Diagnostic Application of Fatty Acid Methyl Ester (Fame) Analysis for the Identification of Meloidogyne Species

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Diagnostic Application of Fatty Acid Methyl Ester (Fame) Analysis for the Identification of Meloidogyne Species
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Sekora, Nicholas Scott
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Doctorate ( Ph.D.)
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University of Florida
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Entomology and Nematology
Committee Chair:
Crow, William T
Committee Members:
Mcsorley, Robert
Dickson, Donald W
Giblin-Davis, Robin M
Kenworthy, Kevin E
Harmon, Phillip

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biochemistry -- fame -- identification -- meloidogyne -- root-knot
Entomology and Nematology -- Dissertations, Academic -- UF
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Entomology and Nematology thesis, Ph.D.
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Abstract:
Previous studies have indicated that fatty acid methyl ester (FAME) analysis has the potential to be used as a diagnostic tool for diagnostic nematode identification.  Four experiments were carried out from May 2010 to April 2012 to evaluate field-based applications, environmental influence, extraction and analysis methods, and detection limits on FAME analysis of Meloidogyne species.  Utilizing Solanum lycopersicum root tissue samples infected with M. arenaria, M. hapla, M. incognita, or M. javanica, FAME analysis was able to separate the four nematode-infected tissues from each other and uninoculated tissue (D2 > 14.08, P 0.0205).  To assess the effect of varying temperatures on nematode FAME profiles, populations of M. incognita and M. javanica were maintained on S. lycopersicum in three diurnal environments and two fixed-temperature environments.  Temperature did not have a significant impact on FAME profiles of M. incognita-infected tissue (D2 5.69, P > 0.3192) or uninoculated S. lycopersicum tissue (D2 3.13, P > 0.1006) sustained in three diurnal environments, but did influence M. javanica-infected tissue (D2 > 27.64, P M. incognita- and M. javanica-infected tissues maintained at 20°C and 26°C became more distinct over 135 days (D2 > 91.83, P 0.0151), but these infected tissues could not be differentiated at 20°C (D2 = 43.27, P = 0.2221).  A comparison of FAME extraction and analysis methods determined Instant FAME extraction and Rapid analysis methods produced more robust and reliable FAME profiles (D2 > 25.08, P 2 = 2.95, P = 0.9999) and reduced the sample size and time required for analysis.  By assessing FAME analysis of M. graminis females at densities of 1, 2, and 5 individuals, single males, and single juveniles, it was possible to calculate the predicted response of a single nematode and establish a preliminary regression (Response = 13,019*(Number) – 10,827; R2 = 0.5928, P ) that could potentially be used to quantify nematodes in a sample.  These experiments indicate that further development of FAME analysis for diagnostic identification of Meloidogyne species should be considered as an alternative to morphological or molecular methods.
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by Nicholas Scott Sekora.
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Thesis (Ph.D.)--University of Florida, 2012.
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1 DIAGNOSTIC APPLICATION OF F ATTY ACID METHYL ESTER (FAME) ANALYSIS FOR THE IDENTIFICATION OF MELOIDOGYNE SPECIES By NICHOLAS SEKORA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FUL FILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012

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2 2012 Nicholas Sekora

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3 Dedicated to all of the aspiring Jedi Knights who look forward to the challenges life holds for them

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4 ACKNOWLEDGEMENTS I would like to thank my director (Dr. Billy Crow), the Academy (Dr. Don Dickson, Dr. Robin Giblin Davis, Dr. Phil Harmon, Dr. Kevin Kenworthy, and Dr. Bob McSorley), and the many supporting actors who helped with this project: Tom Bean for his exceptional driving and dynamic research skills, Dr. Janete Brito for her endlessly positive research advice, Dr. Tesfa Mekete for his priceless guidance and teaching skills, Chelsea Proia for always being a willing grunt worker, David Sekora for h is epic comedic relief and assistance, Stephanie Stocks for reminding me h ow far I have come from the start of my graduate career the entire front office staff (Debbie, Elena, Glinda, Kay, Linda, Maria, Nancy, Nick, Pam, Pamela, Paul, Ruth, and Steve) for always bailing me out of administrational red tape, and the many many other people too numerous to name who have supported me these last three years. I would also like to thank my domestic partners (Tony and Christine) for making the life of a graduate s tudent bearable by being the best family anyone could ask for. Finally, I want to thank meu amor, Vanessinha : Meu amor, voc significa para mim mais do que as riquezas de todos os reinos do passado, do presente e daqueles que ainda esto por vir. Voc me apoiou durante o perodo mais difcil de minha vida. Palavras no podem expressar minha gratido. Este ttulo s foi possvel com seu amor.

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5 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ............................... 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 12 LIST OF ABBREVIATIONS ................................ ................................ ........................... 1 4 ABSTRACT ................................ ................................ ................................ ................... 15 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 17 1.1 Introduction ................................ ................................ ................................ ....... 17 1.2 Nucleic Acid Sequence Analysis ................................ ................................ ....... 18 1.2.1 Polymerase Chain Reaction (PCR) ................................ ......................... 19 1.2.2 Methods Utilizing PCR ................................ ................................ ............. 21 1.2.1.1 Restriction fragment length polymorphisms (RFLP) ....................... 21 1.2.1.2 Real time quantitative PCR (qPCR) ................................ ............... 22 1.2.1.3 DNA barcoding using molecular operational taxonomix units (MOTUS) ................................ ................................ ................................ 23 1.2.1.4 Denaturing gradient gel electrophoresis (DGGE) ........................... 24 1.3 Biochemical Assays ................................ ................................ .......................... 25 1.3.1 Proteins ................................ ................................ ................................ ... 25 1.3.2 Enzyme Linked Immunosorbent Assay (ELISA) ................................ ...... 26 1.3.3 Other Methods ................................ ................................ ......................... 26 1.3.3.1 Glycoproteins ................................ ................................ ................. 26 1.3.3.2 Fatty acid methyl ester (FAME) analysis ................................ ........ 27 1.4 Conclusions ................................ ................................ ................................ ...... 27 2 FATTY ACID METHYL ESTER ANALYSIS USED TO IDENTIFY MELOIDOGYNE SPECIES IN SOLANUM L YCOPERSICUM ROOT TISSUE ....... 31 2.1 Introduction ................................ ................................ ................................ ....... 31 2.2 Materials and Methods ................................ ................................ ...................... 32 2.2.1 Fatty Acid Methyl Ester (FAME) Analysis ................................ ................ 32 2.2.2 Experimental Procedures ................................ ................................ ........ 33 2.2.2.1 FAME evaluation of root ti ssue infected with Meloidogyne spp. .... 33 2.2.2.2 Tissue homogenization ................................ ................................ .. 33 2.2.2.3 Fresh versus dried tissue and standard versus co ncentrated samples ................................ ................................ ................................ .. 33 2.2.3 Statistical Analysis ................................ ................................ ................... 34 2.3 Results ................................ ................................ ................................ .............. 36

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6 2.3.1 FAME Evaluation of Root Tissue Infected with Meloidogyne Species ..... 36 2.3.2 Root Tissue Preparation ................................ ................................ .......... 38 2.3.2.1 Tissue hom ogenation ................................ ................................ ..... 38 2.3.2.2 Fresh versus dried tissue and standard versus concentrated samples ................................ ................................ ................................ .. 38 2.4 Discussion ................................ ................................ ................................ ........ 39 3 TEMPERATURE EFFECTS ON FATTY ACID METHYL ESTER PROFILES OF MELOIDOGYNE INCOGNITA AND M. JAVANICA ................................ ................ 54 3.1 Introduction ................................ ................................ ................................ ....... 54 3.2 Materials and Methods ................................ ................................ ...................... 56 3.2.1 Diurnal Experiment ................................ ................................ .................. 57 3.2.1.1 Sample preparation ................................ ................................ ........ 58 3.2.1.2 FAME analysis ................................ ................................ ............... 58 3.2.2 Constant Temperature Exp eriment ................................ ......................... 58 3.2.2.1 Sample preparation ................................ ................................ ........ 59 3.2.2.2 FAME analysis ................................ ................................ ............... 60 3.2.3 Statistical Analysis ................................ ................................ ................... 60 3.3 Results ................................ ................................ ................................ .............. 62 3.3.1 Diurnal Experiment ................................ ................................ .................. 62 3.3.2 Constant Temperature Experiment ................................ ......................... 64 3.3.2.1 FAME profiles at 45 days ................................ ............................... 64 3.3.2.2 FAME profiles at 90 days ................................ ............................... 64 3.3.2.3 FAME profiles at 135 days ................................ ............................. 66 3.4 Discussion ................................ ................................ ................................ ........ 67 4 APPLICATION OF INSTANT FAME FOR IDENTIFICATION OF MELOIDOGYNE SPP. ................................ ................................ ............................ 90 4.1 Introduction ................................ ................................ ................................ ....... 90 4.2 Materials and Methods ................................ ................................ ...................... 91 4.2.1 Methods Evaluated ................................ ................................ .................. 91 4.2.2 Nematode Populations ................................ ................................ ............ 91 4.2.3 Instant FAME and Rapid Analysis Evaluation ................................ ......... 92 4.2.4 Extraction Comparison Using Equal Tissue Mass ................................ ... 92 4.2.5 Statistical Analysis ................................ ................................ ................... 93 4.3 Results ................................ ................................ ................................ .............. 95 4.3.1 Instant FAME and Rapid Analysis Evaluation ................................ ......... 95 4.3.1.1 Standard extraction versus Instant FAME ................................ ...... 95 4.3.1.2 Standard analysis compared to Rapid analysis ............................. 96 4.3.1.3 Extraction \ analysis coupled comparisons ................................ ...... 96 4.3.2 Extraction Comparison Using Equal Tissue Mass ................................ ... 98 4.4 Discussion ................................ ................................ ................................ ........ 99 5 POPULATION DENSITY AND DETECTION OF MELOIDOGYNE SPECIES USING FATTY ACID METHYL ESTER ANALYSIS ................................ .............. 125

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7 5.1 Introduction ................................ ................................ ................................ ..... 125 5.2 Materials and Methods ................................ ................................ .................... 126 5.2.1 Sample Preparation ................................ ................................ ............... 126 5.2.2 Statistical Analysis ................................ ................................ ................. 126 5.3 Results ................................ ................................ ................................ ............ 128 5.4 Discussion ................................ ................................ ................................ ...... 130 APPENDIX A FATTY ACID PEAK NAMING TABLE FOR THE EUKARY METHOD .................. 139 B FATTY ACID PEAK NAMING TABLE FOR THE RTSBA6 METHOD ................... 147 C COMMON NAMES FOR SATURATED FATTY ACIDS ................................ ........ 151 D COMMO N NAMES FOR UNSATURATED FATTY ACIDS ................................ ... 152 E COMMON FATTY ACID STRUCTURES ................................ .............................. 154 LIST OF REFERENCES ................................ ................................ ............................. 156 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 172

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8 LIST OF TABLES Table page 1 1 Selected publications utilizing molecular sequences for nematode identification. ................................ ................................ ................................ ....... 29 2 1 Number of replicates used of Meloidogyne infected Solanum lycopersicum root tissue and con trols for FAME analysis. ................................ ....................... 42 2 2 Mean FAME concentrations (percentage of total response) of root tissue containing Meloidogyne arenaria M hapla M incognita and M javanica versus uninoculat ed Solanum lycopersicum tissue. ................................ ........... 43 2 3 Mahalanobis distances and P values from canonical discriminant analysis of root tissue treatments from FAME analysis. ................................ ....................... 44 2 4 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates separating uninoculated Solanum lycopersicum from tissue infected with Meloido gyne arenaria M. hapla M. incognita and M. javanica ................................ ............. 45 2 5 Mean FAME concentrations of homogenized and whole Solanum lycopersicum ................................ ................................ ..... 46 2 6 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first canonical variate separating Solanum lycopersicum .............. 47 2 7 Mean FAME concentrations of root tissue infected with Meloidogyne javanica, prepared using a combination of fresh/dried root material and standard/concentrated FAME samples. ................................ .............................. 48 2 8 Mahalanobis distances and P values from canonical discriminant analysis of root tissue preparations analyzed by FAME analysis. ................................ ........ 49 2 9 Correlati on values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates separating fresh and dried root tissue infected with Meloidogyne javanica ......................... 50 3 1 Mean FAME concentrations of two nematode species infecting Solanum lycopersicum sue and an uninoculated control maintained in one of three diurnal temperature environments for 60 days. .............................. 70 3 2 Mahalanobis distances and P values from canonical discriminant analysis comparing FAME profiles of root tissue of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an

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9 uninoculated control maintained with diurnal temperature conditions in either a greenhouse, growth room, or shade house for 60 days. ................................ 71 3 3 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates for separating FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoc ulated control maintained with diurnal temperature conditions in either a greenhouse, growth room, or shade house for 60 days. ................................ 72 3 4 Mean FAME concentrations of two nematode species infecting Solanum lycopersicum and an uninoculated control maintained at either 20C or 26C for 45 days. ................................ ................................ ......... 73 3 5 Mahalanobis distances and P values from canonical discriminant analy sis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 45 days. ................. 74 3 6 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates for separating FAME profiles of Solanum lycopersicum in fected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 45 days. ................. 75 3 7 Mean FAME concentrations of two nematode sp ecies infecting Solanum lycopersicum either 20C or 26C for 90 days. ................................ ................................ ......... 76 3 8 Mahalanobis distances and P values from canonical di scriminant analysis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 90 days. ................. 78 3 9 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates for separating FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 90 days. ................. 79 3 10 Mean FAME concentrations o f two nematode species infecting Solanum lycopersicum either 20C or 26C for 135 days. ................................ ................................ ....... 80 3 11 Mahalanobis distances and P valu es from canonical discriminant analysis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 135 days. ............... 83

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10 3 12 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first two canonical variates for separating FAME profiles of Solanum ly copersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 135 days. ............... 84 4 1 Compar ison of FAME extraction steps for standard and Instant FAME methods. ................................ ................................ ................................ ........... 102 4 2 Gas chromatogram parameters required for standard FAME analysis using the EUKARY method and Rapid FAME analysis usin g the RTSBA6 method. 103 4 3 FAME profiles produced by eight combinations of two nematode species, two extraction methods, and two analysis methods. ................................ ............... 104 4 4 Mean FAME concentrations (percentage of total response) of eight combinations of two nematode species infecting root tissue, two extraction methods, and two analysis methods. ................................ ................................ 105 4 5 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first canonical variate separating standard FAME extraction from Instant FAME extraction of Meloidogyne infected root tissue. ................................ ................................ .......................... 108 4 6 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first canonical variate separating standard FAME analysisfrom Rapid anal ysis of Meloidogyne infected root tissue. ................................ ................................ ................................ ............... 109 4 7 Mahalanobis distances and P values from canonical discriminant analysis comparing two nematode species infecting root tissue, two extraction me thods, and two analysis methods. ................................ ................................ 110 4 8 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates for sepa ration of extraction methods and analysis methods using root tissue infected with either Meloidogyne incognita or M. javanica ............................... 111 4 9 Mahalanobis distances and P values from canonical discrimi nant analysis comparing two nematode species infecting root tissue and two extraction methods using Rapid analysis ................................ ................................ ........ 112 4 10 Correlation values between canonical structure of fatty acids sign ificant in the three canonical variates for separating extraction method and root tissue infected with either Meloidogyne incognita or M. javanica ............................... 113 4 11 Mean FAME concentrations of four com binations of two nematode species and two extraction methods utilizing Rapid analysis. ................................ ........ 114

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11 4 12 Mahalanobis distances and P values from canonical discriminant analysis comparing two FAME extrac tion methods on 40 mg of Solenostemon scutellarioides root tissue infected with either Meloidogyne incognita race 2 or M. javanica race 1 utilizing Rapid analysis. ................................ .................. 117 4 13 Mahalanobis distanc es and P values from canonical discriminant analysis comparing two FAME extraction methods on 40 mg Solenostemon scutellarioides root tissue infected with either Meloidogyne incognita race 2 or M. javanica race 1 utilizing Rapid analysis. ................................ .................. 118 4 14 Correlation values between canonical structure and fatty acids selected by truncated stepwise discriminant analysis in the first three canonical variates for separating extraction methods and Solenos temon scutellarioides root tissue infected with either Meloidogyne incognita or M. javanica in 40 mg tissue samples. ................................ ................................ ................................ 11 9 5 1 Mean FAME concentrations of Meloidogyne graminis females at densitie s of 1, 2, or 5 individuals per sample, single juveniles, and individual males. ......... 132 5 2 Mahalanobis distances and P values from canonical discriminant analysis comparing FAME profiles of Meloid ogyne graminis females at densities of 1, 2, or 5 individuals per sample, individual juveniles, and individual males. ........ 134 5 3 Correlation values between canonical structure and fatty acids sele cted by stepwise discriminant analysis in the first three canonical variates for separating FAME profiles of Meloidogyne graminis females, males, and juveniles. ................................ ................................ ................................ .......... 135

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12 LIST OF FIGURES Figure page 2 1 Fatty acid methyl ester (FAME) extraction method described by Sasser (1990). ................................ ................................ ................................ ................ 51 2 2 Canonical distribution of root FAME profile means subjected t o one of five nematode treatments, Meloidogyne arenaria M. hapla M. incognita M. javanica and uninoculated Solanum lycopersicum ................................ ........... 52 2 3 Canonical distribution of root FAME profile means su bjected to one of four preparations, Meloidogyne javanica infected dried roots, standard preparation, M. javanica infected dried roots concentrated preparation, M. javanica infected fresh roots, standard preparation, and M. javanica infected fresh roots, c oncentrated preparation. ................................ ................................ 53 3 1 Instant FAME extraction and Rapid analysis method developed by MIDI (Newark, DE). ................................ ................................ ................................ ..... 85 3 2 Canonic al discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1 or an uninoculated control maintained with diurnal te mperature conditions in either a greenhouse, growth room, or shade house for 60 days. ................................ 86 3 3 Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Sol anum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 45 days. ................. 87 3 4 Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at eit her 20C or 26C for 90 days. ................ 88 3 5 Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Solanum lycopersicum infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 135 days. ............... 89 4 1 Canonical distribution comparing M. javanica infected tomato root tissue FAME profiles to M. incognita infected tissue using either standard FAME extraction or Instant FAME extraction in combination with either Rapid FAME analysis or standard analysis. ................................ ................................ ........... 121

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13 4 2 Canonical distribution comparing Meloidogyne javanica infected tomato root tissue FAME profiles to M. incognita infected tissue using either standard FAME extraction or Instant FAME extraction. ................................ ................... 122 4 3 Canonical discriminant analysis after full stepwise discriminant analysis comparing 40 mg of Meloidogyne javanica infected Solenostemon scutellarioides root tissue FAME profiles to 40 mg of M. incognita infected tissue using eithe r standard FAME extraction or Instant FAME extraction. ...... 123 4 4 Canonical discriminant analysis after truncated stepwise discriminant analysis comparing 40 mg of Meloidogyne javanica infected S olenostemon scutellarioides root tissue FAME profiles to 40 mg M. incognita infected tissue using either standard FAME extraction or Instant FAME extraction. ...... 124 5 1 Instant FAME extraction an d Rapid analysis method developed by MIDI (Newark, DE). ................................ ................................ ................................ ... 136 5 2 Regression of predicted FAME response against increasing numbers of Meloidogyne graminis females per sample. ................................ ..................... 137 5 3 Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Meloidogyne graminis females at densities of 1, 2, or 5 individuals per sample, individual males, and indiv idual juveniles. ........ 138

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14 LIST OF ABBREVIATION S DGGE Denaturing gradient gel electrophoresis ELISA Enzyme linked immunosorbent assay FAME Fatty acid methyl ester I2 Meloidogyne incognita race 2 I3 Meloidogyne incognita race 3 J1 Meloidogyne javanica race 1 PCR Polymerase chain reaction Q PCR Real time quantitative PCR RA Rapid FAME analysis RE Instant FAME extraction RFLP Restriction fragment length polymorphism SA Standard FAME analysis using EUKARY method SE Standard FAME extr action method

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15 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DIAGNOSTIC APPLICATION OF FATTY ACID METHYL ESTER ( FAME ) ANALYSIS FOR THE IDENTIFICATION OF MELOIDOGYNE SPECIES By Nicholas Sekora December 2012 Chair: William T. Crow Major: Entomology and Nematology Previous studies have indicated that fatty acid methyl ester (FAME) analysis has the potential to be us ed as a diagnostic tool for diagnostic nemato de identification. Four experi ments were carried out from May 2010 to April 2012 to evaluate field based applications, environmental influence, extraction and analysis methods, and detection limits on FAME anal ysis of Meloidogyne species. Utilizing Solanum lycopersicum root tissue samples infected with M. arenaria M. hapla M. incognita or M. javanica FAME analysis was able to separate the four nematode infected tissues from each other and uninoculated tissu e (D 2 > 14.08, P < 0.0205). To assess the effect of varying temperatures on nematode FAME profiles, populations of M. incognita and M. javanica were maintained on S. lycopersicum in three diurnal environments and two fixed temperature environments. Tempe rature did not have a significant impact on FAME profiles of M. incognita infected tissue (D 2 < 5.69, P > 0.3192) or uninoculated S. lycopersicum tissue (D 2 < 3.13, P > 0.1006) sustained in three diurnal environments but did influence M. javanica infected tissue (D 2 > 27.64, P < 0.0001). FAME profiles of M. incognita and M. javanica infected tissues maintained at 20C and 26C became more distinct over 135 days (D 2 > 91.83, P < 0.0151), but these infected tissues could not be

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16 differentiated at 20C (D 2 = 43.27, P = 0.2221). A comparison of FAME extraction and analysis methods determined Instant FAME extraction and Rapid analysis methods produced more robust and reliable FAME profiles (D 2 > 25.08, P < 0.0001) than standard methods (D 2 = 2.95, P = 0.9999) and reduced the sample size and time required for analysis. By assessing FAME analysis of M. graminis females at densities of 1, 2, and 5 individuals, single males, and single juveniles, it was possible to calculate the predicted response of a single nema tode and establish a preliminary regression ( Response = ) that could potentially be used to quantify nematodes in a sample. These experiments indicate that further development of FAME analysis for diagnosti c identification of Meloidogyne species should be considered as an alternative to morphological or molecular methods.

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17 CHAPTER 1 LITERATURE REVIEW 1.1 Introduction DIagnotic strategies for nematode manangement rely heavily on accurate identification of nem atodes present either in soil or plant material. Management can vary greatly based on the genus, species, or, in some cases, host race present. For example, i n the southern United States where cotton peanut and soybean are planted, identification of Me loidogyne species and host races is critical to make a ccurate recommendations for nematicide application, crop rotation, and other management practices (Kirkpatrick and Sasser, 1984; Rodrguez Kbana et al. 1992). In peanut growing regions of Florida, it is essential to identify the species of Meloidogyne species present in a field because both M. arenaria and M. javanica have been shown to infect peanut (Ce tintas et al ., 2003). Additionally, if M. javanica is present, it is important to determine the ph ysiological race or races of the population since races 3 and 4 have demonstrated the ability to infected peanut while races 1 and 2 cannot (Lima et al. 2002). To date no identification methods have been published that can identify species at the physiol ogical race level consistently. Therefore, m any of the molecular nematode identification methods developed are tageted toward species identificaition. Identification of nematode species has been evolving rapidly over the last 20 years. Identification bas ed strictly on morphological methods can range from easy to seemingly impossible depending on the identification resolution desired. For many nematodes, identification to genus (and some species) can be accomplished by visual inspection, such as with Iron us spp. and Longidorus spp However, identification using morphological means requires intense training the use of nematode extraction method s

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18 specific to the habitat of the nematodes and processes that can be time consuming and sometimes labo r intensiv e. With the development of molecular identification methods, investigators are not required to recognize minute morphological characteristics of nematodes, identification is more accurate, and more in depth studies of phylogeny and evolution can be perform ed. However, familiarity with the procedures used is still required. These methods may also be tedious and demand specialized equipment that is not always readily available to some laboratories. This paper is a review of the molecular and biochemical me thods most commonly used in the last 20 years to identify nematode species. These can be broken down into two primary categories: nucleic acid sequence analys e s and methods utilizing specific biochemical components like protein electrophoresis and fatty a cids. This list is not intended to be a complete listing of the studies done using these methods, but does represent the majority of procedures utilized today. 1.2 Nucleic Acid Sequence Analysis Most of the recent work to identify method s for the identif ication of nematode species has focused on genetic differences since these are the basis for the phenotypic expression of proteins and morphological features. DNA based studies among et al. 1986; Powers et al. 1986; Curran and Webster, 1987; Bolla et al. 1988; Kalinski and Huettel 1988), and the increasing accessibility of the polymerase chain reaction (PCR) helped fuel studies on the genetic differences among nematode species. Currently, nearly every study of nematode phylogeny and genetic sequence comparisons utilizes PCR.

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19 1.2.1 Polymerase Chain Reaction (PCR) PCR was developed in 1983 by Dr. Kary Mullis (Saiki et al. 1985). The method he number of copies of the given sequence to levels that can be easily detected and used for further studies. Using PCR helps scientists observe the smallest differences among nematode species, making differentiation much easier than morphological studies of nearly identical species. However, finding genetic differences requires the amplification of the correct area of the o amplification and sequencing require the use of primers that are homologous to a desirable conserved s equence of nucleotides gene, or locus within a genome that can be used to make comparisons among genotypes of a given group of organisms Primers used to begin sequencing of the selected areas can be very specific, selecting the sequence that will help to separate the designated species. Primer loci, such as the internally transcribed sequence 1 (ITS 1), small ribosom al subunit (SSU), and the D2 or D3 expansion segments are the most widely used primers in Nematoda but new primers are being developed wi th more specificity to differentiate closely related species to a greater degree such as the cytochrome oxidase II complex (Powers and Harris, 1993) and HSP 90 (Chitwood, 2003; Skantar and Carta, 2004) Often, the easily accessible primers cannot accurat ely separate certain closely related species, requiring the development of a primer specific for the study. Primer development has become standard practice for most nematode genetic studies (Fullaondo et al. 1999; Carta et al. 2001; Floyd et al. 2005). The primary advantage of using PCR based studies over other available methods is the potentially high degree of nematode species delineation The smallest

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20 differences among genomes can be observed, making identification, phylogeny, and evolutionary infe rence much easier. However, strictly using nucleotide sequences for phylogeny can lead to excessively splitting nematode species based on minute differences (Inserra et al. 2007) Cryptic species are species that cannot be separated morphologically but differ genetically ; there are many articles throughout biology discussing if these minute differences are really different species, just variation among individuals, or the beginnings of evolution within the species (Blouin, 2002; Gomez et al. 2002; Herbe rt et al. 2004; Sudhaus and Kiontke, 2007). However, Fonseca et al (2008) proposed using the differences observed among multiple genes to better determine species delineation and better understand nematode species divergence. This approach, called inte grative taxonomy, approaches species concepts as malleable for a given group of organisms based on morphological, molecular, ecological, and other definitive studies within that group that can be used to better define species and species concepts (Dayrat, 2005). In addition to being potentially overly specific, the equipment required for sequencing the products of a PCR reaction are typically not present in most laboratories. Although sending amplicons to contract laboratories for Sanger sequencing has bec ome common practice, it still adds a step to identifying the amplified sequence, lengthening turnaround of sample identification. Even more specific and potentially expensive equipment is required for studies actually attempting to sequence ntire genome. Despite the potential drawbacks mentioned above, the applicability of PCR has been widely accepted in nematological studies. Descriptions of new species require a

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21 genetic analysis, typically using PCR, and publishing the unique sequence in a database (i.e. GenBank) for future comparisons among species (Kanzaki et al. 2000; Rubtsova et al. 2001; Karssen et al. 2004). Studies of nematode genomes involving PCR appear to have a significant resolving and lasting power in nematology because of their numerous advantages over strictly morphological observations. To date, over 100 papers have been published using PCR for identification within several nematode groups (Table 1). 1.2.2 Methods Utilizing PCR 1.2. 1.1 Restriction f ra gment length p olym orphisms (RFLP) RFLP comparisons, one widely used permutation of PCR, compares fragments of DNA homologues among species that have been broken down using restriction enzymes. Restriction enzymes cleave nucleotide sequences at specific points based on the conformation of the enzyme. For example, the enzyme EcoRI cleaves DNA A phosphodiester bond on both strands, leaving a that do not require a sequence match (Baum et al. 1994) RFLPs are used to compare sequence lengths, as well as the sequence itself, among species to determine relatedness. RFLPs are the basis of all co mparisons amplifying a specific region of an Gasser et al. 1994; Gasser and Haoste, 1995; Reid et al. 1997; Subbotin et al. 1999; Madani et al. 2004; Umehara et al. 2006). RFLPs are advantageous for identifying nematode s pecies. Sequences can range in size with no real limitation on the length of the segment studied except the resolution of the equipment used for sequencing. They can also be used to track

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22 changes in species genomes by determining at which locus a mutatio n occured providing clues to evolutionary events and species divergence The primary drawback of using RFLPs comes with the use of restriction enzymes. To properly compare species with RFLPs, the correct sequence must be selected in both species, requir ing the correct restriction enzyme to cut the nucleotide sequenc e at the right position. Integra l to this is the need to have some idea of the type of primer that will be used in the study; does the sequence of the primer match up with the sequence left b y the restriction enzyme? Once these issues have been addressed, RFLPs can be utilized in many types of PCR applications (Subbotin et al. 2000; Sz a lansk i et al. 1997) A modification of RFLP PCR, multiplex PCR, uses RFLP primers for multiple nematode s pecies in the same reaction mixture. This allows a sample to be examined for several sequences simultaneously without having to use separate reaction mixtures. Multiplex PCR is used primarily where several similar species that are difficult to differenti ate morphologically can be present in a sample (Stanton et al. 1997; Zarlenga et al. 2001; Oliveira et al. 2005; Umehara et al. 2008) However, there are applications where multiplex PCR can be used for detection of a specific nematode from samples tha t include numerous other species (Subbotin et al. 2001). 1 2.1.2 Real time quantitative PCR (qPCR) Real time quantitative PCR is a modification of the original PCR protocol that allows the amplified DNA to be measured in real time as the reaction proceed s. The volume of DNA replicates produced is quantified using the number of amplification reactions and the amount of fluorescent dye present in the reaction mixture. Using the results of the quantification process it is theoretically possible to determin e the amount of DNA from the region amplified per organism, which could have future applications in

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23 ecological studies and other studies where different levels of nematode populations are to be detected or quantified The process is relatively new, but re search has utilized this method for the detection and quantification of Globodera spp. and Heterodera spp. in soil (Madani et al 2005; Quader et al. 200 8 ), determining levels of biological control agents in production areas (MacMillan et al. 2006), and monitoring population levels of virus transmitting nematode species (Holeva et al. 2006; Sato et al. 2007). The incorporation of real time PCR equipment into diagnostic laboratories could help to increase the detection accuracy by reducing the extracti on errors of nematode assay and allow diagnosticians to provide more complete recommendations to clients. 1.2.1.3 DNA barcoding using molecular operational taxonomix units (MOTUS) The prospect of increasing our knowledge of species richness has been a goa l of many scientists since taxonomy began. However, this task was immense and nearly impossible using traditional morphological characterization to separate and identify species within a sample (Floyd et al. 2002; Powers, 2004; Blaxter et al. 2005; De L ey et al. 2005; Creer et al. 2010). By applying PCR techniques to whole samples, many different species from nearly every corner of biology can be detected, making untargeted studies exciting but difficult to interpret The purpose of DNA barcoding is to produce a primer set that can be used to successfully and consistently amplify sequences within a community (MOTUS) and distinguish the number of species present. Using primers specific for a selected group, such as nematodes, can help to reduce the PC R products by preventing the amplification of genomes from un wanted organisms With the use of nematode targeting primers in the PCR reaction, researchers can determine the nematode species richness of a sample as well as determine if any previously undes cribed species are present in soil, forest, and marine

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24 communities (Floyd et al. 2005; Bhadury et al. 2006a; Bhadury et al. 2008; Porazinska et al. 2009; Powers et al. 2009; Derycke et al. 2010; Porazinska et al. 2010; Bucklin et al. 2011). Al thou gh DNA barcoding shows great promise for ecological studies, it is still in its early stages and much work needs to be completed to ensure that certain groups are not overlooked or that other organisms from another phylum are not included erroneously (Blax ter et al. 2005) 1.2. 1.4 Denat uring g radient g el e lectrophoresis (DGGE) Another method of using PCR products similar to DNA barcoding is subjecting the products to gradient electrophoresis that separates DNA segments based on the points at which they de nature during migration within the gel. As opposed to using temperature g radient g el e lectrophoresis (TGGE), DGGE utilizes a chemical gradient to cause denaturation of the DNA molecules. However, u sing a chemical gradient can be problematic since it is d ifficult to consitently replicate the exact mixture required for accurately separating DNA, reproduction of the chemical mixture for future runs may be difficult, and the ionic interactions can cause artificial recombination of DNA strands. Regardless of these pitfalls, DGGE has been included in several studies attempting to describe nematode communities from marine (Cook et al. 2005; Bhadury et al. 2006; Derycke et al. 2007), soil (Foucher and Wilson, 2002; Waite et al. 2003; Foucher et al. 2004; Fuj ii et al. 2004; Griffiths et al. 200 6 ; Donn et al. 2007; Okada and Oba, 2008; Wang et al. 2008; Chen et al. 2010), and Antarctic environments ( Christner et al. 2003; Yergeau et al. 2006). Based on these studies, DGGE may be applicable to nematode c ommunity studies in the future, but it is currently overshadowed by DNA barcoding and multiplex PCR.

