (p<0.05). 
Figure 21. Average fatty acids of fruit surface washes for PGPR+ and PGPR- treated 
heirloom tomato plants.  Error bars indicate stnd error.  Asterisks indicate significant 
difference (p</=0.078). 
Figure 22. Average saturated fatty acids of fruit surface washes for PGPR+ and PGPR- 
treated heirloom tomato plants across cultivars.  Error bars indicate stnd error.  Asterisks 
indicates significant difference (p<0.05). 
Figure 23. Average unsaturated fatty acids of fruit surface washes for PGPR+ and PGPR- 
treated heirloom tomato plants across cultivars.  Error bars indicate stnd error.  Asterisks 
indicates significant difference (p</=0.08). 
Figure 24. Average monounsaturated fatty acid levels of fruit surface washes for PGPR+ 
and PGPR- treated heirloom tomato plants across cultivars.  Error bars indicate stnd 
error.  Asterisks indicates significant difference (p<0.05). 
Figure 25. Analysis of color scale values between PGPR+/-. Error bars indicate stnd 
error.  Asterisk indicates significant differences. (p<0.05) 
Figure 26. Analysis of color scale values between PGPR+/- groups within cultivars. Error 
bars indicate stnd error.  Asterisks indicate significant differences. (p<0.05). 
 vii  
Figure 27. Analysis of texture values between PGPR+/- groups. Error bars indicate stnd 
error.  Asterisks indicate significant differences. (p<0.05). 
Figure 28. Analysis of texture values between PGPR+/- groups for each cultivar. Error 
bars indicate stnd error.  Asterisks indicate significant differences. (p<0.05). 
 
 
 
 
 
 
 
 
 
 
 
.
 viii  
 
Chapter 1: Introduction 
The enteric pathogen Salmonella has been known to cause humans illness known as 
salmonellosis.  Despite good food safety practices, Salmonella presents immense public health 
concern (CDC, 2019) and financial concern to both farmers and consumers (Ribera et al, 2012).  
In recent years there have been a number of Salmonella outbreaks implicating tomato (Solanum 
lycopersicum) in various parts of the world (CDC, 2005), (CDC, 2007), (Greene et al; 2007).   
Finding effective ways to minimize Salmonella enterica subsp. enterica association on 
tomato (Solanum lycopersicum) fruit surfaces can reduce the chance of foodborne illness. The 
Salmonella-tomato association is tomato cultivar-dependent (Han and Micallef, 2014). One of 
the drivers of this variation in bacterial association appears to be related to differential levels of 
phytocompounds among fruit of different cultivars that can impact bacterial-fruit associations. 
Sugars, sugar alcohols and organic acids in tomato fruit washes were associated with increased 
Salmonella growth in these solutions, while medium- to long-chain saturated fatty acids and the 
unsaturated oleic acid were negatively correlated (Han and Micallef, 2016). Further investigation 
into the effect of saturated medium-chain fatty acids on Salmonella growth confirmed the 
inhibitory effect of these compounds (Dev Kumar and Micallef, 2017). 
A potential way to modify the specialized metabolites on the surface of tomato fruit could 
be through the root inoculation of plant-growth promoting-rhizobacteria (PGPR).  One plant-
growth-promoting rhizobacterial species of interest is Pseudomonas sp. S4. This PGPR strain has 
been shown to increase plant vigor and biomass accumulation in tomato plants as well as reduce 
the association of Salmonella with leaf surfaces (Hsu and Micallef, 2017). The mechanism by 
which root colonization with Pseudomonas sp. S4.is able to restrict this plant-bacterial 
1 
 
association is not known. Moreover, the metabolic influences of these PGPR interactions on the 
plant, and specifically on the fruit surface remain a mystery.  However, there has been research 
regarding similar plant-growth-promoting-rhizobacteria modifying fatty acid levels in plants.  
Taken together, these findings could suggest that inoculation of tomato plants with Pseudomonas 
sp. S4 may very well increase specific fatty acid content in the fruit surfaces. 
I, therefore, hypothesize that tomato fruit surfaces with higher medium- to long-chain saturated 
fatty acids and unsaturated oleic acid will demonstrate a lesser association with S. enterica.  The 
second hypothesis is that tomato plants inoculated with Pseudomonas sp. S4 will demonstrate 
higher levels of medium- to long -chain saturated fatty acids and unsaturated oleic acids, in turn 
modulating the Salmonella-tomato association. 
 
Objective: The overall goal of this research is to discover and understand strategies to minimize 
S. enterica association with S. lycopersicum fruit.  In the specific objectives of this project, I set 
out to screen modern and heirloom S. lycopersicum fruit surfaces for fatty acids and to 
understand the role of Pseudomonas sp. S4 in the potential modifications of metabolites of the 
fruit surfaces. 
 
Hypothesis 1, Sugars and Citric Acid analysis: Sugars and citric acid will be associated with 
increased Salmonella growth for both modern and heirloom varieties 
Hypothesis 2, Fatty Acid Analysis: Fatty acids will be associated with inhibited Salmonella 
association 
2 
 
Hypothesis 3, PGPR Analysis: Application of PGPR will be associated with higher fatty acids 
and inhibited Salmonella association. 
Specific Aims: 
?     Aim 1: Screen and analyze modern and heirloom tomato cultivar fruit surfaces for degree of 
Salmonella association  
?     Aim 2: Screen and analyze tomato cultivars for total sugars and citric acid  
?     Aim 3: Screen and analyze tomato cultivars for fatty acid types and levels  
? Aim 4: Compare Salmonella association, fatty acids, citric acid, and total sugars between 
PGPR +/- groups 
? Aim 5: Investigate the impact of PGPR on fruit color and texture traits and relation to 
Salmonella association 
 
 
 
 
 
 
 
 
 
3 
 
Chapter 2: Literature Review 
2.1. Foodborne illnesses due to fresh produce 
The enteric pathogen Salmonella has been known to cause humans illness known as 
salmonellosis.  According to the Center for Disease Control and Prevention (CDC), consumers 
can become infected from a number of agricultural products including animal products and fresh 
produce.  The illness is particularly dangerous in children, the elderly, and those with 
immunocompromised health conditions and results in an estimated 1.35 million illnesses, 26,500 
hospitalizations, and 420 deaths in the United States every year (CDC, 2019) (CDC 2020).  
Furthermore, the financial impacts of foodborne illness outbreaks and deaths in the US are 
estimated to be between $5-6 billion a year (Ribera et al, 2012).  Additionally, the CDC linked 
46% of foodborne illness to fresh fruits and vegetables (Painter et al; 2013).  In recent years there 
have been a number of Salmonella outbreaks implicating tomato (Solanum lycopersicum) in 
various parts of the world (CDC, 2005), (CDC, 2007), (Greene et al; 2007).  There are a number 
of contamination sources for Salmonella including manure composts and irrigation water that 
contribute to cross-contamination of tomato plants (Jablasone et al, 2004, Islam et al, 2004).  The 
persistence of Salmonella in soil environments is dependent on a number of conditions including 
microbial diversity, where the higher level of diversity in indigenous microflora, the lower the 
rate of Salmonella survivability, while the lower level of indigenous microflora diversity, the 
higher the rate of Salmonella survivability (Zibilske and Weaver 1978).  Persistence of 
Salmonella in soil conditions is also dependent on abiotic conditions including air temperature 
and moisture where cooler and wetter conditions were favorable to survivability in the soil (Lee 
et al, 2019).   
 
4 
 
2.2. Salmonella in the Plant Phyllosphere 
Epiphytic attachment and colonization of Salmonella on plants has been explored on a number of 
different plants for both seeds and leaves.  Damaged seeds and rougher, grooved surfaces 
demonstrated higher rates of association with Salmonella as opposed to undamaged seeds and 
smoother surface seeds.  Additionally, the use of fungicides on seed surfaces generally did not 
contribute to a reduction of microbial association (Cue and Chen, 2017).  Differences in the 
morphological structure in lettuce leaves also resulted in different levels of attachment between 
the plant host and Salmonella where the base of leaves harbored microbial growth more than 
middle and upper portions of the leaves.  However, neither leaf grooves nor stomatal density 
could explain the differences in microbial association. (Van der Linden et al, 2016).   
 
Interestingly in other studies, internalization of tomato plant tissues was linked to chemotaxis 
and light induced opening of stomata (Kroupitski et al, 2009). In the epiphytic regions of plants, 
Salmonella attachment is dependent upon a number of microbial advantages including flagella 
for motility and curli fimbriae for adhesion to surfaces.  Cellulose was seen as a major 
component of plant tissue that aided in microbial association. Salmonella also utilizes 
exopolymeric substances in biofilm formation to maintain communal growth in the face of biotic 
and abiotic stresses (Maruzani et al, 2018; Yaron et al, 2014).  Once internalized in plant tissues, 
Salmonella continues to persist and colonize tomato plants by means of de novo biosynthesis of 
amino acids, lipopolysaccharides, and nucleotides, as well as iron acquisition and maintenance of 
cell structure (de Moraes et al, 2017; de Moraes et al, 2018).  At high levels of inoculation, 
Salmonella can move freely through the interior of tomato plants and migrate to different 
portions of the plant (Gu et al, 2011).  It is also possible that universal stress proteins play an 
5 
 
important role in Salmonella being able to mitigate stresses in plant interiors (Kroupitski et al, 
2019).  A number of genes in Salmonella were determined to be important for internal plant 
colonization including stomatal opening, biosynthesis of surface appendages, and callose 
deposition (Montano et al, 2020).  In tomato plants specifically, Salmonella was seen to have 
upregulated oxidative and nitrosative stress response genes as well as genes related to sulfur 
metabolism and anaerobic respiration in order to combat harsh internal plant conditions (Han et 
al, 2020).  Enteric human pathogens like Salmonella have a multitude of different abilities to 
survive and persist not only in the environment, overcoming stressful abiotic conditions, but also 
colonize and persist in the plant phyllosphere and the plant interior. 
 
2.3. Plant Defenses 
Plants have a multitude of defensive mechanisms to deal with biotic stresses and pathogenic 
infections including both physical and chemical, induced and constitutive mechanisms.  Some 
primary metabolites like amino acids provide broad spectrum protection against bacterial 
pathogens, fungi, and insects (Zaynab et al, 2019).   Other constitutive chemical defenses include 
secondary metabolites that act as toxins that deter predators such as alkaloids and terpenoids 
(Wittstock and Gershenzon 2002).  Physical constitutive defenses include barriers such as the 
waxy cuticle that not only prevent plants from water loss and abiotic stresses, but also act as a 
strong barrier against pests and pathogens from being able to enter the plant interior.  
Furthermore, some of these lipids in the surface of the waxy cuticle can act as chemical defenses 
against pathogens (Reina-Pinto and Yephremov, 2009). Aside from constitutive physical and 
chemical layers of defense on the exterior and interior of the plant, the induced 
pathogen/microbe-associated molecular patterns (PAMP/MAMP)-triggered immunity (PTI) 
6 
 
defense response is considered the first line of defense in plants.  PAMP/MAMPs are highly 
conserved and specific molecular markers on the surface of pathogens and microbes that are 
recognized by host plant cell surface receptors compounds known as pattern-recognition 
receptors (PRRs).  Many bacterial pathogens have flagella which are utilized for motility.  
Flagellin is well-known PAMP that host plant PRRs, specifically FLS2 and BAK1 receptor 
complex, can detect.  The recognition of these surface receptors by the plant host in turn 
activates PTI, which results in a calcium signaling cascade system to induce a multitude of 
chemical and defense responses to combat the pathogenic microbes commonly known as 
hypersensitive response (HR) and induced systemic acquired response (SAR).  While HR is a 
more localized defense response that includes callose deposition, SAR activates chemical 
defenses such as a reactive oxygen species burst and expression of defense genes including 
upregulation of secondary metabolites.  Various motile plant signaling pathways are vital to SAR 
including salicylic acid, but the entirety of these mechanisms are still being investigated.   
 
