HPLC in Food Analyis

HPLCfor FoodAnalysis

A Primer

© Copyright Agilent Technologies Company, 1996-2001. All rights reserved. Reproduction, adaption, or translationwithout prior written permission is prohibited, except asallowed under the copyright laws.

Printed in Germany September 01, 2001

Publication Number 5988-3294EN

www.agilent.com/chem

HPLCfor FoodAnalysis

The fundamentals of analternative approach tosolving tomorrow’smeasurementchallenges

AngelikaGratzfeld-Hüsgen andRainer Schuster

A Primer

Acknowledgements

We would like to thank ChristineMiller and John Jaskowiak fortheir contributions to this primer.Mrs. Miller is an applicationchemist with Agilent Technologiesand is responsible for the material contained in chapter 5. Mr. Jaskowiak, who wrote chapter 7,is a product manager for liquidchromatography products atAgilent Technologies.

© Copyright Agilent Technologies Company 1996-2001. All rights reserved. Reproduction,adaption, or translation without priorwritten permission is prohibited, exceptas allowed under the copyright laws.Printed in Germany, September 1, 2001.Publication Number 5988-3294EN

III

Preface Modern agriculture and food processing often involve theuse of chemicals. Some of these chemicals and their func-tions are listed below:

• Fertilizers: increase production of agricultural plants• Pesticides: protect crops against weeds and pests• Antibiotics: prevent bacteria growth in animals during

breeding• Hormones: accelerate animal growth• Colorants: increase acceptability and appeal of food• Preservatives and antioxidants: extend product life• Natural and artificial sweeteners and flavors: improve

the taste of food• Natural and synthetic vitamins: increase the nutritive

value of food• Carbohydrates: act as food binders

Such chemicals improve productivity and thus increasecompetitiveness and profit margins. However, if theamounts consumed exceed certain limits, some of thesechemicals may prove harmful to humans.

Most countries therefore have established official tolerancelevels for chemical additives, residues and contaminants infood products. These regulations must be monitored care-fully to ensure that the additives do not exceed the pre-scribed levels. To ensure compliance with these regulatoryrequirements, analytical methods have been developed todetermine the nature and concentration of chemicals infood products. Monitoring of foodstuffs includes a check of both the raw materials and the end product. To protectconsumers, public control agencies also analyze selectedfood samples.

High-performance liquid chromatography (HPLC) is usedincreasingly in the analysis of food samples to separate anddetect additives and contaminants. This method breaksdown complex mixtures into individual compounds, whichin turn are identified and quantified by suitable detectors

and data handling systems. Because separation and detec-tion occur at or slightly above ambient temperature, thismethod is ideally suited for compounds of limited thermalstability. The ability to inject large sample amounts (up to1–2 ml per injection) makes HPLC a very sensitive analysistechnique. HPLC and the nondestructive detection tech-niques also enable the collection of fractions for furtheranalysis. In addition, modern sample preparation tech-niques such as solid-phase extraction and supercritical fluidextraction (SFE) permit high-sensitivity HPLC analysis inthe ppt (parts per trillion) range. The different detectiontechniques enable not only highly sensitive but also highlyselective analysis of compounds.

IV

Figure 1Match of analyte characteristics to carrier medium

HPLC

Hydrophobic

Polarity

HPLCGC

Volatile NonvolatileVolatility

Volatile carboxylic acids

Nitriles

Nitrosamine

Essential oils

Organo- phosphorous pesticides

Glyphosate

Alcohol

Aromatic esters

PCB

Inorganic ions

Aldehydes Ketones

BHT, BHA, THBQantioxidants

PAHs

Hydrophilic

Sulfonamides

Epoxides

TMS derivative of sugars

C2/C6 hydrocarbons Fatty acidmethylester

Polymer monomers

Glycols

Aromatic amines

Anabolica

Fat soluble vitamins

Triglycerides

Natural food dyes

PG, OG, DG phenols

Amino acids

Synthetic food dyes

Fatty acids

SugarsSugaralcohols

Flavonoids

Antibiotics

Enzymes

Aflatoxins

Phospho-lipids

Its selective detectors, together with its ability to connect amass spectrometer (MS) for peak identification, make gaschromatography (GC) the most popular chromatographicmethod.

HPLC separates and detects at ambient temperatures. Forthis reason, agencies such as the U.S. Food and DrugAdministration (FDA) have adopted and recommendedHPLC for the analysis of thermally labile, nonvolatile, highlypolar compounds.

Capillary electrophoresis (CE) is a relatively new but rap-idly growing separation technique. It is not yet used in theroutine analysis of food, however. Originally CE was appliedprimarily in the analysis of biological macromolecules, butit also has been used to separate amino acids, chiral drugs,vitamins, pesticides, inorganic ions, organic acids, dyes, andsurfactants.1, 2, 3

Part 1 is a catalog of analyses of compounds in foods. Eachsection features individual chromatograms and suggestsappropriate HPLC equipment. In addition, we list chromato-graphic parameters as well as the performance characteris-tics that you can expect using the methods shown. In part 2we examine sample preparation and explain the principlesbehind the operation of each part of an HPLC system—sam-pling systems, pumps, and detectors—as well as instrumentcontrol and data evaluation stations. In the last of 11 chap-ters, we discuss the performance criteria for HPLC, whichare critical for obtaining reliable and accurate results. Part 3contains a bibliography and an index.

V

Contents

Chapter 1 Analytical examples of food additivesAcidulants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Antioxidants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Preservatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6Artificial sweeteners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8Colorants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Flavors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Vanillin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Bitter compounds: hesperidin and naringenin . . . . . . . 14

Chapter 2 Analytical examples of residues andcontaminantsResidues of chemotherapeutics and antiparasitic drugs . . 16

Tetracyclines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Fumonisins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Mycotoxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Bisphenol A diglydidyl-ether (BADGE) . . . . . . . . . . . . . . . . 24Pesticides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Carbamates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Glyphosate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Chapter 3 Analytical examples of naturalcomponentsInorganic anions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Lipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Triglycerides and hydroperoxides in oils . . . . . . . . . . . 35Triglycerides in olive oil . . . . . . . . . . . . . . . . . . . . . . . . . 37

Fatty acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Water-soluble vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . 42Fat-soluble vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Analysis of tocopherols on normal-phase column . . . . 46

Biogenic amines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Amino acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Peptides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

VI

Part OneThe HPLC Approach

Chapter 4 Separation in the liquid phaseSeparation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Reversed-phase materials . . . . . . . . . . . . . . . . . . . . . . . . 58Ion-exchange materials . . . . . . . . . . . . . . . . . . . . . . . . . . 58Size-exclusion gels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Adsorption media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

The advent of narrow-bore columns . . . . . . . . . . . . . . . . . . 59Influence of column temperature on separation . . . . . 60

Chapter 5 Sample preparationSample preparation steps . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Automation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Solids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Ultrasonic bath liquid extraction . . . . . . . . . . . . . . . . . . 63Steam distillation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Supercritical fluid extraction . . . . . . . . . . . . . . . . . . . . . 64

Liquids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Liquid-liquid extraction . . . . . . . . . . . . . . . . . . . . . . . . . 65Solid-phase extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Gel permeation chromatography . . . . . . . . . . . . . . . . . 66Guard columns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Chapter 6 Injection techniquesCharacteristics of a good sample introduction device . . . 70Manual injectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Automated injectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Autosampler with sample pretreatment capabilities . . . . 72

Derivatization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Chapter 7 Mobile phase pumps and degassersCharacteristics of a modern HPLC pump . . . . . . . . . . . . . . 76

Flow ranges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Gradient elution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Gradient formation at high pressure . . . . . . . . . . . . . . . 77Gradient formation at low pressure . . . . . . . . . . . . . . . 77

VII

Part TwoThe Equipment Basics

Pump designs for gradient operation . . . . . . . . . . . . . . . . . 78Low-pressure gradient Agilent 1100 Series pump . . . . 78High-pressure gradient Agilent 1100 Series pump . . . . 80

Degassing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Helium degassing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Vacuum degassing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Chapter 8 DetectorsAnalytical parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Limit of detection and limit of quantification . . . . . . . 87Selectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Linearity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88Qualitative information . . . . . . . . . . . . . . . . . . . . . . . . . . 88

UV detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Diode array detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Three dimensions of data . . . . . . . . . . . . . . . . . . . . . . . . 91Fluorescence detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Cut-off filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Signal/spectral mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Online spectral measurements and multi signal acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . 96Multisignal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Electrochemical detectors . . . . . . . . . . . . . . . . . . . . . . . . . . 98Electrode materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Flow cell aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Automation features . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Mass spectrometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101API interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Refractive index detectors . . . . . . . . . . . . . . . . . . . . . . . . . 104