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25 1.3 Biochemical Assays 1.3.1 Proteins 1958) as a novel observation in nematode s. Several papers followed these first observations finding esterases in many nematode species (Rhode, 1960; Lee, 1964; Geraert, 1965; Bird, 1966). Based on the presence of these enzymes in so many nematode species, a method was developed to identify ne matodes based on electrophoresis (Dickson et al. 1970; Dickson et al. 1971) This method requires the proteins within a nematode migrating through a polyacrylamide gel matrix that separates the proteins by size and charge (Davis, 1964; Ornstein, 1964) After the proteins have separated on the gel, stains are applied specific to the desired enzymes to be observed. Today the enzyme profiles to be observed are primarily esterases and malate dehydrogenase in the genus Meloidogyne ( Esbenshade and Triantaphy llou, 1985; Fargette, 1987; Fargette and Braaksma, 1990; Navas et al. 2002; Cetintas et al. 2003; Oka et al. 2003; Handoo et al. 2004; Karssen et al. 2004; Flores Romero and Navas, 2005; Castagnone Sereno, 2006; Brito et al. 2008) but can be various other allozymes for other nematode groups (Chilton et al. 1992 1992a ; La Rossa et al. 1992; Chilton et al. et al. 1993; George Nascimento and Llanos, 1995; Beveridge, 199 8 ; Noel and Liu, 1998; Andrews and Chilton, 1999). For nematod e identification, isozyme and allozyme analysis can be very useful. Most of these enzymes, with a few exceptions, are species specific in their electrophoretic pattern. However, resolution beyond the species level (biotypes, races, pathotypes, etc.) is n ot reliable with protein studies (Carneiro et al. 2000) Like genetic

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26 studies, these protein assays can be time consuming and relatively expensive due to the specific stains and equipment required for the analyses. 1.3.2 Enzyme L inked I mmunosorbent A ssay ( ELISA ) Enzyme linked immunosorbent assays (ELISA) use antibody labeling to identify an organism based on very specific binding t o the proteins assayed. As in i sozyme and allozyme studies nematode proteins can be run through a polyacrylamide gel to sep arate them and then transferred to cellulose paper for the assay, or the whole nematodes can be placed in a well plate to conduct the assay. The proteins present are then detected by either using a conformation change of the antibody caused by enzyme bind ing to release a dye, or more commonly by adding an enzyme that breaks down to an indicator dye ELISA assays are widely used in the sciences, but have had limited application with nematodes (Davies and Lander, 1992 ; Lawler et al. 1993 ; Ibrahim et al. 1 99 6 ; Kennedy et al. 1997; Ding et al. 1998; Ibrahim et al. 2001; Abrantes, et al. 2004; Lima et al. 2005). Alt hough they have not been developed yet, a movement toward ELISA based identification strips could allow for field identification of nematode species. These so called immunostrips have already been developed for many applications in medical and phytopathological sciences with great success (Fern ndez S nchez et al. 2005; Liebenberg et al ., 2009) so a nematode identification form could be jus t as widely accepted. 1.3.3 Other Methods 1.3.3.1 Glycoproteins Methods using glycoproteins showed promise as a means to identify nematodes below the species level ( McClure and Stynes, 1988 ), but many of these methods have been eclipsed by PCR based metho ds. An alternative method using fatty acids to

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27 identify nematodes has also been proposed ( Sekora et al. 2009, 2010), but the actual application has yet to be determined. Currently, the most widely accepted means of nematode identification are PCR based methods (qPCR and RFLP) and protein assays (isozymes). These methods are reproducible and reliable, making them ideal candidates for nematode assays in diagnostic and regulatory fields as well as in scientific studies. 1.3.3.2 Fatty acid methyl ester (FAM E) analysis Nematode fatty acids have been studied since 1964 (Beames and Fisher, 1964), and many studies compared the fatty acid composition of several nematode genera and species (Sivapalan and Jenkins, 1966; Krusberg, 1967; Krusberg, 1972; Krusberg et a l. 1973; Orcutt et al. 1978; Chitwood and Krusberg, 1981; Chitwood and Krusberg, 1981a ; Hutzell and Krusberg, 1982 ). With the introduction of DNA based methods, fatty acid studies have gone out of favour and have not been conducted as extensively as in previous decades. However, Sekora et al. (2008a) began studies to adapt the FAME (fatty acid methyl ester) system, developed for bacterial identification (Sasser, 1990), for diagnostic nematode identification. These studies found that plant parasitic nem atode genera and species could be identified from juveniles in soil (Sekora et al ., 2009) and that it may be possible to increase the sensitivity of the FAME system to identify individuals within a sample (Sekora et al. 2008). Although the limits of the FAME system have not yet been established, there may be the potential for using it as a means for diagnostic identification in extension and regulatory labs. 1.4 Conclusions Of the numerous methods mentioned, nearly all of them are used by select labs arou nd the world. Many of these methods are used in conjunction with one another to

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28 provide confirmation for results developed using morphological observations. Although still second to morphology, DNA based methods currently appear to be the most widely use d means for identification of many nematode species and could potentially overshadow morphology in recognition of novel species (Blaxter et al. 2005). Although many of these methods are incorporated into nematology labs, diagnostics of nematode soil sampl es is usually still carried out using morphology supplemented by these advanced methods in select circumstances ( Meloidogyne species identification, for example). Using these methods can require certain life stages (juveniles, males, females), some of whi ch are not easily obtained from soil samples (isozyme analysis of female Meloidogyne ) and are not always in the best condition or without accompanying plant material. An additional step in processing to extract the desired compound for analysis (extractin g nematode DNA from plant tissue) may be required before the actual analysis can be performed. Given these restrictions, m ost of the advanced identification methods covered in this chapter would not be applicable for rapid diagnosis of nematode samples I n these instances a method is needed that can isolate the necessary information from the plant tissue without adding cost or an additional, and sometimes lengthy, step. Considering these limitations and requirements, the following dissertation focuses on adapting FAME analysis for use as a diagnostic tool for these special circumstances.

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29 Table 1 1. Selected publications utilizing molecular sequences for nematode identification. Nematode Group Genus Reference Animal Parasites Multiple Gasser and Monti, 1997 Marshallagia and Ostertagia Dallas et al. 2000 Anisakis Pontes, et al. 2005 Dirofilaria and Acanthocheilonema Casiraghi et al. 2006 Toxocara and Toxascaris Li et al. 2007 Entomopathogenic Heterorhabditis and Steinernema Liu and Berry, 1995 Heterorhabditis and Steinernema Pamjav et al. 1999 Heterorhabditis Nguyen et al. 2004 Teratorhabditis Kanzaki et al. 2008 Free living Multiple van der Knaap et al. 1993 Panagrolai mus Abebe and Blaxter, 2003 Marine Nematodes Multiple Pereira et al. 2010 Multiple Thomas et al. 1997 Pseudoterranova Zhu et al. 2002 Multiple Floyd et al. 2005 Terschellingia Bhadury et al. 2008 Multiple Do nn et al. 2011 Plant Parasites Meloidogyne Harris et al. 1990 Meloidogyne Powers and Harris, 1993 Heterodera Szalanski et al. 1997 Pratylenchus Uehara et al. 1998 Heterodera and Meloidogyne Clapp et al. 2000 H eterodera Amiri et al. 2002 Heterodera Maafi et al. 2003 Xiphinema Hbschen et al. 2004 Bursaphelenchus Kang et al. 2004 Rotylenchulus Agu delo et al. 2005 Meloidogyne Powers et al. 2005 Bursaphelenchus Takeuchi et al. 2005 Meloidogyne Tigano et al. 2005 Belonolaimus Gozel et al. 2006 Meloidogyne Adam et al. 2007

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30 Table 1 1. Continued. Hirschmanniella De Ley et al ., 2007 Fergusobia Ye et al ., 2007 Buraphelenchus Ye et al. 2 007a Meloidogyne Hu et al. 2011

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31 C HAPTER 2 F ATTY ACID METHYL EST ER ANALYSIS USED TO IDE NTIFY MELOIDOGYNE SPECIES IN SOLANUM LYCOPERSICUM ROOT TISSUE 2.1 Introduction Many methods have been developed to identify Meloidogyne species, but mos t of th es e techniques require isolation of individuals from soil or roots (B arker et al ., 1985; Powers and Harris 1993) This isolation step can be a limiting factor when the quality of the sample is crucial for the type of analysis to be performed. For ex ample, isozyme analysi s require s healthy females that have begun to produce egg masses (Esbe n shade and T riantaphyllou, 1985) If the sample is old dried, or if the females are damaged by fungi, dehydration, or other means, it can be nearly impos sible to get accurate results. In an attempt to bypass some of the possible difficulties encountered with the most widely used methods, Sekora et al ( 2010 ) were able to use fatty acid methyl ester (FAME) analysis to identify several Meloidogyne species. Even t hough these previous studies were performed using juveniles, it is likely that this method could be used on other life stages such as mature females It is also possible that the FAME method could be used to identify Meloidogyne sp p. within root tissue e liminating the need for isolation of mature females I f nematode species identification using infected root tissue is possible, methods for preparing tissue for analysis need to be evaluated. For example, root tissue dried prior to FAME extraction may pro duce different profiles than fresh tissue immediately submitted to extraction. This could also be true for tissue that is homogenized before extraction since the extraction method may be limited in its ability to penetrate the root tissue. Based on these concerns, the following objectives were developed: 1)

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3 2 determine the ability of the FAME method to identify Meloidogyne species from infected root tissue, 2) conclude if homogenization produces a more reliable FAME profile than whole tissue and 3) evaluate the effect, if any, of fresh versus dried root tissue in conjunction with standard and concentrated extractions on FAME profiles 2.2 Materials and Methods Based on the stated objectives, a series of tests were set up to determine the best preparation of infected root tissue for FAME analysis. These tests included comparisons of Meloidogyne infected roots to uninoculated root tissue, homogenized roots to whole roots, and fresh roots to dried roots combined with standard (dilute) and concentrated FAME prep arations. 2.2.1 F atty Acid Methyl Ester (FAME) Analysis Root tissue samples weighing 40 mg were used for FAME extraction in all experiments. Extraction of fatty acids was conducted using the method described by Sasser (1990) and involved the four steps of saponification, methylation, extraction, and washing (Figure 2 1). Samples were analyzed using an Agilent 6890N Gas Chromatography System (Agilent Technologies, Santa Clara CA ). For each analysis, 2.0 L of sample solution was injected into an Ultra 2 Cross linked 5% Phenyl Methyl Siloxane column (Agilent Technologies, Santa Clara CA ) linked to a flame ionization detector and analyzed using the EUKARY method of the Sherlock Analysis Software ( MIDI Newark, DE). Sample profiles included total response of the sample (mV), responses for each fatty acid observed (mV) and the calculated proportion of each fatty acid response as a percentage of the total response All profiles were exported to a Microsoft Excel spreadsheet (Microsoft Corporation, Redmond, WA) for further analysis.

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33 2.2.2 Experimental Procedures 2.2.2.1 FAME e valuation of r oot t issue i nfected with Meloidogyne s p p. Confirmed single egg mass populations of M eloidogyne arenaria M. hapla M. incognita and M. javanica were maintained on Solanum lycopersicum g reen house conditions at the University of Florida IFAS Greenhouse Complex in Gainesville, FL In July, 2010, samples were selected from root tissue infected with each of the four Meloidogyne species and uninfected root tissu e (negative control). Root samples of each Meloidogyne species were selected by the presence of galls or egg masses ; tissue samples of un inoculated S. lycopersicum were randomly selected throughout the root system Replications were based on the availabi lity of tissue for analysis and ranged from 24 ( M. hapla ) to 78 ( M. arenaria ) ; 260 samples were analyzed in total (Table 2 1) 2.2.2. 2 Tissue homogenization Root tissue of S. lycopersicum was used to compare homogenized tissue to whole tissue wit hout homogenation Two samples, one for each preparation, were selected at random from a single root system; a total of 20 replicates were prepared per treatment for a total of 40 samples Tissue homogenization was achieved by using a modified steel spat ula attached to a Dremel (Robert Bosch Tool Farmington Hills, MI ) while the root sample was submerged in the first FAME reagent ( 3.75 M NaOH in 50% CH 3 OH; Figure 2 1). 2.2.2. 3 Fresh versus dried tissue and standard versus concentrated samples S amples of S lycopersicum tissue infected with Meloidogyne javanica were selected for analysis as descri bed previously. Half of the 48 40 mg samples were subjected to drying in an incubator at 50C for 2 days followed by FAME extraction

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34 whereas the remain ing half i mmediately underwent FAME extraction. From each 2 4 sample set, 1 2 samples of 1.25 mL extract were analyzed directly while the remaining 1 2 were evaporated under a fume hood and reconstituted in 75 L of 50/50 methyl tertiary butyl ether / hexane. Therefore, the experimental design included four treatments with 12 replicates each and was repeated for a total of 96 experimental units. Resulting FAME profiles for each of the samples were analyzed join tly to determine the most desirable combination Independent runs were combined for a larger data set since runs were not a significant factor in the analysis ( P = 0.7948) 2.2.3 Statistical Analysis Exported profiles were imported into SAS ( SAS Institute Cary, NC ) for further analysis. Mean profiles for each character or categorical class (homogenized tissue, M. arenaria infected tissue, etc.) were calculated with PROC MEANS which provided the average response for each fatty acid in all samples for th e given class Additional s tatistical tests were performed using with PROC STEPDISC in combination with PROC CANDISC following the method of Sekora et al (2010 a ). PROC STEPDISC was used to determine which fatty acids were significant for discrimination among classes using a series of stepwise analysis of variance ( ANOVA ) tests t hat evaluate the F value of each fatty acid before and after inclusion (Johnson, 1998) After analysis of each fatty acid, fatty acids significant for delineation ( P < 0.15) were used for canonical discriminant analysis (CDA) with PROC CANDISC. CDA produces class means based on sample variance within each compared class and then represents relationships among classes in dimensional space. The dimensional space is represented by c anonical variates (CAN1, CAN2, up to class n 1) that demonstrate class separation in graphical representation and can be assigned to x

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35 y or z axes depending on the desired class comparisons. Canonical variates are also used to describe the total multiva riance within a test, and the number of variates in these tests was reduced to the fewest that could define at least 75% cumulative proportion of the total multivariance ( n CAN < 3). Separation among classes is defined 1 to 1) of a given fatty acid along the chosen canonical variate. Absolute values approaching |1.000| indicate a high degree of correlation and help to separate c lasses on the specified dimension The greater the value of correlat ion, the greater the spatial distance (Mahalanobis distance or D 2 ) among means graphically along a given canonical variate (Johnson, 1998) For the experiments described in this dissertation high canonical correlation was described by correlations greate r than |0.750| and significant means separation was achieved with D 2 having a P value less than 0.05. Additional information provided by CDA is the canonical correlation and e igenvalue of each canonical variate. Canonical correlation values range from 0 t o 1 and are an indicator of the im portance of each canonical vari ate to the separation of classes. Canonical correlation values approaching 1 are considered more informative for describing the majority of multivariance within a given analysis. The eigenv alue is another statistic similar to canonical correlation that is used to rank canonical variates based on the multivariance ex plained by the selected variate. As with canonical correlations, higher values indicate a greater degree of explained multivari ance in an analysis for the given canonical variate (Johnson, 1998) In total, 396 samples were prepared for FAME analysis. However, samples with FAME profiles of a single fatty acid assigned the observed fatty acid a percent age

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36 abundance of 100%. Theref ore, samples producing one fatty acid w ere excluded from analysis to prevent data skewing. As a result, 356 samples total were analyzed among the three experiments. 2.3 Results 2.3.1 FAME Evaluation of Root Tissue Infected with Meloidogyne S pecies Fatty a cid chain lengths ranged from 10 carbons ( capric acid) to 25 carbons ( pentacosylic N a lcohol). Several fatty acids that have yet to be fully identified by chain length and structural configuration were detected during analysis. Commonly encountered unide ntified peaks in the EUKARY database are designated by their retention time (i.e. unknown 20.588). S everal fatty acid peaks were observed during these experiment s that were not in the EU KARY database and were therefore named based on their respective rete ntion times (unknown 8.281, unknown 13.671, etc.) Some of these unknown fatty acids made up at least 33% of the total fatty acids observed among all tissue treatments One of these unknown fatty acids, u nknown 21.808 was the most prevalent in S. lycoper sicum (31.01%), M. arenaria infected tissue (24.79%), and tissue containing M. incognita (40.73% ) ; root tissue infected with M. hapla or M. javanica also contained 27.00% and 19.95%, respectively of this fatty acid ( Table 2 2). Elaidic acid (18:1 9t) was the most commonly occurring fatty acid i n M. hapla and M. javanica infected tissue (48.58% and 24.94%, respectively), the second most common in tissue containing M. incognita (20.02%), and the third highest for tissue infected with M. arenaria (1 6.44%) but was not observed in uninoculated S. lycopersicum Palmitic acid (16:0) the third mo st predominant fatty acid, was found in both infected and uninfected root tissue and

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37 ranged in concentration from 11.49% in M. incognita containing tissue to 2 1.10% in M. arenaria infected root tissue Because S. lycopersicum tissue was the most predominant tissue in samples, FAME profiles of uninoculated root tissue were similar to those of infected tissue However, there were enough differences in fatty acid expression to differentiate infected root tissue from uninfected, and to discriminate among infection by the different Meloidogyne species using CDA ( P < 0.0026 ; Table 2 3 ; Figure 2 2 ). The first canonical variate (CAN1) described 46.8% of the total varia tion among root treatments. Along CAN1, four fatty acids were responsible for separating S. lycopersicum root tissue from tissue infected with M. hapla elaidic acid, unknowns 11.981 and 8.281 and sebacic acid with absolute values of canonical coefficie nts |0.934|, |0.824|, |0. 811|, and |0.765|, respectively ( Table 2 4). Four other fatty acids unknown 22.682 (|0.845|), pentacosylic N alcohol (|0.813|), unknown 20.5 88 (|0.786|), and unknown 23.670 (|0.770|) were responsible for separating M. hapla in fected tissue and uninoculated S. lycopersicum from tissue infected with M. javanica along CAN2 and accounted for 28.1% of the total variation. All four of these fatty acids were found in tissue containing either M. hapla or M. incognita as well as uninoc ulated S. lycopersicum but were not present in tissue infected with either M. arenaria or M. javanica Al though the four significant fatty acids in CAN2 did not separate root tissue containing M. arenaria from M. incognita infected tissue palmi tic acid was significant for their separation along CAN3 (| 0.951 | ) and accounted for 13.5 % of the variation described by CDA ( Table 2 4 ; Figure 2 2 ).

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38 2.3.2 Root Tissue Preparation 2.3.2.1 Tissue homogenation A total of 11 fatty acids were observed, five in homogen ized tissue and eight in whole tissue (Table 2 5). Of these fatty acids, palmitic acid and unknown 8.281 were the only two found in both tissue preparations. Palmitic acid was the most abundant fatty acid in homogenized tissue samples, accounting for 65% of fatty acids observed. Whole tissue preparations contained six unknown fatty acid peaks that accounted for 86% of the total fatty acid content. Palmitic acid (3.1%) and a nonadecylic N alcohol (9.9%) were the only named fatty acid peaks contributing t o the whole tissue profile. CDA of homogenized and whole tissue revealed a D 2 separation of 10 8 7 ( P < 0.0001). Due to the large number of fatty acids appearing exclusively in either tissue preparation, the eight fatty acids selected by STEPDISC were perfe ctly correlated with t he first canonical variate (CAN1=1 or 1; Table 2 6). Palmitic acid, stearic acid, and unknown 8.281 were aligned with a canonical correlation value of 1 while nonadecylic N alcohol and four unknown fatty acids ( 13.671, 20.588, 21.80 8 and 22.682 ) aligned along CAN1 at 1 (Table 2 6). 2.3.2.2 Fresh versus dried tissue and standard versus concentrated samples Sixty of the 96 total samples analyzed produced usable FAME profiles, of which 44 were from samples dried before extraction. In addition, tissue dried before FAME extraction produced more fatty acids in both standard (17) and concentrated (12) samples than fresh tissue ( 3 and 8 fatty acids respectively; Table 2 7). Al though fatty acid chain lengths of 16 and 18 carbons were the most abundant in all samples, profiles from fresh samples were restricted to these chain lengths while dried samples produced profiles with a wider range of fatty acids (13 to 21 carbons).

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39 Observable differences among profiles were more apparent using CDA, where each type of preparation (fresh/dried and standard/concentrated) was separated by a canonical axis; CAN1 separated standard and concentrated samples while CAN2 divided fresh and dry tissue (Figure 2 3 ). Values of D 2 were greatest when comparing sta ndard to concentrated extractions (D 2 > 14.92, P < 0.0001), but were also significant between fresh and dried tissue that was not concentrated before analysis (D 2 = 11.89, P = 0.0205; Table 2 8). Among combinations of tissue and extraction preparation, st andard extractions of fresh and dried tissue were significantly different from each other, but no statistical difference could be seen between fresh or dried tissue extractions that were concentrated before analysis. 2.4 Discussion These results indicate that identification of Meloidogyne species may be possible using infected root tissue. Separation a mong species was clear using 40 mg of infected tissue, but future research may determine if smaller amount s of tissue could provide a more accurate depictio n of the infecting species and reduce background noise from plant tissue, endophytic fungi, and bacteria. Reducing the amount of tissue per sample while increasing the number of samples analyzed could also help detect mixed populations by preventing a mor e prevalent species from masking a less common species (Goodell and Ferris, 1981) By coupling a reduced amount of tissue with techniques like homogenation and sample concentration before analysis, it may be possible to be as accurate in identification as with a larger sample but without a reduction in sensitivity. Some fatty acids may also serve as potential indicators for a n individual species based on the amount present i n a sample. Previous studies have indicated that fatty

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40 acids such as arachidonic acid could serve as a genus indicator for Heterodera glycines (Sekora et al. 2009 a ), so it is possible that specific fatty acids found within the Meloidogyne group could vary in their incidence among species. In this study we observed that myristic acid, and the overall abundance of seve ral 18 carbon fatty acids could be used as indicators for the presence of specific species in plant tissue Some evidence of this was observed by Sekora et al. (2010) when comparing extracted juveniles of four Meloidogyne species using FAME analysis In their study it was possible to separate the four species and to tentatively discriminate among three host races of M incognita By incorporating the techniques presented in this paper, it may be possible to duplicate th e results of Sekora et al. (2010) with infected plant tissue containing fewer individuals. Future studies will focus on improving these techniques to improve sensitivity as well as to determine the amount of infected plant tissue required for accurate iden tification. At this point in development it will be necessary to include uninfected tissue to act as a baseline for studies comparing Meloidogyne species but it may be possible to create an identification library that focuses only on fatty acids present in Meloidogyne species regardless of host The effect of different plant hosts and cultivars of the same host should also be considered to determine the applicability of this method when comparing nematode species from different plant hosts. Based on t he studies presented in this chapter it may be possible to use FAME analysis of root tissue infected with Meloidogyne s pecies as a means for identification in conjunction with traditional methods. Homogenizing tissue and concentrating the final extractio n product can help increase the sensitivity of samples processed from infected

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41 root tissue without a need to select fresh or dried tissue. Further development of these methods could lead to a rapid alternative for diagnostic identification of Meloidogyne species without the need for isolation of specific life stages or acquiring samples in pristine condition for analysis.

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42 Table 2 1 Number of r eplicat es used of Meloidogyne infected Solanum lycopersicum root tissue and controls for FAME analysis. T reatment Replications M arenaria infected tissue 78 M. hapla infected tissue 24 M. incognita infected tissue 43 M. javanica infected tissue 49 S. lycopersicum alone 44

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43 Table 2 2. Mean FAME concentrations ( percentage of total response ) of root tissue containing Meloidogyne arenaria M hapla M incognita and M javanica versus uninoculated Solanum lycopersicum tissue Fatty Acid Uninoculated S lycopersicum M arenaria M. hapla M. incognita M. javanica iso undecylic 3OH -0.80 1.16 --iso tridecylic 3OH 0.46 0.06 --0.26 Myristic acid -0.58 0.62 -1.05 iso pentadecylic -0.23 0.76 -0.43 15:1 iso F 0.37 0.09 --0.32 Palmitic acid 17.21 21.10 13.69 11.49 14.43 Palmitoleic acid -0.88 0.86 -1.40 Stearic acid 7.07 8.46 6.88 4.94 7.20 t -5.41 8.63 -8.56 Oleic acid 0.33 0.91 -0.10 1.68 Elaidic acid -16.44 48.58 20.02 24.94 Linoleic ac id 3.91 3.97 4.63 2.13 3.49 Nonadecylic N Alcohol 3.74 -1.61 0.92 -c t -0.27 1.04 -0.47 Heneicosylic acid 0.15 ---0.33 Pentacosylic N Alcohol 0.24 -0.75 0.12 -Sebacic acid 2.58 --0.19 Unknown 8.281 20.29 8.72 6.00 8.65 7.64 Unknown 11.981 0.45 2.08 4.31 1.93 -Unknown 13.671 5.68 4.97 6.25 9.28 3.82 Unknown 19.276 ----0.48 Unknown 20.588 3.42 -0.94 0.16 -Unknown 21.808 31.01 24.79 27.00 40.73 19.95 Unknown 22.682 3.52 -1.54 0.79 -Unknown 23.670 3.44 -0.81 0.64 -n 44 78 24 43 49 =Not detected

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44 Table 2 3. Mahalanobis distances (D 2 ) and P values from canonical discrim inant analysis of root tissue treatments from FAME analysis. From Species To Species SL MA MH MI MJ SL D 2 0 5.22 14.08 5.01 6.11 P 1 <0.0001 0.0205 <0.0001 <0.0001 MA D 2 5 .22 0 7.45 1.73 2.19 P <0.0001 1 <0.0001 0.0026 <0.0001 MH D 2 14.08 7.45 0 7.37 10.34 P 0.0205 <0.0001 1 <0.0001 <0.0001 MI D 2 5.01 1.73 7.37 0 2.27 P <0.0 001 0.0026 <0.0001 1 0.0001 MJ D 2 6.11 2.19 10.34 2.27 0 P <0.0001 <0.0001 <0.0001 0.0001 1 = Abbreviations as follows: SL = Solanum lycopersicum MA= Me loidogyne arenaria MH= M. hapla MI= M. incognita and MJ= M. javanica

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45 Table 2 4. C orrelation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) separatin g uninoculated Solanum lycopersicum from tissue infected with Meloidogyne arenaria M. hapla M. incognita and M. javanica Values listed in bold (greater than |0.750|) indicate significant correlation with in the given canonical variate Fatt y Acid CAN1 CAN2 CAN3 iso undecylic 3OH 0.714 0.246 0.636 iso tridecylic 3OH 0.745 0.264 0.047 Myristic acid 0.392 0.522 0.320 iso pentadecylic 0.747 0.015 0.122 Palmitic acid 0.055 0.077 0.951 Palmitoleic acid 0.40 6 0.519 0.388 t 0.583 0.330 0.325 Elaidic acid 0.934 0.088 0.240 Linoleic acid 0.185 0.335 0.673 Heneicosylic acid 0.383 0.316 0.193 Pentacosylic N Alcohol 0.470 0.813 0.235 Sebacic acid 0.765 0.571 0. 135 Unknown 8.281 0.811 0.509 0.094 Unknown 11.981 0.820 0.414 0.208 Unknown 13.671 0.072 0.208 0.612 Unknown 19.276 0.057 0.615 0.208 Unknown 20.5 88 0.568 0.786 0.025 Unknown 21.808 0.149 0.175 0.620 Unknow n 23.670 0.594 0.770 0.089 Unknown 22.682 0.462 0.845 0.130 Canonical Correlation 0.686 0.590 0.452 Eigenvalue 0.889 0.533 0.257 Cumulative Proportion 0.468 0.748 0.884

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46 Table 2 5 Mean FAME concentrat ions ( percentage of total response ) of homogenized and whole Solanum lycopersicum root tissue. Fatty Acid Homogenized tissue Whole tissue iso tridecylic 3OH 1.70 -Palmitic acid 34.29 3.05 Stearic acid 10.62 -Lino leic acid 14.34 -Nonadecylic N Alcohol -9.92 Unknown 8.281 14.99 5.00 Unknown 13.671 -5.10 Unknown 20.588 -10.02 Unknown 21.808 -39.63 Unknown 22.682 -10.12 Unknown 23.670 -9.88 n 12 13 =Not detected

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47 Table 2 6 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first canonical variate separating Solanum lycopersicum homogenized and whole root tissue Fa tty Acid CAN1 Palmitic acid 1 Stearic acid 1 Nonadecylic N Alcohol 1 Unknown 8.281 1 Unknown 13.671 1 Unknown 20.588 1 Unknown 21.808 1 Unknown 22.682 1 Canonical Correlation 0.998 Eigenvalue 2 94.97 Cumulative Proportion 1

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48 Table 2 7. Mean FAME concentrations ( percentage of total response ) of root tissue infected with Meloidogyne javanica prepared using a combination of fresh/dried root material and standard/concentrated FAME s amples Fatty Acid Meloidogyne javanica Fresh Standard M. javanica Fresh Concentrated M. javanica Dried Standard M. javanica Dried Concentrated iso tridecylic 3OH --0.54 -Myristic acid --1.81 0.22 iso pen tadecylic --0.68 0.35 15:1 iso F --0.46 -Palmitic acid 29.64 16.84 14.37 16.26 Palmitoleic acid --2.63 0.28 Stearic acid 27.73 16.68 12.60 15.26 t --17.47 -Oleic acid -0.87 3.2 5 2.32 Elaidic acid -40.77 19.30 35.51 iso elaidic 42.63 13.94 12.27 16.51 Linoleic acid -0.43 4.03 1.82 c t -0.89 0.88 1.80 Eicosapentaenoic acid --0.31 0.09 Heneicosylic acid --0 .67 -Unknown 8.281 -7.18 1.46 6.77 Unknown 19.276 --0.98 -n 3 13 24 20 =Not detected

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49 Table 2 8. Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis of root tissue preparations analyzed by FAME analysis. From Species To Species MJRD MJRDC MJRF MJRFC MJRD D 2 0 15.70 11.89 14.92 P 1 <0.0001 0.0205 <0.0001 MJRDC D 2 15.70 0 29.52 0.82 P <0.000 1 1 <0.0001 0.9049 MJRF D 2 11.89 29.52 0 26.21 P 0.0205 <0.0001 1 <0.0001 MJRFC D 2 14.92 0.82 26.21 0 P <0.0001 0.9049 <0.0001 1 = Abbreviations as f ollows: MJRD= Meloidogyne javanica infected roots dried, MJRDC= M. javanica infected roots dried and concentrated, MJRF= M. javanica infected roots fresh, and MJRFC= M. javanica infected roots fresh and concentrated.