Pathogenic microbes have developed ways to combat PTI using effector proteins that can reduce 
PTI defense responses.  This then activates the second line of plant immunity against pathogens 
known as effector-triggered immunity (ETI).  This then brings about the second line of plant 
immunity against pathogens known as effector-triggered immunity (ETI).  In ETI, plants utilize 
leucine-rich repeating (LRR) resistance proteins (R proteins), which are highly specific to 
different microbe effectors, to target pathogen effectors in the plant cell interior and bring about 
ETI in plant immunity to combat infection.,  When R proteins are not present, pathogens are able 
to bypass ETI and continue infection of plant hosts known as effector triggered susceptibility 
(ETS) (Yuan et al, 2021; Wu et al, 2014; Pruit et al, 2021; Keinath et al, 2010; Naveed et al, 
7 
 
2020).  The realm of plant immunity is highly important to many researchers and the ability to 
resist and mitigate infection from pathogens, but there is less research on plant immune systems 
and human enteric pathogens. 
 
2.4. Salmonella and plant immunity 
While Salmonella is not considered a plant pathogen, there is mounting evidence that human 
pathogens on plants can be sensed by plant immune systems.  Most notable, the flagellin flg22 
peptide PAMP that Salmonella has is recognized by the FLS2 and BAK1 receptor complex 
across plant species. The receptor complex initiates PTI and various defenses strategies including 
ROS accumulation, stomatal closure, and SA accumulation.  There is also a small amount of 
evidence that Salmonella not only has functional type III secretion system (T3SS) effectors 
coded by genetic SPI-1 and SPI-2 areas of its? genome, but that Salmonella may utilize T3SS 
effectors in order to bypass PTI and activate some symptoms of ETI.  While there is more 
research needed on this area, there is presently some evidence suggesting that enteric human 
pathogens like Salmonella elicits at least a PTI immune response from plants, and perhaps a 
limited ETI response as well due to evolution in its? effector proteins (Garcia and Hirt 2014; 
Meng et al, 2013; Zarkhani and Schikora 2021).  Salmonella has been shown to have regulon 
genes encoding to mitigate of ROS and reactive nitrogen species (RNS) damage (Han and 
Micallef 2020).  There is some evidence that the accumulation of these reactive compounds in 
plants may reduce levels of Salmonella levels in tomato plants.  Upon recognition of Salmonella 
by tomato leaves nitric oxide (NO) and ROS were upregulated and significantly limited 
Salmonella microbial populations (Ferelli et al; 2020).  Other metabolites in tomato fruits have 
been identified as inhibitory to Salmonella growth including lauric and myristic acids in one 
8 
 
study (Kumar and Micallef 2017).  Further studies in the metabolomics of tomato plants suggest 
that certain metabolites like sugars, sugar alcohols, and organic acids were associated with 
enhanced Salmonella growth, while various fatty acids were associated with limited Salmonella 
growth (Han and Micallef 2016).  There is a complex balance between beneficial and harmful 
metabolites in tomato plants and the ability to modulate association between Salmonella and 
tomato plants. 
 
2.5. Salmonella-plant pathogen-host plant interactions 
An area of major concern is how the prevalence of phytopathogens may be able to increase the 
level of association between enteric pathogens like Salmonella and host plants.  In one study 
involving tomato plants, Pectobacterium carotovorum, a soft rot phytopathogen, was 
hypothesized to release starches that would benefit the growth of Salmonella, but this was not 
proven accurate.  Instead, a metabolic shift in Salmonella was detected with the co-inoculation 
with the phytopathogen, suggesting that Salmonella is able to synthesize amino acids and 
nucleotides more effectively as means of energy sources (George et al; 2013).  In another study 
of the early development tomato phyllosphere, while Salmonella was able to reduce the levels of 
both phytopathogens Clavibacter michiganensis and Xanthomonas gardneri, only the presence 
of C. michiganensis managed to allow for an increase in Salmonella population suggesting that 
different phytopathogens have different impacts on the association between human pathogens 
and host plants (Rajashekara et al; 2020).  In another study, Salmonella, and bacterial wilt 
pathogen, Ralstonia solanacearum, demonstrated an increase in Salmonella growth in various 
portions of tomato plants suggesting a symbiotic relationship upon co-inoculation (Pollard et al; 
2014). 
9 
 
2.6. Plant-Growth Promoting Rhizomicrobes 
Plant-growth promoting rhizomicrobes (PGPR) are beneficial microbes (bacteria or fungi) 
present in the rhizosphere that engage in a mutualistic and often symbiotic relationship with the 
root systems of a multitude of plants.  Many of these microbes have been identified in their 
ability to solubilize nitrogen and phosphorus in the soil to be more bioavailable to plants and 
potentially act as biofertilizers in a hypothetical effort to limit the use of costly chemical 
fertilizers and pesticides and consequently limit the emission of greenhouse gasses from 
traditional agricultural practices (Vessey 2003).  Additionally, PGPR have been known to 
promote physical plant growth by inducing upregulation of plant growth hormone biosynthesis 
such as IAA (Yousef 2018).  Meanwhile in the phyllosphere, phytohormones such as ethylene 
are promoted as a means to improve crop production.  There is also evidence that PGPR can 
result be sensed and identified by plant immune systems in similar ways that plant pathogens do, 
but plants are able to recognize PGPR from rhizosphere phytopathogens and allow their 
interactions with the host plant (Bhattacharyya and Jha 2012).  The resulting anti-microbial 
defense responses from ISR in the form of increased accumulations of secondary metabolites 
(particularly volatile compounds) and general niche exclusion of microbe-plant symbiosis 
provide evidence that PGPR could also be used as effective biocontrol agents against 
phytopathogens (Mohammad et al; 2009, Beneduzi et al; 2012, Kannojia et al; 2019).  Plant-
growth promoting rhizobacteria Ochrobactrum intermedium was able to modify the fatty acid 
contents of Arachis hypogaea (Paulucci et al, 2015). Rhizobium strain TVPo8 increased fatty 
acids in pepper plants (Silva et al, 2014). Applications of plant growth promoting rhizobacteria 
including Bradyrhizobium. japonicum, Azosprillum. lipoferum, and Pseusomonas. sp. in 
soybeans increased unsaturated fatty acids while decreasing saturated fatty acids (Seyed 2016). 
10 
 
Pseudomonas. sp. was also used to increase oil content in pumpkin (Habibi et al, 2011).  For 
tomato plants, one of the most commonly used PGPR bacterial strains is Pseudomonas sp. which 
has been shown to increase shoot dry weight, antioxidant and lycopene levels, and reduce 
negative impacts from phytopathogens such as Rothia spp. by means of proline and polyphenol 
production.  Interestingly, more beneficial impacts of PGPR Pseudomonas spp. were seen in 
tomato plants when co-inoculated with other PGPR strains of the same genus, suggesting 
potential symbiosis and synergism between bacterial PGPR strains (Almaghrabi et al; 2013, 
Ordookhani et al; 2010, Bano and Muqarab 2017).   
 
 2.7 Plant-Growth Promoting Rhizomicrobes and Human Pathogens on Plants 
The ability of strains of PGPR to reduce enteric human pathogens associating with host plants 
has been explored to a small degree.  In one study, PGPR bacterial strain Bacillus subtilis was 
inoculated into the root systems of leafy greens lettuce and spinach.  While stomatal closure was 
induced from the PGPR while the plants were in the presence of Listeria and Salmonella 
separately, the presence of only Listeria was diminished from the PGPR inoculation while 
Salmonella was not (Markland et al; 2015).  In another study on tomato plants, Paenibacillus 
alvei, was first isolated from the phyllosphere of field tomato plants and then screened against 
Salmonella in the fruits, leaves, and blossoms of new tomato plants.  Results indicated 
significant reduction, and in some cases full elimination of Salmonella microbial population 
from the tomato plant (Allard et al; 2014).  Further studies showed that PGPR bacteria 
Pseudomonas strains not only increased tomato and spinach plant shoot dry weight and leaf 
chlorophyll content in some cultivars, but Salmonella microbial activity was reduced in both the 
spinach and all of the tomato cultivars? phyllosphere (Hsu and Micallef, 2017).  However, the 
effect of the Pseudomonas strains showed different levels of plant growth promotion and 
11 
 
Salmonella reduction, which also differed for the plant host species and cultivars.  It was 
theorized that the inoculation of these agricultural plants with Pseudomonas may have increased 
the accumulation of unfavorable metabolites in the plants such as fatty acids and phenolics (Hsu 
and Micallef 2017).  While more research is needed on the effects of PGPR on acting as a 
biocontrol agent to enteric human pathogens on plants (specifically the antagonistic 
mechanisms), there are some positive indicators in this research, though ultimately the pairing of 
the PGPR strain with the enteric human pathogen and the host plant may vary and correct 
matching may be vital for success. 
 
 2.8 Fruit Ripening 
During fruit development both auxin and cytokinin have been determined as primary fruit 
maturation plant hormones with auxin playing the most significant role during fruit maturation 
(Kumar et al, 2014).  As tomato fruits grow, they begin to reach a ripening stage that is triggered 
by changes in ethylene production in which (1-aminocyclopropane-1-carboxylic acid) ACC is 
converted to ACC oxidase by the enzyme ACC synthase.  When ethylene receptors are degraded 
along specific genetic targets, transcription of ethylene begins.  This is also paired with the 
MADS box domain genes which induce physiological flower formation (Klee and Giovanni, 
2011).  The fruit ripening begins with lipid peroxidation and protein oxidation.  As catalase 
activation increases, the tomato fruit will begin to change color more.  This is also paired with 
hydrogen peroxide accumulation.  Tomato fruit ripening and color changes occur on another 
level as the chlorophyll begins to degrade and chloroplasts are converted to chromoplasts to 
serve as synthesis sites for metabolites such as carotenoids, fatty acids, and amino acids.  
Changes in gene expression in the biosynthesis of ethylene as well as carotenoids have been 
12 
 
demonstrated, but the transcriptional regulation of carotenoid biosynthesis and chlorophyll 
degradation is not well understood (Bramley, 2002).  Many of the genes regulating the 
carotenoid biosynthesis pathway are determined to be under the influence of ethylene production 
levels.  During the ripening process, starches are converted to glucose and fructose (Ho et al, 
1982).  Additionally, ABA (abscisic acid) biosynthesis is crucial in the accumulation of lycopene 
for fruit coloration during ripening (Bai et al, 2021).  Recent studies have also determined the 
importance of auxin (in addition to ethylene) during the later stages of fruit ripening in terms of 
the regulation of volatile organic compound (VOC) metabolic pathways (Cruz et al, 2018, 
Tobaruela et al, 2021).  Interestingly, there is an inverse relationship between the sugar levels 
and malic acid levels in ripening tomato fruits.  Measurements have indicated for that plant 
volatile levels, as well as fatty acids, closely follow the timing of carotenoid development, 
suggesting a triggering of plant volatiles by carotenoid development in the process of fruiting 
(Bramley, 2002; Klee and Giovanni, 2011).  Changes in other compounds in tomato fruit during 
ripening include a conversion of starches to sugars, and an increase in organic acids (Kumar et 
al, 2014) as well as an increase in unsaturated fatty acids C16 and C18 (Palmitic acid and 
Linolenic acid) (Saini et al, 2017) The pericarp of the tomato begins to shift into a softer state as 
ripening occurs as well with increased cell wall separation and increased pigmentation linked to 
increased polygalacturonase activity (Ahrens and Huber 1990, Lazan et al, 1989). 
 