VIII

IX

Chapter 9 Derivatization chemistriesAddition of UV-visible chromophores . . . . . . . . . . . . . . . . 108Addition of a fluorescent tag . . . . . . . . . . . . . . . . . . . . . . . 109Precolumn or postcolumn? . . . . . . . . . . . . . . . . . . . . . . . . . 109Automatic derivatization . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Chapter 10 Data collection and evaluation techniquesStrip chart recorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Integrators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Personal computers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114Local area networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117Networked data systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Chapter 11 Factors that determine performance in HPLCLimit of detection and limit of quantification . . . . . . . . . 121Accuracy and precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122Qualitative information . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

Part ThreeReferences and Index

TheHPLC Approach

A demonstrationof liquid chromatographicseparations infood analysis

Part One

Chapter 1Analytical examplesof food additives

Acidulants Sorbic acid and citric acids are commonly used asacidulants4 and/or as preservatives. Acetic, propionic,succinic, adipic, lactic, fumaric, malic, tartaric, andphosphoric acids can serve as acidulants as well. Acidulantsare used for various purposes in modern food processing.For example, citric acid adds a fresh, acidic flavor, whereassuccinic acid gives food a more salty, bitter taste. Inaddition to rendering foods more palatable and stimulating,acidulants act as

• flavoring agents to intensify certain tastes and maskundesirable aftertastes

• buffering agents to control the pH during foodprocessing and of the finished products

• preservatives to prevent growth of microorganisms

• synergists to antioxidants to prevent rancidity andbrowning

• viscosity modifiers in baked goods

• melting modifiers in cheese spreads and hard candy

• meat curing agents to enhance color and flavor

Sample preparation

Sample preparation depends strongly on the matrix to beanalyzed, but in general steam distillation and solid-phaseextraction techniques can be used.

Chromatographic conditions

High-performance liquid chromatography (HPLC) withUV-visible diode-array detection (UV-DAD) has beenapplied in the analysis of citric acid in wine and in a vodkamixed drink. Retention time and spectral data were used asidentification tools.

2

1

Water

Column compart-ment

Auto-sampler

Isocraticpump +vacuum degasser

Control anddata evaluation

Detector(VWD, DAD or refractive index)

3

Sample preparation filtration

Column 300 x 7.8 mm BioRadHPX 87-H, 9 µm

Mobile phase 0.0035 M H2SO4isocraticFlow rate 0.6 ml/min

Column compartment 65 °C

Injection volume 10 µl

Detector UV-VWDdetection wavelength192 nm or 210 nm

Conditions as above exceptMobile phase 0.007 M H2SO4isocraticDetector UV-DAD

4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.; Official MethodAOAC 986.13: quinic, malic, citric acid in cranberry juice cocktail andapple juice.

Figure 2Analysis of acidulants in white wine

Figure 3Analysis of citric acid in vodka

100mAU

00 5 10 15 20

0190

match 994

Wavelength [nm] 276

20Citric acid

Sample spectrum overlaid with library spectrum

Citric acidGlucose

Fructose

Ethanol

Time [min]

0 5 10 15 20 25

mAU

0

100

200

300

400

White wine

Standard

Oxalic acidCitric acidTartaric acidMalic acidSulfur-trioxideSuccinic acid?

?? ?

?

123456

Lactic acidGlycerolDEGAcetic acidMethanolEthanol

789101112

1

2

34

57 8 96 10 11 12

Time [min]

�

HPLC method performanceLimit of detection 100 ng injected amount,

S/N = 2 equivalent to2 ppm with 50 µlinjected volume

Repeatability ofRT over 10 runs < 0.1 %areas over 10 runs < 3 %

Antioxidants The following compounds are used as antioxidants in foodproducts:4

Natural antioxidants:

• vitamin C• vitamin E

Synthetic antioxidants:

• BHT butylated hydroxytoluene• BHA butylated hydroxyanisole• TBHQ mono-tert-butylhydroquinone• THBP 2,4,5-trihydroxybutyrophenone• PG propyl gallate• OG octyl gallate• DG dodecyl gallate• Ionox-100 4-hydroxymethyl-2,6-di(tert-butyl)phenol• NDGA nordihydroguaiaretic acid• TDPA 3,3'-thiodipropionic acid• ACP ascorbyl-palmitate

Antioxidants may be naturally present in food, or they maybe formed by processes such as smoking. Examples ofnatural antioxidants include tocopherols (vitamin E) and acsorbic acid (vitamin C). A second category of antioxidants comprises the wholly synthetic antioxidants.When these antioxidants are added to foodstuffs, theyretard the onset of rancidity by preventing the oxidativedegradation of lipids. In most countries where antioxidantsare permitted either singly or as combinations in foodstuffs,maximum levels for these compounds have been set.

Sample preparation

Sample preparation depends strongly on the matrix to beanalyzed. For samples low in fat, liquid extraction withultrasonic bath stimulation can be used. For samples withmore complex matrices, solid-phase extraction, liquid/liquidextraction, or steam distillation may be necessary.

4

1


HPLC and UV-visible diode-array detection have beenapplied in the analysis of antioxidants in chewing gum.Spectral information and retention times were used foridentification.

5

Sample preparation ultrasonic liquidextraction withacetonitrile (ACN)

Column 1 100 x 4 mm BDS, 3 µmMobile phase A = water + 0.2 ml

H2SO4, pH = 2.54B = ACN

Gradient start with 10 % Bat 3 min 60 % Bat 4 min 80 % Bat 11 min 90 % B

Flow rate 0.5 ml/minPost time 4 minColumn compartment 30 °CInjection volume 5 µlDetector UV-DAD

detection wavelength260/40 nm,reference wavelength600/100 nm

4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.;AOAC Official Method 983.15: Antioxidants in oils and fats.

5

mAU

1500

1000

500

0

2 4 6 8 10 12

2

13

4 6 87

1 Vitamin C2 PG3 THBP4 TBHQ5 BHA6 4-hydroxy7 BHT8 ACP Chewing gum extract

Standard

Time [min]

Quaternarypump +vacuum degasser


Water Acetonitrile

Column compart-ment

Auto-sampler

Diode- arraydetector

HPLC method performance

Limit of detection 0.1–2 ng (injectedamount), S/N = 2


Figure 4Analysis of antioxidants in chewing gum

�

Preservatives The following compounds are used as preservatives in foodproducts:

• benzoic acid

• sorbic acid

• propionic acid

• methyl-, ethyl-, and propylesters of p-hydroxy benzoicacid (PHB-methyl, PHB-ethyl, and PHB-propyl, respectively)4

Preservatives inhibit microbial growth in foods andbeverages. Various compound classes of preservatives areused, depending on the food product and the expectedmicroorganism. PHBs are the most common preservativesin food products. In fruit juices, in addition to sulfurdioxide, sorbic and benzoic acid are used as preservatives,either individually or as a mixture.

Sample preparation

Sample preparation depends strongly on the matrix to beanalyzed. For samples low in fat, liquid extraction withultrasonic bath stimulation can be used. For samples withmore complex matrices, solid-phase extraction, liquid/liquidextraction, or steam distillation may be necessary.

6

1



Water Acetonitrile

Column compart-ment

Auto-sampler



HPLC and UV-visible diode-array detection have beenapplied in the analysis of preservatives in white wine andsalad dressing. Spectral information and retention timeswere used for identification.

7

Sample preparation Carrez clearing andfiltration for the saladdressing. None forwhite wine.

Column 125 x 4 mmHypersil BDS, 5 µm

Mobile phase A = water + 0.2 mlH2SO4, pH = 2.3B = ACN

Gradient start with 10 % Bat 3 min 60 % Bat 4 min 80 % Bat 6 min 90 % Bat 7 min 10 % B

Flow rate 2 ml/minPost time 1 minColumn compartment 40 °CInjection volume 2 µlDetector UV-DAD

detection wavelength260/40 nm

4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.; AOACOfficial Method 979.08: Benzoate, caffeine, saccharine in carbonatedbeverages.