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50 Table 2 9. Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) separating fresh (standard/concentrated) and dried (standard/concentrated) root tissue infected with Meloidogyne javanic a Values listed in bold (greater than |0.750|) indicate significant correlation with in the given canonical variate Fatty Acid CAN1 CAN2 CAN3 15:1 iso F 0.876 0.477 0.071 Palmitic acid 0.006 0.990 0.140 Palmitoleic acid 0.855 0.518 0.006 Stearic acid 0.170 0.985 0.041 t 0.876 0.477 0.071 Oleic acid 0.494 0.785 0.373 Elaidic acid 0.928 0.266 0.260 Linoleic acid 0.714 0.663 0.225 c t 0.699 0.454 0.552 Hene icosylic acid 0.876 0.477 0.071 Unknown 8.281 0.995 0.034 0.092 Canonical Correlation 0. 897 0. 604 0. 289 Eigenvalue 4.112 0.5 75 0. 091 Cumulative Proportion 0. 861 0. 981 1

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51 Figure 2 1. Fatty acid methyl ester (FAME) extrac tion method described by Sasser ( 1990 )

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52 Figure 2 2 Canonical distribution of root FAME profile means subjected to one of five nematode treatments, Meloidogyne arenaria (MA), M. hapla (MH), M. incognita (MI), M. javanica (MJ), and un inoculated Solanum lycopersicum (SL). D 2 values are greater than 1.73 and significant at P < 0.0026 (Table 2 3) A) CAN1 ( x axis) versus CAN2 ( y axis) and B) CAN1 ( x axis) versus CAN3 ( y axis). A B

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53 Figure 2 3 Canonical distribution of root FAME profile means subjected to one of four preparations, Meloidogyne javanica infected dried roots, standard preparation (MJRD), M. javanica infected dried roots concentrated preparation (MJRDC), M. javanica infected fresh roots, standard preparation (MJRF), and M. ja vanica infected fresh roots, concentrated preparation (MJRFC); CAN1 ( x axis) versus CAN2 ( y axis). D 2 values are listed in Table 2 8 and are significant ( P < 0.0205) for all comparisons except MJRDC to MJRFC (D 2 = 0.82, P = 0.9049)

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54 CHAPTER 3 TEMPERATU RE EFFECTS ON F ATTY ACID METHYL EST ER PROFILES OF MELOIDOGYNE INCOGNITA AND M. JAVANICA 3.1 Introduction Fatty acids are the primary component of biological membranes and help to regulate the physiological functionality of those membranes. Membranes conta in a balance of saturated fatty acids, straight chain fatty acids that have only C C single possess C C double bonds along their carbon chain. Regulation of the propor tions of t hese two types of fatty acids is the primary m e chanism for maintaining membrane flu idity at varying temperatures. Due to the increased molecular movement at higher temperatures, m embranes in these environments contain more saturated fatty acids to maintain rigid ity through the ability of the straight carbon chains to form more van der Waals interactions with other fatty acid chains. Biological membranes containing more chain which prevents the fatty acid chains from packing together as tightly as straight chains and are utilized by organisms in cooler climates where molecular movement is reduced Based on these chemical properties, an organism from a warm environment ( >30C) would have a higher percentage of saturated fatty acids while an organism from a cool environment (<18C) would have a higher proportion of unsaturated fatty acids but the membrane fluidity in these two organisms would be identical (Horton et al. 2001). Organisms have the ability to change the composition of their membranes as their environment warms or cools and these changes can be monitored using various techniques of fatty acid analysis. Studies following the effect of cold accl imation and he at stress of turf grasses on their fatty acid composition have tracked the shift from

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55 saturated to unsaturated fatty acids and indicate that there are primarily four fatty acids that undergo the most change s In a study of physiological changes of bermudag rass ( Cynodon dactylon x C. transvaalensis ) palmitic acid (16:0), stearic acid (18:0), and linoleic acid (18:2) decreased as the length of time at cooler temperatures increased, whereas the percentage of lino lenic acid (18:3) increased (Samala et al. 1998). Similar results were found by Cyril et al. (2002) comparing three seashore paspalum ( Paspalum vaginatum ) germplasms, the former being cold tolerant and the latter t wo being cold susceptible. However, in these experiments stearic acid increased over the period of the cold treatment for all three cultivars. H eat stress and tolerance studies on the fatty acid composition of creeping bentgrass ( Agrostis stolonifera ) cu found that the percentages of palmitic acid and stearic acid increased as those of oleic acid (18:1), linolenic acid, and linoleic acid decreased in leaf tissue (Larkindale and Huang, 2004) Root tissue did not exhibit any significant change in fatty acid composition during the heat treatment. In addition to influencing the fatty acid composition of membranes, temperature can also impact the survival, development, and growth habit of organisms. Bergeson (1959) observed that eggs and juveniles of Meloidogyne incognita acrita had the greatest survival rate at 10C in soil without a plant host present. Survival was decreased as temperature was both increased and decreased. Egg hatching was found to be constant t hrough 22 days at 16C Hatching rates increased at 21 C, 27 C, and 32 C and were arrested at 4 C and 10 C. In addition, studies by Bird and Wallace (1965) found that the optimum hatching rates and mobility occurred at 20 C and 25 C

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56 for M. hapla and 25 C and 30 C for M. javanica Sex determination is also influenced by temperature, as described for M. graminis by Laughlin et al. (1969). T he proportion of males in populations reproducing on bermudagrass increased to nearly 85% at 32 C from less than 10% at lower temperatures. It is possible to differentiate and identify nematode species and life stages based on their fatty acid compositions. Krusberg et al. (1973) observed that there were differences in the fatty acids expressed by Meloidogyne species a t different life stages and that those differences could be used as a means for differentiation. By using fatty acid methyl ester (FAME) analysis, Sekora et al. (2010) confirm ed that it was indeed possible to use fatty acids for the identification of Melo idogyne species. These analyses also indicated that the fatty acid profiles developed could be used for further identification of nematode species based on host and also for studying physiological changes in nematodes. By using the methods developed by S ekora et al. (2010 a ), it is likely that the effect of temperature on the fatty acid profiles of Meloidogyne species, if any, can be resolved. The objectives of this study were to 1) determine if nematode infected tissue varies in its expression of fatty a cids when maintained in diurnal environments with diverse temperature ranges and means, 2) evaluate fixed temperatures over time on the FAME profiles of Meloidogyne infected tissue, and 3) determine if the effects of temperature on FAME profiles of M. inco gnita and M. javanica infected tissue, if any, hinder differentiation of these two organisms. 3.2 Materials and Methods Two experiments were conducted to determine the influence of differing temperatures on the FAME profiles of Meloidogyne incognita race 3 and M. javanica race 1. The first experiment compared three different temperature environments, but

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57 these environments exhibited real world diurnal temperature fluctuations and were weather dependent for their maximum and minimum temperatures. The seco nd experiment utilized two constant temperature environments and evaluated changes in FAME profiles over time to determine what deviations were induced over long term exposure to a fixed temperature. 3.2.1 Diurnal E xperiment To evaluate the effect of fl uctuating day/night cycle temperatures on the FAME profiles of M. incognita and M. javanica S lycopersicum plants inoculated with either species were maintained in three environments exhibiting diurnal temperature fluctuations. The experiment utilized a 3 3 factorial design (nematode temperature) with 20 replications, for a total of 180 experimental units. Pots containing a single in a utoclaved medium containing five parts field soil ( Candler sand ) three parts USGA greens mi x sand, and one part commercial potting medium (ProMix Premier Tech Horticulture, Qu bec, Canada) and inoculated with their respective nematode treatment ( M. incognita M. javanica or uninoculated) Sixty experimental units were maintained in each of t hree diurnal environments with a 12 hour photoperiod : a greenhouse with a 29 .5 C average temperature (34C day/25C night), a growth room with a mean temperature of 26C (28C/24C), and a shadehouse with an average temperature of 1 7.5 C (24C/11C). Pots were grouped by nematode treatment with 0.5 m between treatments to prevent contamination during the 60 day period of the experiment from 1 September to 31 October 2011 Pots were irrigated twice a day using a custom irrigation system and fertilized as n eeded to maintain healthy plant growth.

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58 3.2.1.1 Sample p reparation Root tissue samples were collected by removing two 0.1 g root samples from washed roots within each pot a f t er 60 days Roots samples from uninoculated plants were randomly selected while roots samples from inoculated plants were selected based on the presence of visible galls or females. Immediately before FAME extraction, roots were ground to release all tissues present within the roots as described in Chapter 2 Root evaluation by FAME analysi s included 36 0 samples (2 per experimental unit) 3.2.1.2 FAME a nalysis Extraction of fatty acids was conducted using the method described by Sekora et al. (2010 a ) and involved the four steps of saponification, methylation, extraction, and washing Samples were analyzed using an HP 6890N Gas Chromatography System (Agilent Technologies, Santa Clara CA ). For each analysis, 2.0 L of sample solution was injected into an Ultra 2 Cross linked 5% Phenyl Methyl Siloxane column (Agilent Technologies, Santa Clara CA ) linked to a flame ionization detector and analyzed using the EUKARY method of the Sherlock Analysis Software ( MIDI New ark, DE). Sample profiles included total response of the sample (mV), responses for each fatty acid observed (mV), and the calculated proportion of each fatty acid response as a percentage of the total response. All profiles were exported to a Microsoft Excel spreadsheet (Microsoft Corporation, Redmond, WA) for further analysis. 3.2.2 Constant T emperature E xperiment Meloidogyne incognita and M. javanica w ere evaluated at t wo fixed temperatures (20C and 26C + 2C between day and night cycles ) on S lyco persicum plants in plant growth chambers Root samples w ere collected for evaluation of direct identification of Meloidogyne species in tissue samples. A set of uninoculated tomato

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59 plants serving as contro ls for uninfected root tissue, w ere g rown at each temperature and evaluated in conjunction with inoculated plants at each extraction point. Extraction times were 45, 90, and 135 days after inoculation, based on multipl es of the approximate time required for the completion of a single life cy cle at 20C (45 days) to determine if any changes in fatty acid composition of the nematodes were immediate or progressive over consecutive life cycles. The experiment was conducted following a 3 way factorial design (nematode temperature evaluation ti me) with six replications for a total of 1 08 experimental units. Each pot (experimental unit) contain ed a single plant grown in the same growth medium used in the previous experiment Each plant was inoculated with 500 eggs of M. incognita M. javanica or remained uninoculated. Six replications of each nematode treatment were placed in a growth chamber set at a given temperature (20C or 26C) Chambers contained four dual bulb ballasts fitted with bulbs emitting growth promoting wavelengths and were s et for a photoperiod of 14 hours Within a given chamber, each of the 18 pots was assigned to one of three evaluation times ( 45, 90, or 135 days after inoculation ). Pots were arranged in a completely randomized design within the chamber that was re random ized every nine days to reduce growth habits induced by potential microclimates within a chamber. Pots were checked daily for water loss and watered as needed to prevent excessive drying. 3.2. 2 .1 Sample p reparation Root tissue samples were collected at ea ch evaluation period as described in the diurnal experiment. A total of 216 root tissue samples were selected for FAME analysis (2 per experimental unit)

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60 3.2. 2 .2 FAME a nalysis Fatty acid ext raction and analysis for the 45 day evaluation was performed usi ng the same methods described for the diurnal experiment. In an effort to increase FAME profile resolution and the number of usable samples, root tissue samples from the 90 and 135 day evaluations were subjected to the new Instant FAME extraction and Rap id analysis methods developed by MIDI (Figure 3 1) as described in Chapter 4 Root tissue samples collected for these new methods were 3 mg as opposed to the 0.1 g used for the diurnal experiment. Instant FAME extraction does not utilize water bath heati ng for fatty acid extraction, but substitutes the addition of a series of solvents with vortexing between steps (Figure 3 1). The Rapid analysis method is comparable to standard analysis methods for the fatty acids I t is able to detect between 9 and 20 carbons in chain length and uses the same column for analysis ( MIDI 2011) 3.2. 3 Statistical A nalysis Five comparisons w ere made using the fatty acid analyses of nematodes and root tissues from both experiments 1) among the three nematode treatments at a given temperature, and 2 ) a give n nematode treatment across temperatures. FAME profiles were imported into SAS ( SAS Institute, Cary, NC) for further analysis. Mean profiles for M. incognita J 2 etc.) were calc ulated with PROC MEANS which provided the average response for each fatty acid in all samples for the given class. Additional statistical tests were performed using PROC STEPDISC in combination with PROC CANDISC following the method of Sekora et al (2010 ). Stepwise discriminant analysis (SDA) by PROC STEPDISC was used to determine which fatty acids were significant for discrimination among classes using a series of stepwise analysis of variance (ANOVA) tests that evaluate the F value of each fatty acid

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61 b efore and after inclusion (Johnson, 1998). After analysis of each fatty acid, those significant for delineation ( P < 0.15) were used for canonical discriminant analysis (CDA) with PROC CANDISC. Canonical discriminant analysis produces class means based on sample variance within each compared class and then represents relationships among classes in dimensional space. The dimensional space is represented by canonical variates (CAN1, CAN2, up to class n 1) that demonstrate class separation in graphical repre sentation and can be assigned to x y or z axes depending on the desired class comparisons. Canonical variates are also used to describe the total multivariance within a test, and the number of variates in these tests was reduced to the fewest that could define at least 75% cumulative proportion of the total multivariance ( n CAN < 3). correlation ( 1 to 1) of a given fatty acid along the chosen canonical variate. Absolute values approaching |1.000| indicate a high degree of correlation and help to separate classes on the specified dimension. The greater the value of correlation, the greater the spatial distance (Mahalanobis distance or D 2 ) among means graphically along a g iven canonical variate (Johnson, 1998). For the experiments described in this paper, high canonical correlation was described by correlations greater than |0.750| and significant mean separation was achieved with D 2 having P < 0.05. Additional informatio n provided by CDA is the canonical correlation and eigenvalue of each canonical variate. Canonical correlation values range from 0 to |1.000| and are indicator s of the importance of each canonical variate to the separation of classes. Canonical correlati on values approaching |1.000| are considered more

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62 informative for describing the majority of multivariance within a given analysis. The eigenvalue is another statistic similar to canonical correlation that is used to rank canonical variates based on the m ultivariance explained by the selected variate. As with canonical correlations, higher values indicate a greater degree of explained multivariance in an analysis for the given canonical variate (Johnson, 1998). 3.3 Results 3.3. 1 Diurnal Experiment A total of 122 samples only a third of those prepared, produced usable FAME profiles. V isible trends appeared in the mean FAME profiles for each nematode treatment as the mean environmental temperature decreased but none of these differences were significant ( Table 3 1). For example, the unnamed peak designated u nknown 8.281 increased slightly in M. incognita infected tissue as mean temperature decreased, but decreased in uninoculated root tissue. The most dramatic differences across the three mean temperature s occurred in M. javanica infected tissue. Both palmitic acid and elaidic acid increased from 12.12% and 23.04%, respectively, in infected tissue maintained in the greenhouse environment to 19.21% and 57.41%, respectively, in tissue maintained in the shad ehouse environment (Table 3 1). Meloidogyne javanica infected root tissue maintained in the growth room exhibited a mean FAME profile different from all others with almost 90% comprised of unknown peaks 8.281 13.671 and 21.808 ( based on retention time during analysis ) Canonical discriminant analysis was able to separate each nematode treatment within any of the three temperature environments (Table 3 2). The only overlap among nematode treatments across the three environments was between M. incognita infected plant tissue maintained in the shadehouse and M. javanica infected plant tissue from

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63 the growth room (D 2 = 5.368, P = 0.1835). Meloidogyne incognita infected plant tissue and uninoculated plant tissue were clearly separated within each of the thr ee temperatures, but each formed a group of similar FAME profiles (D 2 < 3.126, P > 0.1006) across temperatures (Figure 3 2). Meloidogyne javanica infected tissue was distinctly separated from other treatments within the three temperatures aside from M. in cognit a infected tissue from the shadehouse (D 2 > 13.526, P < 0.0049), but did not group together as observed for M. incognita infected and uninoculated root tissues. Nine fatty acids were responsible for separating the nine tissue types along the first tw o canonical variates, seven along CAN1 and two along CAN2 (Table 3 3). The first canonical axis defined 51.7% of the total multivariance among the classes and primarily separated the three uninoculated S. lycopersicum tissue s from M. java nica infected ti ssue maintained in the greenhouse (Figure 3 2). Of the fatty acids responsible for this separation, only unknown 8.281 was correlated at greater than |0.900| (|0.912 |). The fatty acids responsible for the separation of uninoculated S. lycopersicum tissue and greenhouse grown M. javanica infected tissue along CAN1 were split into three groups, those found only in M. javanica infected tissue ( iso pentadecylic acid, myristic acid, and palmitoleic acid), fatty acids at higher mean concentration s in uninoculat ed S. lycopersicum tissue than either M. incognita or M. javanica infected tissue (unknown 8.281, unknown 20.588, and sebacic C10 decarboxylase), and elaidic acid that is found in Meloidogyne infected root tissue. The two fatty acids significant along CAN 2 (oleic acid and unknown 13.671) were differentially expressed within each nematode treatment/environment combination and described an additional 34.4% of the total multivariance (Table 3 3)

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64 3.3. 2 Constant Temperature Experiment 3.3.2.1 FAME profiles at 45 days After 45 days, FAME profiles of uninoculated and Meloidogyne infected root tissue did not demonstrate significant separation from each other between temperatures, but this is likely because only 31 of the 72 samples prepared produced FAME profiles that could be analyzed statistically (Table 3 4). Even with the low replication, it is possible to see that uninoculated tissue does not contain either oleic or elaidic acids, but they are found in Meloidogyne infected tissue. The two unknown peaks 13.67 1 and 21.808 we re also found in all tissue types but uninoculated tissue maintained at 20C. Canonical discriminant analysis of the usable FAME profiles produced some differences among the six classes (Table 3 5). The FAME profile of M. incognita infected root tissue maintained at 26C was different from all other classes along CAN1 (D 2 > 27.57, P < 32.12) as a result of the high concentration of elaidic acid (Table 3 6). Although the remaining five classes were distributed along CAN2 (Figure 3 3 A ), no fa tty acids were significant for this separation. However, both unknown peaks ( 13.671 and 21.808 ) were significant along CAN3 and separated uninoculated tissue maintained at 20C from tissue infected by either Meloidogyne species at the same temperature (Fi gure 3 3B) 3.3.2.2 FAME profiles at 90 days More differences among FAME profiles were visible after 90 days (Table 3 7). Using the Instant FAME extraction and rapid analysis methods, all 72 samples produced usable FAME profiles with a greater number of f atty acids ( n = 49) than the standard methods. Because of this increased resolution, more patterns were visible among the six classes. For example, pelargonic acid was not found in uninoculated S.

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65 lycopersicum tissue at either 20C or 26C and arachidic acid the longest detectable saturated fatty acid, was observed at higher mean concentrations in 20C tissues than 26C tissues. However, most of the differences in FAME profiles subjected to either 20C or 26C were variations in the concentration s of se lected fatty acids ( linoleic and arachidonic acids) In tissues infected with either M. incognita or M. javanica the proportion of unsaturated fatty acids to saturated fatty acids increased with temperature from 2.04 to 3.50 in M. incognita infected tissue and 1.87 to 3.9 4 in M. javanica infected tissue; uninoculated tissue only increased by 0.03. Canonical discriminant analysis of the FAME profiles generated a f t er 90 days indicated that the degree of separation between the two temperatures had increased (D 2 > 34.74, P < 0 .0001; Table 3 8) as well as the discrimination among the three nematode treatments at 26C (D 2 > 8.78, P < 0.0005). However, it was statistically unlikely to separate the uninoculated S. lycopersicum tissue from either of the Meloidogyne infected tissue s at 20C (D 2 < 3.84, P > 0.6569). Differences among the three 20C profiles and either 26C Meloidogyne infected tissue profile were explained by 21 fatty acids significantly correlated along CAN1, 13 of which were correlated at greater than |0.900| (Tab le 3 9). These fatty acids accounted for 79.5% of the total multivariance among classes and had mean concentrations in Meloidogyne infected tissues at 26C either both greater than or both less than those of the three 20C tissues (Table 3 7). Uninoculat ed S. lycopersicum tissue was separated from the other five tissues along CAN2 (15.0% of total multivariance) by two fatty acids with mean concentrations greater than those of the other classes ( anteiso c ) and eicosenoic acid which was not detected in uninoculated tissue at 26C but was

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66 present in the other five classes. Although none of the detected fatty acids were significant along CAN3, separation of M. incognita infected and M. javanica infected tissues at 26C was still observed based on differential expression in their respective profiles (Figure 3 4). 3.3.2.3 FAME profiles at 135 days A t the conclusion of the experiment, only 3 0 of the remaining 36 plants were still alive and able to be sampled but all 60 samples produced stati stically usable FAME profiles. Uninoculated S. lycopersicum tissue from both t emperature s did not contain c or c c was not detected in M. incognita infected tissue from either 20C or 26C (Table 3 10). Interestingly, oleic aci d was not identified in tissue infected with either M. incognita or M. javanica at 20C but was present at 26C in tissue infected with either species. Saturated fatty acids of 14 carbons and shorter were generally more abundant in tissues maintained at 2 6C than 20C while arachidic acid was found at higher mean concentrations in 20C tissues. Proportions of unsaturated fatty acids to saturated fatty acids again increased with temperature after 145 days in all three tissue types (1.77 to 1.94 in uninocu lated tissue, 2.03 to 2.97 in M. incognita infected tissue, and 2.02 to 3.32 in M. javanica infected tissue). Using the combination of SDA and CDA, it was possible to separate all six classes from one another (D 2 > 91.83 P < 0. 0151 ) except M. incognita in fected and M. javanica infected tissues from 20C (D 2 = 43.27, P = 0.2221; Table 3 1 1 ). The greatest proportion of multivariance (83.39%) separated uninoculated S. lycopersicum tissues from Meloidogyne infected tissues at 26C (Figure 3 5). The 12 fatty acids responsible for the separation consisted of two groups, those with mean concentrations in 26C Meloidogyne infected tissues greater than uninoculated tissues ( n = 10) and those fatty

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67 acids with a lower mean concentration ( n =2; Table 3 10). The separ ation of uninoculated S. lycopersicum and M. incognita infected tissues at 26C from M. javanica infected tissues (CAN2, 9.0% of multivariance) was due to six fatty acids, four with mean concentrations lower in M. javanica infected tissues and two with hig her concentrations in M. javanica tissues. While the separation of uninoculated tissues along CAN3 was significant at P < 0.0001, no fatty acids were significantly correlated with this canonical variate (Table 3 12) 3.4 Discussion Temperature does not ap pear to have a significant degree of influence on the fatty acids in uninoculated S. lycopersicum root tissue or M. incognita infected S. lycopersicum tissue when plants are maintained in environments with diurnal temperature fluctuations (Table 3 2) but does greatly influence these tissues when they are sustained in fixed temperature environments over a period of time (Tables 3 8 and 3 12) The lack of influence in diurnal environments may be due to the need for these tissues to maintain a mixture of lon g chain, short chain, and unsaturated fatty acids to prevent membrane instability when temperatures rise and fall each cycle. While it appears that the temperature ranges used for the diurnal experiment presented were not enough to prevent FAME profile var iation that would hinder identification, comparing the effects from drastically different environments with larger ranges in diurnal temperatures or a greater difference in day/night average temperature could indicate how stable these profiles are across a wide variety of environments. This could be accomplished by comparing tissue s from areas maintained with diurnal temperature cycles similar to those found in desert climates ( with up to 26C difference

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68 between day and night) and by contrasting tissues fr om cool climates such as Nova Scotia or Britain to tissues from tropical regions similar to Mexico or Indonesia. The influence of the target nematode species may also have a significant impact on the fatty acid variation observed. Although the results fro m the diurnal experiment are unclear, fixed temperature experiments indicated that M. javanic a infected tissue had a larger degree of change in the proportion of saturated to unsaturated fatty acids between 20C and 26C than M. incognita infected tissue ( Tables 3 7 and 3 10) These changes may reflect the adaptation of a given nematode species from the climate of its origin. Similar results could possibly be obtained by comparing a tropical Meloidogyne species, such as M. enterolobii to a cool weather s pecies, like M. hapla The changes observed could indicate the adaptive capabilities of each species to a given temperature range, but a limit may also be detected once the temperature deviates beyond what is commonly encountered by that nematode. Meloido gyne infected tissues increased in their degree of separation over the progress of the three evaluation periods more than uninoculated tissue. The changes over time may reflect the effect of each nematode life cycle acclimatizing to their environment whil e uninoculated S. lycopersicum is unable to change as quickly in a single life cycle. It is also possible that the differences observed in infected tissue are side effects of nematode infection causing stress on the host or even by changing the chemistry within the giant cells over time. Changing the temperature of the environment may help to better understand if these changes are acquired through subsequent life cycles of the nematodes or as the result of increased populations on the host plants. For ex ample, by maintaining tissue at 26C for 90 days and then dropping the

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69 temperature to 20C for another 45 to 90 days it may be possible to discern if the changes progress regardless of temperature when compared to tissue maintained at a constant temperatu re for the entire course of the experiment. The results of these two studies indicate that al though fatty acid profiles of Meloidogyne infected root tissues change when submitted to fixed temperatures for an extended period of time, the changes are less pr onounced when the tissues are maintained in environments with diurnal temperature fluctuation. By not hindering identification of the same Meloidogyne species from two different environments, the possibility of using FAME analysis for diagnostic purposes is more likely. However, the impact of temperature on other nematode species, including others within Meloidogyne should be pursued to determine if these results are consistent. Widening the range of temperatu res studied and introducing temperature chan ges after a period of acclimatization will help to evaluate the full impact of temperature on nematode species and determine if the real world application of FAME analysis for nematode infected root tissue is prospective

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70 Table 3 1. Mean FAME concentrat ions ( percentage of total response ) of two nematode species ( Meloidogyne incognita race 3 [Mi], M. javanica race 1 [Mj]) infecting S olanum lycopersicum root tissue and an uninoculated control (C) maintained in one of three diurnal temperature env ironments for 60 days. Greenhouse (29C) Growth room (26C) Shadehouse (18C) Fatty Acid Mi Mj C Mi Mj C Mi Mj C i so tridecylic 3OH -0.72 0.29 --2.02 --0.49 Myristic acid -2.41 -----1.35 -i so pentadecylic -0.91 -----0.76 -15:1 ISO F -0.61 0.28 --1.46 --0.92 Palmitic acid 15.82 12.12 11.24 9.93 3.72 17.16 14.77 19.21 18.96 Palmitoleic acid -3.50 -----0.94 -Stearic acid 5.56 10.69 3.08 5.97 -7.02 6.00 11.33 5.09 t -23.30 -------Oleic acid -4.34 0.07 --1.22 0.53 0.69 0.52 Elaidic acid 28.27 23.04 -34.64 5.29 -8.42 57.41 -Linoleic acid 5.38 4.67 5.56 4.75 1.15 7.48 1.31 5.22 9.30 Nona decylic N Alcohol 0.47 -5.60 1.14 -2.97 --2.27 c t -1.17 -----0.35 -Heneicosylic acid -0.89 0.32 -----0.40 Pentacosylic N Alcohol 0.31 --0.75 -0.67 ---Sebacic C10 Decarbox --4.43 -0.85 3.56 --2.07 Unknown 8.281 3.56 1.51 21.34 4.21 14.09 16.16 6.18 2.73 13.20 Unknown 11.981 3.91 -0.51 4.79 --3.44 -0.72 Unknown 13.671 12.24 -4.44 13.28 9.12 2.73 15.98 -2.67 Unknown 19.276 -1.31 -------Unknown 20.588 0.41 -5.08 0.99 -3.57 --4.70 Unknown 21.808 29.26 -29.82 30.40 65.77 13.24 45.86 -23.91 Unknown 22.682 0.35 -5.14 0.85 -4.32 --3.47 Unknown 23.670 0.33 -5.05 0.81 -4.40 --2.81 n 17 18 20 7 11 16 8 6 19 =Not detected

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71 Table 3 2. Mahalanobis distances (D 2 ) and P values from canonical d iscriminant analysis comparing FAME profiles of root tissue of S olanum lycopersicum infected with either Meloidogyne incognita race 3 (Mi), M. javanica race 1 (Mj), or an uninoculated control (Rut) maintained with diurnal temperature conditions i n either a greenhouse (G), growth room (R), or shade house (S) for 60 days. From Enviro To Enviro MiG MiR MiS MjG MjR MjS RutG RutR RutS MiG D 2 0 0.905 2.555 35.422 10.723 13.544 20.714 24.706 20.210 P 1 0.9987 0.7319 <0.0001 <0.0001 0.0002 <0.0001 <0.0001 <0.0001 MiR D 2 0.905 0 5.691 38.622 16.244 13.526 28.428 32.195 28.069 P 0.9987 1 0.3192 <0.0001 <0.0001 0.0049 <0.0001 <0.0001 <0.0001 MiS D 2 2.555 5.691 0 35.808 5.368 20.834 14.444 18.142 13.846 P 0.7319 0.3192 1 <0.0001 0.1835 <0.0001 <0.0001 <0.0001 <0.0001 MjG D 2 35.422 38.622 35.808 0 39.046 39.261 42.567 41.509 40.814 P <0.0001 <0.0001 <0.0001 1 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 MjR D 2 10.723 16.244 5.368 39.046 0 27.635 10.279 14.384 10.143 P <0.0001 <0.0001 0.1835 <0.0001 1 <0 .0001 <0.0001 <0.0001 <0.0001 MjS D 2 13.544 13.526 20.835 39.261 27.635 0 38.704 43.217 38.270 P 0.0002 0.0049 <0.0001 <0.0001 <0.0001 1 <0.0001 <0.0001 <0.0001 RutG D 2 20.7 14 28.428 14.444 42.567 10.279 38.704 0 3.126 0.550 P <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 1 0.1006 0.9958 RutR D 2 24.706 32.195 18.142 41.509 14.384 43.217 3.126 0 2.802 P <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.1006 1 0.1997 RutS D 2 20.210 28.069 13.846 40.814 10.143 38.270 0.550 2.802 0 P <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.9958 0.1997 1