The literature reviewed helps in piecing together known variables to investigate Salmonella 
association on tomato fruit surface washes and the impact of PGPR on the phytochemical 
profiles.  This review has outlined the dangers facing the agriculture and food safety industry in 
regard to Salmonella outbreaks and how Salmonella can survive and persist in the phyllosphere.  
13 
 
Studies have also shed light on the intricate balance of favorable and unfavorable metabolites 
present in plants, especially tomato fruits and which ones have been associated with supporting 
or inhibiting Salmonella growth.  Furthermore, this review has investigated the impact of plant 
growth promoting rhizobacteria on not only tomato plants, but also the impact on modulating 
phythochemicals and the potential to reduce Salmonella association.  Lastly, this review 
discussed how the color and texture qualities of tomato fruits change during the ripening process. 
 
 
  
14 
 
Chapter 3: Phytochemical difference in fruit surface washes of Modern and Heirloom 
tomato varieties impact Salmonella enterica growth 
 
1. Introduction 
Enteric pathogen foodborne illness outbreaks of Salmonella enterica subsp. enterica have been 
linked to tomato (Solanum lycopersicum) fruits in several countries over recent years (CDC 
2005, CDC 2007, Greene et al; 2007).  Salmonella has been known to persist on the phyllosphere 
and colonize the interior of tomato plants (Kroupitski et al; 2009, Gu et al; 2011).  Most 
microbial research on Salmonella indicates that motility and biofilm production are vital to the 
adhesion, survivability, and persistence of Salmonella microbial populations (Maruzani et al; 
2018, Yaron et al; 2014).  While Salmonella can colonize the interior of tomato plants from the 
rhizosphere, it would reason that in field scenarios, the enteric human pathogen would more 
likely contaminate the phyllosphere of tomato plants from contaminated soil due to splash effects 
(Lee et al; 2019).  While there are a multitude of nutrients available in the plant interior that 
would favor Salmonella growth, there are also antimicrobial compounds present in plants that 
would serve as deterrents (Ferelli Han et al; 2020, Kumar and Micallef 201).  Furthermore, there 
are a multitude of induced and constitutive defenses available from plants that would further 
diminish Salmonella contamination (Zaynab et al; 2019, Wittstock and Gershenzon 2002, Reina-
Pinto and Yephremov 2009, Yuan et al; 2021).  Previous studies have indicated that while 
sugars, organic acids, and sugar alcohols were correlated with positive Salmonella growth, 
certain fatty acids were associated with negative microbial association (Han and Micallef 2016).  
While most studies regarding Salmonella and tomato plants have involved modernly available 
hybrid varieties, there have been a few studies involving heirloom tomato varieties.  In one 
15 
 
study, red tomato fruit was shown to be more susceptible to Salmonella association compared to 
green or unripened tomato fruit, larger tomatoes had greater Salmonella association than smaller 
cherry tomato fruit, but for both hybrid modern cultivars and heirloom varieties, fruit color was 
generally not an important factor in Salmonella association.  Furthermore, Salmonella 
association was most varied from individual cultivars while field grown tomatoes showed lower 
ability for Salmonella to associate than greenhouse tomato fruits.  The same study found similar 
differences in growth of Salmonella with higher association on mature vs immature fruit, and 
higher association on red pigmented fruit vs varieties that lacked red pigmentation (Marvasi et al; 
2014). 
While much is known of the relationships between Salmonella association and tomato plants, 
there have been few studies on the phytochemical profile of tomato fruits in their relation to 
Salmonella association, and to date only one study involving heirloom tomato fruits and 
Salmonella.  By growing a deeper understanding of the phytochemical profile of tomato fruit 
surfaces for both modernly available and heirloom fruit cultivars and their relation to Salmonella 
association, we can better prepare means to combat foodborne illness outbreaks at a pre-harvest 
stage. 
In order to investigate the relationship between Salmonella and tomato fruit, we evaluated the 
levels of Salmonella growth on fruit surface washes and compared the microbial associations 
with corresponding total sugar quantifications, citric acid levels, and when possible, fatty acid 
levels for both modern cultivars and heirloom varieties.  The correlations between the microbial 
association and phytochemical profiles of the different tomato cultivars help to shed light on the 
complex phyllosphere interactions between tomato fruits and Salmonella that could provide 
16 
 
avenues towards alternative Salmonella-resistant cultivars being used and genetically bred into 
the market. 
 
2. Materials and Methods 
2.1 Field and Greenhouse Design 
During the autumn of 2019, six tomato heirloom varieties (Amish Paste, Black Icicle, Purple 
BumbleBee, Green Zebra, and White Tomesol) were grown in the UMD Greenhouse Complex.  
Plants were first started from seed (n=6 plants per cultivar), placed in cell trays with propagation 
mix in the mist germination rooms until the first set of true leaves appeared, at which point they 
were transferred into 3 gallon pots and placed in greenhouse conditions of 8 hours of light and 16 
hours of dark at 26?C during the day and 14?C at night.  The heirloom varieties were pruned to 
prevent overgrowth and promote fruit production.  At peak ripeness, fruits were aseptically 
harvested using nitrile gloves and sterile Whirlpak bags (Nasco, Wisconsin).  Fruits were 
transferred to the lab, placed in 15?C cold storage rooms if they could not be processed the same 
day, and then photographed and measured for surface area estimations.  Fruits were then placed 
in 30 mL of 5% methanol/95% DI water and were placed on a shaker for 2 h at 200 rotations per 
minute (rpm).  Halfway through the collection, fruits were rotated to ensure maximum surface 
area coverage.  These washes were then used for microbial assays, and total sugar and citric acid 
quantification.  Preliminary fatty acid analysis in the spring of 2020 showed that only one or two 
fatty acids could be identified, so the second round of heirloom tomato fruits had an additional 
second wash of 100% ethanol at 200 rpm in order to collect a more detailed fatty acid profile in 
addition to the primary 5% methanol wash. 
17 
 
In the summer of 2020, 8 hybrid varieties (Mountain Merit, Mountain Gem, Dixie Red, Red 
Pride, BHN 589, Mountain Fresh, Charger, and Celebrity) were grown at the UMD wye facility 
in high tunnels.  At peak ripeness, the tomatoes were harvested and subjected to the procedures 
as described.  In the autumn of 2020, a second round of heirloom tomatoes were grown in the 
UMD greenhouse and separated into two groups, one inoculated with PGPR Pseudomonas sp. 
(Chapter 3) and one control group without PGPR.  These greenhouse heirloom varieties were 
harvested at peak ripeness and transferred to the Plant Science Building where they were 
immediately processed for 5% methanol surface washes.  Modern varieties wash samples n=39 
(Mountain Merit n=5, Mountain Gem n=5, Dixie Red n=6, Red Pride n=5, BHN 589 n=4, 
Mountain Fresh n=5, Charger n=4, and Celebrity n=5).  Heirloom varieties wash samples n= 94 
(Amish Paste n=14, Black Icicle n=17, Emerald Evergreen n=13, Green Zebra n=13, Purple 
BumbleBee n=17, White Tomesol n=20). 
 
2.2 Color and Texture Analysis 
For many of the fruit from the second round (2021), before the initial washes were taken from 
the fruit, a series of color and texture analyses was performed to investigate any relationship 
between quality analysis on phytochemistry and microbial Salmonella association.  First, a 
colorimeter was connected to the lab computer and a blank was taken with a protected white 
slide.  Then two opposite sides of each tomato were measured in the CIELAB color space where 
values ?L? scaled lightness or luminance (0 being darker/black and 100 being brighter/white), 
?a? scaled red/green coordinates, ?b? scaled yellow/blue coordinates, ?C? scaled chroma 
(distance from the lightness axis where positive is brighter and negative is darker), and ?H? 
scaled hue (angle starts at the +a* axis and is expressed in degrees) (Figure 1) (Hill et al, 1997). 
18 
 
  
Figure 1. CIELAB color scale (L= light vs dark, a=red vs green, b=yellow/blue, c=bright vs 
dark, h=angular position around a central or neutral point). 
 
Texture measurements were taken using a fruit texture analyzer in a similar fashion to previous 
studies involving fruit texture quality analysis (Farcuh et al, 2020, Rolle et al, 2011).  A 16 mm 
probe was standardized using a 2 kg weight.  The mechanical fruit texture analyzer was able to 
calculate stiffness(g/sec), firmness (N), and toughness(g*sec).  Single sides of the individual 
fruits were analyzed for texture analysis to minimize structural damage to the tomato fruit and 
reduce the risk of puncturing the waxy cuticle surface before surface washes could be collected 
while color data was taken for two opposite sides of each tomato fruit.  Both color and texture 
data of the individual tomato fruits were averaged across individual fruits for each batch because 
some sample batches were comprised of individual fruits and some batches were composed of 
multiple fruits.  By averaging the color and texture data across all the individual tomato fruits in 
the batches, we were able to compare color and texture data to corresponding batch microbial 
19 
 
data and phytochemical data.  ANOVA and students t tests were used for color and texture data 
due to a normal distribution of data.  Heirloom varieties color/texture samples n= 33 (Amish 
Paste n=6, Black Icicle n=9, Emerald Evergreen n=3, Green Zebra n=5, Purple BumbleBee n=5, 
White Tomesol n=5). 
 
2.3 Microbial Measurements 
In order to mimic realistic field settings as much as possible, a trio of Salmonella strains 
(Salmonella Javiana ATCC BAA-1593; a clinical isolate from a tomato outbreak, Salmonella 
Braenderup 04E61556-2-99; clinical isolate), and and Salmonella Newport; a pond water 
environmental isolate that matched a tomato outbreak strain (Greene et al., 2008) were used to 
measure the degree to which different tomato fruit surface washes could support Salmonella 
growth and survival.  Previous lab in vitro settings, Salmonella species have commonly been 
grown on tryptic soy agar (TSA) broth and media.  Serial dilutions of suspended Salmonella 
colonies in 0.1% peptone water or 1x PBS solutions have been used to accurately quantify and 
analyze microbial populations through colony forming unit (CFU) counting (Han and Micallef 
2016).  From -80?C deep freeze, the three rifampicin-resistant strains were streaked on TSA 
plates (company, location, country) with rifampicin antibiotic (50?g/ml) (TSA-R) (company, 
location, coutry) added.  After inoculating at 35?C for 20 h, colony forming units were visible.  
Using a nephelometer (Brand, location, country), 3 separate 10 mL 1x PBS suspensions at an 
optical density (OD) of McFarland=0.5 were prepared for each Salmonella strain using colonies 
from the fresh culture plates.  A series of dilutions were used to enumerate the suspensions 
where 100ul of the initial 0.5OD solutions were removed and placed in 900ul of PBS before 
being vortexed and further diluted.  At the third dilution, all 3 strains were combined into a 3mL 
20 
 
cocktail in equal volume.  This cocktail was further diluted in the same manner two more times 
to prepare the final inoculum.  This was enumerated on TSA-R plates for counting the next day.  
For inoculation of fruit washes, 100 ul of ~4 logCFU/ml were added to 900 ul of the tomato fruit 
washes and vortexed for a final inoculum load of ~3 logCFU. A few tubes were plated right 
away for T0 (time 0 h) counts and the rest incubated at 35?C with shaking at 200 rpm for a 20 h 
(T20) count.  The following day, the fruit wash suspensions went through three serial dilutions at 
which point all 3 had 20 ul plated and incubated at 35 o C for 20 h before colony count recovery 
occurred the following day.  The colony counts and corresponding back calculations allowed us 
to accurately quantify the ability of the tomato fruit surface washes to support the Salmonella 
strains. 
 