�

PHB-

prop

yl

Absorbance (scaled)

librarySpectral library match 99950

30

10

200 320Wavelength [nm]

sample

Standard

White wine

Salad dressing

mAU60

50

40

30

20

10

0

1 2 3 4Time [min]

Sorb

ic a

cid

PHB-

met

hyl

PHB-

ethy

l

BHA

BHT

Benz

oic

acid

Figure 5Analysis of preservatives in white wine and salad dressingHPLC method performance

Limit of detection 10 ppm, S/N = 2Repeatability ofRT over 10 runs < 0.1 %areas over 10 runs < 3 %

Artificialsweeteners

The following compounds are used as artificial sweetenersin food products:

• acesulfam

• aspartame

• saccharin4

Nowadays, low-calorie sweeteners are widely used in foodsand soft drinks. Investigations of the toxicity of thesecompounds have raised questions as to whether they aresafe to consume. As a result, their concentration in foodsand beverages is regulated through legislation in order toprevent excessive intake.

Sample preparation

Sample preparation depends strongly on the matrix to beanalyzed. For sample low in fat, liquid extraction at low pHwith ultrasonic bath stimulation can be used. For sampleswith more complex matrices, solid-phase extraction,liquid/liquid extraction, or steam distillation may benecessary.

8

1



Water Methanol

Column compart-ment

Auto-sampler

Diode- arraydete

Fluores-cencedetector

ctor


The HPLC method presented here for the analysis ofaspartame is based on automated on-column derivatizationand reversed-phase chromatography. UV spectra wereevaluated as an additional identification tool.5

9

Derivatization agent o-phthalaldehyde (OPA)mercapto-propionic acid (MPA)

Column 100 x 2.1 mmHypersil ODS, 5 µm

Mobile phase A = 0.01 mM sodiumacetateB = methanol

Gradient start with 5 % Bat 5 min 25 % Bat 10 min 35 % Bat 13 min 55 % Bat 18 min 80 % Bat 20 min 95 % B

Flow rate 0.35 ml/minPost time 5 minColumn compartment 40 °CInjection volume 1 µlInjector program for online derivatization

1. Draw 5.0 µl from vial 3 (borate buffer)2. Draw 0.0 µl from vial 0 (water)3. Draw 1.0 µl from vial 1 (OPA/MPA)4. Draw 0.0 µl from vial 0 (water)5. Draw 1.0 µl from sample6. Mix 7 µl (6 cycles)7. Inject

DetectorsUV-DAD: detection wavelength

338/20 nm orfluorescence: excitation wavelength

230 nm,emission wavelength445 nm

5. A.M. Di Pietra et al., “HPLC analysis of aspartame and saccharin in pharmaceutical and dietary formulations”; Chromatographia, 1990, 30, 215–219.4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.; OfficialMethod AOAC 979.08: Benzoate, caffeine, saccharin in soda beverages.

�

0

10

20

30

40

50

Time [min]0 2 4 6 8 10

Aspartame spectra

original

derivatizedscal

ed

250 300 350 400Wavelength [nm]

mAU

60

Aspartame

Figure 6Chromatogram and spectra of derivatized and non derivatizedaspartame


Limit of detectionfor fluorescence 200 pg (injected amount),

S/N = 2for DAD 1 ng (injected amount),

S/N = 2Repeatabilityof RT over 10 runs < 0.1 %of areas over 10 runs < 5 %

Colorants We have selected the food color E104 Quinolin yellow andE131 Patent blue as application examples. Synthetic colorsare widely used in the food processing, pharmaceutical, andchemical industries for the following purposes:4

• to mask decay

• to redye food

• to mask the effects of aging

The regulation of colors and the need for quality controlrequirements for traces of starting product and by-productshave forced the development of analytical methods. Nowa-days, HPLC methods used are based on either ion-pairingreversed-phase or ion-exchange chromatography. UV absorption is the preferred detection method. The UVabsorption maxima of colors are highly characteristic. Maxima start at approximately 400 nm for yellow colors,500 nm for red colors, and 600–700 nm for green, blue, and black colors. For the analysis of all colors at maximumsensitivity and selectivity, the light output from the detectorlamp should be high for the entire wavelength range.However, this analysis is not possible with conventionalUV-visible detectors based on a one-lamp design. Therefore,we have chosen a dual-lamp design based on one deuteriumand one tungsten lamp. This design ensures high light outputfor the entire wavelength range.

Sample preparation

Whereas turbid samples require filtration, solid samplesmust be treated with 0.1 % ammonia in a 50 % ethanol andwater mixture, followed by centrifugation. Extraction isthen performed using the so-called wool-fiber method. Afterdesorption of the colors and filtration, the solution can beinjected directly into the HPLC instrument.

10

1

Water Acetonitrile

Column compart-ment

Auto-sampler

Quaternarypump +vacuumdegasser


Diode-arraydetector


The HPLC method presented here for the analysis of dyes isbased on ion-pairing reversed-phase chromatography. UVspectra were evaluated as an additional identification tool.6

11

Sample preparation injection without further preparation

Column 125 x 3 µmHypersil BDS, 3 mm

Mobile phase A = 0.01 M NaH2PO4+0.001 M tetrabutyl-ammoniumdihydrogen-phosphate, pH = 4.2B = ACN

Gradient start with 15 %in 10 min to 40 %in 14 min to 90 %until 19 min at 90 %in 20 min to 15 % ACN

Stop time 20 minPost time 4 minFlow rate 0.8 ml/minColumn compartment 40 °CInjection volume 1 µlDetector UV-DAD

signal A: 254/50 nm (foroptimization ofseparation)signal B: 350/20 nmsignal C: 465/30 nmsignal D: 600/40 nm

4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.; OfficialMethod AOAC 981.13: Cresidine sulfonic acid in FD&C Red No. 40;Official Method AOAC 982.28: Intermediates and reaction by-products in FD&Y Yellow No. 5; Official Method AOAC 977.23: 44’ (Diazoamino)dibenzene sulfonic acid (DAADBSA) in FD&C Yellow No. 6; Official Method AOAC 980.24: Sulfanilic acid in FD&C Yellow No. 6.6. A.G. Huesgen, R.Schuster, “Sensitive analysis of synthetic colorsusing HPLC and diode-array detection at 190–950 nm”, Agilent Application Note 5964-3559E, 1995.

�

0 2 4 6 8 10 12 14

mAU

2

4

6

8

10

12

465 nm/30 nm

600 nm/40 nm

Patent blueChinolin yellow

Time [min]

Woodruff lemonade

Spectra of different colors

300 400 500 600 700 800

Norm

0

10203040

Patent blue Brilliant Amaranthred

Tartrazineyellow

Wavelength [nm]

blue

Figure 7Analysis of synthetic colors in lemonade. Overlay of spectra ofyellow, red, blue and “black” colors


Limit of detection 2 ng (injected amount)for UV-DAD S/N = 2Repeatabilityof RT over 10 runs < 0.2 %of areas over 10 runs < 3 %

Flavors The following compounds are examples of flavoring agentsused in food products:

• lupulon and humulon (hop bittering compounds)

• vanillin

• naringenin and hesperidin (bittering compounds)

Three major classes of compounds are used as flavoringagents: essential oils, bitter compounds, and pungencycompounds. Although the resolution afforded by gaschromatography (GC) for the separation of flavorcompounds remains unsurpassed, HPLC is the method ofchoice if the compound to be analyzed is low volatile orthermally unstable.

Sample preparation

Turbid samples require filtration, whereas solid samplesmust be extracted with ethanol. After filtration, the solutioncan be injected directly into the HPLC instrument.

12

1

Vanillin



Water Acetonitrile

Column compart-ment

Auto-sampler



The HPLC method presented here for the analysis of vanillinis based on reversed-phase chromatography. UV spectrawere evaluated as an additional identification tool.7

13

Sample preparation injection without further preparation


Mobile phase A = water + 0.15 mlH2SO4 (conc.), pH = 2.3B = ACN

Gradient start with 10 % Bat 3 min 40 % Bat 4 min 40 % Bat 6 min 80 % Bat 7 min 90 % B

Flow rate 0.8 ml/minPost time 3 minColumn compartment 30 °CInjection volume 5 µlDetector UV-DAD


Conditions as above, exceptColumn 100 x 2.1 mm

Hypersil ODS, 5 µmMobile phase A = water + 5 mM

NaH2PO4B = methanol

Gradient at 10 min 70 % BFlow rate 0.4 ml/min

7. Herrmann, A, et al.;,“Rapid control of vanilla-containing productsusing HPLC”; J. Chromatogr., 1982, 246, 313–316.�

Time [min]0 1 2 3 4 5 6 7

Norm.