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72 Table 3 3. Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first t hree canonical variates (CAN1, CAN2 CAN3 ) for separating FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained with diurnal temperature conditions in either a greenhouse (29C), growth room (26C), or shade house (18C) for 60 days Values liste d in bold (greater than |0.750|) indicate significant correlation within the given canonical variate. Fatty Acid CAN1 CAN2 CAN3 i so tridecylic 3OH 0.283 0.588 0.196 Myristic acid 0.793 0.570 0.154 i so pentadecylic 0.795 0.4 97 0.268 Palmitoleic acid 0.768 0.636 0.021 Stearic acid 0.670 0.337 0.504 t 0.723 0.680 0.105 Oleic acid 0.631 0.755 0.004 Elaidic acid 0.811 0.420 0.392 Pentacosylic N Alcohol 0.093 0.237 0.110 Sebacic C 10 Decarbox 0.833 0.346 0.201 Unknown 8.281 0.912 0.193 0.002 Unknown 11.981 0.227 0.747 0.217 Unknown 13.671 0.024 0.803 0.518 Unknown 19.276 0.723 0.680 0.105 Unknown 20.588 0.840 0.308 0.267 Unknown 21.808 0.389 0.539 0.661 Canonical Correlation 0.918 0. 884 0.629 Eigenvalue 5.375 3.570 0.654 Cumulative Proportion 0.517 0.861 0.924

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73 Table 3 4 Mean FAME concentrations ( percentage of total response ) of two nematode species infecting S olanum lycopersicum root tissue ( Meloidogyne incognita race 3 [ Mi ], M. javanica race 1 [ Mj ]) and an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 45 days. Fatty Acid C20 Mi 20 Mj 20 C26 Mi 26 Mj 26 Palmitic acid 48.59 24.78 27.68 37.58 27.28 42.63 Stearic acid 51.41 27.83 27.26 17.55 17.64 26.77 Oleic acid -4.38 4.67 -1.89 5.15 Elaidic acid ----30.52 1.03 Linoleic acid ---8.92 10.11 12.31 Unknown 13.671 -13.65 10.56 11.22 1.56 2.22 Unknown 21.808 -29.36 22.78 17.14 2.60 4.24 n 1 8 4 6 3 9 =Not detected

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74 Table 3 5 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis comparing FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3 ( Mi ), M. javanica race 1 ( Mj ), or an uninoculated control (C) maintai ned at either 20C (20) or 26C (26) for 45 days. From Species To Species C20 C26 Mi 20 Mi 26 Mj 20 Mj 26 C20 D 2 0 6.87 3.29 32.12 2.71 2.70 P 1 0.4280 0.8138 0.0053 0.8817 0.8375 C26 D 2 6.87 0 9.40 30.37 7.86 2.19 P 0.4280 1 0.0083 <0.0001 0.0392 0.2143 Mi 20 D 2 3.29 9.40 0 36.28 0.21 4.68 P 0.8138 0.0083 1 <0.0001 0.9974 0.0957 Mi 26 D 2 32.12 30.37 36.28 0 34.92 27.57 P 0.0053 <0.0001 <0.0001 1 <0.0001 <0.0001 Mj 20 D 2 2.71 7.86 0.21 34.92 0 3.26 P 0.8817 0.0392 0.9974 <0.0001 1 0.3294 Mj 26 D 2 2.70 2.19 4.68 27.57 3.26 0 P 0 .8375 0.2143 0.0957 <0.0001 0.3294 1

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75 Table 3 6 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) for separating FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 45 days Values listed in bold (greater than |0.750|) ind icate significant correlation within the given canonical variate. Fatty Acid CAN1 CAN2 CAN3 Palmitic acid 0.411 0.581 0.673 Stearic acid 0.450 0.541 0.507 Elaidic acid 0.996 0.087 0.023 Unknown 13.671 0.547 0.05 5 0.833 Unknown 21.808 0.550 0.306 0.770 Canonical Correlation 0.923 0. 752 0.396 Eigenvalue 5.729 1.305 0.186 Cumulative Proportion 0.786 0.965 0.991

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76 Table 3 7 Mean FAME concentrations ( percentage of to tal response ) of two nematode species infecting S olanum lycopersicum root tissue ( Meloidogyne incognita race 3 [ Mi ], M. javanica race 1 [ Mj ]) and an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 90 days. Fatty Acid C20 Mi 20 Mj 20 C 26 Mi 2 6 Mj 26 Pelargonic acid -0.44 0.19 -0.24 0.03 i so undecylic 0.13 0.12 0.16 0.22 0.27 0.07 Lauric acid 0.10 0.23 0.16 0.31 0.15 0.22 anteiso tridecylic 0.22 0.03 -0.09 -0.09 i so tridecylic 0.13 0.12 ---0.07 Myristic acid 0.75 0.52 0.44 0.70 1.67 1.37 anteiso myristic -0.15 -0.04 0.10 0.14 iso myristic -0.29 -0.12 0.68 0.64 iso pentadecylic 0.46 0.60 0.27 3. 97 3.04 2.82 15:1 iso F 0.08 0.04 -0.18 -0.09 15:1 iso G --0.03 -0.12 0.09 15:1 iso H/13:0 3OH 0.03 0.05 -0.04 0.20 0.10 c 0.03 0.05 0.04 0.07 --c 0.05 0.05 -0.10 --Palmitic acid 16.96 17.03 18.25 17.47 9.44 8.23 Palmitic 10 methyl 0.05 0.02 0.07 -0.14 0.09 Palmitic N A lcohol 0.11 0.02 ---0.02 anteiso palmitic 0.18 0.09 0.17 0.69 0.20 0.14 iso palmitic 0.45 0.26 0.11 2.03 1.83 1.92 c 0.02 0.03 --1.90 1.84 Palmitoleic alcohol 0.03 0.40 0.28 0.08 -0.13 c c 0.83 0.90 0.69 1.90 4.20 3.03 c 0.15 -0.08 --0.07 Margaric acid 0.53 0.45 0.79 0.78 0.45 0.67 anteiso margaric 0.35 0.21 0.18 0.99 0.60 1.06

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77 Table 3 7 Continued. Fatty Acid C20 Mi 20 Mj 20 C 26 Mi 26 Mj 26 cyclo margaric 0.11 0.23 -1.36 1.15 1.01 is o margaric 3.64 3.67 3.68 2.10 1.33 1.53 iso margaric 3OH 0.01 0.16 0.12 --0.03 17:1 iso c 0.02 0.04 --0.13 0.20 c -0.23 --0.03 0.13 c 0.14 0.12 0.07 0.46 0.18 0.17 Stearic acid 4.22 5.05 4.99 5.38 5.09 4.85 Stearic 2OH 4.84 4.32 4.04 10.81 16.54 23.67 iso stearic 0. 26 0.14 0.25 0.05 0.34 0.15 c 0.18 0.24 0.30 0.74 1.96 0.96 c 0.04 0.09 0.07 0.11 0.06 -cis vaccenic acid 8.95 9.02 8.26 7.07 15.65 13.48 cis vaccenic 11 methyl 0.13 0.02 0.11 0.44 0.51 0.82 Oleic acid -0.29 -1.82 2.01 3.23 Linoleic/ anteiso stearic 35.24 32.78 34.18 20.38 8.28 5.58 linole n ic acid 2.23 2.67 2.53 2.21 2.06 1.42 Nonadecylic acid 0.10 0.10 0.04 -0.04 0.03 cyclo nonadecylic C 10 1.29 1.99 1.85 3.47 5.00 5.02 cyclo nonadecylic C 8 0.39 0.31 0.33 0.91 1.26 1.37 Arachidic acid 8.47 8.66 9.64 5.45 4.79 4.34 iso arachidic 5.78 6.14 6.24 2.67 3.79 3.50 c -0.08 -0.06 1.19 1.01 Eicosen oic acid 0.14 0.08 0.06 -0.07 0.09 Arachidonic acid 0.05 0.15 0.23 0.39 1.73 1.99 n 1 2 1 2 1 2 1 2 1 2 1 2 =Not detected

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78 Table 3 8 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis comparing FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3 (I), M. javanica race 1 (J), or an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 90 days. From Species To Species C20 C26 Mi 20 Mi 26 Mj 20 Mj 26 C20 D 2 0 41.88 3.84 93.14 3.83 93.76 P 1 <0.0001 0.6569 <0.0001 0.6602 <0.0001 C26 D 2 41.88 0 34.74 53.24 35.4 5 54.53 P <0.0001 1 <0.0001 <0.0001 <0.0001 <0.0001 Mi 20 D 2 3.84 34.74 0 82.92 2.29 84.48 P 0.6569 <0.0001 1 <0.0001 0.9656 <0.0001 Mi 26 D 2 93.14 53.24 82.92 0 91.78 8.78 P <0.0001 <0.0001 <0.0001 1 <0.0001 0.0050 Mj 20 D 2 3.83 35.45 2.29 91.78 0 93.10 P 0.6602 <0.0001 0.9656 <0.0001 1 <0.0001 Mj 26 D 2 93.76 54.53 84.48 8.78 93.10 0 P <0.0001 <0.00 01 <0.0001 0.0050 <0.0001 1

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79 Table 3 9 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) for separating FAME profile s of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 90 days Values listed in bold (greater than |0.750|) indicate signifi cant correlation within the given canonical variate. Fatty Acid CAN1 CAN2 CAN3 Fatty Acid CAN1 CAN2 CAN3 anteiso tridecylic 0.199 0.019 0.406 c 0.868 0.422 0.228 Myristic acid 0.932 0.233 0.184 c 0.037 0.363 0.235 anteiso myristic 0.523 0.266 0.131 c 0.243 0.933 0.002 iso myristic 0.899 0.293 0.070 Stearic acid 0.254 0.641 0. 251 iso pentadecylic 0.759 0.640 0.029 iso stearic 0.062 0.691 0.549 15:1 iso G 0.866 0.379 0.176 c 0.875 0.019 0.477 c 0.678 0.708 0.007 cis vaccenic 11 methyl 0.928 0.151 0.314 Palmitic acid 0.933 0.349 0.073 Oleic acid 0.938 0.198 0.277 Palmitic N A lcohol 0.350 0.374 0.226 Linoleic / ante iso stearic 0.995 0.076 0.055 anteiso palmitic 0.064 0.978 0.050 cyclo nonadecylic C10 0.988 0.108 0.010 iso palmitic 0.859 0 .482 0.048 cyclo nonadecylic C 8 0.984 0.135 0.080 16:1 c 0.937 0.345 0.030 Arachidic acid 0.937 0.286 0.069 c c 0.963 0.012 0.264 iso arachidic 0.762 0.623 0.078 c 0.327 0.441 0.411 c 0.942 0.314 0.120 Margaric acid 0.084 0.567 0.445 Eicosenoic acid 0.112 0.877 0.151 cyclo margaric 0.794 0.586 0.062 Arachidonic acid 0.966 0.224 0.079 iso margaric 0.968 0.238 0.051 Pelargonic acid 0.247 0.394 0.434 iso margaric 3OH 0.589 0.354 0.062 Canonical Correlation 0.973 0.877 0.650 Eigenvalue 17.69 3.33 0.73 Cumulative Proportion 0.795 0.945 0.977

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80 Table 3 10 Mean FAME concentrations ( percentage of total re sponse ) of two nematode species infecting S olanum lycopersicum root tissue ( Meloidogyne incognita race 3 [ Mi ], M. javanica race 1 [ Mj ]) and an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 135 days. Fatty Acid C20 Mi 20 Mj 20 C26 Mi 26 Mj 26 Pelargonic acid ---0.38 0.23 0.05 iso undecylic 3OH -0.13 0.07 0.25 -0.07 Lauric acid 0.12 0.15 0.29 0.15 0.14 0.31 Lauric 2OH 0.18 0.07 0.06 -0.25 -Tr idecylic acid 0.16 0.04 0.04 0.26 -0.08 anteiso tridecylic 0.27 -0.23 1.38 0.30 0.43 13:1 at 12 13 -0.08 0.04 0.34 0.51 0.05 Myristic acid 1.00 0.86 0.98 1.57 1.53 1.29 Myristic 2OH 0.06 0.12 -0.34 0.00 0.33 anteiso myristic -0.13 0.06 0.17 0.14 0.12 iso myristic 0.19 0.15 0.21 0.05 0.27 0.63 iso myristic 3OH 0.07 0.11 0.06 -0.19 -anteiso pentadecylic 0.37 0.22 0.53 1.08 1.12 1.23 iso pentadecylic 0.76 0.45 0.87 0.66 3.19 2.43 15:1 iso G 0.11 0.07 --0.36 0.17 15:1 iso H/13:0 3OH 0.05 0.07 0.06 0.24 -0.24 15:1 iso c --0.09 0.34 -0.04 c 0.16 0.09 0.10 0.37 -0.25 Palmitic acid 19.09 18 .77 15.86 19.84 10.39 9.65 Palmitic 2OH 0.11 0.40 0.15 0.24 0.06 0.32 Palmitic N alcohol 0.16 -0.16 0.20 0.09 0.03 anteiso palmitic 0.19 0.21 0.08 0.96 --iso palmitic 0.44 0.28 0.45 1.12 1.29 1.16 iso p almitic 3OH 0.11 0.09 0.17 0.10 0.10 0.19 16:1 2OH -0.06 -0.15 0.08 0.25 c 0.06 -0.08 0.42 -0.18

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81 Table 3 10 Continued. Fatty Acid C20 Mi 20 Mj 20 C26 Mi 26 Mj 26 c -0.10 0.27 -2.86 1.15 Palmitoleic A lcohol 0.32 0.13 0.49 0 .37 0.10 0.45 c c 0.62 0.69 1.52 1.94 2.84 2.64 Margaric acid 1.10 0.45 0.89 0.53 1.07 0.89 Margaric 10 methyl 0.11 0.13 0.05 0.09 --anteiso margaric 0.51 0.49 0.52 1.13 0.52 0.91 cyclo margar ic 0.11 0.15 0.20 0.17 0.43 1.04 iso margaric 4.26 2.51 2.90 2.81 1.22 1.34 iso margaric 3OH -0.07 0.57 1.10 0.41 0.39 c 0.06 0.15 0.05 0.15 0.19 0.28 c 0.22 0.14 0.16 0.05 0.29 0.16 17: c 0.05 0.17 0.17 0.14 0.29 0.38 Stearic acid 5.01 5.05 5.07 6.03 6.41 5.39 Stearic 2OH 3.59 2.74 3.08 4.91 8.13 12.04 iso stearic 0.59 2.41 1.18 0.55 0.54 0.16 18:1 2OH 0.20 -0.11 0.12 0.08 0.10 18:1 c 0.56 0.94 1.10 0.76 1.14 0.74 c 0.43 0.04 0.09 0.33 -0.08 cis vaccenic acid 6.48 11.60 15.66 4.16 16.80 16.76 cis vaccenic 11 methyl -0.23 0.04 0.13 0.54 0.71 Oleic acid ----5.59 4.73 Linoleic / ante iso stearic 29.37 30.31 24.00 25.73 10.14 9.97 linole n ic acid 2.49 2.27 2.11 0.87 1.27 2.15 Nonadecylic acid 0.10 0.04 0.06 0.27 --cyclo nonadecylic C10 1.29 1.60 1.32 2.46 2.76 3.99 cyclo nonadec ylic C8 0.26 0.31 0.45 0.40 1.30 1.27 c c 0.07 0.14 -0.32 --Arachidic acid 8.21 7.08 9.15 3.19 4.16 4.84

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82 Table 3 1 0 Continued. Fatty Acid C20 Mi 20 Mj 20 C26 Mi 26 Mj 26 iso arachidic 6.67 5.19 4.87 2.53 2.37 3.06 c -0.39 0.91 -1.55 1.38 Eicosenoic acid 0.32 0.16 0.10 --0.09 Eicosadienoic acid 0.07 0.24 0.19 2.60 0.60 -Arachidonic acid -0.04 0.08 0.32 1.31 1.19 n 10 1 2 1 0 8 1 1 9 =Not detected

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83 Table 3 1 1 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis comparing FAME profiles of S olanum lycop ersicum root tissue infected with either Meloidogyne incognita race 3 (I), M. javanica race 1 (J), or an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 135 days. From Species To Species C20 C 26 Mi 20 Mi 26 Mj 20 Mj 26 C20 D 2 0 142.96 91.83 949.23 110.92 1142.00 P 1 0.0013 0.0151 <0.0001 0.0056 <0.0001 C26 D 2 142.96 0 139.11 922.61 170.96 1209.00 P 0.0013 1 0.0009 <0.0001 0.0002 <0.000 1 Mi 20 D 2 91.83 139.11 0 873.26 43.27 1024.00 P 0.0151 0.0009 1 <0.0001 0.2221 <0.0001 Mi 26 D 2 949.23 922.61 873.26 0 746.14 158.90 P <0.0001 <0.0001 <0.0001 1 <0.0001 0.0007 Mj 20 D 2 110.92 170.96 43.27 746.14 0 851.47 P 0.0056 0.0002 0.2221 <0.0001 1 <0.0001 Mj 26 D 2 1142.00 1209.00 1024.00 158.90 851.47 0 P <0.0001 <0.0001 <0.0001 0.0007 <0.0001 1

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84 Table 3 1 2 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first t wo canonical variates (CAN1 and CAN2) for separating FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3, M. javanica race 1, or an uninoculated control maintained at either 20C or 26C for 135 days Values listed in bold (greater than |0.750|) indicate significant correlation within the given canoni cal variate. Fatty Acid CAN1 CAN2 Fatty Acid CAN1 CAN2 iso undecylic 3OH 0.450 0.374 cyclo margaric 0.887 0.216 Lauric acid 0.416 0.619 iso margaric 0.853 0.119 Lauric 2OH 0.144 0.257 iso margaric 3OH 0.081 0.589 Tridecylic acid 0.471 0.474 c 0.476 0.063 anteiso tridecylic 0.158 0.707 c 0.931 0.101 13:1 at 12 13 0.261 0.900 Stearic acid 0.408 0.892 Myristic acid 0.432 0.837 iso stearic 0.523 0.373 Myris tic 2OH 0.153 0.194 c 0.203 0.011 anteiso myristic 0.256 0.542 c 0.556 0.289 iso myristic 3OH 0.147 0.154 cis vaccenic acid 0.739 0.447 anteiso pentadecylic 0.705 0.515 cis vaccenic 11 methyl 0.944 0.012 iso pentadecylic 0.951 0.214 Oleic acid 0.979 0.165 15:1 iso G 0.770 0.272 Linoleic / ante iso stearic 0.973 0.137 15:1 iso H/13:0 3OH 0.128 0.122 linole n ic acid 0.058 0.907 15:1 iso c 0.357 0.578 Nonadecylic acid 0.628 0.57 9 c 0.181 0.279 cyclo nonadecylic C10 0.838 0.177 Palmitic N A lcohol 0.467 0.469 cyclo nonadecylic C8 0.990 0.125 anteiso palmitic 0.562 0.624 c c 0.597 0.566 iso palmitic 0.697 0.637 Arachidic acid 0.422 0.756 iso palmitic 3OH 0.458 0.570 iso arachidic 0.578 0.613 16:1 2OH 0.619 0.147 Eicosenoic acid 0.382 0.558 c 0.150 0.486 Arachidonic acid 0.960 0.277 c 0.832 0.327 Pelargonic acid 0.027 0.936 Margaric acid 0.459 0.062 Canonical Correlation 0.998 0.979 Eigenvalue 216.10 23.07 Cumulative Proportion 0.834 0.923

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85 Figure 3 1. Instant FAME extraction and Rapid analysi s method developed by MIDI (Newark, DE).

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86 Figure 3 2. Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3 (Mi), M. ja vanica race 1 (Mj), or an uninoculated control (Rut) maintained with diurnal temperature conditions in either a greenhouse (G), growth room (R), or shade house (S) for 60 days.

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87 Figure 3 3 Canonical discriminant analysis after stepwise discriminant ana lysis comparing FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3 ( Mi ), M. javanica race 1 ( Mj ), or an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 45 days. A) CAN1 ( x axis) versus CAN2 ( y axis) and B) CAN1 ( x axis) versus CAN3 ( y axis). A B

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88 Figure 3 4 Canonical discriminant analysis after stepwise discriminant analysis comparing FAME profiles of Solanum lycopersicum root tissue infected with either Meloidog yne incognita race 3 ( Mi ) M. javanica race 1 ( Mj ) or an uninoculated control (C) maintained at either 20C (20) or 26C (26) for 90 days. A) CAN1 ( x axis) versus CAN2 ( y axis) and B) CAN1 ( x axis) versus CAN3 ( y axis). A B

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89 Figure 3 5 Canonical discrimin ant analysis after stepwise discriminant analysis comparing FAME profiles of S olanum lycopersicum root tissue infected with either Meloidogyne incognita race 3 ( Mi ), M. javanica race 1 ( Mj ), or an uninoculated control (C) maintained at either 20 C (20) or 26C (26) for 135 days.

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90 CHAPTER 4 APPLICATION OF INSTANT FAME FOR IDENTIFICATION OF MELOIDOGYNE SPP. 4 .1 Introduction Studies have indicated that Meloidogyne sp ecies can be identified within root tissue using the standard fatty acid methyl este r (FAME) analysis (Sekora et al. 2010a) This identification procedure involves extracting nematode fatty acids from root tissue and then analyzing the proportions of each fatty acid within an extraction. The standard extraction method for FAME analysi s of 1 to 72 samples requires a process that takes approximately 3.5 hours to complete using at least 40 mg of tissue ( Kunitsky et al. 2005; Sasser, 1990). The subsequent analysis using gas chromatography can take 20 to 45 minutes depending on the type o f analysis performed and the chain length of the target fatty acids. Therefore, t o extract and analyze 30 samples using the standard methods would take 14 to 27 hours and be limited by the speed of sample analysis. To alleviate these time limitations, MID I developed their Instant FAME extraction and Rapid analysis method to completely extract and analyze a sample in 15 minutes. According to MIDI the addition of 250 L each of a series of three kit based reagents to 3 mg of tissue will produce a sample eq uivalent to one produced using their standard extraction method in only five minutes. To analyze this sample a method utilizing higher temperature ramping and increased pressure than standard analysis methods allow s fatty acids ranging in chain length fr om 9 to 20 carbons to be identified in less than 10 minutes. Using these proposed extraction and analysis methods, the same 30 samples analyzed previously would take 7.5 hours to complete, a time reduction of 47 to 74% depending on the analysis method use d

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91 Based on these claims, FAME analysis of nematode infected root tissue could be greatly simplified and more easily adapted for diagnostic applications. The objective of this chapter w as to d etermine if FAME identification of Meloidogyne sp ecies in root tissue can be adapted to the Instant FAME extraction and Rapid analysis to reduce sample analysis time by comparing 1) standard methods to Instant FAME and Rapid analysis using recommended quantities of infected tissue and 2) standard extraction to Instant FAME extraction using equal tissue mass 4 .2 Materials and Methods 4 .2.1 Methods Evaluated The methods evaluated in these experiments included combinations of extraction methods and analysis methods as follows: standard FAME extraction (SE), Instant FAME extraction (RE), standard FAME analysis with the EUKARY method (SA), and Rapid FAME analysis with the RTSBA6 method (RA). SE and RE FAME extraction methods vary in many ways, but primarily in the volumes of reagents used and the requirement of water bath heating in the standard extraction method ( Table 4 1). Sample size requirements also differ between extraction methods with SE demanding at least 40 mg of tissue and RE needing only 3 mg of tissue. Both SA and RA methods have an initial temperature of 17 0C and a final temperature of 310C, but temperature ramping and column pressure are higher using RA ( Table 4 2). Analysis run time for RA (about 6 minutes) is also considerably shorter than SA (40 minutes). 4 .2.2 Nematode Populations Four nematode popul ations reared in a greenhouse were used to evaluate the Instant FAME and Rapid analysis methods, Meloidogyne incognita races 2 and 3 and two isolates of M javanica race 1. Meloidogyne incognita race 3 and one isolate of M.

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92 javanica race 1 were maintained on Solanum lycopersicum M. incognita race 2 and the second M. javanica race 1 isolate were maintained on Solenostemon scutellarioides Populations from S. lycopersicum were used for comparing Instant FAME methods to stan dard methods while the S. scutellarioides populations were used to compare extraction methods using equal tissue sample size 4 .2.3 Instant FAME and Rapid Analysis Evaluation An experiment was conducted to compare the relative performance of the various co mbinations of extraction methods and analyses. Root tissue samples of S. lycopersicum M. incognita race 2 or M. javanica race 1 was subjected to extraction and analysis methods in a 2 2 factorial design with the SE RE SA RA Standard extraction and analysis was conducted using 40 mg of infected tissue as mentioned previously (Chapter 2 ); rapid extraction and analysis followed the methods described by MIDI (2011 ). Tw enty samples were prepared using extractions from M. incognita and M. javanica tissue using either extraction method (80 total extractions) and analyzed with both the standard EUKARY method and the Rapid RTSBA6 method (160 total analyses). 4 .2.4 Extraction Comparison Using Equal Tissue Mass An experiment was conducted to determine if using the root tissue amount normally used for SE (40 mg) could be used for RE. Samples containing 40 mg of S scutellarioides root tissue infected with either M. incognita ra ce 2 or M. javanica race 1 were used to evaluate extracting 40 mg of tissue with RE Each sample combination

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93 (nematode, extraction) was replicated 20 times for a total of 80 samples. All samples were analyzed using RA 4 .2.5 Statistical Analysis Extracti on and analysis methods were scrutinized for repeatability of results and robustness of profiles while still being able to separate M. incognita from M. javanica P rofiles were imported into SAS ( SAS Institute, Cary, NC) for further analysis. Mean profil PROC MEANS which provided the average response for each fatty acid in all samples for the given class. Additional statistical tests were performed using with PROC STEPDISC in combination with PROC CANDISC following the method of Sekora et al (2010). Stepwise discriminant analysis (SDA) by PROC STEPDISC was used to determine which fatty acids were significant for discrimination among classes using a series of stepwise analysi s of variance (ANOVA) tests that evaluate the F value of each fatty acid before and after inclusion (Johnson, 1998). After analysis of each fatty acid, fatty acids significant for delineation ( P < 0.15) were used for canonical discriminant analysis (CDA) with PROC CANDISC. C anonical discriminant analysis produces class means based on sample variance within each compared class and then represents relationships among classes in dimensional space. The dimensional space is represented by canonical variates (C AN1, CAN2, up to class n 1) that demonstrate class separation in graphical representation and can be assigned to x y or z axes depending on the desired class comparisons. Canonical variates are also used to describe the total multivariance within a test and the number of variates in these tests was reduced to the fewest that could define at least 75% cumulative proportion of the total multivariance ( n CAN < 3).

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94 correlatio n ( 1 to 1) of a given fatty acid along the chosen canonical variate. Absolute values approaching |1.000| indicate a high degree of correlation and help to separate classes on the specified dimension. The greater the value of correlation, the greater the spatial distance (Mahalanobis distance or D 2 ) among means graphically along a given canonical variate (Johnson, 1998). For the experiments described in this paper, high canonical correlation was described by correlations greater than |0.750| and signific ant means separation was achieved with D 2 having a P < 0.05. Additional information provided by CDA is the canonical correlation and e igenvalue of each canonical variate. Canonical correlation values range from 0 to | 1 .000| and are an indicator of the imp ortance of each canonical variate to the separation of classes. Canonical correlation values approaching | 1 .000| are considered more informative for describing the majority of multivariance within a given analysis. The eigenvalue is another statistic sim ilar to canonical correlation that is used to rank canonical variates based on the multivariance explained by the selected variate. As with canonical correlations, higher values indicate a greater degree of explained multivariance in an analysis for the g iven canonical variate (Johnson, 1998). Six c lasses were used in SDA and CDA to produce comparisons between extractions (SE and RE) analyses (SA and RA) nematode species infecting tissue (I2 and J1), and among all eight possible combinations ( I2 SESA, J1 R ESA, etc. ). A total of 30 comparisons were made for the first experiment and 6 were made for the extraction comparison in the second experiment.

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95 4 .3 Results 4 .3.1 Instant FAME and Rapid Analysis Evaluation Of the 160 total prepared samples 118 produced u sable FAME profiles ( profiles with > 2 fatty acids; Table 4 3 ) Samples prepared using the Instant FAME method generated 48 of 80 profiles that could be utilized for statistical analysis; 70 of the 80 standard extraction samples produced usable profiles. Additionally, all 80 of the samples prepared for Rapid analysis produced adequate FAME profiles for statistical comparison while only 38 of the samples analyzed using standard analysis yielded usable FAME profiles Among the 160 samples analyzed, 79 fatt y acids were observed with expression varying from 0 to 81.48% in 118 usable profiles ( Table 4 4 ). 4 .3.1.1 Standard extraction versus Instant FAME Standard extraction (SE) yielded more total fatty acids (79) than RE (55 ) but > 65% of these were expressed a t concentrations less than 1.00% of the total response ( Table 4 4 ). For SE and RE cis vaccenic acid was found at the highest concentration (23.2 and 41.2%, respectively) followed by palmitic acid (15.1%) and ste a ric acid (12.2%) in SE extractions and lin oleic acid ( 12.7% ) and palmitic acid (12.0%) in RE extractions. C anonical discriminant analysis of extraction methods was able to separate profiles generated with the SE procedure from those produced with RE ( P < 0.0001, D 2 =19). From the 3 6 fatty acids se lected by SDA for CDA, five were negatively correlated with the SE method ( iso lauric palmitoleic /16:1 6c, stearic 2OH, cis vaccenic and arachidic acids ; Table 4 5 ). All six of these fatty acids were found at higher relative concentrations in samples extracted using the RE method than in samples subjected to SE extraction.