2.4 Total Sugar Quantifications 
Using the tomato fruit washes, we followed a total sugar quantification protocol using a 
spectrophotometer (Cuesta et al; 2003).  Aliquots of 100ul of the surface washes were mixed 
with 100 ul of 5% phenol solution (brand, location, country) and 500ul of concentrated sulfuric 
acid (brand, location, country).  The centrifuge tubes were then heated at 100 o C for 5min and 
then vortexed before being read in the spectrophotometer (brand/model, location, country) at 
490nm.  Sucrose stocks and blanks were used to establish a standard curve.  Total sucrose 
concentration was read as mg sucrose/ml of wash.  Measurements of the total sugar 
quantifications were analyzed by cultivar and against the microbial data.  When evaluating sugar 
values, similarly to the microbial analysis, comparisons were made via t test one way analysis 
between the modern and heirloom varieties, but wilcoxon each pair tests were made within both 
the modern and heirloom cultivars due to an uneven distribution of data points.  
21 
 
 
2.5 Citric Acid Measurements 
The citric acid content of the surface fruit washes was measured using [Megazyme citric acid 
assay] (Megazyme, Cork, Ireland) following the microplay assay protocols.  First, the hydrated 
solutions were prepared according to the instructions in the protocol.  Then, a stock solution of 
solutions 1, 2, and 3 (buffer solution, NADH/PVP solution, and L-MDH/D-LDH) was created so 
that a consistent 72 ul could be added to each well plate and reduce variation in the smaller 
volumes being used.  20ul of the fruit washes were added to 180ul of DI water (while 200ul 
water was used as the blank and 20ul standard solution and 180ul DI water was used to make the 
standard solution).  After the addition of the stock solution mix to each sample, blank, and 
standard well plate, at which point spectrophotometer readings were taken on a Synergy 
microplate reader at 340nm.  The mixtures were incubated at 37?C for 4 mins, then 2ul of the 
enzyme solution 4 was added to each well and mixed before taking an additional reading.  3rd 
and sometimes 4th readings were taken while continuing to incubate at 37degC for 2 mins in-
between readings to ensure that the reactions had all taken place between the first and second 
readings.  Using the change in standard well reading and any present dilution factors, 
measurements were recorded in mg/ml. 
 
2.6 Fatty Acids 
For investigating the fatty acid profiles of the fruit washes, we used a fatty acid methyl 
esterification technique (FAME) and gas chromatography mass spectrometry (GC-MS) on an 
Agilent 6890N GC system coupled with a JEOL Mstation magnetic sector mass spectrometer.  
The fatty acids in the 100% ethanol fruit washes were derivatized by ester derivatization as 
22 
 
described.  Once dried, the metabolites would be suspended in 500ul of hydrochloric [SM2] acid 
in methanol and heated at 78?C for one hour before having 500ul of 99% hexane added.  Then 
5ml of calcium carbonate solution was added and vortexed.  The solutions then went through 
micro centrifuge at 1000rpm for 10 mins and the hexane layer was recovered.  Another 500ul of 
hexane was added again and the samples centrifuged again before the next layer of hexane was 
added to the initial recovered layer.  The hexane-metabolite mixes were dried [SM3] and 
suspended in 125ul of methanol with 10ul of methyl octanoate (TCI, Japan) as an internal 
standard added.  Samples were run in the GCMS and spectra read outs were compared to NIST 
database and sample standards[SM4]  methyl myristate (TCI, Japan), methyl palmitate (Sigma, 
Malaysia), methyl linoleate (arcos organics, USA), methyl linolenate (arcos organics, USA), 
methyl stearate (Alfa Aesar, USA), methyl erucate (Restek, USA), methyl arachidate (Alfa 
Aesar, China).  Areas under the curve were calculated relative to the area under the internal 
standard curve and calibrated with respect to fruit surface areas for statistical analysis.  The fatty 
acid methyl ester GCMS analysis was done for the heirloom variety cultivars.  Peak area under 
the curve for each spectra was corrected for relative internal methyl octanoate standard followed 
by a correction for each sample batch fruit surface area.  In comparing relative fatty acid levels, 
Wilcoxon each pair tests were used due to an uneven distribution of data.  The gas 
chromatography measurements were performed on an Agilent 6890N system coupled with a 
JEOL high-resolution magnetic sector mass spectrometer (JMS-700 MStation) with the EI ion 
source (70 eV). The mass spectrometer was operated in the mode of high scan speed and low 
resolution (1000) with the mass range from 50 to 500 daltons. A silica capillary column (Agilent 
DB-5, 60 m length, 250 ?m I.D.) was used with helium (at 1 ml/min) as the carrier gas. Analysis 
was performed as follows: injection volume was 1 ?l, the inlet temperature was 285 ?C in split 
23 
 
mode (split ratio = 2), the column temperature was programmed from 70 ?C at 3.0 min, then 
increased to 310 ?C at the rate of 15 ?C/min and then held at 310 ?C for another 6.0 minutes.  
Heirloom varieties fatty acid samples n= 54 (Amish Paste n=8, Black Icicle n=13, Emerald 
Evergreen n=9, Green Zebra n=5, Purple BumbleBee n=9, White Tomesol n=10).  
2.7 Statistical Analysis 
When looking at the microbial counts from the T0 and T20 points, the change (delta) in log 
colony forming units(CFU)/ml, was used to distinguish the degree of microbial association with 
the surface washes.  Additionally, microbial counts were adjusted in regards to relative surface 
area of the tomato fruits.  When comparing modern and heirloom varieties in terms of 
Salmonella association, we used a t test to compare means.  Evenly distributed data was analyzed 
using students t test while uneven distribution of data was analyzed using Wilcoxon each pair 
test.  Regression analysis was used to determine the degree of influence of variables on 
Salmonella association and the correlations with microbial counts.   All data was analyzed using 
JMP pro15 2.0.   
3. Results 
3.1 Microbial Analysis 
Surface washes from fruit of modern cultivars were in general better able to support modern 
Salmonella growth (average count = 2.0 delta log/CFU/ml) than washes from heirloom fruit 
(average count = 1.7 delta log/CFU/ml) but this difference was only weakly significantly 
different (p=0.06) (Figure 2). 
24 
 
 
Figure 2. Analysis of Salmonella growth on exudate washes of Heirloom and Modern varieties. 
Error bars indicate stnd error. Asterisk indicates significant differences. (p=0.06) 
r  
Using a priori multiple comparisons, no statistical difference in Salmonella counts were detected 
among the modern cultivars.  ?Dixie Red? and ?Red Pride? supported the highest Salmonella 
populations, with delta logCFU differences between T20 and T0 of 2.3 and 2.2 log/CFU/ml, 
respectively.  On the other hand, ?Mountain Gem? and ?Charger? supported the least growth, with 
1.7 ?logCFU/ml values modern(Figure 2).  When analyzing the heirloom varieties, cultivar 
?Emerald Evergreen? fruit washes supported the highest population of Salmonella (2.6 
25 
 
?logCFU/ml) and was statistically different from all other heirloom cultivars (p<0.05) except for 
?Amish Paste? (Figure 3). In fact, ?Emerald Evergreen? provided the most favorable solution for 
Salmonella growth overall and was comparable to the modern cultivar ?Dixie Red?.  Comparing 
all cultivars together revealed that ?Dixie Red? was also different from ?Purple Bumblebee? and 
?Black Icicle?.  Excluding ?Emerald Evergreen? from the heirloom group revealed a strong 
difference between modern and heirloom fruit surface washes in their ability to support 
Salmonella (p=0.005) (figure 3). 
 
 
 
 
Figure 3. Analysis of Salmonella growth on fruit surface washes within Heirloom and Modern 
varieties. Error bars indicate stnd error. Letters denote significant differences. (p<0.05) 
 
3.2 Color and Texture Analysis 
 
While none of the field modern varieties were analyzed for color and texture, the second round 
of greenhouse heirloom varieties were analyzed for color and texture.  In terms of ?L? scaling 
(light vs dark), cultivar white tomesol (WT) showed the lightest color followed by green zebra 
26 
 
(GZ), then both purple bumblebee (PBB) and emerald evergreen (EE), then amish paste (AP), 
and finally black icicle (BI) as the darkest.    For ?C? chroma scaling (bright vs dull), cultivars 
amish paste, and green zebra showed the highest chroma followed by emerald evergreen, black 
icicle, purple bumblebee, and white tomesol.  For ?h? hue (a combination scaling of ?a? and 
?b?), cultivar white tomesol (WT) showed the highest hue followed by GZ, EE, PBB, BI and AP 
as the lowest hue cultivars (p<0.05) (Figure 4). 
 
 
Figure 4. Analysis of color scale values by cultivar for Heirloom varieties. Error bars indicate 
stnd error.  Letters indicate significant differences. (p<0.05) 
 
For texture analysis, data was analyzed using ANOVA and student's t test.  There were no Commented [SM1]: Not Tukey? Just checking 
significant differences detected between the heirloom cultivars in terms of stiffness.  However, 
for both toughness and firmness, cultivar PBB demonstrated the highest values while cultivars 
AP, BI, and WT demonstrated the lowest toughness and firmness values (p<0.05) (Figure 5).  
27 
 
Stiffness was measured in g/sec, firmness was measured in g, and toughness was measured in 
g*sec. 
 
  
 
Figure 5. Analysis of texture values by cultivar within Heirloom varieties. Error bars indicate 
stnd error.  Letters indicate significant differences. (p<0.05) 
 
3.3 Sugar Analysis 
 
Overall, heirloom varieties had a higher level of total sugars (25.1 g/100 ml) compared to 
modern varieties (6.2 g/100 ml) (p<0.001) (Figure 6), even when ?Emerald Evergreen? was 
excluded (24.5 g/100 ml; p<0.001) 
 
28 
 
 
Figure 6. Analysis of total sugar quantification between Heirloom and Modern varieties. Error 
bars indicate stnd error. Asterisk indicates significant difference. (p<0.05) 
 
Within the modern cultivar group, significantly different sugar values were detected between 
?Mountain Merit? having higher total sugar values than cultivar ?Charger? (p<0.05).  However, 
cultivars ?Dixie Red? and ?Charger? approached significance (p=0.07) (Figure 7).  Within the 
heirloom varieties, cultivars PBB and EE approached significant difference (p=0.07) however 
none of the cultivar sugar quantification differences managed to reach statistically different 
values (p<0.05) (Figure 7).  Comparing the modern cultivars with the heirloom varieties revealed 
29 
 
several differences.  While total sugars varied more in modern cultivars compared to heirloom 
cultivars, the modern cultivars demonstrated overall lower total sugars compared to the heirloom 
cultivars (Figure 7).  Modern cultivar Mt Gem supported some of the least Salmonella growth among modern 
cultivars and yet has highest sugars among the modern cultivars. Heirloom cultivar EE has similar total sugars as most other 
heirloom cultivars and yet is more favorable to Salmonella.  Meanwhile, heirloom cultivar PBB is lowest for bacterial growth, 
but not the lowest for sugars when compared to modern cultivars.  (Figure 7). 
 