0

100

200

300

400

Vanillin alcohol

4-hydroxy benzoic acidVanillin

4-hydroxybenzaldehyde

Ethyl-vanillin

Coumarin

Standard

Vanillin extract

Figure 8Determination of the quality of vanillin extract

Match 991

Vanillin

Vanillin

CognacStandard

60

50

40

30

20

10

mAU

00 2 4 6 8 10

SyringaaldehydeGallic acid

Salicyl-aldehyde

50403020100

Time [min]

217 400Wavelength [nm]

Figure 9Analysis of vanillin in cognac. Identification of vanillin throughspectra comparison


Limit of detection 0.2–5 ng (injectedamount) S/N = 2

Repeatabilityof RT over 10 runs < 0.2 %of areas over 10 runs < 1 %

Bitter compounds:hesperidin and

naringenin

Sample preparation for bitter compounds in orange juice8

The samples were prepared according to Carrez 1 and 2.This method uses potassium ferrocyanide and zinc sulfatefor protein precipitation.


The HPLC method presented here for the analysis ofhesperidin and naringenin is based on reversed-phasechromatography. UV spectra were evaluated as anadditional identification tool.

14

1

0.5 1 1.5 2 2.5

mAU

-5

0

5

10

15

20

Orange juice

StandardHesperidin

Time [min]

Naringenin

Figure 10Analysis of bitter compounds in orange juice

8. Official Methods of Analysis; Horwitz, W., Ed.; 14th ed.; AOAC: Arlington, VA, 1984; secs 12.018–12.021.�

Sample preparation The orange juice wasprepared according toCarrez 1 and 2.


Mobile phase A = water + 0.15 ml/lH2SO4 (conc.), pH = 2.4B = ACN

Gradient start with 20 % Bat 3 min 20 % Bat 5 min 90 % Bat 6 min 20 % B

Flow rate 2 ml/minPost time 1 minColumn compartment 40 °CInjection volume 1 µlDetector UV-DAD



Limit of detection 1 ng (injected amount),for DAD S/N = 2Repeatabilityof RT over 10 runs < 0.2 %of areas over 10 runs < 1 %.

Chapter 2Analytical examplesof residues and contaminants

Residues ofchemotherapeuticsand antiparasiticdrugs

In addition to several other drugs, nitrofurans andsulfonamides such as sulfapyridine, N-acetyl metabolite,ethopabat, chloramphenicol, meticlorpindol, metronidazol,ipronidazol, furazolidone, and nicarbazin are frequently fedto domestic cattle.

Modern intensive animal breeding demands permanentsuppression of diseases caused by viruses, bacteria,protozoa, and/or fungi. A number of chemotherapeutics areavailable for the prevention and control of these diseases.After application, residues of these drugs can be found infoods of animal origin such as milk, eggs, and meat. Thesechemotherapeutics can cause resistancy of bacteria.Because of the toxic nature of chemotherapeutics, forexample, choramphenical, government agencies in manycountries, including the United States, Germany, and Japan,have set tolerance levels for residues of these drugs.

Simple and reliable analysis methods are necessary in orderto detect and quantify residues of chemotherapeutic andantiparasitic drugs in food products. Malisch et al. havedeveloped an HPLC method to determine 11 of thesecompounds.9,10 The internal standard (ISTD) comprisesbenzothiazuron and pyrazon.

Sample preparation

After homogenization or mincing and pH adjustment, the samples were extracted using liquid/liquid extractionfollowed by degreasing, purification, and concentration.

16

2



Water Acetonitrile

Column compart-ment

Auto-sampler


17

Sample preparation Sample preparation was done according toreference9

Column 250 x 4.6 mmSpherisorb ODS-2, 5 µm

Mobile phase A = sodium acetatebuffer, 0.02 M, pH = 4.8B = ACN/water (60:40)

Gradient start with 8 % Bat 5 min 8 % Bat 7 min 20 % Bat 14 min 23 % Bat 16 min 33 % Bat 19 min 40 % Bat 21 min 50 % Bat 26 min 60 % Bat 30 min 80 % Bat 33 min 90 % Bat 43 min 90 % Bat 55 min 8 % B

Flow rate 1.5 ml/minInjection volume 20 µlDetector UV-DAD

detection wavelengths275/80 nm, 315/80 nm,and 360/80 nm,reference wavelength500/100 nm

9. H. Malisch, et al.,“Determination of residues of chemotherapeuticand antiparasitic drugs in food stuffs of anomaly origin with HPLC andUV-Vis diode-array detection”, J. Liq. Chromatogr., 1988, 11 (13),2801–2827.14.10. EC Guideline 86/428 EWG 1985.


The HPLC method presented here for the analysis ofresidues of drugs in eggs, milk, and meat is based onreversed-phase chromatography and multisignal UV-visiblediode-array detection (UV-DAD). UV spectra wereevaluated as an additional identification tool.

Figure 11Analysis of residues in an egg sample. Identification throughspectra comparison

HPLC method performanceLimit of detection 0.001–0.05 mg/kgRepeatabilityof RT over 10 runs < 0.12 %of areas over 10 runs < 1.5 %

�

80

40

0250 300 350 400

Pyrazont = 9 minmatch 998

R

offset

0

10

20

10 20 30

Egg sample

Standard

Time [min]

12

3

4

5

6,7

8

9

10

11

mAU

1 metronidazol2 meticlorpindol3 sulfapyridine4 furazolidone

5 pyrazon6 ipronidazol7 chloramphenicol8 N-acetyl metabolite of 3

9 3-ethopabat10 benzothiazuron11 nicarbazin

80

40

0250 300 350 400

Sulfapyridinet = 12.2 minmatch 997R

offset

Wavelength [nm] Wavelength [nm]

Scal

ed

Scal

ed

Sample preparation 1 g sample was mixedwith citric acid (100 mg).➔ add 1 ml nitric acid(30 %) or 0.1 m oxalicacid➔ add 4 ml methanol5 min in the ultrasonicbath➔ add water up to 10 mltotal volume➔ centrifuge➔ inject

Column 100 × 4 mmHypersil BDS, 3 µm

Mobile phase A = water, pH = 2.1 withsulfuric acidB = ACN

Gradient start with 15 % Bat 10 min 60 % B

Flow rate: 0.5 ml/minColumn compartment 25 ºCDetector UV-DAD

detection wavelength355 nm/20 nm, reference wavelength 600/100 nm

Tetracyclines Tetracyclines are used worldwide as oral or parenteralmedication in the form of additives in animal feed. Infood-producing animals, these drugs exhibit a high degreeof activity toward a wide range of bacteria.9, 11

Sample preparation

After homogenization or mincing and addition of mineralacids to dissociate tetracyclines from proteins, the sampleswere extracted using liquid/liquid extraction followed bydegreasing and/or deproteinization, purification, andconcentration.12


The HPLC method presented here for the analysis of meat isbased on reversed-phase chromatography and UV-visiblediode-array detection. UV spectra were evaluated as anadditional identification tool.

18


Limit of detectionfor UV-DAD 100 ppbRepeatabilityof RT over 10 runs < 0.2 %of areas over 10 runs < 2 %

250 400

Pork muscle

Blank

Oxytetracycline 1.8 ng

370 ppb

6

5

4

3

2

1

0

2 4Time [min]

6 8

Oxytetracycline3

2

1 Library match 980

Wavelength [nm]

Figure 12Trace analysis of tetracycline residues in meat. Identication ofoxytetracycline through spectra comparison

9. H. Malisch et al., “Determination of residues of chemotherapeutic andantiparasitic drugs in food stuffs of anomaly origin with HPLC and UV-Visdiode-array detection” J. Liq. Chromatogr., 1988, 11 (13), 2801–2827.14.11. M.H. Thomas, J. Assoc. Off. Anal.; 1989 , 72 (4) 564.12. Farrington et. al., “Food Additives and Contaminants, 1991, Vol. 8, No. 1, 55-64”.

�

2

19

Fumonisins Fumonisins are characterized by a 19-carbon aminopoly-hydroxyalkyl chain which is diesterified with propane-1,2,3-tricarboxylic acid. Analogues B 1-3 in figure 13 show adifference only in the number and position of the hydroxylgroups present on the molecule.

Fragmentation experiments using collision induced disso-ciation (CID) show no difference between fumonisins B2and B3. Consequently, it was necessary to separate thesecompounds chromatographically for quantitative analysis.However, in crude corn extracts the CID-fragment ionsprovide important confirmatory information. In order toobtain spectra of the fragment ions as well as the pseudo-molecular ions in a single scan, operating at maximumsensitivity, the fragmentor voltage was set to 230 V whilescanning from 150 amu to 680 amu and then to 100 Vwhen scanning from 690 amu to 800 amu.