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96 4 .3.1.2 Standard analysis compa red to Rapid analysis An average of 75 fat ty acids was observed using RA versus only 9 with SA Of these observed fatty acids, 91% and 33% were present at less than 1.00% mean concentration in samples analyzed by RA and SA respectively. In samples analy zed with RA cis vaccenic linoleic and palmitic acids had the highest mean concentration, while vaccenic acid palmitic acid and 18:1 8t were the most predominant in samples subjected to SA C anonical discriminant analysis indicated a significant degree of separation between RA and SA ( P < 0.0001, D 2 = 782). Stepwise discriminant analysis chose 35 fatty acids for further analysis with CDA, five of which were negatively correlated with RA ( palmitoleic acid stearic acid 18:1 8t, elaidic acid and linoleic acid ; Table 4 6 ). The only one of these fatty acids observed in samples utilizing RA ( stearic acid ) had a mean concentration 40% low er than samples analyzed with SA 4 .3.1.3 Extraction \ analysis coupled comparisons A greater number of fatty acids were observed in M. incognita and M. javanica infected tissue samples utilizing the SERA combination (73 and 75, respectively) than with any o ther extraction/analysis combination ( Table 4 4 ). Root samples of M. incognita and M. javanica submitted to the RESA combination had the fewest number of fatty acids observed (3 and 4, respectively), followed by SESA combinations (9 and 7, respectively) a nd RERA (32 and 46, respectively). More f atty acids containing hydroxyl ( OH) groups were observed in samples submitted to SE than in samples that underwent the RE procedure. Additionally, 18C unsaturated fatty acids ( cis vaccenic acid elaidic acid lin oleic acid etc.) differed in their expression between R A and S A

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97 regardless of extraction method For example, elaidic acid was only observed in SA samples, while cis vaccenic and linoleic acids were only observed in RA samples. Classes utilizing SA coul d not be differentiated from one another in 66% of CDA comparisons ( P > 0. 2854 2.95 < D 2 < 39.95 ; Table 4 7 ). All classes using RA were significantly different from all others using CDA ( P < 0.0001, D 2 > 25.0 8 ). Analysis methods and extraction methods within the RA category were visibly separated by canonical variates ; CAN1 separated SA from RA and CAN2 separated RA into RE and SE groups ( Figure 4 1 ) Stepwise discriminant analysis selected 41 fatty acids for use in CDA, 11 of which were significant fo r separating RA from SA along CAN1 ( Table 4 8 ). From these 11 fatty acids, 5 ( palmitoleic cis vaccenic acid 16:1 5c, arachidic acid and stearic 2OH) were highly correlated (canonical correlation > |0.914|) and were only found in samples analyz ed using RA Extraction methods within samples utilizing RA were demarcated by five fatty acids (17:1 9c, 17:1 8c, lauric 2OH, 15:1 5c, and pentadecylic 3OH) found only in SERA combinations. The fatty acid myristic 2OH was also significant in CAN2 and wa s only observed in SERA combinations since the mean expression in J1RERA samples was equal to its standard error (0.03174 + 0.03174). Using only RA M. incognita could be distinguished from M. javanica using either extraction method ( P < 0.0001, D 2 > 99 ; T able 3 9 Figure 4 2 ). Stepwise discriminant analysis selected 54 fatty acids for CDA, 39 of which were significant for separating extraction methods and Meloidogyne species ( Table 4 10 ). Extraction methods were separated along CAN1 by 30 highly correlat ed fatty acids the majority of which only appeared in SE samples Six of the eight fatty acids separating I2 and J1 along CAN2

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98 within RE or SE were found at higher mean concentrations in I2RE and J1SE than in their respective counterparts, J1RE and I2SE. The single fatty acid with significant correlation along CAN3 ( stearic acid |0.813|) helped to further separate I2 and J1 within each extraction method. 4 .3.2 Extraction Comparison Using Equal Tissue Mass A total of 112 fatty acids were observed among t he 80 samples analyzed, but the actual number of fatty acids found in a single nematode/extraction combination ranged from 99 to 110 ( Table 4 11 ). The most prevalent fatty acid detected was cis vaccenic acid in SE of M. incognita and M. javanica infected tissue (35.65 and 27.91%, respectively), whereas linoleic / ante iso stearic was most abundant in M. incognita and M. javanica infected tissue that was submitted to RE (30.94 and 30.49%, respectively). Both RE and SE extraction methods produced comparable pr oportions of saturated (mean 2.39 and 2.28%, respectively) and unsaturated fatty acids (mean 4.30 and 4.18%, respectively). However, SE samples of M. incognita and M. javanica infected tissue possessed proportions of hydroxylated fatty acids (mean 0.21 an d 0.22%, respectively) at more than twice that of RE samples (mean 0.10 and 0.09% respectively ). C anonical discriminant analysis coupled with S DA produced canonical means with very large D 2 values (D 2 > 18,374,852, Table 4 1 2 ), canonical correlations ( 1.0 0, data not shown ) and eigenvalues (approaching infinity, data not shown ) among classes. Alt hough this analysis graphically demonstrated the differences among classes ( Figure 4 3 ), it was not adequate for determining which fatty acids contributed to thes e differences. As a result, a truncated SDA was used that had fewer total steps (32) than the full SDA possible (80 total steps). While this reduced SDA does not demonstrate

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99 the full degree of separation among classes, it does allow for a more complete c omparison. Employing the abridged SDA c lasses were still clearly separated by extraction method and species ( P < 0.0001, D 2 > 80100; Table 4 1 3 ). This SDA selected 74 fatty acids for CDA, 60 of which were highly correlated along the three canonical varia tes ( Table 4 1 4 ) The greatest amount of multivariance among classes was between I2SE and J1RE, acco unting for 99.5% of the total m ultivariance. Forty three fatty acids were highly correlated along CAN1, nineteen of which were correlated at greater than |0.900|. The majority of these fatty acids were observed at higher concentrations in one extraction method versus the other method, but none were found exclusively in a given extraction method. The remaining 16 fatty acids significantly correlated in CAN2 and CAN3 (8 fatty acids each), al though explaining only 0.5% of the total multivariance, separated M. incognita infected tissue from M. javanica infected tissue within each extraction method. The best spatial separation of M. incognita infected tissue fr om M. javanica infected tissue was along CAN 3 separat ing them within S E but was less significant ( P = 0.0006) than the separation of infected tissue along CAN2 and within RE ( P < 0.0001) 4 .4 Discussion Root tissue infected with M incognita race 2 or M. javanica race 1 could be differentiated from one another using either the Instant FAME or standard extraction methods, but standard extraction (SE) appeared to be more efficient at extracting fatty acids from tissue. However, closer inspection of the FAM E profiles produced by standard extraction methods showed that more art e facts may be produced during this extraction method than the Instant FAME method. For example, fatty acids containing

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100 hydroxyl ( OH) groups were observed in samples submitted to stand ard extraction at concentrations more than twice those of samples that underwent the Instant FAME procedure. This could be a result of the half hour of boiling in 3.0 M NaOH during the first step of the extraction procedure and could present artificial re sults. Additionally, the five fatty acids that were negatively correlated with the standard extraction method ( iso lauric acid palmitoleic /16:1 6c, stearic 2OH, cis vaccenic acid and arachidic acid ; Table 4 5 ) were only found in samples that were anal yzed using the Rapid analysis procedure. T hese differences may be due to the chemical nature of the extraction methods, but the variation of fatty acid concentrations may not be critical if separation of Meloidog yne species is still achieved. Using the R apid analysis method provide d more consistent FAME profiles than the standard analysis method for separation of Meloidogyne infected root tissue All 120 samples analyzed by Rapid analysis produced FAME profiles that could be used for identification and s tatistical analysis, compared to 38 of 80 using standard extraction methods. Similar to differences in extraction methods, elaidic acid was only found in samples undergoing standard analysis and not in samples utilizing the Rapid method. Many fatty acids were not observed in standard analysis samples and indicated a greatly reduced sensitivity compared to Rapid analysis. This reduced sensitivity was most apparent when attempting to separate infected root tissue using either extraction method. The inabil ity of the SA method to produce FAME profiles that can separate Meloidogyne species makes it inferior to the Rapid method for nematode applications. Separation between M. incognita and M. javanica infected tissue is pos sible using 3.0 mg of root tissue, bu t larger sample sizes coupl ed with Instant FAME extraction and

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101 Rapid analysis provides greater resolution between M. incognita and M. javanica infected tissue Statistically there is no difference between standard extraction methods and Instant FAME extra ctions using 40 mg of root tiss ue. Discrimination of root tissue infected with Meloidogyne species is possible using either extraction method, but Instant FAME provides extractions that are more statistically robust and consistent than standard extraction methods. Because of the greatly increased resolution between nematode infected root tissues t he coupled Instant FAME and Rapid analysis procedures using 40 mg of plant tissue may provide a more rapid method for diagnostic identification of Meloidogyne sp ecies than traditional methods Future work will focus on determining the sensitivity of Instant FAME extractions for nematode densities down to single individuals We will also a ssess the se FAME methods for quantification of Meloidogyne species with in r oot tissue.

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102 Table 4 1. Comparison of FAME extraction steps for standard and Instant FAME methods. Extraction Step Standard Extraction Instant FAME Extraction Saponification Reagent 3.00 M NaOH 0.82 M KOH in CH 3 OH V olume 1.0 mL 250 L Mixing Vortex 10 seconds Vortex 10 seconds Heating 100C waterbath for 5 minutes, repeat vortex, 100C waterbath for 25 minutes ; cool to room temperature None Methylation Reagent 2.93 M HCl in 41.25% aqueous CH 3 OH Completed during saponification Volume 2.0 mL Mixing Vortex 5 seconds Heating 80C + 1C for 10 minutes ; cool rapidly in flowing water Extraction Reagent 50/50 by volume hexane/methyl tert butyl ether n Hexane Vol ume 1.25 mL 250 L Mixing Tumble for 10 minutes Vortex 3 seconds Base Wash Reagent 0.3 M NaOH Neutralization step with 1.92 M HCl Volume 3.0 mL 250 L Mixing Tumble for 5 minutes followed by 10 15 minutes resting None Tr ansfer 1.0 mL of top phase to 1.5 mL vial, evaporate, reconstitute in 75 L extraction reagent, transfer to spring vial 150 L of top phase to spring vial

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103 Table 4 2. Gas chromatogram parameters required for standard FAME analysis us ing the EUKARY method and Rapid FAME analysis using the RTSBA6 method. Gas Chromatography Parameter Standard EUKARY Analysis Rapid RTSBA6 Analysis Column Initial Temperature 170C 170C Initial Pressure 9.0 psi 2 1.0 psi Ramp Temperature 5C per minute for 28:00 2 8 C per minute for 4:07, then 60C per minute Final Temperature 310C, hold for 12:00 310C hold for 1:15 min Run Time 40:00 minutes 5:4 8 minutes Fatty Acids Detected 9:0 to 30:0 carbons 9:0 to 20:0 carbons Calibration Standard MIDI Calibration Mix 2 MIDI Calibration Mix 1 =Both methods utilize an Ultra 2 Cross linked 2% Phenyl Methyl Siloxane 0.2 m m 25 m column with 0.33 m film

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104 Table 4 3 FAME profiles produced b y eight combinations of two nematode species ( Meloidogyne incognita race 2 [I 2 ], M. javanica race 1 [J1]), two extraction methods ( Instant FAME extraction [RE], standard extraction [SE]), and two analysis methods (Rapid analysis [RA], and standard analysis [SA]) Usable profiles contain at least two fatty acids. Extraction/Analysis Combination Average Fatty Acids per Profile Usable Profiles out of 20 Reps I 2 RERA 32 20 I 2 RESA 3 3 I 2 SERA 73 20 I 2 SESA 9 18 J1RERA 46 20 J1RESA 4 5 J1SERA 75 20 J1SESA 7 12

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105 Table 4 4 Mean FAME concentrations ( percentage of total response ) o f eight combinations of two nematode species infecting root tissue ( Meloidogyne incognita race 2 [I 2 ], M. javanica race 1 [J1] ), two extraction methods ( Instant FAME extraction [RE], standard extraction [SE]), and two analysis methods (Rapid analysis [RA], and standard analysis [SA]). Nematode/Extraction/Analysis Combination Fatty Acid I 2 RERA I 2 RESA I 2 SERA I 2 SESA J1RERA J1RESA J1SERA J1SESA Capric acid 0.08 -0.07 -0.03 -0.28 -Capric 2 OH --0.09 ---0.13 -Capric 3 OH 0.33 -0.03 ---0.13 -Undecylic acid 0.16 -0.02 ---0. 07 -Undecylic 2 OH 0.12 -0.06 ---0.17 -Lauric acid 0.21 -0.58 -0.41 -0.29 -Lauric 2 OH --1.05 ---1.78 -Lauric 3 OH --0.08 -0.02 -0.08 -anteiso lauric --0.10 -0.03 -0.11 -iso lauric 0.12 -0.03 -0.12 -0.08 -Tridecylic acid --0.16 -0.13 -0.05 -Tridecylic 2 OH 0.18 -0.09 -0.03 -0.18 -anteiso tridecylic 0.09 -0.05 ---0.06 -iso t ridecylic 0.07 -0.07 -0.18 -0.22 -13:1 at 12 13 --0.09 -0.03 -0.06 -Myristic acid 2.87 -1.68 1.39 1.66 -1.54 1.62 Myristic 2 OH --0.16 -0.03 -0.44 -anteiso myristic --0.96 --0.70 -iso myristic --0.10 -0.05 -0.07 -Pentadecylic 2 OH --0.10 ---0.26 -Pentadecylic 3 OH --0.14 ---0.18 -anteiso pentadecylic 0.03 -0.17 -0.02 -0.27 -iso pentadecylic 1.47 -1.34 -1.09 -1.59 -15:1 anteiso A --0.66 ---0.31 -15:1 iso F ------0.22 -

PAGE 106

106 Table 4 4 Continued. Fatty Acid I2RERA I2RESA I2SER A I2SESA J1RERA J1RESA J1SERA J1SESA 15:1 iso G --1.04 ---0.52 -c --0.13 ---0.19 -c 0.03 ---0.03 -0.19 -Palmitic acid 11.30 11.20 11.58 21.68 11.59 17.29 8.95 21.52 Palmitic 2 OH --0.03 -0.05 -0.13 -Palmitic N A lcohol 0.07 -0. 03 -0.02 -0.19 -anteiso palmitic --0.19 -0.02 -0.17 -iso palmitic 0.08 -0.11 -0.05 -0.25 -iso palmitic 3 OH --0.04 -0.04 -0.06 -16:1 2 OH --0.56 ---0.45 -16:1 i so G 0.03 -0.04 ---0.07 -16:1 iso H --0.08 -0.02 -0.08 -c 0.64 -0.59 -0.42 -0.80 -cis vaccenic --0.20 ---0.03 -cis vaccenic ---0.33 ---1.62 cis vaccenic A lcohol 0.03 -0.04 -0.02 -0.11 -cis vaccenic c 2.34 -1.72 -1.98 -2.41 -Margaric acid --1.02 ---0.73 -Margaric 10 methyl --0.02 ---0.06 -Margaric 2 OH --0.03 -0.05 -0.23 -anteiso margaric --0.83 -0.08 -0.60 cyclo margaric --0.42 ---0.29 -iso margaric 0.95 -1.73 -0.76 -1.80 -iso margaric 3 OH --2.58 ---1.09 -17:1 iso c --0.52 -0.05 -0.45 -17:1 anteiso A --0.06 -0.02 -0.07 -17:1 anteiso c --0.40 ---0.24 -

PAGE 107

107 Table 4 4 Continued. Fatty Acid I2RERA I2RESA I2SER A I2SESA J1RERA J1RESA J1SERA J1SESA 17:1 iso I/ anteiso --0.05 -0.02 -0.08 -c --0.09 -0.07 -0.20 -c --0.13 ---0.24 -c --0.06 ---0.16 -Stear ic acid 8.18 7.32 9.46 16.98 7.20 1.62 8.50 15.74 Stearic 10 methyl --0.14 -0.02 -0.02 -Stearic 2 OH 1.24 -0.89 -0.71 -1.04 -iso stearic --0.09 -0.13 -0.17 -18:1 iso H --0.11 ---0.07 -c 1.08 -1.00 0.07 1.09 -1.30 -cis vaccenic 50.83 -38.37 -48.13 -42.68 ----21.12 ---21.47 c 0.12 -1.18 1.08 --0.26 -Elaidic acid -81.48 -27.29 -60.63 -29.64 Linoleic / Stearic 11.30 -9.72 -19.20 -7.19 -Linoleic acid ---5.13 -20.47 -5.64 linole n ic acid 1.58 -0.69 ---0.77 -Nonadecylic acid --0.33 ---0.17 -cycl o nonadecylic C10 --0.67 -0.03 -1.28 -iso nonadecylic --0.21 ---0.09 -c /19:1 --0.18 ---0.02 -c c /19 cy clo --0.21 -0.02 -0.07 -Arachidic acid 0.67 -1.37 -1.13 -1.73 -iso arachidic 0.13 -0.04 -0.11 -0.04 -2.23 -2.11 -2.43 -2.77 -Eicosenoic acid --0.19 -0.07 -0.13 -Arachidonic acid 0.02 -0.03 -0.18 -0.37 -n 20 3 20 18 20 5 20 12 =Not detected

PAGE 108

108 Table 4 5 Correlation values between canonical structure and fatty acids selected by stepwise discriminant analysis in the first canonical variate separating stan dard FAME extraction from Instant FAME extraction of Meloidogyne infected root tissue Fatty Acid CAN1 Capric acid 1 Capric 2 OH 1 Undecylic 2 OH 1 Lauric 2 OH 1 anteiso lauric 1 iso lauric 1 iso myristic 1 Pa lmitic acid 1 anteiso palmitic 1 palmitoleic 1 Palmitoleic 1 Margaric acid 1 Margaric 10 methyl 1 iso margaric 3 OH 1 17:1 iso c 1 17:1 anteiso A 1 17:1 anteiso c 1 17:1 iso I/ anteiso 1 c 1 c 1 c 1 Stearic acid 1 Stearic 10 methyl 1 Stearic 2 OH 1 iso stearic 1 18:1 iso H 1 c 1 Elaidic acid 1 Linoleic / stearic 1 Nonadecylic acid 1 cyclo nonadecy lic C10 1 c /19:1 1 Arachidic acid 1 c 1 Eicosenoic acid 1 Canonical Correlation 0.90 8 Eigenvalue 4.67 Cumulative Proportion 1

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109 Table 4 6 Correlation values between canonical structure and fat ty acids selected by stepwise discriminant analysis in the first canonical variate separating standard FAME analysis (EUKARY method) from Rapid analysis of Meloidogyne infected root tissue Fatty Acid CAN1 Capric 3 OH 1 Lauric acid 1 Lauric 2 OH 1 Lauric 3 OH 1 anteiso lauric 1 13:1 at 12 13 1 anteiso pentadecylic 1 iso pentadecylic 1 15:1 iso G 1 Palmitic N A lcohol 1 16:1 iso H 1 Palmitoleic acid 1 Palmitoleic A lcohol 1 Palmitolei c /16:1 w6c 1 Margaric acid 1 Margaric 10 methyl 1 iso margaric 1 iso margaric 3 OH 1 17:1 iso I/ anteiso 1 17:1 w9 c 1 Stearic acid 1 Stearic 2 OH 1 18:1 iso H 1 18:1 w5 c 1 cis vaccenic 1 18:1 w8 t 1 Elaidic acid 1 Linoleic / stearic 1 Linoleic acid 1 linole n ic acid 1 cyclo nonadecylic C10 1 iso nonadecylic 1 Arachidic acid 1 iso arachidic 1 20:1 w7c 1 Canonical Correlation 0.9 97 Eigenvalue 173.82 Cumulative Proportion 1

PAGE 110

110 Table 4 7 Mahalanobis dista nces (D 2 ) and P values from canonical discriminant analysis comparing two nematode species infecting root tissue ( Meloidogyne incognita race 2 [I2], M. javanica race 1 [J1]), two extraction methods ( Instant FAME extraction [RE], standard extraction [SE]), and two analysis methods (Rapid analysis [RA], and standard analysis [SA]) From Analysis To Analysis I2RERA I2RESA I2SERA I2SESA J1RERA J1RESA J1SERA J1SESA I2RERA D 2 0 64 1.26 104.43 619. 70 25.08 67 8.47 195.4 1 627. 19 P 1 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 I2RESA D 2 64 1.26 0 8 48.27 1 2.19 79 1.81 39.95 100 1 .00 10.30 P <0.0001 1 <0.0001 0.9 929 <0.0001 0. 2854 <0.0001 0.99 9 4 I2SERA D 2 104.43 8 48.27 0 826. 71 77.51 88 5.48 83.2 6 834. 20 P <0.0001 <0.0001 1 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 I2SESA D 2 619. 70 1 2.19 826. 71 0 770. 25 31. 58 979. 17 2.95 P <0.0001 0. 9 929 <0.0001 1 <0.0001 0.0 08 2 <0.0001 0.999 9 J1RERA D 2 25.08 79 1.81 77.51 770. 25 0 829. 02 156.09 777. 74 P <0.0001 <0.0001 <0.0001 <0.0001 1 <0.0001 <0.0001 <0.0001 J1RESA D 2 67 8.47 39.95 88 5.48 31. 58 829. 02 0 103 8 .00 3 2.21 P <0.0001 0. 2854 <0.0001 0.0 08 2 <0.0001 1 <0.0001 0.018 1 J1SERA D 2 195.41 100 1 .00 83.2 6 979. 17 156.09 103 8 .00 0 986. 66 P <0.0001 <0.0001 <0.0001 <0.0001 < 0.0001 <0.0001 1 <0.0001 J1SESA D 2 627. 19 1 0.30 834.2 0 2.95 777. 74 3 2.21 986. 66 0 P <0.0001 0.99 9 4 <0.0001 0.999 9 <0.0001 0.018 1 <0.0001 1

PAGE 111

111 Table 4 8 Correlation values between canonic al structure and fatty acids selected by stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) for separation of extraction methods (standard/ Instant FAME ) and analysis methods (standard/ Rapid ) using root tissue infected w ith either Meloidogyne incognita or M. javanica Values listed in bold (greater than |0.750|) indicate significant correlation with in the given canonical variate Fatty Acid CAN1 CAN2 CAN3 Fatty Acid CAN1 CAN2 CAN3 Capric a cid 0.644 0.613 0.420 iso margaric 3 OH 0.510 0.498 0.694 Lauric acid 0.854 0.020 0.480 17:1 iso c 0.630 0.676 0.381 Lauric 2 OH 0.582 0.810 0.018 17:1 anteiso A 0.722 0.646 0.190 Lauric 3 OH 0.698 0.646 0.291 17:1 anteiso c 0.557 0.604 0.562 anteiso lauric 0.706 0.653 0.248 17:1 iso I/ anteiso 0.698 0.697 0.028 iso lauric 0.755 0.480 0.443 c 0.579 0.813 0.009 Tridecylic acid 0.658 0.008 0.557 c 0.537 0.816 0.206 iso tridecylic 0.810 0.186 0.435 Stearic 10 methyl 0.451 0.245 0.858 Myristic 2 OH 0.5 74 0.794 0.200 Stearic 2 OH 0.914 0.115 0.111 Pentadecylic 3 OH 0.595 0.783 0.164 iso stearic 0.757 0.406 0.131 anteiso pentadecylic 0.657 0.747 0.026 cis vaccenic 0.951 0.272 0.122 15:1 iso F 0.414 0.743 0.526 E laidic acid 0.864 0.122 0.003 15:1 c 0.593 0.793 0.119 Linoleic / Stearic 0.789 0.528 0.028 16:1 2 OH 0.583 0.682 0.433 Linoleic acid 0.718 0.105 0.003 16:1 iso H 0.672 0.693 0.258 linole n ic acid 0.545 0.133 0.109 c 0.944 0.138 0.123 Non adecylic acid 0.533 0.547 0.638 c / palmitoleic 0.411 0.310 0.852 iso nonadecylic 0.507 0.491 0.702 Palmitoleic acid 0.631 0.084 0.002 c /19:1 0.382 0.260 0.882 Palmitoleic A lcohol 0.702 0.631 0.306 Arac hidic acid 0.937 0.323 0.009 Palmitoleic c 0.961 0.100 0.209 Arachidonic acid 0.599 0.484 0.547 Margaric acid 0.572 0.647 0.495 Canonical Correlation 0.995 0.949 0.845 E igenvalue 183.09 18.60 5.45 Cumulative Proportion 0.871 0.960 0.985

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112 Table 4 9 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis comparing two nematode species infecting root tissue ( Melo idogyne incognita race 2 [I2], M. javanica race 1 [J1]) and two extraction methods ( Instant FAME extraction [RE], standard extraction [SE]) using Rapid analysis From Analysis To Analysis I2RE I2SE J1RE J1SE I2RE D 2 0 277.58 99.24 374.20 P 1 <0.0001 <0.0001 <0.0001 I2SE D 2 277.58 0 121.80 150.12 P <0.0001 1 <0.0001 <0.0001 J1RE D 2 99.24 121.80 0 282.84 P <0.0001 <0.0001 1 <0.0001 J1SE D 2 374.20 150.12 282.84 0 P <0.0001 <0.0001 <0.0001 1

PAGE 113

113 Table 4 10 Correlation values between canonical structure of fatty acids s ignificant in the three canonical variates (CAN1, CA N2, CAN3) for separating extraction method (standard/ Instant FAME ) and root tissue infected with either Meloidogyne incognita or M. javanica Values listed in bold (greater than |0.750|) indicate significant correlation with in the given canonical variate Fatty Acid CAN1 CAN2 CAN3 Fatty Acid CAN1 CAN2 CAN3 Capric 2 OH 0.977 0.114 0.178 Palmitoleic /16:1 6 c 0.030 0.989 0.141 Capric 3 OH 0.416 0.786 0.457 Margaric acid 0.854 0.289 0.433 Undecylic acid 0.376 0.771 0.515 Margaric 10 methyl 0.908 0.415 0.056 Lauric acid 0.337 0.936 0.106 Margaric 2 OH 0.793 0.467 0.390 Lauric 2 OH 0.975 0.181 0.129 cyclo margaric 0.845 0.303 0.440 Lauric 3 OH 0.964 0.233 0.125 iso margaric 0.914 0.021 0.406 Tridecylic 0.310 0.932 0.187 17:1 iso 5 c 0.925 0.226 0.305 Tridecylic 2 OH 0.193 0.831 0.522 17:1 anteiso A 0.986 0.169 0.004 13:1 at 12 13 0.808 0.544 0.224 17:1 anteiso 9 c 0.806 0.359 0.470 Myristic acid 0.758 0.438 0.483 17:1 8 c 0.972 0.206 0.111 Myristic 2 OH 0.938 0.340 0.075 Stearic acid 0.5 54 0.180 0.813 anteiso myristic 0.861 0.278 0.427 Stearic 2 OH 0.162 0.771 0.617 Pentadecylic 3 OH 0.973 0.044 0.227 iso stearic 0.760 0.113 0.640 a nteiso pentadecylic 0.969 0.189 0.161 18:1 iso H 0.812 0.351 0.466 Palmitic N A lcohol 0.588 0.806 0.071 18:1 7 c 0.831 0.465 0.304 anteiso palmitic 0.928 0.241 0.284 cyclo nonadecylic C10 0.970 0.232 0.067 iso palmitic 3 OH 0.885 0.249 0.392 Arachidic acid 0.971 0.055 0.231 16:1 2 OH 0.890 0.225 0.397 iso arachidic 0.961 0.214 0.176 16:1 iso G 0.799 0.527 0.290 Eicosenoic acid 0.838 0.521 0.161 Palmitoleic A lcohol 0.840 0.540 0.048 Canonical Correlation 0.99 2 0.9 77 0. 922 Eigenvalue 59.04 21.21 5.66 Cumulative Proportion 0. 687 0.9 34 1

PAGE 114

114 Table 4 11 Mean FAME concentrations ( percentage of total response ) of four combinations of two nematode species ( Meloidogyne incognita race 2 [I2], M. javanica race 1 [J1]) and two extraction methods ( Instant FAME extraction [RE], standard extraction [SE]) utilizing Rapid analysis (RA). Both extractions were carried out using 40 mg of infected Solenostemon scutellarioides root tissue. Fatty Acid I2RE I2SE J1 RE J1SE Fatty Acid I2RE I2SE J1RE J1SE Capric acid 1.23 0.09 2.02 0.03 Myristic 2 OH 0.06 0.18 0.08 0.19 Capric 2 OH 0.06 0.53 0.08 0.45 Myristic 3 OH /16:1 iso I 0.08 0.02 0.13 0.09 Capric 3 OH 0.04 0.03 0.06 0.05 anteiso myristic 0.28 0 .75 0.10 0.87 iso capric 0.06 0.03 0.08 0.01 iso myristic 0.18 0.17 0.23 0.15 Undecylic acid 0.06 0.02 0.04 0.01 iso myristic 3 OH 0.05 0.07 0.06 0.07 Undecylic 2 OH 0.08 0.05 0.09 0.03 14:1 iso E 0.01 0.03 0.04 0.01 Undecylic 3 OH 0. 07 0.03 0.04 0.01 c 0.18 0.05 0.17 0.10 anteiso undecylic 0.05 0.07 0.07 0.14 Pentadecylic 2 OH 0.11 0.04 0.07 0.07 iso undecylic 0.13 0.01 0.15 0.01 Pentadecylic 3 OH 0.05 0.03 0.06 -iso undecylic 3 OH 0.07 0.03 0.02 0.06 anteiso pentadecylic 0 .09 0.20 0.19 0.14 Lauric acid 0.53 0.49 0.83 0.55 iso pentadecylic 0.99 1.33 0.96 1.06 Lauric 2 OH 0.10 1.20 0.21 0.85 iso pentadecylic 3 OH 0.14 0.05 0.04 0.03 Lauric 3 OH 0.26 0.06 0.30 0.05 15:1 anteiso A 0.59 0.32 0.65 0.42 Lauric Aldehyde 0.12 0.03 0.12 -15:1 iso F 0.09 0.05 0.22 0.02 anteiso lauric 0.44 0.04 0.35 0.05 15:1 iso G 0.03 0.34 0.04 0.40 iso lauric -0.04 0.09 0.03 15:1 iso H/13:0 3 OH 0.07 0.46 0.10 0.47 iso lauric 3 OH 0.06 0.02 0.08 0.12 15 :1 iso c 0.05 0.11 0.15 0.12 12:1 3 OH -0.01 0.05 0.04 c 0.09 0.04 0.11 0.01 Tridecylic acid 0.20 0.10 0.23 0.11 c 0.10 0.03 0.16 0.04 Tridecylic 2 OH 0.08 0.36 0.09 0.49 c 0.06 0.02 0.17 -13:0 3 OH /15:1 i so H 0.03 -0.10 -Palmitic acid 13.23 11.62 13.34 14.47 anteiso tridecylic 0.01 0.12 0.14 0.10 Palmitic 10 methyl 0.08 0.02 0.06 -iso tridecylic 0.24 0.10 0.20 0.08 Palmitic 2OH 0.05 0.39 0.12 0.55 iso tridecylic 3 OH 0.23 -0.08 -Palmitic 3OH 0.14 0.03 0.05 0.01 13:1 at 12 13 0.09 0.02 0.07 -Palmitic N A lcohol 0.07 0.20 0.10 0.21 Myristic acid 1.24 1.89 1.66 1.55 anteiso palmitic 0.06 0.09 0.05 0.29

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115 Table 4 11 Continued. Fatty Acid I2RE I2SE J1RE J1SE Fatty Acid I2RE I2SE J1RE J1SE iso palmitic 0.06 0.02 0.12 0.02 c 0.11 0.20 0.05 0.15 iso palmitic 3OH 0.10 0.04 0.05 -Stearic acid 5.76 8.43 5.90 7.61 16:1 2OH -0.41 0.08 0.41 Stearic 10 methyl -0.05 0.19 0.07 16:1 iso G 0.05 0.07 0.14 0.08 Stearic 2OH 0.39 0.65 0.19 0.57 16:1 iso H 0.08 0.05 0.02 0.02 iso stearic 0.40 0.19 0.27 0.12 c 0.10 0.04 0.03 -18:1 2OH 0.05 0.04 -0.04 c 0.75 0.76 0.63 0.47 18:1 iso H 0.15 0.05 0.06 0.02 c c -0.11 0.02 0.15 c 1.08 1.16 0.76 0.97 Palmitoleic A lcohol 0.06 0.02 0.24 0.03 cis vaccenic 27.39 35.65 25.47 27.91 c c 1.76 1.96 1.46 1.45 cis vaccenic 11 m ethyl 0.13 0.15 0.03 0.07 0.01 0.01 0.05 0.06 Oleic acid 0.30 1.39 -0.63 Margaric acid 0.47 0.57 0.48 0.67 Linoleic / ante iso stearic 30.94 16.72 30.49 25.25 Margaric 10 methyl 0.03 0.02 0.09 -linolenic acid 0.04 0.23 0. 26 0.21 Margaric 2OH 0.07 0.30 0.13 0.31 Nonadecylic acid 0.17 0.21 0.12 0.12 Margaric 3OH 0.05 -0.06 -anteiso nonadecylic 0.07 0.02 0.03 -anteiso margaric 0.15 0.13 0.20 0.14 cyclo nonadecylic C10 0.04 0.62 0.16 0.65 cyclo ma rgaric 0.08 0.10 0.08 0.28 cyclo nonadecylic C8 0.19 0.03 0.11 0.03 iso margaric 0.49 0.78 0.63 0.67 iso nonadecylic 0.12 0.25 0.06 0.19 iso margaric 3OH 0.27 0.51 0.16 0.33 19:1 iso I 0.13 0.07 0.17 0.10 17:1 iso c 0.09 0.30 0.12 0.36 c c 0.14 0.20 0.09 0.20 17:1 anteiso A 0.09 0.03 0.06 0.01 c c /19 cy clo 0.07 0.31 0.03 0.18 17:1 anteiso B/ iso I 0.07 0.02 0.08 0.04 c c 0.04 0.02 0.05 -17:1 anteiso c 0.11 0.29 0.09 0.33 c c 0.08 0.11 0.09 0.03 17:1 iso I/ anteiso B 0.02 0.00 0.07 0.02 Arachidic acid 2.05 1.72 2.63 2.00 17:1 iso c 0.08 0.01 0.01 0.01 iso arachidic 0.04 0.31 0.12 0.25 c 0.08 0.01 0.02 0.01 20: 1.25 1.66 1.36 1.20 c 0.05 0.15 0.01 0.07 Eicosenoic acid 0.32 0.25 0.28 0.25 c 0.10 0.07 0.18 0.16 Arachidonic acid 0.27 0.33 0.47 0.33 c 0.09 0.05 0.16 0.05 Pelargonic acid 0.18 0.05 0.24 0.02