Figure 7. Analysis of total sugar quantification within cultivars. Error bars indicate stnd error.  
Asterisks indicate significant differences. (p<0.05) 
 
 
 
3.4 Citric Acid Analysis 
 
Another component investigated in this experiment was the level of citric acid in the fruit washes 
and the correlation with Salmonella association.  A non-parametric test was used for comparing 
modern and heirloom averages while wilcoxon each pair tests were used for comparisons within 
the cultivars of each variety.  In the initial comparison between modern and heirloom varieties, it 
30 
 
was seen that heirloom varieties had a weakly statistically significant higher amount of citric acid 
compared to the modern varieties (p=0.098) (Figure 8). 
 
Figure 8. Analysis of citric acid across heirloom and modern varieties. Error bars indicate stnd 
error. Asterisk indicates significant difference. (p=0.098) 
  
Meanwhile, within modern cultivars, Mt. Merit had the highest level of citric acid while cultivars 
Charger, Celebrity, and Mt. Fresh had the lowest citric acid levels (p<0.05) (Figure 10).  For the 
heirloom varieties, cultivar EE demonstrated the highest citric acid levels while BI and PBB 
demonstrated the two lowest citric acid levels (p<0.05) (Figure 10).  When comparing the 
31 
 
modern and heirloom varieties, the modern cvs. ?Mountain Merit?, Mountain Gem? and BHN# 
589? had higher citric acid levels than the heirloom 'Purple Bumblebee? (p<0.01). On the other 
hand, the heirloom variety ?Emerald Evergreen? had higher citric acid levels than the modern 
cvs. of ?Mountain Fresh? (p<0.01), ?Celebrity and ?Charger? (p<0.05) (Figure 9). 
 
 
Figure 9. Analysis of citric acid within cultivars. Error bars indicate stnd error. Asterisks indicate 
significant differences. (p<0.05) 
 
 
 
 
 
3.5 Fatty Acid Analysis 
 
There were seven main fatty acids peaks identified using standards in the spectra. Four of these 
were saturated fatty acids: arachidic acid (eicosanoic acid, C20:0), stearic acid (octadecanoic 
acid, C18:0), palmitic acid (hexadecanoic acid, C16:0), myristic acid (tetradecanoic acid, C14:0), 
and three were unsaturated: linoleic acid (C18:2 cis-9,12), linolenic acid (C18:3 cis-9,12,15), 
erucic acid (docosenoic acid, C22:1 cis-13). 
32 
 
In general, cultivars EE and AP had the lowest levels of saturated fatty acids while BI, PBB and 
WT had the highest. Our data showed that stearic acid and hexadecanoic acid were higher in 
cultivars WT, PBB, and BI (p<0.05 ) than cultivars AP and EE.   Meanwhile cultivars BI, PBB, 
and WT had higher myristic acid (p<0.05) and compared to cultivar AP.  To a lesser degree, 
myristic acid was also somewhat lower in GZ and (p<0.1) compared to AP. WT and BI had 
slightly higher levels of hexadecanoic acid (palmitic acid) than GZ (p<0.1). Additionally, for 
arachidic acid, cultivar WT had higher levels compared to cultivar EE (p<0.05) (Figure 10). 
 
Figure 10. Analysis of saturated fatty acids.  Error bars indicate stnd error.  Asterisks indicate 
significant differences. (p<0.05) 
Fewer cultivar differences were detected for polyunsaturated fatty acids (linoleic and linolenic 
acids). Our data showed that cultivars PBB, WT (p<0.05) and BI (p<0.1) had higher levels of 
linoleic acid compared to cultivar EE.  Also, cultivars PBB, WT, and BI had higher levels of 
linolenic acid compared to cultivar AP (p<0.05). Some other weaker differences were for 
augmented levels of linolenic and linoleic acids in PBB compared to GZ (p<0.1) (Figure 11). 
33 
 
 
Figure 11. Analysis of unsaturated fatty acids.  Error bars indicate stnd error.  Letters indicate 
significant differences. (p<0.05)  
The only monounsaturated fatty acid detected in the GCMS spectra for our fruit washes was 
erucic acid.  In our analysis, PBB, BI, WT (p<0.01) and GZ (p<0.05) had more erucic acid 
compared to cultivar EE (Figure 12). Slightly higher levels of erucic acid were also detected in 
PBB than AP (p<0.1). 
 
34 
 
Figure 12. Analysis of monounsaturated fatty acids.  Error bars indicate stnd error.  Asterisks 
indicate significant differences. (p<0.05)  
 
In general, cultivars EE and AP had the lowest levels of saturated fatty acids while BI, PBB and 
WT had the highest. Our data showed that stearic acid and hexadecanoic acid were higher in 
cultivars WT, PBB, and BI (p<0.05) than cultivars AP and EE.   Meanwhile cultivars BI, PBB, 
and WT .   
 
3.6. Relationship between phytochemicals in fruit and Salmonella growth 
To assess whether sugar and citric acid or fatty acid levels in heirloom compared to modern 
tomato fruit washes could significantly predict Salmonella growth in fruit washes, multiple 
regression was employed. The results of the regression using sugar and citric acid values as 
predictors for modern varieties showed that the model explained 6% of variance significantly 
(R^2=0.6, p<0.001).  Citric acid (p<0.01) and sugars (p<0.05) were positively correlated with 
Salmonella growth for modern varieties.  For the heirloom regression model using citric acid and 
sugars as predictors, the model showed that 21% of the variance of Salmonella could be 
explained, but was not significant (R^2=0.21, p=0.31) with neither citric acid (p=0.17) nor 
sugars (p=0.38) showing significant contributions to Salmonella variance (Appendix Table 1). 
4. Discussion and Conclusion 
4.1 Microbial-Sugar-Citric Acid Analysis Discussion 
The purpose of our study was to investigate the color, texture, and phytochemical profiles of 
heirloom and common variety tomato fruit surfaces and to analyze correlations of these profiles 
to Salmonella association in order to better understand the relationships between tomato fruit 
35 
 
surfaces and potential Salmonella association to pave a path for the reduction of Salmonella at a 
pre-harvest stage. Firstly, the main comparison was between Modern and Heirloom variety 
tomato fruit phytochemical profiles.  In order to both mimic realistic surface contact scenarios 
with Salmonella from the soil and to capture phytochemical metabolites from the tomato surface, 
we both grew Salmonella and chemically analyzed tomato fruit surface washes.  From our 
results, there are several components that contribute to the bacterial growth of Salmonella on the 
tomato fruit washes.  For the modern varieties, although there was only a weakly significant 
difference in microbial association, there were significant differences in sugar levels and weakly 
significant differences in citric acid levels between modern and heirloom cultivars. The cultivar 
EE demonstrated the highest Salmonella association as well as some of the highest sugars and 
citric acid levels while cultivar Charger demonstrated some of the lowest Salmonella association 
and some of the lowest sugars and citric acid levels.  Salmonella has been known to utilize 
glucose as a major carbon source (Bowden et al; 2009), but tomato fruits are known to contain 
glucose, fructose, and galactose (Zhao et al; 2016), and our method of total sugar quantification 
only measured total sugars instead of individual sugars. Furthermore, heirloom varieties as a 
whole had higher sugar and citric acid levels than modern varieties, yet in our regression 
analysis, only in the heirloom cultivars did sugars and citric acid levels significantly contribute to 
Salmonella growth distribution and demonstrate positive correlation with microbial counts.  We 
might expect that the heirloom varieties would have higher levels of Salmonella association than 
modern varieties due to their higher sugars and citric acid levels, but this did not appear to be 
true.  While citric acid at high levels are known to have anti-microbial properties (Al-Rousan et 
al; 2018) it is possible that the surfaces washes did not contain high enough levels to demonstrate 
anti-microbial effects, and it is also possible that Salmonella could utilize citric acid in a different 
36 
 
state as an energy source as citrate with the help of 2-methylcitrate synthase (Horswill and 
Escalante-Semerena 1999).  Notably, the regression model even for the heirloom cultivars when 
including only sugars and citric acids could explain only 21% of the microbial count distribution, 
suggesting that for both heirloom and modern cultivars, other metabolites have a more 
significant impact on Salmonella association.  Furthermore, cultivar PBB had higher toughness 
and firmness compared to cultivar AP, suggesting that the toughness and firmness of the waxy 
cuticle could play a part in the releasing of favorable phytochemical metabolites that could 
support Salmonella growth.   
 
 
There are also a number of additional compounds that were not analyzed in these experiments 
that could be deterring microbial growth.  When looking at the heirloom varieties, there appears 
to be a larger degree of variation within the cultivars compared to the modern cultivars.  Studies 
done on the genetic diversity of cultivated tomato fruits have indicated a large dip in the 1960s 
followed by a significant increase in recent decades.  It is also known that older heirloom 
varieties have a higher nutritional value compared to modern cultivars and could potentially be 
used in modern breeding varieties to increase nutritional value (Schouten et al; 2019) (Fita et al; 
2015) (Zsogon et al; 2018).  While there is still debate on the degree to which modern breeding 
has led to a loss in genetic variation and in what specific ways, our research has indicated at least 
a wider variation in phytochemical profile of the tomato surface in heirloom varieties for 
Salmonella growth compared to modern varieties.  Some of these variations could be correlated 
with differences in genetic variation for the comparison between these specific heirloom and 
37 
 
modern cultivars that were investigated.  It is possible that other heirloom and other modern 
cultivars would have less variation as well. 
   
4.2 Fatty Acids Discussion 
Previous studies have identified medium chain fatty acids as correlated with reduced Salmonella  
association (Han and Micallef 2016), but this research was conducted on modern cultivars when 
we instead investigated heirloom cultivars.   The saturated fatty acids (myristic acid, 
hexadecanoic acid, stearic acid, and arachidic acid) data showed that cultivars BI, PBB, and WT 
had higher myristic acid compared to cultivar AP.  Cultivars PBB, WT, and BI also had higher 
hexadecanoic acid and stearic acid compared to cultivars AP and EE.  Additionally, for arachidic 
acid, cultivar WT had higher levels compared to cultivar EE.  Similar trends were seen with 
cultivars PBB and BI having some of the highest unsaturated fatty acids compared to cultivar 
EE.  Similarly, cultivar PBB had higher erucic acid compared to cultivar EE.  Much of this is in 
line with the differences seen in the microbial growth for the heirloom cultivars, but no negative 
correlations are seen.  The similarities in the differences between the microbial growth and 
several of the fatty acids, especially for cultivars EE vs PBB (the two most extreme), show that 
fatty acids might play a role in deterring Salmonella growth, but ultimately it appears to depend 
upon the cultivar.  Fatty acids and color/texture values were included in chapter 4 regression 
models for comparing PGPR+/- groups as chapter 3 was focused on comparing heirloom and 
modern cultivars and only sugars and citric acid levels were measured for the modern cultivars.  
Previous studies have shown antimicrobial properties from certain fatty acids either through the 
disruption of bacterial cell membranes (Ricke 2003) or through the reduction in activation of 
Salmonella pathogenicity genes (Van Immerseel et al, 2004).  Interestingly, previous studies also 
38 
 
showed linolenic acid being negatively correlated with Salmonella growth (Han and Micallef 
2016), which is in line with cultivars demonstrating higher linolenic acid also on average having 
lower Salmonella association. 
 