Sample preparation

Extraction according to § 35, LMBG.13


The Agilent 1100 Series LC/MSD proved to be capable of detecting and quantifying fumonisins at 250 picogramsper component regardless of their chemical structure andwithout the need for derivatization during the samplepreparation procedure. The Agilent 1100 Series LC/MSDprovided optimum sensitivity in the selected ion monitor-ing mode. Even when operating in scan mode (150 amu to800 amu), the Agilent 1100 Series LC/MSD still providedsensitivity more than a factor of 10 better than reportedfor a fluorescence detector.

LC/MS conditionsColum Zorbax Eclipse

XDB-C18, 2.1 mm x 150 mm, 5 µm

Mobile phase A 5 mM ammonium acetate pH3

Mobile phase B acetonitrileGradient 0 min 33% B

8 min 60% B9 min 33% B

Flow rate 250 µl/minInjection vollume 5 µlColumn compartment 40°C

Ionization mode API-ES positive or APCI negative

Nebulizer pressure 30 psigDryng gas temp. 350°CDrying gas flow 6 l/minVcap. 4000 voltsFragmentor 100 voltsScan range m/z 120 –820

20

200000

100000

0200 300 400 500 600 700

FB1

334.

4 352.

437

0.5

392.

541

1.6

722.

572

3.5

0

200000

100000

m/z

200 300 400 500 600 700 m/z

200 300 400 500 600 700 m/z

163.

117

0.1

220.

1

336.

235

4.4

376.

6

750.

576

9.5

728.

5

706.

5 707.

570

4.7

250000

150000

50000

FB3

FB2

336.

435

4.5

512.

0

553.

5

706.

570

7.3

708.

7

728.

5

728.

5

Figure 13Mass spectra of Fumonisins B 1,2,3 when the fragmentor is ramped from 230 to 100V

1 2 3 4 5 6 7 8 Time [min]

9.86

2

6.24

1

7.67

5

MS EIC m/z 723

3.23

7

FB1

FB1MS EIC m/z 335

3.22

8

MS EIC m/z 707FB3 FB2

6.24

8

7.68

3

FB3 FBMS EIC m/z 337

2

1000006000020000

50000

150000

250000

100000200000300000

2000060000

100000

Figure 14Identification of different Fumonisin species in corn extract by retentiontime with further confirmation through fragment ion

2

13. Lebensmittel- und Bedarfsgegenständegesetz, Paragraph 35, Germany.�

21

Mycotoxins The following mycotoxins have been analyzed: aflatoxinsG2, G1, B2, B1, M2, and M1; ochratoxin A; zearalenone; andpatuline.

Mycotoxins are highly toxic compounds produced by fungi.They can contaminate food products when storageconditions are favorable to fungal growth. These toxins areof relatively high molecular weight and contain one or moreoxygenated alicyclic rings. The analysis of individualmycotoxins and their metabolites is difficult because morethan 100 such compounds are known, and any individualtoxin is likely to be present in minute concentration in ahighly complex organic matrix. Most mycotoxins areassayed with thin-layer chromatography (TLC). However,the higher separation power and shorter analysis time ofHPLC has resulted in the increased use of this method. The required detection in the low parts per billion (ppb)range 4,13 can be performed using suitable sample enrichment and sensitive detection.

Sample preparation

Samples were prepared according to official methods.13

Different sample preparation and HPLC separationconditions must be used for the different classes ofcompounds. The table on the next page gives an overviewof the conditions for the analysis of mycotoxins infoodstuffs.


The HPLC method presented here for the analysis of myc-otoxins in nuts, spices, animal feed, milk, cereals, flour, figs,and apples is based on reversed-phase chromatography,multisignal UV-visible diode-array detection, and fluores-cence detection. UV spectra were evaluated as an additionalidentification tool.

Column class Matrix Sample preparation Chromatographic conditions

Aflatoxins nuts, ➯ extraction Hypersil ODS, 100 × 2.1 mm id, 3-µmG2 , G1 , B2 , B1 , spices, according to Para. particlesM2 , M1 animal 35, LMBG*8,12 water/methanol/ACN (63:26:11) as

feed, milk, isocratic mixture**dairy flow rate: 0.3 ml/min at 25 °Cproducts DAD: 365/20 nm

Fluorescence detector (FLD):excitation wavelength 365 nm,emission wavelength 455 nm

Ochratoxin A cereals, ➯ extraction Lichrospher 100 RP18, 125 × 4 mmflour, figs according to id, 5-µm particles

Para. 35, LMBG water with 2 % acetic acid/ACN

➯ acidify with HCl (1:1)*

➯ extract with flow rate: 1 ml/min at 40 °C

toluene FLD: excitation wavelength 347 nm,

➯ SiO2 cleanup eluteemission wavelength 480 nm

toluene/aceticacid (9:1)

Zearalenone cereals ➯ extract with Hypersil ODS, 100 × 2.1 mm id, 3 µmtoluene particles

➯ Sep-pak cleanup water/methanol/ACN (5:4:1)

➯ elute toluene/ace- isocratic mixture*

tone (95:5) flow rate: 0.45 ml/min at 45 °C

➯ AOAC 985.18:4 DAD: 236/20 nm

α-zearalenol and FLD: excitation wavelength 236 nm,zearalenone in emission wavelength 464 nmcorn

Patuline apple ➯ cleanup on Extrelut Superspher RP18, 125 × 4 mm id,products

➯ silica gel cleanup

➯ elute toluene/ethylacetate (3:1)

22

2

* Lebensmittel- undBedarfsgegenständegesetz, Germany

** 100 % B is recommended for cleaning the column

4-µm particleswater 5 %–95 % ACNflow rate: 0.6 ml/min at 40 °CDAD: 270/20 nm

or

Lichrospher diol, 125 × 4 mm id,5-µm particleshexane/isopropanol (95:5) asisocratic mixtureflow rate: 0.6 ml/min at 30 °CDAD: 270/20 nm

23

13. Lebensmittel- und Bedarfsgegenständegesetz, Paragraph 35, Germany.4. Official Methods of Analysis, Food Compositions; Additives, NaturalContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2.; AOAC OfficialMethod 980.20: aflatoxins in cotton seed products; AOAC Official Method986.16: Aflatoxins M1 , M2 in fluid milk; AOAC Official Method 985.18:α-zearalenol.

�

DAD: 365 nm

20

15

10

5

02 Time [min]

4 6 8 10

FLD:

mAU

365 nmem455 nmex

1

λ

λ

M2 5

ng

G 1 5

ng

B 1 5

ng

Figure 15Analysis of aflatoxins with UV and fluorescence detection

FLD

DAD1

2

3

4

5

mAU

Pistachio nut

2 4 6Time [min]

8

Figure 16Analysis of aflatoxins in pistachio nuts with UV and fluorescence detection


Limit of detection 1–5 µg/kgRepeatabilityof RT over 10 runs < 0.12 %of areas over 10 runs < 1.5 %Linearityof UV-visible DAD 1–500 ngof fluorescence 30 pg to 2 ng

Water Methanol

Column compart-ment

Auto-sampler




Diode-arraydetector

Bisphenol A diglycidyl-ether(BADGE)

Bisphenol A diglycidyl-ether (BADGE) is present in thethree most common coatings (epoxy lacquer, organosollacquer and polyester lacquer) used to protect the insidesurfaces of cans used for food packaging. In canned foodscontaining a high proportion of fat, BADGE tends to migrateinto the fatty phase where it remains stable, whereas inwater it is hydrolyzed.

BADGE was originally determined to be mutagenic duringin vitro tests but a later re-assessment, using in vivo tests,led to a different conclusion. While further tests are beingperformed, a maximum concentration of 1 mg BADGE perkg of food has been agreed.

Sample preparation

Extracted with water/alcohol 50/50 or n-heptane at refluxtemperature for six hours.


A fast separation was developed by using the enhancedspecificity provided by the Agilent 1100 Series LC/MSD inCID (collision induced dissociation) mode allowing thedetection of BADGE via the molecular ion combined withconfirmation using the most abundant fragment ion.