PAGE 116

116 Table 4 11 Continued. Fatty Acid I2RE I2SE J1RE J1SE Pelargonic 3OH 0.05 0.0 3 0.01 0.0 1 unknown 10.9525 0.10 0.0 5 0.03 0.0 2 n 20 20 20 20 =Not detected

PAGE 117

117 Table 4 1 2 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis (with full stepwise discriminant analysis prior) comparing two FAME extraction methods ( Instant FAME extraction [RE], standard extraction [SE]) o n 40 mg of Solenostemon scutellarioides root tissue infected with either Meloidogyne incognita race 2 (I2) or M. javanica race 1 (J1) utilizing Rapid analysis To Analysis I2RE I2SE J1RE J1SE I2RE D 2 0 113,385,980 83,340,926 40,487,884 P 1 <0.0001 <0.0001 <0.0001 I2SE D 2 113,385,980 0 213,256,435 18,374,852 P <0.0001 1 <0.0001 <0.0001 J1RE D 2 83,340,926 213,256,435 0 132,766,463 P <0.0001 <0.0001 1 <0.0001 J1SE D 2 40, 487,884 18,374,852 132,766,463 0 P <0.0001 <0.0001 <0.0001 1

PAGE 118

118 Table 4 1 3 Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis (with truncated stepwise discriminant analysis prior) comparing tw o FAME extraction methods ( Instant FAME extraction [RE], standard extraction [SE]) o n 40 mg Solenostemon scutellarioides root tissue infected with either Meloidogyne incognita race 2 (I2) or M. javanica race 1 (J1) utilizing Rapid analysis To Analysis I2RE I2SE J1RE J1SE I2RE D 2 0 2,175,521 80,100 751,766 P 1 <0.0001 0.0002 <0.0001 I2SE D 2 2,175,521 0 2,987,898 374,119 P <0.0001 1 <0.0001 <0.0001 J 1RE D 2 80,100 2,987,898 0 1,257,481 P 0.0002 <0.0001 1 <0.0001 J1SE D 2 751,766 374,119 1,257,481 0 P <0.0001 <0.0001 <0.0001 1

PAGE 119

119 Table 4 1 4 Correlation values between canonical structure and fatty acids selected by truncated stepwise discriminant analysis in the first three canonical variates (CAN1, CAN2, CAN3) for separating extraction method s (standard/ Instant FAME ) and Solenostemon scutellarioides root tissue infected with ei ther Meloidogyne incognita or M. javanica in 40 mg tissue samples Values listed in bold (greater than |0.750|) indicate significant correlation within the given canonical variate Fatty Acid CAN1 CAN2 CAN3 Fatty Acid CAN1 CAN2 CAN3 Capric acid 0.923 0.252 0.291 15:1 iso G 0.885 0.088 0.458 Capric 2OH 0.967 0.148 0.208 15:1 iso H/13:0 3OH 0.924 0.146 0.354 Capric 3OH 0.625 0.356 0.695 15:1 iso 0.049 0.969 0.241 iso capric 0.831 0.140 0.538 c 0.812 0.142 0.566 Undecylic 2OH 0.788 0.025 0.615 Palmitic acid 0.426 0.128 0.896 anteiso undecylic 0.381 0.178 0.907 Palmitic 10 methyl 0.793 0.267 0.547 iso undecylic 0.951 0.006 0.309 Palmit ic 2OH 0.789 0.175 0.588 iso undecylic 3OH 0.204 0.933 0.296 Palmitic 3OH 0.589 0.667 0.456 Lauric acid 0.721 0.691 0.047 Palmitic N A lcohol 0.895 0.249 0.370 Lauric 2OH 0.975 0.208 0.072 anteiso palmitic 0.404 0.090 0.910 Lauric 3OH 0.939 0.038 0.341 iso palmitic 0.894 0.371 0.252 Lauric A ldehyde 0.847 0.064 0.528 16:1 iso H 0.026 0.872 0.489 anteiso lauric 0.915 0.258 0.310 c 0.301 0.675 0.673 iso tridecylic 0.852 0.290 0.437 c 0.019 0.241 0.970 iso tridecylic 3OH 0.711 0.616 0.339 c c 0.823 0.155 0.546 Myristic 2OH 0.895 0.201 0.398 Palmitoleic A lcohol 0.773 0.626 0.097 Myristic 3OH 0.821 0.329 0.466 c c 0.535 0.340 0.774 iso myristic 0.740 0.479 0.471 c 0.241 0.465 0.852 iso myristic 3OH 0.820 0.493 0.292 Margaric acid 0.689 0.044 0.724 14:1 iso E 0.023 0.856 0.516 Margaric 2OH 0.886 0.277 0.371 c 0.986 0.166 0.008 Margaric 3OH 0.950 0.059 0.307 Pentadecylic 2OH 0.693 0.721 0.006 cyclo margaric 0.381 0.095 0.919 15:1 anteiso A 0.998 0.043 0.047 iso margaric 0.810 0.586 0.005 Continued on next page

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120 Table 4 1 4 Continued Fatty Acid CAN1 CAN2 CAN3 Fatty Acid CAN1 CAN2 CAN3 iso margaric 3OH 0.957 0.158 0.242 linolenic acid 0.299 0.935 0.192 17:1 iso c 0.850 0.138 0.508 Nonadecylic acid 0.492 0.341 0.801 17:1 anteiso A 0.743 0.383 0.550 cyclo nonadecylic C10 0.899 0.235 0.370 17:1 anteiso c 0.899 0.008 0.437 cyclo nonadecylic C8 0.780 0.538 0.321 c 0.933 0.151 0.327 iso nonadecylic 0.980 0.198 0.005 c 0.821 0.505 0.265 19:1 iso I 0.966 0.252 0.055 Stearic acid 0.983 0.164 0.081 c c 0.903 0.326 0.279 St earic 10 methyl 0.391 0.912 0.125 c c /19 cy clo 0.994 0.014 0.107 Stearic 2OH 0.952 0.296 0.085 c c 0.037 0.233 0.972 iso stearic 0.683 0.444 0.580 Arachidic acid 0.857 0.502 0.118 18:1 2OH 0.52 3 0.850 0.052 0.579 0.396 0.713 c 0.703 0.625 0.339 Eicosenoic acid 0.733 0.583 0.349 Linoleic / ante iso stearic 0.960 0.182 0.211 Arachidonic acid 0.368 0.929 0.035 Canonical Correlation 1 1 0. 999 Eigenvalue 499291 2037 441 Cumulative Proportion 0. 995 0.9 99 1

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121 Figure 4 1 Canonical distribution comparing M. javanica infected tomato root tissue (J1) FAME profile s to M. incognita infected tissue (I2) using either standard FAME extraction (SE) or Instant FAME extraction (RE) in combination with either Rapid FAME analysis (RA) or standard analysis (SA) Sample sizes were 40 mg for SE and 3 mg for RE.

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122 Figure 4 2 Cano nical distribution comparing M eloidogyne javanica infected tomato root tissue (J1) FAME profile s to M. incognita infected tissue (I2) using either standard FAME extraction (SE) or Instant FAME extraction (RE). All extractions were analyzed using Rapid FAM E analysis (RA). Sample sizes were 40 mg for SE and 3 mg for RE. A) CAN1 ( x axis) versus CAN2 ( y axis) and B) CAN1 ( x axis) versus CAN3 ( y axis). A B

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123 Figure 4 3 C anonical discriminant analysis after full stepwise discriminant analysis comparing 40 mg of Meloidogyne javanica infected Solenostemon scutellarioides root tissue (J1) FAME profile s to 40 mg of M. incognita infected tissue (I2) using either standard FAME extraction (SE) or Instant FAME extraction (RE). All extractions were analyzed using Rapid F AME analysis (RA).

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124 Figure 4 4 C anonical discriminant analysis after truncated stepwise discriminant analysis comparing 40 mg of Meloidogyne javanica infected Solenostemon scutellarioides root tissue (J1) FAME profile s to 40 mg M. incognita infected ti ssue (I2) using either standard FAME extraction (SE) or Instant FAME extraction (RE). All extractions were analyzed using Rapid FAME analysis (RA).

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125 CHAPTER 5 POPULATION DENSITY A ND DETECTION OF MELOIDOGYNE SPECIES USING F ATTY ACID METHYL EST ER ANALYSIS 5. 1 Introduction Previous work by Sekora et al. (2009) comparing fatty acid profiles of Rotylenchulus reniformis and Meloidogyne incognita at multiple population densities has indicated that it may be possible to use the information gained from fatty acid me thyl ester ( FAME ) analysis of a specific nematode species to estimate the number of individuals of the given species in a sample. Each analysis provides a the amount of identified lipid in the sample as a function of electrical response (mV), as a subset of information that could be used to set up prediction intervals for the expected response of a sample given a certain number of individuals. Since fatty acid compositions can vary depending on the life stage analyzed (Krusberg et al ., 19 73; Sekora et al. 2008; Sekora et al ., 2009), it is crucial to study the effects of increasing numbers of individuals on FAME profiles and response before accurate quantification can be achieved. It is expected that lipid compositions will change as the tissues within a nematode develop into a n adult, but the degree of those changes between juvenile and adult may or may not influence quantification using FAME profiles. Sekora et al (2009) found significant differences among life stages of Heterodera gly cines ; egg producing females produced FAME profiles distinct from those of cysts and eggs. Quantification of a sample containing mixed life stages of H. glycines or any other nematode species, would likely require profiles based on increasing numbers of each life stage. Another critical aspect of quantification is the use of extraction and analysis methods that are sensitive enough to detect minute quantities of fatty acids. More

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126 efficient and precise methods of FAME extraction and analysis ( Instant FAM E and Rapid analysis) have recently been developed by MIDI (Newark, DE), and these methods have been shown to be excellent at increasing the abi l ity of FAME analysis to separate Meloidogyne species within root tissue (Sekora and Crow, 2011). It is expecte d that the increased resolution of the Instant FAME and Rapid analysis methods will reduce the number of individuals required for FAME analysis from those published by Sekora et al (2009). Therefore, the objective of this study is to determine the minimu m number of nematodes of various life stages required to produce a FAME profile adequate for quantification using the improved extraction and analysis methods. 5.2 Materials and Methods 5.2.1 Sample Preparation M ature females (F), males (M), and second sta ge juveniles (J) of Meloidogyne graminis were hand picked from a stock population maintained under g reen house conditions on Paspalum notatum ( bahiagrass) at the University of Florida Picked nematodes were immediately placed in 0.25 mL of the first extrac tion reagent (5% KOH in methanol) and the remainder of the extraction procedure was carried out once enough nematodes had been picked to complete an entire replicate (within 10 minutes; Figure 5 1). Twelve replications of five treatments ( samples containi ng one two or five females one male or one juvenile ) were prepared for FAME extraction using the Instant FAME method ( MIDI Newark, DE ). A total of 60 samples were prepared for FAME analysis. 5.2.2 Statistical Analysis Comparisons w ere made usi ng the fatty acid analyses of s a m ples containing each life stage of M. g r aminis as well as the multiple densities of M. graminis females. FAME

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127 profiles were imported into SAS ( SAS Institute, Cary, NC) for further analysis. Mean which provided the average response for each fatty acid in all samples for the given class. Additional statistical tests were performed using PROC STEPDISC in combination with PROC CANDISC following the method of Sekora et al (2010). Stepwise discriminant analysis (SDA) by PROC STEPDISC was used to determine which fatty acids were significant for discrimination among classes using a series of stepwise analysis of variance (ANOVA) tests that evaluate the F value of each fatty acid before and after inclusion (Johnson, 1998). After analysis of each fatty acid, fatty acids significant for delineation ( P < 0.15) were used for canonical discriminant analysis (CDA) with PROC CANDISC. Canonical discriminant ana lysis produces class means based on sample variance within each compared class and then represents relationships among classes in dimensional space. The dimensional space is represented by canonical variates (CAN1, CAN2, up to class n 1) that demonstrate class separation in graphical representation and can be assigned to x y or z axes depending on the desired class comparisons. Canonical variates are also used to describe the total multivariance within a test, and the number of variates in these tests w as reduced to the fewest that could define at least 75% cumulative proportion of the total multivariance ( n CAN < 3). correlation ( 1 to 1) of a given fatty acid along the c hosen canonical variate. Absolute values approaching |1.000| indicate a high degree of correlation and help to separate classes on the specified dimension. The greater the value of correlation, the greater the

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128 spatial distance (Mahalanobis distance or D 2 ) among means graphically along a given canonical variate (Johnson, 1998). For the experiments described in this paper, high canonical correlation was described by correlations greater th an |0.750| and significant mean separation was achieved with D 2 havi ng P < 0.05. Additional information provided by CDA is the canonical correlation and eigenvalue of each canonical variate. Canonical correlation values range from 0 to |1.000| and are indicator s of the importance of each canonical variate to the separatio n of classes. Canonical correlation values approaching |1.000| are considered more informative for describing the majority of multivariance within a given analysis. The eigenvalue is another statistic similar to canonical correlation that is used to rank canonical variates based on the multivariance explained by the selected variate. As with canonical correlations, higher values indicate a greater degree of explained multivariance in an analysis for the given canonical variate (Johnson, 1998). Regression analysis of total response against increasing numbers of M. g r aminis females was performed using the PROC REG procedure. The best fit linear regression was obtained, and the predicted values and 95% confidence intervals were graphed overlaying the actual response values. 5.3 Results In total, 51 of the 60 prepared samples produced FAME profiles that were useful for further statistical analysis Samples containing females of M. gr am inis had fewer fatty acids than profiles derived from males or juveniles, and the number of fatty acids present did not increase as more females were added to a sample (Table 5 1). Oleic aci d was observed as the most prevalent fatty acid in samples containing males or females, but myristic acid was most abundant in samples cont aining juveniles. Juvenile

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129 and male samples contained 17 of 25 and 18 of 24 fatty acids, respectively, at concentrations between 2.0% and 6.0%. Less predominant fatty acids (linolenic/stearic, arachidonic acid, etc.) were detected as the number of femal es in a sample increased, which reduced the overall proportion of palmitic and stearic acids. B oth were found in higher concentrations in single female samples than samples containing single males or juveniles. Canonical discriminant analysis following SD A of the FAME profiles distinctly separated juveniles and males from the three female densities (Table 5 2 ; Figure 4 3 ). While the three female profile densities could not be statistically separated (D 2 < 11.69, P > 0.3625), single males and juveniles wer e distinctive from each other (D 2 = 1009.00, P < 0.0001) as well as the clustered female profiles (D 2 > 412.56, P < 0.0001). Single males and juveniles were separated by five fatty acids along CAN1 (64.1% of multivariance; Table 5 3), all of which were fo und at higher mean concentrations in single juvenile samples than samples containing single males (Table 5 1). CAN2 (34.7% of total multivariance) separated single male samples from the three female densities with 11 fatty acids (Table 5 3). Of these 11 fatty acids, only stearic acid was observed at a higher concentration in samples containing females of M. graminis (Table 5 1). Although CAN3 was not significant for separating the five classes ( P = 0.7090), pinoleic acid was still significant for separat ion of the three female densities (Table 5 3; Figure 5 3). Total responses of individual males (5 ,342.3 + 817. 1 ) were similar to those of individual females (5 ,650.7 + 1833. 2 ). Total response increased seemingly linearly from single female samples as the number of individuals increased to two (11,115. 6 +

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130 3 141.2) and five (54,73 7 0 + 13,042.0) per sample. Total responses of samples containing single juveniles (3 77 7.0 + 931. 9 ) were less than either single males or females, but still more than half that o f a single mature female. Regression analysis of female total response indicated that response was linearly correlated with the number of females per sample (R 2 = 0. 5928 P < 0.0001 ), but the observed responses appeared to increase with a conical spread a s female numbers increased (Figure 5 2). 5.4 Discussion Variation in response was observed in all life stages with positive signals and ranged from 406.13 to 18,912.23 for a single female (data not shown). Some variation was expected since each individual may differ in its FAME composition based on its size, age, maturity, time since feeding, and possibly by the presence of internal parasites. These variations were inflated when observing five mature females in a sample (total response ranged from 9192.96 to 103,530.70) and indicate that further studies need to be conducted to determine the factors for this variation before advanced utilization, such as quantification, is pursued. Another type of variation in response had an impact on the fatty acids detect ed. By increasing the number of nematodes in a sample, fatty acids that were found at low levels in a single individual (or not at all, like anteiso pentadecylic acid) had a greater chance of detection. These fatty acids appear to decrease the proportion of other fatty acids, like stearic and palmitic acids, but in reality do not affect their responses. The refore, the reduction in proportion for stearic and palmitic acids is only an a djustment to account for the responses of the newly detected fatty acid s. The Agilent 6890N Gas Chromatography System (Agilent Technologies, Santa Clara CA ) that this study employed has the ability to increase or decrease sensitivity of

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131 an injected sample through use of a split/splitless valve. The split/splitless valve all ows for a portion of the injected sample to be shunted away from the chromatography column to prevent overload and damage to the column from samples with high lipid content. The proportion of sample analyzed is diluted with carrier gas (N 2 ) that moves the comp o unds through the column. The dilution is defined by the ratio N : S where N is the proportion of N 2 and S is the proportion of sample by volume. Samples are typically run at a split/splitless ratio of 25:1 with the Rapid analysis method. By reducing this ratio it is possible to detect more minute quantities of lipid within a sample. However, reducing this ratio requires more strict scrutiny of the FAME profiles produced since the detection of artefacts may also be increased. Using the coupled Instan t FAME and Rapid extraction methods it was possible to obtain distinct FAME profiles from single nematodes as opposed to the 250 reported for standard extraction and analysis methods (Sekora et al. 2008). This reduction in the required number of individu als makes using FAME methods for population studies possible since these studies are typically conducted using single individuals. Currently, single females would be the likely choice for analysis, but work to further increase the sensitivity of the syste m may indicate that it may be possible to use individual males of juveniles.

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132 Table 5 1. Mean FAME concentrations ( percentage of total response ) of Meloidogyne graminis females (F) at densities of 1, 2, or 5 individuals per sample, single juveniles (J1) and individual males (M1) Fatty Acid F1 F2 F5 J1 M1 Undecylic acid 0.79 --4.85 3.83 Lauric 2 OH 3.35 6.97 1.09 1.38 -Lauric 3 OH ---7.63 2.25 Tridecylic 3 OH /15:1 iso ---2.39 5.57 Myristic acid 0.77 2.42 3.20 14.25 0.88 Myristic 2 OH -0.18 -0.59 3.21 anteiso pentadecylic -1.32 0.87 5.17 -15:1 5c 0.23 0.29 -2.13 2.84 P a l mitic acid 18.45 14.30 7.50 5.40 9.70 Palmitic 2 OH ---5.65 1.65 Palmitic 3 OH ---3.55 3.10 16:1 5c 0.18 1.55 1.37 1.77 2.61 Palmitoleic /16:1 6c 0.87 0.41 2.25 0.50 2.60 Stearic acid 16.35 14.98 8.19 3.51 4.19 Stearic 3 OH ---4.08 2.26 iso stearic ---4.33 3.97 18:1 5c 0.28 1.43 1.70 -2.32 cis vaccenic 43.12 45.06 61.42 1.70 21.36 Linoleic / Stearic -0.2 2 1.23 -0.86 linoleic acid 9.07 1.99 2.57 6.35 2.07 cyclo nonadecylic C10 ---1.32 2.75 iso nonadecylic ---3.12 3.01 19:1 iso I ---2.62 2.98 19:1 7c/19:1 6c ---7.11 -Arachid ic acid 1.97 1.79 2.81 2.51 6.59

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133 Table 5 1. Continued. Fatty Acid F1 F2 F5 J1 M1 20:1 7c 4.57 7.09 5.47 2.92 4.54 Arachidonic acid --0.33 5.15 4.89 Total Response (mV) 5650.72 1111 5.59 54,736.99 3776.96 5342.32 n 11 12 12 9 7 =Not detected

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134 Table 5 2. Mahalanobis distances (D 2 ) and P values from canonical discriminant analysis comparing FAME profiles of Meloidogyne graminis females (F) a t densities of 1, 2, or 5 individuals per sample individual juveniles (J1) and individual males (M1) From Count To Count F1 F2 F5 J1 M1 F1 D 2 0 11.69 15.90 608.55 412.56 P 1 0.3625 0.4326 <0.0001 <0.0001 F2 D 2 11.69 0 12.59 572.35 495.72 P 0.3625 1 0.6096 <0.0001 <0.0001 F5 D 2 15.90 12.59 0 518.16 425.56 P 0.4326 0.6096 1 <0.0001 <0.0001 J1 D 2 608.55 572.35 518.16 0 1009.00 P <0.0001 <0.0001 <0.0001 1 <0.0001 M1 D 2 412.56 495.72 425.56 1009.00 0 P <0.0001 <0.0001 <0.0001 <0.0001 1

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135 Table 5 3. Correlation values between canonical structure and fatty acids selected by st epwise discriminant analysis in the first t hree canonical variates (CAN1, CAN2, and CAN 3 ) for separating FAME profiles of Meloidogyne graminis females (1, 2, and 5 individuals per sample), males ( one individu al per sample), and juveniles (one individual pe r sample) Values listed in bold (greater than |0.750|) indicate significant correlation within the given canonical variate. Fatty Acid CAN1 CAN2 CAN3 Undecylic acid 0.556 0.814 0.166 Lauric 2 OH 0.148 0.739 0.020 Lauric 3 O H 0.851 0.522 0.045 Tridecylic 3 OH /15:1 iso 0.021 0.995 0.020 Myristic acid 0.976 0.198 0.094 Myristic 2 OH 0.304 0.938 0.063 anteiso pentadecylic 0.971 0.119 0.144 15:1 w5c 0.260 0.951 0.034 Palmitic acid 0.583 0.526 0.590 Palmitic 2 OH 0.852 0.519 0.045 Palmitic 3 OH 0.515 0.853 0.017 Palmitoleic /16:1 w6c 0.522 0.594 0.313 Stearic acid 0.449 0.801 0.346 Stearic 3 OH 0.708 0.703 0.033 iso stearic 0.489 0.868 0.015 cis vac cenic 0.654 0.669 0.247 Linoleic / Stearic 0.451 0.309 0.706 linoleic 0.303 0.183 0.862 cyclo nonadecylic C10 0.032 0.995 0.017 iso nonadecylic 0.462 0.883 0.013 19:1 iso I 0.369 0.925 0.006 19:1w7c/19:1 w6c 0.95 9 0.276 0.057 20:1 w7c 0.579 0.546 0.425 Arachidonic acid 0.472 0.880 0.016 Canonical Correlation 0.995 0. 992 0.743 Eigenvalue 109.75 59.60 1.233 Cumulative Proportion 0.641 0.988 0.996

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136 Figure 5 1. Instant FAME extraction and Rapid analysis method developed by MIDI (Newark, DE).

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137 Figure 5 2. Regression of predicted FAME response (mV) against increasing numbers of Meloidogyne graminis females per sample.

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138 Figure 5 3. Canonical discriminan t analysis after stepwise discriminant analysis comparing FAME profiles of Meloidogyne graminis females (F) at densities of 1, 2, or 5 individuals per sample individual males (M 1 ), and individual juveniles (J 1 ). A) CAN1 ( x axis) versus CAN2 ( y axis) and B) CAN1 ( x axis) versus CAN3 ( y axis). A B

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139 APPENDIX A F ATTY ACID PEAK NAMIN G TABLE FOR THE EUKARY METHO D Fatty Acid v Nom. ECL w Nom. RT x Cal/Ind y Qnt Cal z Unknown 8.281 8.281 2.059 No Pelargonic acid 9.000 2.401 C Yes Ca prylic 3OH 9.385 2.584 No Capric p rimary a lcohol 9.468 2.623 No Unknown 9.521 9.521 2.648 No iso capric 9.605 2.688 No Capric acid 10.000 2.876 C Yes Pelargonic 3OH 10.408 3.145 No Unknown 10.531 10.531 3.226 No iso undecylic 10.605 3.275 No anteiso undecylic 10.693 3.333 No Lauric alde hyde 10.914 3.478 No Unknown 10.928 10.928 3.488 No Undecylic acid 11.000 3.535 C Yes Unknown 11.097 11.097 3.620 No Capric 2OH 11.157 3.672 I No Suberic (C8 dicarbox ) 11.195 3.706 No Capric 3OH 11.423 3.905 I No Lauric p rimary a lco hol 11.490 3.964 No Unknown 11.541 11.541 4.008 No iso lauric 11.608 4.067 No anteiso lauric /12:2 6 c 11.689 4.138 No 12:2 6 c / anteiso lauric 11.699 4.147 No 12:1 9 c 11.772 4.211 No 12:1 8 c 11.789 4.225 No 12:1 7 c 11.806 4.240 No 12:1 6 c 11.850 4.279 No 12:1 5 c 11.897 4.320 No 12:1 3 c 11.932 4.351 No Unknown 11.981 11.981 4.393 No Lauric acid 12.000 4.410 C Yes iso undecylic 3OH 12.090 4.509 No U nknown 12.112 12.112 4.534 No Undecylic 2OH 12.158 4.584 No Pelargonic d icarbox 12.213 4.645 No Lauric 2CH 3 12.314 4.757 No Undecylic 3OH 12.441 4.897 No Undecylic DMA 12.468 4.927 No U nknown 12.486 12.487 4.948 No Unknown 12.553 12.553 5.021 No iso tridecylic 12.612 5.086 No

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1 40 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal anteiso tridecylic 12.701 5.184 No 1 3:1 9 c 12.772 5.262 No 13:1 8 c 12.790 5.282 No 13:1 7 c 12.809 5.303 No 13:1 6 c 12.852 5.351 No 13:1 5 c 12.900 5.404 No 13:1 3 c or 12 12.932 5.439 No Tridecylic acid 13.000 5.514 C Yes iso lauric 3OH 13.098 5.643 No Lauric 2OH 13.178 5.748 No Sebacic C10 dicarbox 13.230 5.817 No 12:1 3OH 13.289 5.895 No 14:1 iso E 13.388 6.025 No Lauric 3OH 13.455 6.113 No Lauric DMA 13.471 6.134 No Myristic N a lcohol 13.518 6.196 No Unknown 13.566 13.566 6.259 No iso myrist ic 13.618 6.328 No Unknown 13.671 13.671 6.398 No 14:2 6 c /14:0 anteiso 13.705 6.442 No 14:1 11 c 13.754 6.507 No 14:1 9 c 13.773 6.532 No 14:1 8 c 13.791 6.5 56 No 14:1 7 c 13.812 6.583 No 14:1 6 c 13.854 6.639 No 14:1 5 c 13.901 6.701 No 14:1 3 c 13.933 6.743 No 11:1 2OH 13.946 6.760 No Unknown 13.962 13.962 6.781 No Myristic acid 14.000 6.831 C Yes iso tridecylic 3OH 14.110 6.995 No Tridecylic 2OH 14.191 7.117 No Unknown 14.258 14.258 7.217 No 14:1 c is 7 DMA 14.2 91 7.266 No Lauric 2CH 3 14.316 7.303 No iso 15:1 AT 5 14.387 7.410 No 15:1 iso F 14.414 7.450 No 15:1 iso G 14.441 7.490 No Tridecylic 3OH 14.470 7.534 No Unk nown 14.503 14.503 7.583 No Pentadecylic N a lcohol 14.534 7.629 No Myristic 2,4 d imethyl 14.573 7.688 No iso pentadecylic 14.621 7.759 No anteiso pentadecylic 14.711 7.894 No

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141 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal 15:1 11 c 14.754 7.958 No 15:1 9 c 14.772 7.985 No 15:1 8 c 14.792 8.015 No 15:1 7 c 14.815 8.049 No Phytanic acid 14.835 8.079 No 15:1 6 c 14.8 56 8.111 No 15:1 5 c 14.905 8.184 No 15:1 3 c 14.937 8.232 No Lauric a ldehyde 14.952 8.254 No Unknown 14.967 14.967 8.277 No Pentadecylic acid 15.000 8.3 26 C Yes iso myristic 3OH 15.117 8.515 No Unknown 15.176 15.176 8.611 No Myristic 2OH 15.205 8.658 I No Unknown 15.273 15.273 8.768 No 16:1 c is Alcohol 7 15.386 8.951 No 16 :1 Alcohol 7 t 15.415 8.997 No 16:1 iso G 15.442 9.041 No 16:1 iso H 15.460 9.070 No 16:1 iso I/14:0 3OH 15.482 9.106 No Myristic 3OH/16:1 iso I 15.490 9.119 I No Palmitic N a lcohol 15.549 9.214 No iso palmitic 15.626 9.339 No Unknown 15.665 15.665 9.402 No 16:2 6 c 15.714 9.481 No 16:1 11 c 15.755 9.548 No 16:1 9 c 15.773 9.577 No 16:1 8 c 15.793 9.609 No 16:1 7 c 15.817 9.648 No 16:1 7 t 15.835 9.677 No iso pentadecylic 2OH/16:1 6 c 15.851 9.703 No 16:1 6 c / 15 iso 2OH 15.856 9.711 No 16:1 5 c 15.909 9.797 No 16:1 3 c 15.939 9.845 No Palmitic acid 16.000 9.944 C Yes iso pentadecylic 3OH 16.135 10.172 No Pentadecylic 2OH 16.217 10.311 No 16:1 c is 7 DMA ( 9) 16.240 10.350 No Unknown 16.286 16.286 10.428 No 17:1 a lcohol ( 8?) 16.371 10.572 No ISO 17:1 AT 10 16.387 10.599 No ISO 17:1 AT 9 16.415 10.646 No ISO 17:1 G 16.434 10.678 No ISO 17:1 5 c 16.460 10.722 No