4.3 Discussion Conclusion 
Overall, it appears there are multiple factors that go into promoting Salmonella growth like 
sugars, citric acid, and low toughness and firmness while certain factors can also deter 
Salmonella growth such as low sugars, low citric acid levels, higher levels of certain fatty acids, 
and high toughness and firmness.  It would reason that having higher toughness and firmness can 
limit Salmonella from having entry points into the fruit interior in a field scenario, and it also 
would reason that having high levels of toughness and firmness can reduce the release of 
favorable metabolites.  Ultimately, being able to deter Salmonella growth on tomato fruit 
surfaces seems to be a complex balance between a lack of favorable metabolites and a greater 
level of unfavorable metabolites that differs between cultivars and between heirloom vs modern 
tomato varieties.  It is important to keep in mind that many metabolites were not analyzed in 
these experiments that could shed more light on Salmonella association with tomato fruits.  
Some of the most notable anti-microbial metabolites that could be playing a factor are volatile 
organic compounds (VOCs) such as terpenoids, phenolics, and flavonoids (Schulz-Bohm; et al 
2017, Tako et al; 2020).  Future studies should investigate these compounds in modern and 
heirloom varieties and their relationship with Salmonella association.  
 
  
39 
 
Chapter 4: Inoculation of Solanum lycopersicum (tomato) plants with plant-growth 
promoting rhizobacteria Pseudomonas sp. (S4) 
1. Introduction 
In this chapter, we investigated the impact of tomato root inoculation of PGPR Pseudomonas sp. 
on the phyllosphere, specifically the phytochemical profile change of the heirloom tomato fruits 
and the potential mitigation of Salmonella association.  Plant-growth promoting rhizobacteria 
(PGPR) are a class of beneficial bacteria that engage in a mutualistic, symbiotic relationship with 
a wide range of plants.  Many of the impacts of PGPR that have been studied are focused on the 
impacts of induced systemic resistance (ISR) against biotic pathogens, to prime plants against 
future abiotic stresses such as drought and salinity (Beneduzi et al; 2012, Bhattacharyya and Jha 
2012, Arora et al; 2011).  After engaging in a mutualistic relationship with PGPR, microbes such 
as Bacillus and Pseudomonas aid plants in nitrogen fixation, plant growth promotion, plant 
hormone synthesis, and aid in resistance against plant pathogens (Sivasakthi at al; 2014).  PGPR 
including Bacillus have also been known to help plants in resistance to abiotic stress such as 
salinity, drought, and heavy metals in potato plants (Gururani et al; 2013). There is also some 
research on the impacts of PGPR with the nutritional quality of plant produce.  Some studies 
have shown PGPR (many including Pseudomonas) to increase vitamin quantity lycopene 
content, and texture in tomato fruit (Loganathan at al; 2014, Sharafzadeh et al; 2012, Mena-
Violante et al; 2007).  For tomato plants in particular, one of the most commonly used PGPR 
bacterial strains is Pseudomonas sp. which has been shown to increase shoot dry weight, 
antioxidant and lycopene levels, and reduce negative impacts from phytopathogens such as 
Spodoptera litura by means of proline and polyphenol production (Bano and Muqarab 
2017).  Interestingly, more beneficial impacts of PGPR Pseudomonas sp. were seen in tomato 
40 
 
plants when co-inoculated with other PGPR strains of the same genus, suggesting potential 
symbiosis and synergism between bacterial PGPR strains (Almaghrabi et al; 2013, Ordookhani1 
et al; 2010). 
.  As previously described in the literature review, there have been a few studies indicating 
limited success with PGPR in mitigating enteric human pathogens on plants (Markland et al; 
2015, Allard et al; 2014), and there has only been one study on using Pseudomonas to lessen the 
association of Salmonella with tomato plants (Hsu and Micallef 2016).  It is possible that the 
inoculation of tomato rhizosphere with PGPR Pseudomonas could induce a systemic immune 
response that upregulates unfavorable metabolites for Salmonella and possibly downregulate 
favorable metabolites for Salmonella to reduce the association and potentially provide an avenue 
for reduced foodborne illness outbreaks with the use of PGPR in pre-harvest agriculture stages.  
In this study, we aimed to determine if the inoculation of tomato roots with PGPR Pseudomonas 
sp. can modulate the phytochemical profile of tomato fruit surfaces to be unfavorable to 
Salmonella growth and subsequently limit Salmonella growth.  There in this study we aimed to 
analyze whether or not the inoculation of heirloom tomato plants with PGPR Pseudomonas sp. 
would be able to modulate the phytochemical profile of the surface of the heirloom tomato fruits 
and inhibit Salmonella association. 
 
2. Materials and Methods 
2.1 Greenhouse Design and PGPR Inoculation 
Similarly to the heirloom variety tomato plants outlined in chapter 3, six heirloom tomato 
cultivars Amish Paste (AP), Black Icicle (BI), Emerald Evergreen (EE), Green Zebra (GZ), 
Purple Bumble Bee (PBB), and White Tomesol (WT), were planted in the UMD Greenhouse 
41 
 
Research Complex.  In the autumn of 2019, only non-PGPR tomato plants were considered, but 
in the autumn of 2020, two new groups were introduced.  Of each cultivar, four PGPR non-
inoculated and four PGPR-inoculated plants were divided once transferred from the mist 
germination room to the larger quart pots.  Growing conditions were set at 8 hours of light and 
16 hours of dark at 26 ?C during the day and 14 ?C at night.  Rifampicin (rif) resistant 
Pseudomonas sp. (unconfirmed to be species spp., so classified as Pseudomonas sp.) strain S4 
(Dr. Brain Klubek (Southern Illinois University Carbondale) has been previously kept in our lab. 
Frozen stock of Pseudomonas sp. strains were streaked on Trypticase Soy Agar (TSA) plates and 
incubated at 30?C for 48 hours. Single colonies were transferred to Trypticase Soy Broth (TSB) 
and grown to late-log phase.  Suspensions were incubated at 200pm, 30deg C for 20 hours before 
being pelletized at 10,000 rpm for 15 min and diluted with 1x PBS to OD=0.5.  Tomato plants 
received 2 mL of 108 CFU/mL bacterial suspension or 1xPBS at the base of stems.  Two separate 
root inoculations were carried out 2-days and 9-days post re-potting.  Successful root 
colonization with each strain of Pseudomonas was confirmed by colony enumeration of root 
rinsates on TSA-rif plates upon completion of experiments.   the heirloom varieties were pruned 
to prevent overgrowth and promote fruit production.  At peak ripeness, fruits were harvested 
using nitrile gloves and sterile whirl pak bags to maintain sterility.  Fruits were taken to the 
UMD PLSC Plant Science building, and in the food safety lab then had their pictures taken to 
account for surface area later on.  Fruits were first placed in 30mL of 5% methanol/95% DI 
water and were placed on a shaker for 2 hours at 200 rotations per minute (rpm).  Halfway 
through the collection, fruits were rotated to ensure maximum surface area coverage.  After the 
initial wash, the tomato fruits were dried and transferred to new whirl pak bags in a second 100% 
ethanol wash at 200rpm for 2 hours in order to maximize the collection of the fatty acid profiles 
42 
 
for the tomato fruit surfaces.  PGPR+ group surface wash samples n= 57 (Amish Paste n=12, 
Black Icicle n=10, Emerald Evergreen n=8, Green Zebra n=11, Purple BumbleBee n=9, White 
Tomesol n=7).  PGPR+ group color/texture samples n= 43 (Amish Paste n=7, Black Icicle n=9, 
Emerald Evergreen n=7, Green Zebra n=7, Purple BumbleBee n=6, White Tomesol n=7). 
 2.2 Plant Growth Promotion Analysis 
Two additional investigations were done for the comparison between PGPR+ (the group of 
plants inoculated with PGPR) and PGPR- (the group of plants not inoculated with PGPR).  The 
first was simply to measure for plant growth promotion and the second was to analyze for leaf 
chlorophyll analysis.  In order to test for plant growth promotion, plants were harvested just 
before flower formation began (approximately 6 weeks after planting).  Tomato plants were cut 
directly at the base of the stem and wrapped in pre-weighed aluminum foil to minimize water 
loss.  Then plant samples were weighed with both the foil wrappings and the plant samples 
together.  Samples and their assigned foil wrappings were then placed in large ovens in the plant 
science building and dried at 700 C for 20 hours before finally being weighed once more in dried 
plant samples with their respective foil wrappings.  This allowed us to calculate the final fresh 
weights and dry weights of each sample.   
2.3 Additional Methods and Materials Notes 
The methods and materials for the tomato growth conditions (Chapter 3 section 2.1), microbial 
analysis (Chpt. 3, 2.3), color/texture analysis (Chpt. 3, 2.2), total sugar quantification (Chpt. 3, 
2.4), fatty acid GCMS analysis (Chpt. 3, 2.6), and citric acid (Chpt. 3, 2.5) analysis for both the 
non-PGPR inoculated group and the PGPR-inoculated group remained the same as in Chapter 3. 
3. Results 
3.1 Fresh Weight Dry Weight Analysis 
43 
 
Prior to fresh weight and dry weight growth promotion analysis, Pseudomonas PGPR 
establishment in the rhizosphere of the PGPR+ plant group was confirmed by recording 
Pseudomonas colony growth on TSA-rif plates in the tomato root rinses.  Although there was no 
significant difference between the PGPR+ and PGPR- dry weight across all cultivars, the 
difference approached significance (p= 0.085).  For fresh weight analysis, there was a significant 
difference between the two groups which the inoculated group had higher fresh weight (p<0.01) 
(Figure 13).  
 
Figure 13.  Average fresh weight and dry weight of heirloom plants inoculated (PGPR+) and 
uninoculated (PGPR-) with PGPR Pseudomonas sp. at 6 weeks post-germination.  Error bars 
indicate stnd error.  Asterisks indicates significant difference. (p</=0.0857) 
 
44 
 
When looking at the individual cultivars, rhizosphere colonization with PGPR appeared to 
promote plant growth as indicated by fresh weights of cultivars AP, EE, GZ, and WT, but growth 
promotion in dry weight was only recorded for cultivars BI, EE, and WT (Figure 14).
 
Figure 14. Average fresh weight and dry weight of both PGPR+ and PGPR- heirloom tomato 
plants by cultivar at 6 weeks.  Error bars indicate standard error.  Asterisk indicates significant 
difference (p<0.05). 
3.2 Microbial Analysis 
In terms of the microbial association with the fruit surface washes for the heirloom cultivars, we 
recorded a statistically lower level of Salmonella across all of the heirloom varieties compared to 
the modern varieties (p< 0.001) (Figure 15). 
45 
 
 
Figure 15. Analysis of Salmonella growth on exudate washes of Heirloom varieties with and 
without PGPR. Error bars indicates stnd error.  Asterisk indicates significant differences. 
(p<0.05) 
 
Breaking down the data by individual cultivar, I analyzed the impact of PGPR inoculation on 
Salmonella outcomes, in a one way t-test,.   Cultivars BI and WT, demonstrated lower 
Salmonella association in the treated group compared to the non-inoculated group (p<0.05).  
Additionally, cultivars Ap (p=0.08), EE (p=0.1) and GZ (p=0.1) approached significantly lower 
Salmonella growth in the tretaed group compared to the untreated group (Figure 16) 
46 
 
 
Figure 16. Analysis of Salmonella growth on exudate washes within Heirloom varieties PGPR+/-
. Error bars indicate stnd error.  Asterisks indicate significant differences. (p</=0.05)  
 
3.3 Sugar Analysis 
Similarly to the previous chapter, we investigated the phytochemical tomato fruit surface 
changes caused by the PGPR inoculation starting with the total sugar quantification across all 
cultivars.  While the treated group had lower levels of total sugars in the fruit surface washes, it 
47 
 
was not a statistically significant difference (p=0.119), however removing three outliers (GZ and 
WT/PGPR- and EE/PGPR+) gave a p-value of 0.06 (data not shown). (Figure 17). 
 