24

2

25

LC/MS conditionsColum Zorbax Eclipse

XDB-C8, 2.1 mm x 50 mm, 5 µ

Mobile phase A 5 mM ammonium acetate in water, pH3

Mobile phase B acetonitrileGradient 0 min 25% B

5 min 50 % BFlow rate 300 µl/minInjection volume 1 µlColumn compartment 40 °CDetector UV-DAD

210 nm/6 nm, ref. 360/60 nm254 nm/6 nm,ref. 360/60 nm

Ionization mode API-ES positiveNebulizer pressure 50 psigDryng gas temp. 350 °CVcap. 3500 voltsFragmentor 70 voltsScan range m/z 250 –400Scan speed 2 s/scan

7.99

28.

341

12.1

12 12.4

2913

.773

14.0

9515

.059

15.9

18

20.7

12

0 2.5 5 7.5 1510 12.5 2017.5

UV-Vis 230 nm

MS EIC m/z 358

-12

-8-6

-10

-4-202

mAU

300000

500000

100000

Time [min]

Figure 17Extract from tuna 0.2 ppm, 1 µl injected

-10

5

-5

10

0

mAU

0.57

40.

769

5.92

9

10.1

85 10.4

94

10.8

15

14.3

6713.4

6113

.874

13.3

32

15.3

43

15.9

49

15.1

00

16.3

2916

.509 17

.30216

.861

17.9

22

UV-Vis 230 nm

10.8

70

MS EIC m/z 358

300000

500000

100000

0 2.5 5 7.5 1510 12.5 2017.5Time [min]

Figure 18Extract from sardine 20 ppm, 1 µl injected

Pesticides The following compound classes of pesticides have beenanalyzed: triazines, phenylurea-herbicides, methabenzthiaz-uron, diquat, paraquat, and mercaptobenzothiazol.Carbamates and glyphosate also have been analyzed butwith different equipment. In most countries, growing concern about the residues of pesticides in food products isevident. Therefore, regulations limiting the concentrationof pesticides in foodstuffs have been introduced to protectconsumers from contaminated food products. Severalmethods are used to control these limits. HPLC is recom-mended for the analysis of low volatile compounds and forcompounds that are unstable when heated.

Sample preparation

Sample preparation and enrichment depend strongly on thematrix. Drinking water samples, for example, must beextracted using solid-phase extraction, whereas vegetablesare extracted with liquid/liquid extraction after homo-genization, followed by additional cleaning and sampleenrichment.

26

2

14. Specht, W. “Organochlor- und Organophosphor-Verbindungen sowiestickstoffhaltige sowie andere Pflanzenschutzmittel”, DFG-Methoden-sammlung, 1982, 19.



Water Acetronitrile

Column compart-ment

Auto-sampler


�


The HPLC method presented here was used for the analysisof pesticides in salad samples and spices.

27

Sample preparation Salad was homogenizedand then extracted withliquid/liquid extraction.The extract was cleanedwith gel permeationchromatography usingcyclohexane/ethyl ace-tate. Spices were pre-pared according toSpecht14 with gel per-meation chromatography.

Column 100 × 3 mmHypersil BDS, 3 µm

Mobile phase water/ACN (95:5)Gradient at 10 min 25 % ACN

at 26 min 42 % ACNat 34 min 60 % ACN

Flushing time 10 min at 100 % ACNPost time 6 minFlow rate 0.5 ml/minOven temperature 42 °CInjection volume 3–10 µlDetector UV-DAD

detection wavelengths214/15 nm, 230/20 nm,and 245/20 nmreference wavelength400/80 nm

Time [min]10 15 20 25 30 35 40

mAU

0

40

80

120

Carbendazim*

Vinclozolin

Folpet

3 differentsalad samples


Limit of detection 0.01 µg/lRepeatabilityof RT over 10 runs < 0.2 %of areas over 10 runs < 1 %

Figure 19Analysis of pesticide residues in three different salad samples* Carbendazim has a low recovery rate of only approximately 40 %

10 20 30 40 50

mAU

0

20

40

60

80

100

Paprika (Spain)

Paprika (Turkey)

Time [min]

Nitro compounds

Procymidon

Vinclozolin

Chlorpyripho-ethyl

Figure 20Analysis of pesticide residues in two paprika samples

Sample preparation noneColumn 250 x 4 mm C18 phase

from Pickering, 5 µmMobile phase water/methanol

(MeOH, 88:12)Gradient at 2 min 12 % MeOH

at 42 min 66 % MeOHat 46 min 66 % MeOHat 46.1 min 100 % MeOHat 49 min 100 % MeOH

Flow rate 0.8 ml/minColumn compartment 37 °CInjection volume 10 µl standardFluorescence detector

Excitation wavelength: 230 nm or 330 nmEmission wavelength: 425 nmPhotomultiplier gain: 12Response time: 4 s

Derivatization reagent pumpflow rate for hydrolization agent:0.3 ml/min (NaOH)flow rate for derivatization agent:0.3 ml/min (OPA)

28

15. ”A new approach to lower limits of detection and easy spectralanalysis” Agilent Primer 5968-9346E, 2000�


Limit of detection 100 ppt, S/N = 2Repeatabilityof RT over 10 runs < 0.1 %of areas over 10 runs < 0.5–5 %

2

Carbamates Chromatographic conditions

The HPLC method presented here was used for the directanalysis of carbamates in water with postcolumnderivatization.15 Fruits and vegetables must be extracted atneutral pH with water prior to HPLC analysis.

10 15 20 25 30 35 40 45

%F

3.5

4

4.5

5

5.5

1 2

34

6

7 9 14

15

17

19

20

Sample A

10 15 20 25 30 35 40 453.5

4

4.5

5

5.5

58

10 11

12 1316

18

21

22

23

Sample B

%FTime [min]

Time [min]

Sample B5 oxamyl8 thiofanox sulfoxide10 thiofanox sulfone11 3-hydroxycarbofuran12 methiocarb sulfoxide13 methiocarb sulfone

Sample A1 butocarboxim sulfoxide2 aldicarb sulfoxide3 butoncarboxim sulfone4 aldicarb sulfone6 methomyl7 ethiofencarb sulfoxide

9 ethiofencarb sulfone14 butocarboxim15 aldicarb17 propoxur19 carbaryl20 ethiofencarb

16 3-ketocarbofuran18 carbofuran21 1-naphthol22 thiofanox 23 methiocarb

Figure 21Analysis of two different carbamate standards



Water Methanol

Pickeringpost-columnderivatiza-tion system

Auto-sampler



The HPLC method presented here was used for the directanalysis of glyphosate in water with postcolumnderivatization.16

29

Glyphosate

16. R. Schuster, “A comparison of pre- and post-column sample treatment for the analysis of glyphosate”, Agilent Application Note5091-3621E , 1992.

�

Sample preparation noneColumn 150 x 4 mm cation

exchange, K + form fromPickering, 8 µm

Mobile phase A = 5 mM KH2PO4 ,pH = 2.0B = 5 mM KOH

Flow rate 0.4 ml/minGradient at 15 min 0 % B

at 17 min 100 % BColumn compartment 55 °CInjection volume 50 µl standardFluorescence detector

Excitation wavelength: 230 nm or 330 nmEmission wavelength: 425 nmPhotomultiplier gain: 12Response time: 4 s

Derivatization reagent pumpflow rate for hydrolization agent:0.3 ml/min(OCl*)flow rate for derivatization agent:0.3 ml/min (OPA)


Limit of detection 500 pptRepeatabilityof RT over 10 runs < 0.8 %of areas over 10 runs < 2.2 %

7.5

7

6.5

6

5.5

5

2.5 5 7.5 10 12.5 15 17.5 20Time [min]

Norm.Glyphosate

AMPA

Figure 22Analysis of glyphosate standard



Water KOH

Auto-sampler


Pickeringpost-columnderivatiza-tion system

30

Chapter 3Analytical examples of naturalcomponents

Inorganic anions Anions containing halogen, nitrogen, and sulfur are used asadditives in food industries. For example, nitrites act as preservatives in smoked sausage. Nowadays, dedicatedinstrumentation such as special columns and electro-conductivity detectors are used in the analysis of inorganicanions. Because specialized equipment has a very limitedapplication range, a method was developed for analyzinganionsusing reversed-phase chromatography and indirectUV detection. Another, more selective and sensitiveapproach for the analysis of selected anions is electro-chemical detection.

Sample preparation

Excepting filtration, sample preparation normally is unnecessary if the sample is aqueous. Other matrices can be extracted with hot water, followed by filtration.

32

3

Auto- sampler



Water/ACN

Columncompart-ment

Auto-sampler

Variablewave-lengthdetector

33

Sample preparation filtrationColumn HP-IC (modifiers for the

mobile phase areincluded)

Mobile phase water/acetonitrile (ACN)(86:14), adjusted topH = 8.6 withcarbonate-free NaOH

Flow rate 1.5 ml/minOven temperature 40 ºCInjection volume 25 µlDetector UV-VWD

detection wavelength266 nm


The HPLC method presented here was used for the analysisof anions in drinking water.