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142 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal 17:1 iso I/ anteiso B 16.477 10.751 No 17:1 anteiso B/i I 16.486 10.766 No P entadecylic 3OH 16.505 10.798 No anteiso 17:1 AT 9 16.524 10.831 No 17:1 anteiso A 16.540 10.858 No 2,3 dihydroxy pentadecylic 16.553 10.880 No Margaric p rimary a lcohol 16.558 10.888 No Margaric a lcohol 16.562 10.895 No iso margaric 16.629 11.008 No anteiso margaric 16.722 11.166 No 17:1 11 c 16.757 11.225 No 17:1 9 c 16.772 11.250 No 17:1 8 c 16.793 11.286 No 17:1 7 c 16.819 11.330 No 17:1 6 c 16.860 11.399 No cyclo margaric 16.888 11.446 No 17:1 5 c 16.914 11.490 No 17:1 3 c 16.941 11.536 No Unknown 16.975 16.975 11.594 No Margaric acid 17.000 11.636 C Yes 16:1 2OH 17.047 11 .717 No Unknown 17.154 17.154 11.901 No a nteiso margaric DMA 17.196 11.974 No Palmitic 2OH 17.235 12.041 I No Myristic d icarboxilic 17.256 12.077 No Unknown 17.300 17.300 12.15 3 No Linoleic a lcohol 17.322 12.190 No Oleic a lcohol 17.361 12.258 No linoleic a lcohol 17.379 12.289 No 18:1 12 c a lcohol 17.387 12.302 No Elaidic a lcohol 17.410 12.342 No 18:1 iso G 17.440 12.394 No 18:1 iso H 17.460 12.428 No Margaric DMA 1 7.469 12.444 No 18:1 ( ?) a lcohol 17.495 12.488 No Palmitic 3OH 17.520 12.531 No linoleic acid 17.574 12.624 No Stearidonic acid 17.640 12.738 No Unknown 17.678 17. 678 12.804 No Linoleic acid 17.719 12.874 No 18:1 11 c 17.753 12.933 No Oleic acid 17.770 12.962 No linoleic /18:1 8 c 17.786 12.989 No 18:1 8 c / linoleic 17.795 13.0 05 No

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143 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal iso elaidic 17.822 13.051 No Elaidic acid 17.825 13.057 No Unknown 17.838 17.838 13.079 No 18:1 8 t 17.840 1 3.082 No 18:1 6 c 17.860 13.117 No 18:1 5 c 17.918 13.217 No 18:1 3 c 17.943 13.260 No Stearic acid 18.000 13.358 C Yes 19:1 ( 11?) a lcohol 18.124 13.571 No iso margaric 3OH 18.164 13.640 No Unknown 18.197 18.197 13.697 No Unknown 18.218 18.218 13.733 No 18:1 9 c DMA 18.224 13.744 No cis vaccenic DMA 18.285 13.848 No U nknown 18.316 18.316 13.902 No 19:1 ( 8?) a lcohol 18.390 14.029 No Unknown 18.473 18.473 14.172 No Nonadecylic N a lcohol 18.592 14.377 No iso nonadecylic 18.633 14.447 No 19:2 6 c 18.720 14.597 No 19:1 11 c 18.754 14.656 No 19:1 9 c 18.771 14.685 No 19:1 8 c 18.796 14.728 No 19:1 7 c /19:1 9 t 18.823 14.774 No 19:1 9 t /19:1 7 c 18.828 14.783 No 19:1 8t 18.845 14.812 No 19:1 6 c / c yclo nonadecylic 18.862 14.842 No c yclo nonadecylic C10 /19:1 18.868 14.852 No c yclo nonadecylic C11 18.901 14.909 No 19:1 5 c 18.923 14.946 No 19:1 3 c 18.945 14.984 No Nonadecylic acid 19.000 15.079 C Yes Unknown 19.055 19.055 15.174 No 18:1 2OH 19.088 15.231 No Unknown 19.225 19.225 15.468 N o Stearic 2OH 19.264 15.535 No Unknown B 19.276 15.556 No c yclo nonadecylic C9 DMA 19.322 15.636 No Arachidonic acid 19.392 15.757 No Eicosapentaenoic acid 19.453 15.862 No Unknown 19.470 19.470 15.892 No Unknown 19.521 19.521 15.980 No Dihomo linoleic acid 19.556 16.040 No Arachidic N a lcohol 19.600 16.116 No

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144 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal iso arachidic 19.635 16.177 No Docosadienoic acid 19.660 16.220 No Oleic 12OH 19.681 16.256 No cis stearic 9,10 epoxy 19.703 16.294 No Eicosadienoic acid 19.726 16.334 No 20:1 12 c 19.744 16.365 No 20:1 11 c 19.754 16.383 No Eicosenoic acid 19.771 16.412 No 20:1 8 c / eicosatrienoic 19.796 16.455 No eicosatrienoic /20:1 8 c 19.807 16.474 No 20:1 7 c /20:1 9t 19.825 16.505 No 20:1 9 t /20:1 7 c 19.833 16.519 No 20:1 6 c 19.867 16.578 No 20:1 5 c 19.923 16.675 No 20:1 3 c 19.948 16.718 No Stearic 12OH 19.975 16.765 No Arachidic acid 20.000 16.808 C Yes Unk nown 20.084 20.084 16.950 No c yclo nonadecylic C11 2OH 20.189 17.126 No 13 eicosynoic 20.209 17.160 No Unknown 20.241 20.241 17.214 No Unknown 20.257 20.257 17.241 No Nonadecylic 2OH 20.279 17.278 No Unknown 20.343 20.343 17.386 No Nonadecylic 3OH 20.566 17.762 No Unknown 20.588 20.588 17.799 No Heneicosylic p rimary a lcohol 20.613 17.841 No iso heneicosylic 2 0.637 17.881 No anteiso heneicosylic 20.738 18.052 No 21:1 11 c 20.755 18.080 No 21:1 9 c 20.772 18.109 No 21:1 7 c 20.828 18.203 No 21:1 6 c 20.866 18.267 No 21:1 5 c 20.928 18.372 No 21:1 3 c 20.949 18.407 No Heneicosylic acid 21.000 18.493 C Yes Unknown 21.111 21.111 18.676 No Unknown 21.252 21.252 18.908 No Stearic N a lcohol 21.283 18.959 No Cervonic acid 21.334 19.042 No 22:1 ( 11?) a lcohol 21.370 19.102 No Adrenic acid 21.384 19.125 No 22:1 9 c a lcohol 21.400 19.151 No Clupianodonic acid 21.466 19.260 No

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145 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal Arachidic 3OH 21.578 19.444 No Behenic p rimary a lcohol 21.627 19.524 No Docosadienoic acid 21.744 19.717 No 22:1 11 c 21 .751 19.728 No Erucic acid 21.774 19.766 No Unknown 21.808 21.808 19.822 No 22:1 7 c /22:3 3 c 21.833 19.863 No 22:1 6 c 21.871 19.926 No 22:1 5 c 21.931 20.024 No 22:1 3 c 21.951 20.057 No Behenic acid 22.000 20.138 C Yes Unknown 22.138 22.138 20.358 No Unknown 22.267 22.267 20.563 No Heneicosylic 2OH 22.308 20.628 No Unknown 22.374 22.374 20.7 33 No Heneicosylic 3OH 22.597 21.088 No Tricosylic p rimary a lcohol 22.643 21.161 No Unknown 22.682 22.682 21.223 No 23:1 9 c 22.787 21.390 No 23:1 7 c 22.836 21.468 No Tricosylic acid 23.000 21.729 C Yes Unknown 23.166 23.166 21.985 No Unknown 23.283 23.283 22.166 No Behenic 2OH 23.325 22.231 No Unknown 23.390 23.390 22.332 No Nervonic a lcohol 23.434 22.400 No Tetracosapentaenoic acid 23.467 22.451 No Behenic 3OH 23.608 22.668 No Unknown 23.670 23.670 22.764 No 2 4:2 6 c 23.752 22.891 No Nervonic acid 23.787 22.945 No 24:1 6 c 23.872 23.076 No 24:1 3 c 23.954 23.203 No Lignoceric acid 24.000 23.274 C Yes Unknown 24.098 24.098 23.421 No Unknown 24.196 24.196 23.568 No Tricosylic 2OH 24.337 23.779 No Unknown 24.407 24.407 23.884 No Tricosylic 3OH 24.625 24.211 No Pentacosylic N a lcohol 24.669 24.277 No Pentacosylic acid 25.000 24.773 C Yes Unknown 25.052 25.052 24.856 No Coprostane 25.138 24.993 No Unknown 25.339 25.338 25.313 No

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146 Fatty Acid Nom. ECL Nom. RT C al/Ind Qnt Cal Lignoceric 2OH 25.355 25.340 No 5 Cholestane 25.511 25.589 No Unknown 25.545 25.545 25.644 No Lignoceric 3OH 25.640 25.796 No Cholesteryl palmitat e 25.938 26.272 No Unknown 26.295 26.295 26.842 No Unknown 26.335 26.335 26.906 No Pentacosylic 2OH 26.366 26.955 No Pentacosylic 3OH 26.654 27.416 No Cerotic 3OH 27.668 29.036 No Montanic acid 28.000 29.566 C Yes Cholesterol 28.210 30.045 No Cholestanol 28.295 30.239 No Campesterol 29.250 32.420 No Stigmasterol 29.577 33.166 No Melissic acid 30.00 0 34.132 C Yes s itosterol 30.236 34.671 No Fucosterol 30.262 34.730 No v Structural notations: ( ) functional group located at carbon numbered from terminal carbon, ( c or cis ) all double bonds in cis or Z configuration, ( t or trans ) all double bonds in trans or E configuration, (OH) hydroxyl group at indicated carbon, ( iso ) fatty acid is in iso configuration, ( anteiso ) fatty acid is in anteiso configuration, ( cyclo ) fatty acid has a cyclic O bond at indicated carbon, ( DMA) fatty acid structure contains dimethyl acetal tail, ( methyl ) fatty acid has a methyl group at the indicated carbon, ( a ldehyde) fatty acid structured with an aldehyde tail, ( a lcohol) fatty acid tail has CH 2 OH tail instead of CH 3 d peak structure has yet to be determined as is listed by retention time. w Nominal estimated chain length (ECL) of given fatty acid. x Nominal retention time (RT) of given fatty acid after sample injection. y Fatty acid is used for calibration mi x (C) or indicator (I) of calibration shift z Amount of fatty acid can be quantified (Qnt) during calibration (Cal).

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147 APPENDIX B FATTY ACID PEAK NAMI NG TABLE FOR THE RTS BA6 METHOD Fatty Acid v Nom. ECL w Nom. RT x Cal/Ind y Qnt Cal z Pelargonic acid 9.0000 1.0670 C Yes Caprylic 3OH 9.4120 1.1285 No U nknown 9.560 9.5600 1.1506 No iso capric 9.6160 1.1589 No Capric acid 10.0000 1.2162 C Yes Pelargonic 3OH 10.4310 1.2980 No iso unde cylic 10.6180 1.3335 No anteiso undecylic 10.7050 1.3500 No Lauric a ldehyde 10.9300 1.3927 No U nknown 10.9525 10.9525 1.3970 No Undecylic acid 11.0000 1.4060 C Yes Capric 2OH 11.1774 1.4470 I No Capri c 3OH 11.4480 1.5095 I No U nknown 11.543 11.5430 1.5314 No iso lauric 11.6210 1.5495 No anteiso lauric 11.7100 1.5700 No U nknown 11.825 11.8250 1.5966 No 12:1 at 11 12 11.9250 1.6197 No Lauric acid 12.0000 1.6370 C Yes iso undecylic 3OH 12.1080 1.6657 No Undecylic 2OH 12.1910 1.6878 No Undecylic 3OH 12.4650 1.7607 No U nknown 12.502 12.5020 1.7705 No iso tridecylic 12.6230 1.8027 No anteiso tri decylic 12.7140 1.8269 No 13:1 at 12 13 12.9580 1.8918 No Tridecylic acid 13.0000 1.9030 C Yes iso lauric 3OH 13.1200 1.9382 No Lauric 2OH 13.2040 1.9628 No 12:1 3OH 13.3250 1.9982 No 14:1 iso E 13 .3960 2.0190 No Lauric 3OH 13.4830 2.0445 No U nknown 13.591 13.5910 2.0762 No iso myristic 13.6280 2.0870 No anteiso myristic 13.7180 2.1134 No 14:1 5 c 13.9160 2.1714 No U nknown 13.951 13.9510 2.1816 No Myristic acid 14.0000 2.1960 C Yes iso tridecylic 3OH 14.1320 2.2367 No Tridecylic 2OH 14.2240 2.2651 No U nknown 14.263 14.2630 2.2772 No

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148 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal 15:1 iso 9 c 14.4130 2.3235 No 15:1 iso F 14.4420 2.3324 No 15:1 iso G 14.4600 2.3380 No 15:1 iso H/13:0 3OH 14.4760 2.3429 No 13:0 3OH/15:1 i so H 14.5030 2.3513 No U nknown 14.502 14.5160 2.3553 No 15:1 anteiso A 14.5510 2.3661 No iso pentadecylic 14.6320 2.3911 No anteiso pentadecylic 14.7250 2.4198 No 15:1 8 c 14.8140 2.4473 No 15:1 6 c 14.8750 2.4661 No 15:1 5 c 14.9260 2.4819 No U nknown 14.969 14.9690 2.4951 No Pentadecylic acid 15.0000 2.5047 C No iso myristic 3OH 15.1470 2.5515 No Myristic 2OH 15.2332 2.5789 I No Palmitoleic a l c ohol 15.4140 2.6365 No 16:1 iso G 15.4550 2.6495 No 16:1 iso H 15.4820 2.6581 No 16:1 iso I/14:0 3OH 15.5011 2.6642 No 14:0 3OH/16:1 iso I 15.5153 2.6687 I No Palmitic N a l c ohol 15.5740 2.6874 No iso palmitic 15.6330 2.7062 No U nknown 15.669 15.6690 2.7176 No anteiso palmitic 15.7270 2.7361 No 16:1 11 c 15.7820 2.7536 No 16:1 9 c 15.8000 2.7593 No 16:1 7 c /16:1 6 c 15.8400 2.7721 No 16:1 6 c /16:1 7 c 15.8750 2.7832 No 16:1 5 c 15.9280 2.8001 No Palmitic acid 16.0000 2.8230 C Yes iso pentadecyl ic 3OH 16.1620 2.8748 No Pentadecylic 2OH 16.2550 2.9046 No 17:1 iso 10 c 16.4140 2.9555 No Palmitic 10 methyl 16.4350 2.9622 No 17:1 iso 9 c 16.4470 2.9660 No 17:1 iso 5 c 16.4830 2.9776 No 17:1 iso I/ anteiso B 16.4980 2.9824 No 17:1 anteiso B/ iso I 16.5120 2.9868 No Pentadecylic 3OH 16.5330 2.9936 No 17:1 anteiso 9 c 16.5520 2.9996 No 17:1 anteiso A 16.5710 3.0057 No U nknown 16.586 16.5860 3.010 5 No iso margaric 16.6370 3.0268 No

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149 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal anteiso margaric 16.7330 3.0576 No 17:1 9 c 16.7830 3.0736 No 17:1 8 c 16.8150 3.0838 No 17:1 7 c 16.8360 3.0905 No 17:1 6 c 16.8810 3.1049 No 17:0 c y c lo 16.9150 3.1158 No 17:1 5 c 16.9300 3.1206 No Margaric acid 17.0000 3.1430 C Yes 16:1 2OH 17.0980 3.1740 No iso palmitic 3OH 17.1740 3.1 980 No anteiso margaric 16.7330 3.0576 No 17:1 9 c 16.7830 3.0736 No 17:1 8 c 16.8150 3.0838 No 17:1 7 c 16.8360 3.0905 No 17:1 6 c 16.8810 3.1049 No c y c lo margaric 16.9150 3.1158 No 17:1 5 c 16.9300 3.1206 No Palmitic 2OH 17.2655 3.2269 I No Margaric 10 methyl 17.4150 3.2741 No 18:1 iso H 17.4900 3.2978 No Palmitic 3OH 17.5480 3.3162 No linolenic acid 17.6000 3.3326 No iso stearic 17.6360 3.3440 No ante iso stearic / linoleic 17.7310 3.3740 No Linoleic / ante iso stearic 17.7560 3.3819 No Oleic acid 17.7940 3.3939 No cis vaccenic acid 17.8475 3.4108 No 18:1 6 c 17.9020 3.4280 No 18:1 5 c 17.9370 3.4391 No Stearic acid 18.0000 3.4590 C Yes cis vaccenic 11 methyl 18.0860 3.4857 No iso margaric 3OH 18.1930 3.5190 No Margaric 2OH 18.2880 3.5486 No Stearic 10 methyl 18.3950 3.5818 No 19:1 iso I 18.4980 3.6139 No Margaric 3OH 18.5650 3.6347 No iso nonadecylic 18.6380 3.6574 No anteiso nonadecylic 18.7380 3.6885 No 19:1 11 c /19:1 9 c 18.7750 3.7000 No 19:1 9 c /19:1 11 c 18.7920 3 .7053 No U nknown 18.815 18.8150 3.7125 No 19:1 7 c /19:1 6 c 18.8370 3.7193 No 19:1 6 c / 7 c /19 c y 18.8570 3.7255 No cyclo nonadecylic C10 18.8870 3.7349 No

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150 Fatty Acid Nom. ECL Nom. RT Cal/Ind Qnt Cal c y c lo nonadecylic C8 18.9320 3.7489 No Nonadecylic acid 19.0000 3.7700 C Yes 18:1 2OH 19.1460 3.8142 No Stearic 2OH 19.2980 3.8603 No Nonadecylic 10 methyl 19.3720 3.8827 No Arachidon ic acid 19.4660 3.9112 No Stearic 3OH 19.5800 3.9457 No iso arachidic 19.6360 3.9627 No Eicosadienoic acid 19.7390 3.9939 No Eicosenoic acid 19.7910 4.0097 No 20:1 7 c 19.8500 4.0276 No Arachidic acid 20.0000 4.0730 C Yes v Structural notations: ( ) functional group located at carbon numbered from terminal carbon, ( c or cis ) all double bonds in cis or Z configuration, ( t or trans ) all double bonds in trans or E configuration, (OH) hydroxyl group at indicated carbon, ( iso ) fatty acid is in iso configuration, ( anteiso ) fatty acid is in anteiso configuration, ( cyclo ) fatty acid has a cyclic O bond at indicated carbon, (DMA) fatty acid structure cont ains dimethyl acetal tail, ( methyl ) fatty acid has a methyl group at the indicated carbon, ( a ldehyde) fatty acid structured with an aldehyde tail, ( a lcohol) fatty acid tail has CH 2 OH tail instead of CH 3 determined as is listed by retention time. w Nominal estimated chain length (ECL) of given fatty acid. x Nominal retention time (RT) of given fatty acid after sample injection. y Fatty acid is used for calibration mix (C) or indicator (I) of cali bration shift z Amount of fatty acid can be quantified (Qnt) during calibration (Cal).

PAGE 151

151 APPENDIX C COMMON NAMES FOR SAT URATED FATTY ACIDS Common Name Chain Length Structural Formula Pelargonic acid 9:0 CH 3 (CH 2 ) 7 COOH Capric acid 10:0 CH 3 (CH 2 ) 8 COOH Undecylic acid 11:0 CH 3 (CH 2 )9COOH Lauric acid 12:0 CH 3 (CH 2 ) 10 COOH Tridecylic acid 13:0 CH 3 (CH 2 ) 11 COOH Myristic acid 14:0 CH 3 (CH 2 ) 12 COOH Pentadecylic acid 15:0 CH 3 (CH 2 ) 13 COOH Palmitic acid 16:0 CH 3 (CH 2 ) 14 COOH Margaric acid 17:0 CH 3 (CH 2 ) 15 COOH Stearic acid 18:0 CH 3 (CH 2 ) 16 COOH Nonadecylic acid 19:0 CH 3 (CH 2 ) 17 COOH Arachidic acid 20:0 CH 3 (CH 2 ) 18 COOH Heneicosylic acid 21:0 CH 3 (CH 2 ) 19 COOH Behenic acid 22:0 CH 3 (CH 2 ) 20 COOH Tricosylic acid 23:0 CH 3 (CH 2 ) 21 COOH Lignoceric acid 24:0 CH 3 (CH 2 ) 22 COOH Pentacosylic acid 25:0 CH 3 (CH 2 ) 23 COOH Cerotic acid 26:0 CH 3 (CH 2 ) 24 COOH Heptacosylic acid 27:0 CH 3 (CH 2 ) 25 COOH Montanic acid 28:0 CH 3 (CH 2 ) 26 COOH Nonacosylic acid 29:0 CH 3 (CH 2 ) 27 COOH Melissic acid 30:0 CH 3 (CH 2 ) 28 COOH Henatriacontylic acid 31:0 CH 3 (CH 2 ) 29 COOH Lacceroic acid 32:0 CH 3 (CH 2 ) 30 COOH Psyllic acid 33:0 CH 3 (CH 2 ) 31 COOH Geddic acid 34:0 CH 3 (CH 2 ) 32 COOH Ceroplastic acid 35:0 CH 3 (CH 2 ) 33 COOH Hexatriacontylic acid 36:0 CH 3 (CH 2 ) 34 COOH

PAGE 152

152 APPENDIX D COMMON NAMES FOR UNS ATURATED FATTY ACIDS Common Name Structure Palmitoleic acid c Hexadecatrienoic acid 9 c Vaccenic acid t cis vaccenic acid c Oleic acid c Elaidic acid t Linoleic acid c Rumenic acid Z ,9 E linolenic acid c Rumelenic acid E ,7 Z ,9 E Eleos tearic acid E ,7 E ,9 Z Eleostearic acid E ,7 E ,9 E Catalpic acid E ,7 Z ,9 Z Punicic acid Z ,7 E ,9 Z linolenic acid c Calendic acid Z ,8 E ,10 E Calendic acid E ,8 E ,10 E Jacaric acid Z ,8 E ,10 Z Pinolenic acid c ,9,13 c Stearidonic acid c Parinaric acid E ,5 Z ,7 Z ,9 E Parinaric acid t Eicosenoic acid c Eicosadienoic acid c Eicosatrienoic acid c Dihomo linolenic acid c Podocarpic acid c ,9 c ,15 c Mead acid c Eicosatetraenoic acid c Arachidonic acid c Eicosapentaenoic acid (Timnodonic acid) c Bosseopentaenoic acid Z ,8 E ,10 E ,12 Z ,15 Z Heneicosapentaenoic acid c Erucic acid c Docosadienoic acid c Adrenic acid c Docosapentaenoic acid (Clupanodonic a cid) c Docosapentaenoic acid (Osbond acid) c Docosahexaenoic acid (Cervonic acid) c Nervonic acid c Tetracosatetraenoic acid c Tetracosapentaenoic acid 2 c

PAGE 153

153 Tetracosapentaenoic acid c Tetracosahexaenoic acid (Nisinic acid) c Structural notations: ( c ) all double bonds in cis or Z configuration, ( t ) all double bonds in trans or E config uration, ( Z ) preceding double bond location is in cis configuration, ( E ) preceding double bond is in trans configuration.

PAGE 154

154 APPENDIX E COMMON FATTY ACID ST RUCTURES Fatty acid Structure Saturated fatty acid Saturated fatty acid meth yl ester (FAME) trans unsaturated FAME cis unsaturated FAME iso FAME anteiso FAME FAME aldehyde FAME alcohol

PAGE 155

155 FAME hydroxyl (OH) FAME dimethylacetal (D MA) cyclo FAME

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156 LIST OF REFERENCES Abebe, E. and M. Blaxter. 2003. Comparison of biological, molecular, and morphological methods of species identification in a set of cultured Panagrolaimus isolates. Journal of Nematology 3 5:119 128 Abrantes, I., M., de O., M. C. V. dos Santos, I. L., P. M. da Conceio, M. J. M. da Cunha, and M. S. N. de A. Santos. 2004. Biochemical and molecular characterization of plant parasitic nematodes Phytopathologia Mediterranea 43:232 258 Ada m, M. A. M., M. S. Phillips, and V. C. Blok. 2007. Molecular diagnostic key for identification of single juveniles of seven common and economically important species of root knot nematode ( Meloidogyne spp.). Plant Pathology 56:190 197 Agudelo P., R. T. Robbins, J. McD. Stewart, and A. L. Szalanski. 2005. Intraspecific variability of Rotylenchulus reniformis from cotton growing regions in the United States. Journal of Nematology 37:105 114 Allen, M. W. 1952. Observations on the genus Meloidogyne Goeldi, 1987. Proceedings of the Helminthological Society of Washington 19:44 51 Amiri, S., S. A. Subbotin, and M. Moens. 2002. Identification of the beet cyst nematode Heterodera schachtii by PCR. European Journal of Plant Pathology 108:497 506 Andr ews, R. H., and N. B. Chilton. 1999. Multilocus enzyme electrophoresis: a valuable technique for providing answers to problems in parasite systems. International Journal for Parasitology 29:213 253 Barker, K. R., C. C. Carter, and J. N. Sasser. 1985. An Advanced Treatise on Meloidogyne 2 vol. North Carolina State University Department of Plant Pathology, Raleigh, NC. Baum, T. J., S. A. Lewis, and R. A. Dean. 1994. Isolation, characterization, and application of DNA probes specific to Meloidogyne arenaria Molecular Plant Pathology 84:489 494 Beames, Jr., C. G., and F. M. Fisher, Jr. 1964. A study on the neutral lipids and phospholipids of the acanthocephalan Macracanthorhynchus hirudinaceaus and Moniliformis dubius Comparative Biochemistry a nd Physiology 13:401 412 Bergeson, G. B. 1959. The influence of temperature on the survival of some species of the genus Meloidogyne in the absence of a host. Nematologica 4:344 354 Beveridge, I. 1998. Allozyme electrophoresis difficulties encounte red in studies on helminths. International Journal for Parasitology 28:973 979

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157 Bhadury, P., M. C. Austen, D. T. Bilton, P. J. D. Lambshead, A. D. Rogers, and G. R. Smerdon. 2006. Development and evaluation of a DNA barcoding approach for the rapid iden tification of nematodes. Marine Ecology Progress Series 326:1 9 Bhadury, P., M. C. Austen, D. T. Bilton, P. J. D. Lambshead, A. D. Rogers, and G. R. Smerdon. 2006a. Molecular detection of marine nematodes from environmental samples: overcoming eukaryot ic interference. Aquatic Microbial Ecology 44:97 103 Bhadury, P., M. C. Austen, D. T. Bilton, P. J. D. Lambshead, A. D. Rogers, and G. R. Smerdon. 2008. Evaluation of combined morphological and molecular techniques for marine nematode ( Terschellingia s pp.) identification. Marine Biology 154:509 518 Bird, A. F. 1966. Esterases in the genus Meloidogyne Nematologica 12:359 361 Bird, A. F. and H. R. Wallace. 1965. The influence of temperature on Meloidogyne hapla and M. javanica Nematologica 11: 581 589 Blaxter, M., J. Mann, T. Chapman, F. Thomas, C. Whitton, R. Floyd, and E. Abebe. 2005. Defining operational taxonomic units using DNA barcode data. Philosophical Transactions of the Royal Society B 360:1935 1943 Blouin, M. S. 2002. Molecular prospecting for cryptic species of nematodes: mitochondrial DNA versus internal transcribed spacer. International Journal for Parasitology 32:527 531 Bolla, R. I., C. Weaver, and R. E. K. Winter. 1988. Genomic differences among pathotypes of Bursaphel enchus xylophilus Journal of Nematology 20:309 316 Brito, J. A., R. Kaur, R. Cetintas, J. D. Stanley, M. L. Mendes, E. J. McAvoy, T. O. Powers, and D. W. Dickson. 2008. Identification and isozyme characterization of Meloidogyne spp. Infecting horticul tural and agronomic crops, and weed plants in Florida Nematology 10:757 766 Bucklin, A., D. Steinke, and L. Blanco Bercial. 2011. DNA barcoding in marine metazoa. Annual Review of Marine Science 3:471 508 Carneiro, R. M. D. G., M. R. A. Almeida, and P. Qunherve. 2000. Enzyme phenotypes of Meloidogyne spp. populations. Nematology 2:645 654 Carta, L. K., A. M. Skantar, and Z. A. Handoo. 2001. Molecular, morphological, and thermal characters of 19 Pratylenchus spp. and relatives using the D3 seg ment of the nuclear LSU rRNA gene. Nematropica 31:195 209

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158 Casiraghi, M., C. Bazzocchi, M. Mortarino, E. Ottina, and C. Genchi. 2006. A simple molecular method for discriminating common filarial nematodes of dogs ( Canis familiaris ). Veterinary Parasito logy 141:368 372 Castagnone Sereno P. 2006. Genetic variability and adaptive evolution in parthenogenetic root knot nematodes. Heredity 96:282 289 Cetintas, R., R. D. Lima, M. L. Mendes, J. A. Brito, and D. W. Dickson. 2003. Meloidogyne javanica on peanut in Florida. Journal of Nematology 35 : 433 436 of molecular methods for monitoring soil nematodes and their us e as biological indicators. European Journal of Soil Biology 46:319 324 Chilton, N. B., I. Beveridge, and R. H. Andrews. 1992. Detection by allozyme electrophoresis of cryptic species of Hypodontus macropi (Nematoda: Strongyloidea) from macropodid marsupials. International Journal for Parasitolo gy 22:271 279 Chilton, N. B., I. Beveridge, and R. H. Andrews. 1992 a Apparent lack of genetic variation within Pelecitus roemeri (Nematoda: Filarioidea) from three Australian species of macropodid marsupial. International Journal for Parasitology 22:1 023 1027 Chilton, N. B., I. Beveridge, and R. H. Andrews. 1993. Electrophoretic comparison of Rugopharynx longibursaris Kung and R. omega Beveridge (Nematoda: Strongyloidea), with the description of R. sigma n. sp. from pademelons, Thylogale spp. (Marsu pialia: Macropodidae). Systematic Parasitology 26:159 169 Chitwood, D. J. 2003. Research on plant parasitic neamtode biology conducted by the United States Department of Agriculture Agricultural Research Service. Pest Management Sciecne 59:748 753 Ch itwood, D. J., and L. R. Krusberg. 1981. Diacyl, alkylacyl, and alkenylacyl phospholipids of Meloidogyne javanica females. Journal of Nematology. 13:105 111 Chitwood, D. J., and L. R. Krusberg. 1981 a Diacyl, alkylacyl and alkenylacyl phospholipids of the nematode Tu r batrix aceti Comparative Biochemistry and Physiology. 69B:115 120 Christner, B. C., B. H. Kvitko II, J. N. Reeve. 2003. Molecular identification of bacteria and eukarya inhabiting an Antarctic cryoconite hole. Extremophiles 7:177 183

PAGE 159

159 Cook, A. A., P. Bhadury, N. J. Debenham, B. H. M. Meldal, M. L. Blaxter, G. R. Smerdon, M. C. Austen, P. J. D. Lambshead, and A. D. Rogers. 2005. Denaturing gradient gel electrophoresis (DGGE) as a tool for identification of marine nematodes. Marin e Ecology Progress Series 291:103 113 Creer, S., V. G. Fonseca, D. L. Porazinska, R. M. Giblin Davis, W. Sung, D. M Powers, M. Packer, G. R. Carvalho, M. L. Blaxter, P. J. D. Lambshead, and W. K. Thomas. 2010. Ultrasequencing of the meiofaunal biosphere : practice, pitfalls and promises. Molecular Ecology 19:4 20 Curran, J., M. A. McClure, and J. M. Webster. 1986. Genotypic differentiation of Meloidogyne populations by detection of restriction fragment length difference in total DNA. Journal of Nema tology 18:83 86 Curran, J. and J. M. Webster. 1987. Identification of nematodes using restriction fragment length differences and species specific DNA probes. Canadian Journal of Plant Pathology 9:162 166 Cyril, J., G. L. Powell, R. R. Duncan, and W. V. Baird. 2002. Changes in membrane lipid fatty acids of seashore paspalum in response to low temperature exposure. Crop Science 42:2031 2037 Dallas, J. F., R. J. Irvine, O. Halvorsen, and S. D. Albon. 2000. Identification by polymerase chain reactio n (PCR) of Marshallagia marshalli and Ostertagia gruehneri from Svalbard reindeer. International Journal of Parasitology 30:863 866 Davies, K. G. and E. B. Lander. 1992. Immunological differentiation of root knot nematodes ( Meloidogyne spp.) using mono clonal and polyclonal antibodies. Nematologica 38:353 366 Davis, B.J. 1964. Disc electrophoresis II method and application to human serum proteins. Annals of the New York Academy of Sciences 121:404 427 Dayrat, B. 2005. Towards integrative taxonomy. Biological Journal of the Linnean Society 85:407 415 De Ley, I. T., M. Mundo Ocampo, M. Yoder, and P. De Ley. 2007. Nematodes from vernal pools in the Santa Rosa Plateau Ecological Reserve, California I. Hirschmanniella santarosae sp. n. (Nematoda: Pr atylenchidae), a cryptic sibling species of H. pomponiensis Abdel Rahman & Maggenti, 1987. Nematology 9:405 429 De Ley, P., I. T. De Ley, K. Morris, E. Abebe, M. Mundo Ocampo, M. Yoder, J. Heras, D. Waumann, A. Rocha Olivares, A. H. J. Burr, J. G. Baldwi n, and W. K. Thomas. 2005. An integrated approach to fast and informative morphological