 
Figure 17. Analysis of Sugar analysis within Heirloom varieties for both PGPR +/- . Error bars 
indicate stnd error.  Asterisk indicates significant differences. (p<0.05) 
 
Assessing the impacts of PGPR treatment by cultivar, the cultivars BI (p<0.01) had lower total 
sugars in the treated group compared to the untreated group.  No other cultivar showed any 
significant differences (Figure 18). 
48 
 
 
 
Figure 18. Analysis of Sugar analysis within Heirloom varieties for both PGPR +/-. Error bars 
indicate stnd error.  Asterisks indicate significant differences. (p<0.05) 
 
3.4 Citric Acid Analysis 
Another comparison was made between the PGPR+/- treated groups based on the content of 
citric acid in the fruit surface washes.  We observed a significant difference in the citric acid 
49 
 
levels where the group treated with PGPR had a lower level of citric acid compared to the 
untreated group (p<0.001) (Figure 19). 
 
Figure 19. Average citric acid of fruit surface washes for PGPR+ and PGPR- treated heirloom 
tomato plants.  Error bars indicate standard error.  Asterisk indicates significant difference 
(p<0.05). 
 
Breaking down data by individual cultivars, every heirloom cultivar, other than cultivar PBB, 
demonstrated significantly lower citric acid levels in the treated group compared to the untreated 
group (p<0.05) (Figure 20). 
50 
 
 
 
Figure 20. Average citric acid of fruit surface washes for PGPR+ and PGPR- treated heirloom 
tomato plants across cultivars.  Error bars indicate standard error.  Asterisk indicates significant 
difference (p<0.05). 
 
3.5 Fatty Acid Analysis 
The largest comparison in this research project was comparing the fatty acid levels between the 
PGPR+/- groups.  We first looked at the fatty acid levels of each peak identified (myristic acid, 
51 
 
hexadecanoic acid, linoleic acid, linolenic acid, stearic acid, erucic acid, and arachidic acid) in 
the GCMS spectra across all heirloom cultivars.  We observed that the levels of the unsaturated 
fatty acids linoleic acid and linolenic acid (both p<0.05), and the saturated fatty acids myristic 
(p<0.05), stearic (p=0.06) and palmitic (p=0.078) acids were all higher in the treated group 
compared to the untreated group.  All other fatty acid levels showed no significant differences 
across all heirloom cultivars (Figure 21). 
 
52 
 
Figure 21. Average fatty acids of fruit surface washes for PGPR+ and PGPR- treated heirloom 
tomato plants.  Error bars indicate stnd error.  Asterisks indicate significant difference 
(p</=0.078). 
 
For the saturated fatty acids, cultivar AP showed higher myristic (p=0.07) acids in the PGPR 
treated group, and cultivar EE showed higher hexadecanoic acid, stearic acid, and arachidic acid 
(all p<0.01)  in the PGPR treated group.  All other saturated fatty acids for the other cultivars 
exhibted no significant differences (Figure 22). 
 
 
Figure 22. Average saturated fatty acids of fruit surface washes for PGPR+ and PGPR- treated 
heirloom tomato plants across cultivars.  Error bars indicate stnd error.  Asterisks indicates 
significant difference (p<0.05). 
 
53 
 
In the unsaturated fatty acids group, cultivar EE had higher levels of linoleic acid (p<0.01) in the 
treated group while cultivar PBB had higher levels of linolenic acid (p<0.05) in the treated group 
compared to the untreated group.  Cultivars AP, EE (both (p=0.08) and BI (p=0.098) showed a 
weak significant difference for linolenic acid in which the treated group had a higher level 
compared to the untreated group. All other cultivars had no significant differences between the 
unsaturated fatty acid levels (Figure 22). 
 
 
Figure 23. Average unsaturated fatty acids of fruit surface washes for PGPR+ and PGPR- treated 
heirloom tomato plants across cultivars.  Error bars indicate stnd error.  Asterisks indicates 
significant difference (p</=0.08). 
54 
 
 
Finally, we investigated the monounsaturated fatty acid, erucic acid, in which only cultivar EE 
demonstrated higher levels of erucic acid (p<0.01) in the treated group compared to the untreated 
group.  All other cultivars failed to show any significant difference between the treated and 
untreated groups (Figure 23). 
 
 
Figure 24. Average monounsaturated fatty acid levels of fruit surface washes for PGPR+ and 
PGPR- treated heirloom tomato plants across cultivars.  Error bars indicate stnd error.  Asterisks 
indicates significant difference (p<0.05). 
 
55 
 
3.6 Relationship between phytochemicals in fruit washes and Salmonella growth 
Employing a regression model with the phytochemical metabolites to investigate the variation in 
Salmonella growth, we included sugars, citric acids, and fatty acids for both PGPR+/- groups. 
For the PGPR- group, the regression model explained 34% of the Salmonella variation 
significantly (R^2=0.34, p<0.01) with citric acid, sugars, and linolenic acid (p<0.05) being 
positively correlated with microbial growth, and hexadecanoic acid being negatively correlated 
with microbial growth (p<0.05).  Meanwhile for the PGPR+ regression model, the model could 
explain 17% of the Salmonella variation weakly significantly (R^2=0.17, p=0.08) with stearic 
acid being positively correlated with microbial growth (p<0.05) and both myristic acid and 
hexadecanoic acid being negatively correlated with microbial growth (p<0.05) (Table 2 
Appendix). 
 
3.7 Color and Texture Analysis 
The final component of this investigation was a comparison between the PGPR treated and 
untreated groups in regards to the tomato fruit color and texture values.  First, we 
looked at color scale values across all cultivars, we found no significant differences in Hue, 
Chroma, or Lightness between the PGPR+/- groups. (Figure 25) 
56 
 
 
Figure 25. Analysis of color scale values between PGPR+/-. Error bars indicate stnd error.  
Asterisk indicates significant differences. (p<0.05) 
 
Breaking down the data by cultivar, ?Lightness? was significantly lower in the PGPR treated 
groups for cultivars GZ and PBB.  Color value ?Chroma? was lower for PGPR treated groups for 
cultivars BI, GZ, and PBB, and value ?Hue? was higher in cultivar EE. (p<0.05) (Figure 26). 
 
 
57 
 
 
Figure 26. Analysis of color scale values between PGPR+/- groups within cultivars. Error bars 
indicate stnd error.  Asterisks indicate significant differences. (p<0.05). 
 
We were able to detect higher stiffness values in the PGPR treated groups across all cultivars 
compared to the untreated groups (p<0.05) (Figure 27). 
58 
 
 
Figure 27. Analysis of texture values between PGPR+/- groups. Error bars indicate stnd error.  
Asterisks indicate significant differences. (p<0.05). 
 
Lastly, we compared the differences in texture values between the PGPR treated and untreated 
groups for each of the cultivars.  We measured weakly significant higher stiffness (p=0.056) and 
toughness (p=0.086) values in cultivar AP.  We also measured higher stiffness (p=0.088) in the 
treated group of cultivar EE.  All other cultivars did not demonstrate significant differences 
between the treated and untreated groups (p<0.05) (Figure 28). 
59 
 
 
Figure 28. Analysis of texture values between PGPR+/- groups for each cultivar. Error bars 
indicate stnd error.  Asterisk indicate significant differences. (p<0.05). 
 
 
 
3.8 Relationship between color/texture values in fruit washes and Salmonella growth 
Employing a regression model with the phytochemical metabolites to investigate the variation in 
Salmonella growth, we included both color and texture values for both PGPR+/- groups.  For the 
PGPR- group, the regression model explained 18% of the Salmonella variation, but was not 
significant (R^2=0.18, p=0.62).  Meanwhile for the PGPR+ regression model, the model could 
explain 55% of variation significantly (R^2=0.55, p<0.01) with Hue being positively correlated 
with microbial growth (p<0.05), Lightness being negatively correlated with microbial growth 
60 
 
(p<0.05), and firmness being weakly negatively correlated with microbial growth (p=0.052)  
(Table 3 Appendix). 
 
4. Discussion and Conclusion 
4.1 Salmonella Association Discussion 
As previously described in the literature review, the inoculation of PGPR, specifically 
Pseudomonas rhizobacteria, have been known to elicit a multitude of positive changes in 
agricultural plants including abiotic and biotic stress tolerance.  In this chapter, we investigated 
the impact of Pseudomonas on modulating heirloom tomato fruit surface phytochemical profiles 
and the resulting connection to Salmonella association.  Firstly, in, we determined that across all 
cultivars the treated group showed lower Salmonella association, and we also saw that all 
cultivars other than PBB demonstrated at least weakly significantly lower microbial association.  
With the knowledge of what cultivars and to what degree the inoculation of these tomato plants 
with PGPR occurred, we can address other variables that the PGPR inoculation had on the 
tomato plants and the properties on the tomato fruit surfaces that could help explain these 
differences. 
 
4.2 PGPR Growth Promotion, Color Texture Discussion 
We then wanted to measure if there was an actual impact on the plant growth to the six different 
cultivars in order to determine if there was indeed an induced response from the plants and 
subsequent plant growth.  Interestingly, we saw plant growth promotion in the PGPR treated 
group for either or both fresh and dry weights for every cultivar except PBB.  Most cultivars 
showed fresh weight growth, and cultivar EE showed the most fresh weight and dry weight 
61 
 
growth.  Cultivar BI was the only one that showed only dry weight growth promotion and not 
fresh weight growth promotion. It is possible that there were issues fully drying the plant weights 
in the ovens, leading to inconsistent data there.  Overall, though it depends on the cultivar, we 
did see growth promotion from the PGPR for most plants.  Another component to consider is 
how the PGPR impacted the fruit surface color and texture qualities.  Across all cultivars, the 
PGPR treatment did not alter color scale values, but it did result in higher stiffness.  Within the 
cultivars, we saw that cultivars PBB and GZ with the PGPR treatment had lower Lightness and 
Chroma levels.  Additionally, cultivar BI showed lower Chroma levels while cultivar EE 
demonstrated higher Hue levels in the PGPR treated group.  Within cultivars for the texture 
values, only cultivars AP and EE demonstrated higher stiffness values in the PGPR treated 
group. Furthermore, regression analysis only showed significance for the PGPR+ group where 
Hue was positively correlated with Salmonella growth and Lightness and firmness were 
negatively correlated with microbial growth.  This data suggests the inoculation of tomato plants 
with PGPR Pseudomonas could potentially modulate pigmentation metabolites (Marvasi et al; 
2014) such as anthocyanins and carotenoid levels such as lycopene (Zameer et al; 2016), which 
could explain the lower lightness and chroma levels in some of the PGPR inoculated cultivar, 
and the higher hue level in the cultivar EE inoculated group.  This could also be related to 
reduced Salmonella association as anthocyanins and lycopene have demonstrated anti-microbial 
properties (Hraishawi et al; 2020, Ma et al; 2019).  Only one previous study has investigated the 
use of PGPR on the firmness of tomato fruits and they also observed increased firmness in the 
inoculated group compared to the non-inoculated group and suggested that ethylene modulation 
from the PGPR impacting ethylene pathways in the plant could hypothetically be the cause 
(Mena-Violante & Olalde-Portugal, 2007). 
62 
 
 
4.3 Role of Sugars and Citric Acid in Salmonella-tomato interaction 
 Some of the phytochemical metabolites modulated by the inoculation of PGPR studied were 
total sugars and citric acid,.  While across all cultivars, total sugars were not significantly 
decreased by the PGPR, we do see that at least for cultivar BI (which was also less impacted in 
plant growth promotion), that total sugars were reduced, which could partially explain the 
decrease in Salmonella association as a means of reducing available nutrients for continued 
persistence. Although our study looked at total sugars, Salmonella is known to have a preference 
for glucose compared to other sugars present.  It is possible that different cultivars exuded a 
higher level of glucose compared to other sugars in the fruit surfaces washes, which could 
hypothetically explain the differences in correlations.  Meanwhile for citric acid, we observed 
decreased citric acid in the surface washes across all cultivars except for cultivar PBB (which 
was not impacted in terms of plant growth).  This aligns with the impact of PGPR on plant 
growth and citric acid reduction.  Regression analysis for PGPR+/- groups showed positive 
correlation between sugars/citric acid and microbial growth only in PGPR- group.  Citric acid at 
high levels have shown anti-microbial properties for Salmonella (Jeanne-Marie et al; 1997) (Al-
Nabulsi at al; 2014).  It is possible that at lower levels Salmonella could be utilizing citric acid 
that gets converted to citrate to metabolize as a nutrient source, explaining the positive 
correlation (Wynosky-Dolfi at al; 2014).  The lack of correlation and lower levels of citric acid 
in the PGPR inoculated group could be a result of metabolic changes from the PGPR, but this is 
contrary to previous findings of increased citric acid in tomato fruits with PGPR inoculation 
(Gonz?lez Rodr?guez et al; 2018) (Kalozoumis et al; 2021).  It is possible that our work with 
63 
 
different PGPR strains and investigations with heirloom tomato varieties, as well as focusing just 
on the tomato surface contributed to different findings.  
 