Figure 23Analysis of anions in drinking water with indirect UV-detectionHPLC method performance

Limit of detectionfor UV-VWD 0.1–1 ppb with S/N = 2

and 25 µl injectedvolume


Time [min]2 4 6 8 10

mAU

-20

0

20

40

60

80

100

Standard

Drinking water

F

Cl

BrH PO

Cl = 15 ppm

NO = 0.9 ppm3

NO2 4

SO = 40 ppm4

SO4NO3

HCO3-

- - -

- - - 2

2

-

-- 2

- 2

Sample preparation Table salt was dissolvedin water.

Column 200 x 4 mmSperisorb ODS2, 5 µm

Mobile phase water with 5.2 g/lK2HPO4 + 3 g/ltetrabutylammoniumdi-hydrogenphosphat/ACN(85:15)

Flow rate 1 ml/minOven temperature ambient 24 ºCInjection volume 0.1 µlDetector electrochemical (ECD)

Electrode: glassy carbon,Working potential: 1 VOperation mode: amperometry

Chromographic conditions for electrochemical detection

The HPLC method presented here was used for the analysis of iodide in table salt.17

34

HPLC method performanceLimit of detectionfor ECD 40 µg/lRepeatability ofRT over 10 runs < 0.1 %areas over 10 runs 3 %Linearity min 50 pg to 150 ng

.

100

120

140

160

180

Table salt

2 4 6 8 10 12 14

I -

Time [min]

Standard

mV

I -

Figure 24Analysis of iodide in table salt

17. A.G. Huesgen, R. Schuster, ”Analysis of selected anions with HPLCand electrochemical detection”, Agilent Application Note 5091-1815E, 1991.�

3

Auto- sampler



Water

Columncompart-ment

Auto-sampler

Electro-chemicaldetector

35

Lipids

Triglycerides andhydroperoxides in oils

Both saturated and unsaturated triglycerides have beenanalyzed. Fats and oils are complex mixtures oftriglycerides, sterols, and vitamins. The composition oftriglycerides is of great interest in food processing anddietary control. Owing to the low stability of triglyceridescontaining unsaturated fatty acids, reactions with light andoxygen form hydroperoxides, which strongly influence thetaste and quality of fats and oils. Adulteration with foreignfats and the use of triglycerides that have been modified bya hardening process also can be detected throughtriglyceride analysis.

The HPLC method presented here was used to analyzetriglycerides, hydroperoxides, sterols, and vitamins withUV-visible diode-array detection (UV-DAD). Spectra wereevaluated in order to trace hydroperoxides and todifferentiate saturated from unsaturated triglycerides.Unsaturated triglycerides in olive oil have a very distinctivepattern. Other fats and oils are also complex mixtures oftriglycerides but exhibit an entirely different pattern.Adulteration with foreign fats and the use of refinedtriglycerides in olive oil also can be detected throughtriglyceride analysis.

Sample preparation

Triglycerides can be extracted from homogenized sampleswith petrol ether. Fats and oils can be dissolved intetrahydrofuran.17



Water Acetonitrile

Column compart-ment

Auto-sampler


Sample preparation Samples were dissolvedin tetrahydrofuran (THF).

Column 200 x 2.1 mmHypersil MOS, 5 µm

Mobile phase A = waterB = ACN/methyl-tert.butylether (9:1)

Gradient at 0 min 87 % Bat 25 min 100 % B

Post time 4 minFlow rate 0.8 ml/minColumn compartment 60 ºCInjection volume 1 µl standardUV absorbance

200 nm and 215 nm to detect triglycerides240 nm to detect hydroperoxides280 nm to detect tocopherols and decom-posed triglycerides (fatty acids with threeconjugated double bonds)

36

Time [min]

140

120

100

80

60

40

20

0

5 10 15 20 25

215 nm

240 nm

H

LLL

Abs

orba

nce

[sca

led]

00L

000

S00

PLL

ydroperoxides

*

**

*

*

**

Figure 25Triglyceride pattern of aged sunflower oil. The increased response at 240 nm indicates hydroperoxides

Good quality Poor quality

mAU20

15

10

5

0

13.0 23.0Time [min]

20

15

10

5

0

13.0 23.0Time [min]

215 nm

280 nm

215 nm

280 nm

mAUOlive oil

LLL

LL0

00L

000

S00

LL0

LL0

00L

000

S00

Figure 26Analysis of olive oil. The response at 280 nm indicates a conjugateddouble bond and therefore poor oil quality

3

HPLC method performanceLimit of detection

for saturated triglycerides > 10 µgfor unsaturated triglycerides

fatty acids with 1 double bond >150 ngfatty acids with 2 double bonds > 25 ngfatty acids with 3 double bonds < 10 ng


37

Triglycerides in olive oil Unsaturated triglycerides in olive oil have very characteris-tic patterns. Other fats and oils are also complex mixturesof triglycerides but with different patterns.

Sample preparation information

Triglycerides can be extracted from homogenized sampleswith petrol ether. Fats and oils can be dissolved intetrahydrofurane.


The presented HPLC method was used to analyze theunsaturated triglycerides, LnLnLn, LLL, and OOO.18

Sample preparation Samples were dissolvedin tetrahydrofurane.

Column 200 × 2.1 mmHypersil MOS, 5 µm

Mobile phase acetone/ACN (30:70)Flow rate 0.5 ml/minColumn compartment 30 ºCInjection volume 2 µlDetector refractive index

HPLC method performanceLimit of detectionfor ECD 50 µg/l with S/N = 2Repeatability ofRT over 10 runs < 0.3 %areas over 10 runs 5 %

2 4 6 8

mV

40

60

80

100

120

140

160

180

200

StandardOlive oil

Rape oil

Time [min]

LnLn

Ln

LLL

000

Figure 27Analysis of the triglyceride pattern of olive and rape oil

18. “Determination of triglycerides in vegetable oils”, EC Regulation No. L248, 28ff.�

Auto- sampler



Acetronitrile

Columncompart-ment

Auto-sampler

Refractiveindexdetector

Saturated and unsaturated fatty acids from C4 through C22have been analyzed. Fatty acids are the primary compo-nents of oils and fats and form a distinctive pattern in eachof these compounds. For example, butter and margarinescan be differentiated by the percentage of butyric acid inthe triglycerides. To determine the fatty acid pattern of a fator oil, free fatty acids first are obtained through hydrolysis.Derivatization is then performed to introduce a chro-mophore, which enables analysis of the fatty acids usingHPLC and UV-visible detection.

Sample preparation

The triglycerides were hydrolyzed using hot methanol andKOH, followed by derivatization.


The HPLC method presented here was used in the analysisof the fatty acid pattern of dietary fat. The method involveshydrolysis with hot KOH/methanol and online derivatizationwith bromophenacyl bromide.

38

3

Fatty acids



Water Acetonitrile

Column compart-ment

Auto-sampler

Variablewavelengthdetector

39

C18-

3

C18-

2C1

8-1

C14

C16

C18

C20

C22

1400

1000

600

200

mAU

15 20 25 30Time [min]

Standard

Dietary fat

Standard

Figure 28Analysis of a dietary fat triglyceride pattern. Overlay of one sampleand two standard chromatograms

Time [min]20 22 24 26 28 30 32

Norm

0

10

20

30

40

VWDDAD

C10,

9.9

ng

C12,

4.0

ng

C14,

3.0

ng

C16,

6.7

ng

C18,

4.5

ng

C20,

5.2

ng

C22,

3.3

ng

Figure 29Trace analysis of triglycerides with a diode-array and a variablewavelength detector in series

HPLC method performanceLimit of detection 200 pg injected amount,

S/N = 2Repeatability ofRT over 10 runs < 0.1 %areas over 10 runs 5 %

Sample preparation0.215 g fat was hydrolyzed with 500 µlMEOH/ KOH at 80 ºC for 40 min in athermomixer. After cooling 1.5 ml ACN/THF(1:1) was added, and the mixture was shakenfor 5 min. The mixture was then filteredthrough a 0.45-µm Minisart RNML fromSatorius.

Column 200 x 2.1 mm, MOS, 5 µmMobile phase A = water (70 %)

B = (ACN + 1 % THF) (30 %)

Gradient at 5 min 30 % Bat 15 min 70 % Bat 17 min 70 % Bat 25 min 98 % B

Flow rate 0.3 ml/minColumn compartment 50 °CDetector variable wavelength,

258 nmDerivatization 60 mg/ml bromophenacyl

bromide was dissolvedin ACN.