PAGE 160

160 vouchering of nematodes for applications in molecular barcoding. Philosophical Transactions of the Royal Society B 360:1945 1958 Derycke, S. T. Backeljau, C. Vlaemi nck, A. Vierstraete, J. Vanfleteren, M. Vinex, and T. Moens. 2007. Spatiotemporal analysis of population genetic structure in Geomonhystera disjuncta (Nematoda: Monhysteridae) reveals high levels of molecular diversity. Marine Biology 151:1799 1812 Der ycke, S. J. Vanaverbeke, A. Rigaux, T. Backeljau, and T. Moens. 2010. Exploring the use of cytochrome oxidase c subunit 1 (COI) for DNA barcoding of free living marine nematodes. PLoS ONE 5:e13716 Dickson, D. W., D. Huisingh, and J. N. Sasser. 1971. Dehydrogenases, acid and alkaline phosphatases, and esterases for chemotaxonomy of selected Meloidogyne Ditylenchus Heterodera and Aphelenchus spp. Journal of Nematology 3:1 16 Dickson, D. W., J. N. Sasser, and D. Huisingh. 1970. Comparative disc el ectrophoretic protein analysis of selected Meloidogyne Ditylenchus Heterodera and Aphelenchus spp. Journal of Nematology 2:286 293 Ding, X., J. Shields, R. Allen, and R. S. Hussey. 1998. A secretory cellulose binding protein cDNA cloned from the roo t knot nematode ( Meloidogyne incognita ). Molecular Plant Microbe Interactions 11:952 959 Donn, S., B. S. Griffiths, R. Neilson, and T. J. Daniell. 200 7 DNA extraction from soil nematodes for multi sample community studies. Applied Soil Ecology 38:20 26 Donn, S., R. Neilson, B. S. Griffiths, and T. J. Daniell. 2011. Greater coverage of the phylum Nematoda in SSU rDNA studies. Biology and Fertility of Soils 47:333 339 Esbenshade, P. R. and A. C. Triantaphyllou. 1985. Use of enzyme phenotypes for identification of Meloidogyne species. Journal of Nematology 17:6 20 Fargette, M. 1987. Use of the esterase phenotype in the taxonomy of the genus Meloidogyne 2. Esterase phenotypes observed in West African populations and their characterization. Rev ue de Nmatologie 10:45 56 Fargette, M. and R. Braaksma 1990. Use of the esterase phenotype in the taxonomy of the genus Meloidogyne position. Revue de Nmatologie 13:375 386 Fernndez Snchez, C. C. J. McNeil, K. Rawson, O. Nilsson, H. Y. Leung, and V. Gnanapragasam 2005. One step immunostrip test for the simultaneous

PAGE 161

161 d etection of free and total prostate specific antigen in serum Journal of Immunological Methods 307:1 12 Flores Romer o P., and A. Navas. 2005. Enhancing taxonomic resolution: distribution dependent genetic diversity in populations of Meloidogyne Nematology 7:517 530 Floyd, R., E. Abebe, A. Papert, and M. Blaxter. 2002. Molecular barcodes for soil nematode identification Molecular Biology 11:839 850 Floyd, R. M., A. D. Rogers, P. J. D. Lambshead, and C. R. Smith. 2005. Nematode specific PCR primers for the 18S small subunit rRNA gene. Molecular Ecology Notes 5:611 612 Fonesca, G., S. Derycke, and T. Moens. 2008. Integrative taxonomy in two free living neamtode species complexes. Biological Journal of the Linnean Society 94:737 753 Foucher, A. and M. Wilson. 2002. Development of a polymerase chain reaction based denaturing gradient gel electrophoresis technique to study nematode species biodiversity using the 18s rDNA gene. Molecular Ecology Notes 2:45 48 Foucher, A. L. J. L., T. Bongers, L. R. Noble, and M. Wilson. 2004. Assessment of nematode biodiversity using DGGE of 18s rDNA following extraction of nema todes from soil. Soil Biology and Biochemistry 36:2027 2032 Fullaondo, A., E. Barrena, M. Viribay, I. Barrena, A. Salazar, and E. Ritter. 1999. Identification of potato cyst nematode species Globodera rostochiensis and G. pallida by PCR using specific primer combinations. Nematology 1:157 163 Fujii, T., S. Morimoto, Y. T. Hoshino, H. Okada, Y. Wand, H. Chu, and S. Tsushima. 2004. Studies of diversity and functions of soil microbes and nematodes in NIAES using nucleic acids extracted from soil. Japa nese National Institute for Agro Environmental Sciences Tsukuba, Japan Gasser, R. B., N. B. Chilton, H. Hoste, and L. A Stevenson. 1994. Species identification of Trichostrongyle nematodes by PCR linked RFLP. International Journal for Parasitology 24: 291 293 Gasser, R. B. and H. Hoste. 1995. Genetic markers for closely related parasitic nematodes. Molecular and Cellular Probes 9:3115 320 Gasser, R. B., and J. R. Monti. 1997. Identification of parasitic nematodes by PCR SSCP of ITS 2 rRNA. Molec ular and Cellular Probes 11:201 209

PAGE 162

162 George Nascimento, M. and A. Llanos. 1995. Micro evolutionary implications of allozymic and morphometric variations in sealworms Pseudoterranova sp. (Ascaridoidea: Anisakidae) among sympatric hosts from the southeaste rn Pacific Ocean. International Journal for Parasitology 25:1163 1171 Geraert, E. 1965. The head structures of some tylenchs with special attention to the amphidial apertures. Nematologica 11:131 136 Goodell, P.B. and H. Ferris. 1981. Sample optimi zation for five plant parasitic nematodes in an alfalfa field. Journal of Nematology 13:304 313 Gomez, A., M. Serra, G. R. Carvalho, and D. H. Lunt. 2002. Speciation in ancient cryptic species complexes: evidence from the molecular phylogeny of Brachio nus plicatilis (ROTIFERA). Evolution 56:1431 1444 Gozel, U., B. Adams, K. Nguyen, R. Inserra, R. Giblin Davis, and L. Duncan. 2006. A phylogeny of Belonolaimus populations in Florida inferred from DNA sequences. Nematropica 36:149 165 Griffiths, B. S. S. Donn, R. Neilson, and T. J. Daniell. 2006. Molecular sequencing and morphological analysis of a nematode community. Applied Soil Ecology 32:325 337 Handoo, Z. A., A. P. Nyczepir, D. Esmenjaud, J. G. van der Beek, P. Castagnone Sereno, L. K. Carta, A. M. Skantar, and J. A. Higgins. 2004. Morphological, molecular, and differential host characterization of Meloidogyne floridensis n. sp. (Nematoda: Meloidogynidae), a root knot nematode parasitizing peach in Florida. Journal of Nematology 36:20 35 H arris, T. S., L. J. Sandall, and T. O. Powers. 1990. Identification of single Meloidogyne juveniles by polymerase chain reaction amplification of mitochondrial DNA. Journal of Nematology 22:518 524 Herbert, P. D. N., E. H. Penton, J. M. Burns, D. H. Ja nzen, and W. Hallwachs. 2004. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator Proceedings of the National Academy of Sciences 101:14812 14817 Holeva, R., M. S. Phillips, R. Neilson, D J. F. Brown, V. Young, K. Boutsika, and V. C. Blok. 2006. Real time PCR detection and quantification of vector trichodorid nematodes and Tobacco rattle virus Molecular and Cellular Probes 20:203 211 Holt, S. J. 1958. Inigogenic staining methods fo r esterases. General Cytochemical Methods 1:375 398

PAGE 163

163 Horton, R. H., L. A. Moran, R. S. Ochs, D. J. Rawn, and K. G. Scrimgeour. 2001. Principles of Biochemistry 3 rd ed. Prentice Hall, NJ Hu, M. X., K. Zhuo, and J. L. Liao. 2011. Multiplex PCR for th e simultaneous identification and detection of Meloidogyne incognita M. enterolobii and M. javanica using DNA extracted directly from individual galls. Phytopathology 101:1270 1277 Hbschen, J., L. Kling, U. Ipach, V. Zinkernagel, N. Bosselut, D. Esmen jaud, D. J. F. Brown, and R. Neilson. 2004. Validation of the specificity and sensitivity of species specific primers that provide a reliable molecular diagnostic for Xiphinema diversicaudatum X. index and X. vuittenezi European Journal of Plant Patho logy 110:779 788 Hutzell, P. A. and L. R. Krusberg. 1982. Fatty acid compositions of Caenorhabditis elegans and C. briggsae Comparative Biochemistry and Physiology. 73B:517 520 Ibrahim, S. K., K. G. Davies, and R. N. Perry. 1996. Identification of the root knot nematode, Meloidogyne incognita using monoclonal antibodies raised to nonspecific esterases. Physiological and Molecular Plant Pathology 49:79 88 Ibrahim, S. K., S. T. Minnis, A. D. P. Barker, M. D. Russell, P. P. J. Haydock, K. Evans, S. R W oods, and A. Wilcox. 2001. Evaluation of PCR, IEF and ELISA techniques for the detection and identification of potato cyst nematodes from field soil samples in England and Wales. Pest Management Science 57:1068 1074 Inserra, R. N., A. Troccoli, U. Gozel, E. C. Bernard, D. Dunn, and L. W. Duncan. 2007. Pratylenchus hippeastri n. sp. (Nematoda: Pratylenchidae) from amaryllis in Florida with notes on P. scribneri and P. hexincisus Nematology 9:25 42 Johnson, D. E. 1998. Applied multivariate method s for data analysis Duxbury Press, Pacific Grove, CA Kalinski, A. and R. N. Huettel 1988. DNA restriction fragment length polymorphism in races of the soybean cyst nematode, Heterodera glycines Journal of Nematology 20:532 538 Kang, J. S., K. S. Ch oi, S. C. Shin, I. S. Moon, S. G. Lee, and S. H. Lee. 2004. Development of an efficient PCR based diagnosis protocol for the identification of the pinewood nematode Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae). Nematology 6:279 285 Kanzaki, N., F. Abe, R. M. Giblin Davis, K. Kiontke, D. H. A. Fitch, K. Hata, and K. Son. 2008. Teratorhabditis synpapillata Sudhaus, 1985 (Rhabditida:

PAGE 164

164 Rhabditidae) is an associate of the red palm weevil, Rhynchophorus ferrugineus (Coleoptera: Curculionidae). N ematology 10:207 218 Kanzaki, N., K. Tsuda, and K. Futai. 2000. Description of Bursaphelenchus conicaudatus n. sp. (Nematoda: Aphelenchoididae), isolated from the yellow spotted longicorn beetle, Psacothea hilaris (Coleoptera: Cerambycidae) and fig tree s, Ficus carica Nematology 2:165 168 Karssen, G., R. J. Bolk, A. C. van Aelst, I. van den Beld, L. F. F. Kox, G. Korthals, L. Molendijk, C. Zijlstra, R. van Hoof, and R. Cook. 2004. Description of Meloidogyne minor n. sp. (Nematoda: Meloidogynidae), a root knot nematode associated with yellow patch disease in golf courses. Nematology 6:59 72 Kennedy, M. J., J. E. Schoelz, P. A. Donald, and T. L. Niblack. 1997. Unique immunogenic proteins in Heterodera glycines eggshells. Journal of Nematology 29:2 76 281 Kirkpatrick, T. L. and J. N. Sasser. 1984. Crop rotation and races of Meloidogyne incognta in cotton root knot management. Journal of Nematology 16:323 328 Krusberg, L. R. 1967. Analyses of total lipids and fatty acids of plant parasitic nema todes and host tissues. Comparative Biochemistry and Physiology. 21:83 90 Krusberg, L. R. 1972. Fatty acid compositions of Turbatrix aceti and its culture medium. Comparative Biochemistry and Physiology. 41B:89 98 Krusberg, L. R., R. S. Hussey, and C. L. Fletcher. 1973. Lipid and fatty acid compositions of females and eggs of Meloidogyne incognita and M. arenaria Comparative Biochemistry and Physiology. 45B:335 341 Kunitsky, C., G. Osterhout, and M. Sasser. 2005. Identification of microorgan isms using fatty acid methyl ester (FAME) analysis and the MIDI Sherlock Microbial Identification System. Encyclopedia of Rapid Microbiological Methods, MIDI Newark, DE La Rossa, G., E. Pozio, P. Rossi, and K. D. Murrell. 1992. Allozyme analysis of Tr ichinella isolates from various host species and geographical regions. Journal of Parasitology 78:641 646 Larkindale, J. and B. Huang. 2004. Changes of lipid composition and saturation level in leaves and roots for heat stressed and heat acclimated cre eping bentgrass ( Agrostis stolonifera ). Environmental and Experimental Botany 51:57 67

PAGE 165

165 Laughlin, C. W., A. S. Williams, and J. A. Fox. 1969. The influence of temperature on development and sex determination of Meloidogyne graminis Journal of Nematolo gy 1:212 215 Lawler, C., P. Joyce, and M. A. Harmey. 1993. Immunological differentiation between Bursaphelenchus xylophilus and B. mucronatus Nematologica 39:536 546 Lee, D. L. 1964. Esterase enzymes in two free living nematodes Proceedings of th e Helminthological Society of Washington 31:285 288 Li, M. W., R. Q. Lin, H. H. Chen, R. A. Sani, H. Q. Song, and X. Q. Zhu. 2007. PCR tools for the verification of the specific identity of ascaridoid nematodes from dogs and cats. Molecular and Cellula r Probes 21:349 354 Liebenberg, A., M. J. Freeborough, C. J. Visser, D. U. Bellstedt, and J. T. Burger. 2009. Genetic variability within the coat protein gene of Grapevine fanleaf virus isolates from South Africa and the evaluation of RT PCR, DAS ELISA and ImmunoStrips as virus diagnostic assay Virus Research 142:28 35 Lima, L. M., M. F. Grossi de Sa, R. A. Pereira, and R. H. C. Curtis. 2005. Immunolocalisation of secreted excreted products of Meloidogyne spp. using polyclonal and monoclonal antibod ies. Fitopatologia Brasileira 30:629 633 Lima, R. D., M. L. Mendes, J. A. Brito, R. Cetintas, and D. W. Dickson. 2002. The occurrence of Meloidogyne javanica on peanut in Florida. American Peanut Research and Education Society Proceedings 34:103 Liu, J., and R. E. Berry. 1995. Determination of PCR conditions for RAPD analysis in entomopathogenic nematodes (Rhabditida: Heterorhabditidae and Steinernematidae). Journal of Invertebrate Pathology 65:79 81 Maafi, Z. T., S. A. Subbotin, and M. Moens. 20 03. Molecular identification of cyst forming nematodes (Heteroderidae) from Iran and a phylogeny based on ITS rDNA sequences. Nematology 5:99 111 MacMill an, K. V. Blok, I. Young, J. Crawford, and M. J. Wilson. 2006. Quantification of the slug parasite nematode Phasmarhabditis hermaphrodita from soil samples using real time qPCR. International Journal for Parasitology 36:1453 1461 Madani, M., S. A. Subbotin, and M. Moens. 2005. Quantitative detection of the potato cyst nematode, Globodera pallida a nd the beet cyst nematode, Heterodera schachtii using real time PCR with SYBR green I dye. Molecular and Cellular Probes 19:81 86 Madani, M., N. Vovlas, P. Castillo S. A. Subbotin, and M. Moens. 2004. Molecular characterization of cyst nematode speci es ( Heterodera spp.) from the

PAGE 166

166 Mediterranean Basin using RFLPs and sequences of ITS rDNA. Journal of Phytopathology 152:229 234 McClure, M. A. and B. A. Stynes. 1988. Lectin binding sites on the amphidal exudates of Meloidogyne Journal of Nematology 2 0:321 326 MIDI 2011. Sherlock Instant FAME Users Guide. MIDI Newark, DE Navas, A., J. A. L pez, G. Esp rrago, E. Camafeita, and J. P. Albar. 2002. Protein variability in Meloidogyne spp. (Nematoda: Meloidogynidae) revealed by two dimensional gel e lectrophoresis and mass spectrometry. Journal of Proteome Research 1:421 427 Nguyen, K. B., D. L. Shapiro Ilan, R. J. Stuart, C. W. McCoy, R. R. James, and B. J. Adams. 2004. Heterorhabditis mexicana n. sp. (Rhabditida: Heterorhabditidae) from Tamaulip as, Mexico, and morphological studies of the bursa of Heterorhabditis spp. Nematology 6:231 244 Noel, G. R. and Z. L. Liu. 1998. Esterase allozymes of soybean cyst nematode, Heterodera glycines from China, Japan, and the United States. Journal of Nem atology 30:468 476 or rabbit laboratory reared and goat wild populations of Trichostrongylus colubriformis International Journal for Parasitology 23:1087 1089 Oka, Y. G. Karssen, and M. Mordechai. 2003. Identification, host range and infection process of Meloidogyne marylandi from turf grass in Israel. Nematology 5:727 734 Okada, H., and H. Oba. 2008. Comparison of nematode community similarities assed by polyme rase chain reaction denaturing gradient gel electrophoresis (DGGE) and by morphological identification. Nematology 10:689 700 Oliveira, C. M. G., B. Fenton, G. Malloch, D. J. F. Brown, and R. Neilson. 2005. Development of species specific primers for t he ectoparasitic nematode species Xiphinema brevicolle X. diffusum X. elongatum X. ifacolum and X. longicaudatum (Nematoda: Longidoridae) based on ribosomal DNA sequences. Annals of Applied Biology 146:281 288 Orcutt, D. M., J. A. Fox, and C. A. Jake 1978. The sterol, fatty acid, and hydrocarbon composition of Globodera solanacearum Journal of Nematology. 10:264 269 Ornstein, L. 1964. Disc electrophoresis I background and theory. Annals of the New York Academy of Sciences 121:321 341

PAGE 167

167 Pamjav H., D. Triga, Z. Buzs, T. Vellai, A. Lucskai, B. Adams, A. P. Reid, A. Burnell, C. Griffin, I. Glazer, M. G. Klein, and A. Fodor. 1999. Novel application of PhastSystem polyacrylamide gel electrophoresis using restriction fragment length polymorphism internal transcribed spacer patterns of individuals for molecular identification of entomopathogenic nematodes. Electrophoresis 20:1266 1273 Pereira, T. J., G. Fonseca, M. Mundo Ocampo, B. C. Guilherme, and A. Rocha Olivares. 2010. Diversity of free living marine nematodes (Enoplida) from Baja California assessed by integrative taxonomy. Marine Biology 157:1665 1678 larval anisakid nematodes from marine fishes of Madeira by PCR based approach, with evidence for a new species Journal of Parasitology 91:1430 1434 Porazinska, D. L., R. M. Giblin Davis, L. Faller, W. Farmerie, N. Kanzaki, K. Morris, T. O. Powers, A. E. Tucker, W. Sung, and W. K. Thomas. 2009. Eval uating high throughput sequencing as a method for metagenomic analysis of nematode diversity. Molecular Ecology Resources 9:1439 1450 Porazinska, D. L., W. Sung, R. M. Giblin Davis, and W. K. Thomas. 2010. Reproducibility of read numbers in high throug hput sequencing analysis of nematode community composition and structure. Molecular Ecology Resources 10:666 676 Powers, T. O. 2004. Nematode molecular diagnostics: from bands to barcodes. Annual Review of Phytopathology 42:367 383 Powers, T. O. and T. S. Harris. 1993. A polymerase chain reaction method for identification of five major Meloidogyne species. Journal of Nematology 25:1 6 Powers, T. O., P. G. Mullin, T. S. Harris, L. A. Sutton, and R. S. Higgins. 2005. Incorporating molecular identi fication of Meloidogyne spp. into a large scale regional nematode survey. Journal of Nematology 37:226 235 Powers, T. O., D. A. Neher, P. Mullin, A Esquivel, R. M. Giblin Davis, N. Kanzaki, S. P. Stock, M. M Mora, and L. U ribe Lorio. 2009. Tropical ne m a tode diversity: vertical stratification of nematode communities in a Costa Rican humid lowland rainforest. Molecular Ecology 18:985 996 Powers, T. O., E. G. Platzer, and B. C. Hyman. 1986. Species specific restriction site polymorphism in root knot n ematode mitochondrial DNA. Journal of Nematology 18:288 293

PAGE 168

168 Quader, M., L. Nambiar, and J. Cunningham. 2008. Conventional and real time PCR based species identification and diversity of potato cyst nematodes ( Globodera spp.) from Victoria, Australia. Nematology 10:471 478 Reid, A. P., W. M. Hominick, and B. R. Briscoe. 1997. Molecular taxonomy and phylogeny of entomopathogenic nematode species (Rhabditida: Steinernematidae) by RFLP analysis of the ITS region of the ribosomal DNA repeat unit. System atic Parasitology 37:187 193 Rhode R. A. 1960. Acetylcholinesterase in plant parasitic nematodes and an anticholinesterase from asparagus. Proceedings of the Helminthological Society of Washington 27:121 123 Rodrguez Kbana, R., J. Pinochet, D. G. Ro bertson, and L. Wells. 1992. Crop rotation studies with velvetbean ( Mucuna deeringiana ) for the management of Meloidogyne spp. Suppliment to Journal of Nematology 24:662 668 Rubtsova, T. V., S. A. Subbotin, D. J. F. Brown, and M. Moens. 2001. Descrip tion of Longidorus sturhani sp. n. (Nematoda: Longidoridae) and molecular characterisation of several longidorid species from Western Europe. Russian Journal of Nematology 9:127 136 Saiki, R. K., S. Scharf, F. Faloona, K. B. Mullis, G. Horn, H. A. Erlich and N. Arnheim. 1985. Enzymatic amplification of globulin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science 230:1350 Samala, S., J. Yan, and W. V. Baird. 1998. Changes in polar lipid fatty acid compositi Science 38:188 195 Sasser, M. 1990. Bacterial identification by gas chromatographic analysis of fatty acid methyl esters (GC FAME). Technical Note 101, MIDI Newark, DE Sato, E., Y. Y Min, T. Shirakashi, S. Wada, and K. Toyota. 2007. Detection of the root lesion nematode, Pratylenchus penetrans (Cobb), in a nematode community using real time PCR. Japanese Journal of Nematology 37:87 92 Sekora, N. S., K. S. Lawrence, E. van Santen, J. A. McInroy. 2008. A s tep w ise d ilution s cheme to d etermine the n umber of n ematodes r equired for a ccurate FAME i dentification. Southeastern Biology 55:243. Sekora, N. S., K. S Lawrence, E. van Santen, J. A. McInroy. 2008 a Fingerprinting nematode fatty acid compositions as a means for identification. Proceedings of the National Beltwide Cotton Conference, Vol. 1:235 244. National Cotton Council, Memphis TN. Online: www.cotton.org/beltwide /proceedings

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169 Sekora, N. S., K. S. Lawrence, E. van Santen, J. A. McInroy. 2009. Delineating mixed populations of Rotylenchulus reniformis and Meloidogyne incognita with FAME analysis. Proceedings of the National Beltwide Cotton Conference, 1:159 165 National Cotton Council, Memphis TN. Online: www.cotton.org/beltwide/proceedings Sekora N. S., K. S. Lawrence, P. Agu delo, E. van Santen, and J. A. McInroy. 2009 a Using FAME analysis to compar e, differentiate, and identify multiple nematode species. Journal of Nematology 41:163 173 Sekora N. S., K. S. Lawrence, P. Agu delo, E. van Santen, and J. A. McInroy. 2010. Differentiation of Meloidogyne species with FAME analysis. Nematropica 40:163 175 Sekora, N. S., M. L. Mendes, and W. T. Crow. 2010 a I dentification of Meloidogyne species infecting tomato using FAME analysis. Nematropica 40:153 Sekora, N. S. and W. T. Crow. 2011. Adaptation of Instant FAME analysis for Meloidogyne species i dentifi cation. Nematropica 41:391 Sivapalan, P., and W. R. Jenkins. 1966. Phospholipid and long chain fatty acid composition of the nematode Panagrellus redivivus Proceedings of the Helminthological Society of Washington. 33:149 157 Skantar, A. M. and L. K. Carta. 2004. Molecular characterization and phylogenetic evaluation of the Hsp90 gene from selected neamtodes. Journal of Nematology 36:466 480 Stanton, J., A. Hugall, and C. Moritz. 1997. Nucleotide polymorphisms and an improved PCR based mtDNA diagnostic for parthenogenetic root knot nematodes ( Meloidogyne spp.). Fundamentals and Applied Nematology 20:261 268 Subbotin, S. A., P. D. Halford, and R. N. Perry. 1999. Identification of populations of potato cyst nematodes from Russia using protein electrophoresis, rDNA RFLPs and RAPDs. Russian Journal of Nematology 7:57 63 Subbotin, S. A., D. Peng, and M. Moens. 2001. A rapid method for the identification of the soybean cyst nematode Heterodera glycines using duplex PCR. Nematology 3:3 65 371 Subbotin, S. A., L. Waeyenberge, and M. Moens. 2000. Identification of cyst forming nematodes of the genus Heterodera (Nematoda: Heteroderidae) based on the ribosomal DNA RFLP. Nematology 2:153 164

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170 Sudhaus, W. and K. Kiontke. 2007. Comparison of the cryptic nematode species Caenorhabditis brenneri sp. n. and C. remani (Nematoda: Rhabditidae) with the stem species pattern of the Caenorhabditis elegans group. Zootaxa 1456:45 62 Szalanski, A. L., D. D. Sui, T. S. Harris, and T. O. Powers. 1997 Identification of cyst nematodes of agronomic and regulatory concern with PCR RFLP of ITS1. Journal of Nematology 29:255 267 Takeuchi, Y., N. Kanzaki, and K. Futai. 2005. A nested PCR based method for detecting the pine wood nematode, Bursaphelenchu s xylophilus from pine wood. Nematology 7:775 782 Thomas, W. K., J. T. Vida, L. M. Frisse, M. Mundo, and J. G. Baldwin. 1997. DNA sequences from formalin fixed nematodes : integrating molecular and morphological approaches to taxonomy. Journal of N ema tology 29:250 254 Tigano, M. S., R. M. D. G. Carneiro, A. Jeyaprakash, D. W. Dickson, and B. J. Adams. 2005. Phylogeny of Meloidogyne spp. based on 18S rDNA and the intergenic region of mitochondrial DNA sequences. Nematology 7:851 862 Uehara, T., T. Mizukubo, A. Kushida, and Y. Momota. 1998. Identification of Pratylenchus coffeae and P. loosi using specific primers for PCR amplification of ribosomal DNA. Nematologica 44:357 368 Umehara, A., Y. Kawakami, J. Araki, and A. Uchida. 2008. Multiplex P CR for the identification of Anisakis simplex sensu stricto, Anisakis pegreffii and other anisakid nematodes. Parasitology International 57:49 53 Umehara, A., Y. Kawakami, T. Matsui, J. Araki, and A. Uehida. 2006. Molecular identification of Anisakis s implex sensu stricto and Anisakis pegreffii (Nematoda: Anisakidae) from fish and cetacean in Japanese waters. Parasitology International 55:267 271 v an d er Knaap, E., R J. Rodriguez, and D W. Freckman, 1993. Differentiation of bacterial feeding nemato des in soil ecological studies by means of arbitrarily primed PCR Soil Biology and Biochemistry 25 : 1141 1151 Dogan, V. Wolters, T. Bongers, M. Bongers, G. Bakonyi, P. Nagy, E. M. Papatheodorou, G. P. Stamou, and S. Bostrm. 2003. Design and evaluation of nematode 18S rDNA primers for PCR and denaturing gradient gel electrophoresis (DGGE) of soil community DNA. Soil Biology and Biochemistry 35:1165 1173 Wang, S. B ., Li, Q., Liang, W. J., Jiang, Y., and Jiang, S. W. 2008. PCR DGGE analysis of nematode diversity in Cu contaminated soil. Pedosphere 18:621 627

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171 Ye, W., R. M. Giblin Davis, H. Braasch, K. Morris, and W. K. Thomas. 2007. Phylogenetic relationships am ong Bursaphelenchus species (Nematoda: Parasitaphelenchidae) inferred from nuclear ribosomal and mitochondrial DNA sequence data. Molecular Phylogenetics and Evolution 43:1185 1197 Ye, W., R. M. Giblin Davis, K. A. Davies, M. Purcell, S. J. Scheffer, G. S. Taylor, T. D. Center, K. Morris, and W. K. Thomas. 2007. Molecular phylogenetics and the evolution of host plant associations in the nematode genus Fergusobia (Tylenchida: Fergusobiinae). Molecular Phylogenetics and Evolution 45:123 141 Yergeau, E., S. Bokhorst, A. H. L. Huiskes, H. T. S. Boschker, R. Aerts, and G. A. Kowalchuk. 2006. Size and structure of bacterial, fungal and nematode communities along an Antarctic environment gradient. FEMS Microbiology Ecology 59:436 451 Zarlenga, D. S., M. B Chute, L. C. Gasbarre, and P. C. Boyd. 2001. A multiplex PCR assay for differentiating economically important gastrointestinal nematodes of cattle. Veterinary Parasitology 97:199 209 Nascimento and R. B. Gasser. 2002. SSCP based identification of members within the Pseudoterranova decipiens complex (Nematoda: Ascaridoidea: Anisakidae) using genetic markers in the internal transcribed spacers of ribosomal DNA. Parasitology 124:615 623

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172 BIOGRAPHICAL SKETCH Nicholas Sekora grew up trying to escape from hot, humid weather, but to date has had no luck He completed his B. S. in e nvironmental b iology with a c hemistry minor and concentration in b otany at the University of North Alabama in 2007 While attending UNA, Nick was active in Beta Beta Beta as both a chapter officer and a regional officer. Nick went on to co mplete his M. S. in p lant p athology at Auburn University. During his time at Auburn, Nick presented more than ten papers and post ers for his work to evaluate identification of plant parasitic nematodes using FAME analysis. Nick was invited to present his thesis work to the Entomology and Nematology Department at the University of Florida in January of 2009, which allowed him to sec ure a position in that department to begin his doctoral degree later that year with Dr. Billy Crow In May 2009, Nick assisted Dr. David Weaver of Auburn University in teaching a crop breeding class at Northwest A gricultural and F orestry University in Yan gling, Shaanxi, China His responsibilities included helping Dr. Weaver communicate with the Chinese students aiding Chinese and American students with homework assignments as well as instructing Dr. Weaver how to survive using only chopsticks to eat Currently, Nic k is working with clarifying the taxonomic nightmare of Meloidogyne and hopes to develop a quick and accurate field identification system for growers In his free time, Nick works with Dr. Tesfa Me kete conducting taxonomic studies. H e also practices applied mechanical engineering of automobiles and dabbles in atomic and light physics