4.4 Fatty Acids Discussion 
Fatty acids in previous studies were seen to be correlated with negative Salmonella growth for 
tomato fruits.  For our PGPR analysis across all cultivars, we found that the unsaturated linoleic 
and linolenic acids, as well as the saturated myristic acid, hexadecanoic acid, and stearic acid 
were all in weakly significant higher accumulation for the PGPR treated group compared to the 
untreated group.  Looking at the individual cultivars, cultivar EE demonstrated the highest 
accumulation of fatty acids, while cultivar AP had an increase in stearic acid, and PBB had an 
increase in linolenic acid.  Cultivar EE demonstrated the highest Salmonella association in PGPR 
uninoculated plants and a significant reduction in Salmonella favorability when plants were 
inoculated with PGPR.  This cultivar also had the greatest changes in fatty acid profiles, 
suggesting that the lower the initial fatty acid levels were more strongly induced by PGPR and 
may have contributed to reducing microbial association on the tomato fruit surface.  Regression 
analysis demonstrated a positive correlation for linolenic acid with microbial counts and a 
negative correlation with hexadecanoic acid with microbial counts in the non-PGPR group.  For 
the PGPR-inoculated group, regression analysis showed stearic acid being positively correlated 
with microbial growth and both myristic and hexadecanoic acids being negatively correlated 
with microbial growth.  Once again, we see that the impact of PGPR differs between cultivars.  
In some of these cultivars, and perhaps in even some of the individual sample batches of tomato 
fruits, there was more of an increase in certain fatty acid accumulations that resulted in reduced 
Salmonella growth.  Unfortunately sample sizes were too small to do regression analysis on each 
64 
 
individual cultivar for both PGPR+/- groups.  Within both PGPR treated and untreated groups, 
hexadecanoic acid was negatively associated with Salmonella growth.  For the PGPR-treated 
group, it is possible the inoculation of PGPR induced an increase in myristic acid that provided 
an additional inhibitory effect to Salmonella and that the PGPR induced a large enough increase 
in hexadecanoic acid to counter the supportive effect of the stearic acid induced increase.  
 
 
4.5 Conclusion 
Across all of our studies, it appears the impact of PGPR Pseudomonas inoculation in tomato 
plants on their fruit surface depends on the cultivar and the phytochemical metabolite.  For 
example, PGPR didn?t have an impact on fresh weight growth promotion for cultivar BI, but the 
application of PGPR did reduce sugar levels and Salmonella association.   This means that 
compared to other cultivars, BI may have increased dark-colored anthocyanin content (resulting 
in reduced Chroma) and reduced the release of sugars into the surface wash from the application 
of PGPR, thus limiting Salmonella growth.  However, the application of PGPR impacting plant 
growth promotion successfully for the cultivars also aligned with reduction in citric acid levels 
for the treated cultivars, where all except cultivar PBB had both impacted by PGPR treatment.  
Meanwhile, other cultivars like EE demonstrated increased plant growth promotion as well as 
most of the fatty acids increased in accumulation, suggesting a method of increased antagonistic 
metabolites to limit Salmonella association.  The induced systemic responses from PGPR on 
tomato plants are not entirely known, and with the variety in heirloom varieties in their size, 
coloration, and inherent phytochemical profile differences, it appears that PGPR impacts these 
different cultivars in different ways.  Some of these alterations could by limiting metabolites that 
65 
 
Salmonella can synthesize and use as nutrients to persist, or by means of increasing metabolites 
that would impede upon Salmonella synthesis of nutrients, thus limiting their persistence on the 
fruit surface washes.  Much of the variation from the regression analysis could not be explained 
from the metabolites and color/texture values investigated here, meaning that much of the 
Salmonella association seems to be from other metabolites than what was investigated here.  
Complicating our data analysis further is that much of the regression analysis could not be run 
within the cultivars due to small sample sizes.  Future investigations would do well to focus on 
anti-microbial metabolites that could be increased from PGPR such as carotenoids, anthocyanins 
and other VOCs that could limit Salmonella growth, and to focus on the direct genetic impacts of 
PGPR on these synthesis pathways.  Additionally, greater success with PGPR in reducing 
Salmonella could be achieved in using different species of PGPR, or even a co-inoculum of 
multiple species for greater symbiosis. 
 
 
 
 
 
  
66 
 
Chapter 5: Conclusions and Future Directions 
The purpose of this research was divided into two main sections.  In chapter 3, we investigated 
the correlations between the phytochemical profiles of the fruit surfaces of heirloom and modern 
tomato varieties as well as some of the impacts of fruit surface color and texture qualities.  We 
determined that the heirloom varieties supported a lower level of Salmonella compared to the 
modern varieties (p=0.06), yet the heirloom varieties contained larger levels of sugars and citric 
acids that were themselves correlated with higher Salmonella suggesting that other metabolites 
or factors may play a more important role in the differences in microbial association.  Some of 
the variation within the heirloom varieties proved puzzling such as the cultivar EE which had 
similar sugar levels as other cultivars but was far more favorable to Salmonella.  Some of this 
variation can be explained by differences in citric acid levels, fatty acids, and to some degree 
differences in coloration levels that differed from other cultivars such as BI and PBB that were 
less favorable to Salmonella. Another factor between heirloom and modern cultivars could be 
that the heirloom varieties may have had higher or lower levels of anthocyanins or terpenoids 
present compared to the modern varieties, but these metabolites were not measured in this 
research.  While the modern varieties were grown in large flow tunnels, the heirloom varieties 
were often crowded together in small tables in the greenhouse, potentially resulting in volatile 
compounds from the glandular trichomes rubbing off on the heirloom fruit surface, which could 
in part explain some of the differences in Salmonella growth as well.  Another factor could be 
that the heirloom varieties (being typically smaller in surface area compared to the modern 
varieties) could have had higher levels of stiffness and firmness, resulting in lesser Salmonella 
association, but coloration and texture data was not measured for the modern cultivars.  Finally, 
fatty acids were not measured in the modern varieties, and it is possible that certain fatty acids 
67 
 
were higher in heirloom cultivars, but again these were not measured for modern varieties.  
Future studies when looking at the phytochemical profiles of heirloom and modern varieties 
would do well to analyze some of these blind spots we encountered in this study.  In chapter 4, 
we analyzed the impact PGPR Pseudomonas had on modulating the phytochemical profile of 
various tomato fruits as well as the impact on color and texture quality, and the resulting impacts 
of Salmonella association.  Similarly to the non-PGPR analysis in chapter 3, we found a large 
degree of variation in the heirloom cultivars. Furthermore, we found a trend where the cultivars 
that demonstrated more increased plant growth promotion from the PGPR treatment also 
demonstrated some of the more exaggerated alterations in metabolite accumulation.  We found 
total sugars to be weakly positively correlated with Salmonella growth, and we also found citric 
acid to be positively correlated with Salmonella growth.  Meanwhile, we found that some fatty 
acids (specifically hexadecanoic acid in both treatment groups and myristic acid in the PGPR-
treated group) were associated with inhibited Salmonella growth.  The inoculation of PGPR 
resulted in a small degree of sugar reduction and a reduction in citric acid as well as slight 
increases in certain fatty acids (depending on the cultivar), reinforcing the idea that not only are 
sugars and citric acid beneficial to Salmonella growth while some fatty acids are inhibitory, but 
that PGPR can induce a systemic response in tomato fruits that limit favorable metabolites for 
Salmonella while increasing unfavorable metabolites.  Additionally, the PGPR treatment 
appeared to increase the stiffness of fruit surfaces, which could result in higher fatty acids 
accumulating in the tomato fruit surfaces and reducing available sugars and citric acids.  Oddly 
enough, the inoculation of PGPR appeared to impact different cultivars in different ways.  While 
most cultivars demonstrated increased plant growth, cultivar PBB (the only cherry variety) did 
not demonstrate different plant growth promotion.  The fatty acid levels of this cultivar also did 
68 
 
not change from the inoculation, but this cultivar also had some of the highest fatty acid levels 
without the inoculation.  Meanwhile cultivar EE, which had some of the lowest fatty acid levels 
without the PGPR inoculation demonstrated some of the most universally dramatic increases in 
fatty acids.  It is possible that there may be a threshold in which how much metabolites can be 
altered in the tomato fruit surfaces when inoculated with PGPR.  Some of these changes could 
also be increasing pigment molecules that could be inhibitory to Salmonella.  Future studies 
would do well to investigate more clearly some of the metabolites not measured in modern 
cultivars and to go further to investigate some of the potential inhibitory impacts of terpenoids, 
volatile compounds, and anthocyanins both presumably present to varying degrees in diverse 
heirloom varieties and modern varieties.  Connecting the impact of PGPR on these specific 
metabolites for both heirloom and modern varieties may be able to help explain more of the 
variation seen in Salmonella growth.  What could also improve some of the PGPR results seen in 
this study could be to do a co-inoculum with other microbe or fungal PGPR varieties, or to try 
several different individual strains to see if certain symbiotic relationships would work better 
than others.  These results ultimately shed light on some of the complex relationships between 
enteric human pathogens, plant hosts, human health, and symbiotic microbes, and are the first to 
include and focus on heirloom tomato varieties.  While more research is needed, this work helps 
pave the way for potential genetic breeding programs, and organic means of introducing 
biofertilizer rhizobacteria into agricultural practices to modulate the phytochemical profiles of 
tomato fruits to reduce Salmonella association at a pre-harvest stage, ultimately reducing 
foodborne illness outbreaks, improving the state of agriculture, and helping to build a better 
world. 
  
69 
 
Appendix 1: Supplementary tables  
 
Table 1. Regression analysis using sugars and citric acid as variables to explain Salmonella 
variation between modern and heirloom cultivars. 
 
 
 
 
Table 2. Regression analysis using sugars, citric acid, and fatty acids as variables to explain 
Salmonella variation between PGPR+/- groups. 
 
 
 
 
 
70 
 
 
Table 3. Regression analysis using color and texture values as variables to explain Salmonella 
variation between PGPR+/- groups. 
 
71 
 
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