Injector program for online derivatization1. Draw 2.0 µl from vial 2 (ACN)2. Draw 1.0 µl from air3. Draw 1.0 µl from vial 3 (derivatization

agent)4. Draw 0.0 µl from vial 4 (wash bottle)

(ACN/THF, 50:50)5. Draw 1.0 µl from sample6. Draw 0.0 µl from vial 4 (wash bottle)7. Draw 1.0 µl from vial 3 (derivatization

agent)8. Draw 0.0 µl from vial 4 (wash bottle)9. Draw 1.0 µl from vial 5 (acetonitrile +

5 % TEA)10. Draw 0.0 µl from vial 4 (wash bottle)11. Mix 9 µl in air, 30 µl/min speed, 10 times12. Wait 2.0 min13. Inject

Carbohydrates The following carbohydrates have been analyzed: glucose,galactose, raffinose, fructose, mannitol, sorbitol, lactose,maltose, cellobiose, and sucrose. Food carbohydrates arecharacterized by a wide range of chemical reactivity andmolecular size. Because carbohydrates do not possesschromophores or fluorophores, they cannot be detectedwith UV-visible or fluorescence techniques. Nowadays,however, refractive index detection can be used to detectconcentrations in the low parts per million (ppm) range andabove, whereas electrochemical detection is used in theanalysis of sugars in the low parts per billion (ppb) range.

Sample preparation

Degassed drinks can be injected directly after filtration.More complex samples require more extensive treatment,such as fat extraction and deproteination. Sample cleanupto remove less polar impurities can be done throughsolid-phase extraction on C18 columns.

40

3

Auto- sampler



Water

Columncompart-ment

Auto-sampler

Refractiveindexdetector

4. Official Methods of Analysis, Food Compositions; Additives, NatuaralContaminants, 15th ed; AOAC: Arlington, VA, 1990, Vol. 2; AOAC OfficialMethod 980.13: Fructose, glucose, lactose, maltose, sucrose in milk chocolate;AOAC Official Method 982.14: Glucose, fructose, sucrose, and maltose inpresweetened cereals; AOAC Official Method 977.20: Separation of sugars inhoney; AOAC Official Method 979.23: Saccharides (major) in corn syrup;AOAC Official Method 983.22: Saccharides (minor) in corn syrup; AOAC Official Method 984.14: Sugars in licorice extracts.

41

Norm

200

400

600

800

Standard

Lemonade

Raffinose

Citric acid? Lactose

Glucose

Galactose

Fructose5 10 15Time [min]

Figure 30Analysis of carbohydrates in lemonade

Time [min]

Lact

ose

5 10 15 20

Corn extractCellbiose Sucrose

Norm

80

100

120

140

160

180Fr

ucto

se

Gluc

ose

Gala

ctos

e

Raffi

nose

Maltose

Standard

Standard

Figure 31Analysis of carbohydrates in corn extract


The HPLC method presented here was used to analyzemono-, di-, and trisaccharides as well as sugar alcohols.

�

HPLC method performanceLimit of detection < 10 ng with S/N = 2Repeatability ofRT over 10 runs < 0.05 %areas over 10 runs 2 %

Sample preparation Samples were directlyinjected.

Column 300 x 7.8 mm Bio-RadHPXP, 9 µm

Mobile phase waterColumn compartment 80 ºCFlow rate 0.7 ml/minDetector refractive index

Vitamins Fat-soluble vitamins, such as vitamins E, D, and A, andwater-soluble vitamins, such as vitamins C, B6, B2, B1, andB12, have been analyzed.

Vitamins are biologically active compounds that act ascontrolling agents for an organism’s normal health andgrowth. The level of vitamins in food may be as low as a fewmicrograms per 100 g. Vitamins often are accompanied byan excess of compounds with similar chemical properties.Thus not only quantification but also identification ismandatory for the detection of vitamins in food. Vitaminsgenerally are labile compounds that should not exposed tohigh temperatures, light, or oxygen. HPLC separates anddetects these compounds at room temperature and blocksoxygen and light.19 Through the use of spectral information,UV-visible diode-array detection yields qualitative as well asquantitative data. Another highly sensitive and selectiveHPLC method for detecting vitamins is electrochemicaldetection.

Sample preparation

Different food matrices require different extractionprocedures.19 For simple matrices, such as vitamin tablets,water-soluble vitamins can be extracted with water in anultrasonic bath after homogenization of the food sample.

42



Water Acetonitrile

Column compart-ment

Auto-sampler


3

Water-soluble vitamins

Chromatographic conditions for UV detection

The HPLC method presented here was used to analysisvitamins in a vitamin drink.

43

Sample preparation filtrationColumn 100 x 4 mm

Hypersil BDS, 3 µmMobile phase A= water with pH = 2.1

(H2SO4) = 99 %B = ACN 1 %

Gradient at 3.5 min 1 % Bat 11 min 25 % Bat 19 min 90 % B

Post time 6 minFlow rate 0.5 ml/minColumn compartment 30 ºCInjection volume 2–5 µlDetector UV-DAD


0 2 4 6 8 10 12

Norm

0

500

1000

1500

Citric acid

Standard

B1 B6

Pant

othe

nic

acid

B12

Biot

inRi

bofla

vinFo

lic a

cid,

d

Vitamintablet

Saccharin

Time [min]

Vita

min

C

Ribo

flavi

n 5'

phos

HPLC method performanceLimit of detection < 500 pg (injected

amount), S/N = 2Repeatability ofRT over 10 runs < 0.2 %areas over 10 runs < 2 %

Figure 32Analysis of water-soluble vitamins in a vitamin tablet

250 350 450 550

Norm

0

400

800 Riboflavin

250 350 450 550

Norm

200

600

1000

250 350 450 5500

200

400

Folic acid

nmnm

nm

Norm

Vitamin B B B1, 6, 12

Figure 33Spectra of water-soluble vitamins

19. L.M. Nollet, “ Food Analysis by HPLC”, New York, 1992.�

Sample preparation Vitamin preparation wasdiluted with water 1:100

Column 125 x 4 mm, LichrospherRP 18, 5 µm

Mobile phase water + 0.02 M KH2PO4 +0.03 M tetrabutylammo-niumhydrogensulfat +0.03 M heptanesulfonicacid + 2 % ACN

Stop time 15 minFlow rate 0.8 ml/minColumn compartment 30 ºCInjection volume 1 µl standard

0.5 µl sampleDetector electrochemical

Working electrode: glassy carbonOperation mode: amperometryWorking potential: 1.2 VRange: 0.5 µAReferenceelectrode: AgCl/KClResponse time: 1 s

44

Auto- sampler



Water

Columncompart-ment

Auto-sampler


20. A.G. Huesgen, R. Schuster, “Analysis of selected vitamins withHPLC and electrochemical detection”, Agilent Application Note 5091-3194E , 1992.

�

HPLC method performanceLimit of detection 30 pg (injected amount)

S/N = 2Repeatability ofRT over 10 runs < 0.5 %areas over 10 runs < 5 %Linearity 30 pg to 1 ng

Chromatographic conditions for electrochemical detection

The HPLC method presented here was used in the analysisof vitamins in animal feed.20

Standard

Vitamin CmV

0 1 2 3 4 5 6Time [min]

120

140

160

180

200

220

240

Vitamin B 6

Vitamin B 6

Figure 34Analysis of vitamin B6 in a vitamin preparation

3

45

Fat-soluble vitamins

Column 100 x 2.1 mmHypersil MOS, 5 µm

Mobile phase A = waterB = ACN (70 %)

Gradient at 15 min 90 % Bat 16 min 95 % B

Post time 3 minFlow rate 0.5 ml/minColumn compartment 40 ºCInjection volume 2–5 µlDetector UV-DAD

detection wavelengths230/30 nm, 400/100 nm;reference wavelengths280/40 nm, 550/100 nm


Limit of detection 1 ppb with S/N = 2Repeatability ofRT over 10 runs < 0.82 %areas over 10 runs < 2.2 %

Sample preparation

Different food matrices require different extractionprocedures. These procedures include alkaline hydrolysis,enzymatic hydrolysis, alcoholysis, direct solvent extraction,and supercritical fluid extraction of the total lipid content.


The HPLC method presented here was used in the analysisof a vitamin standard.

2 4 6 8 10 12 14

mAU

0100

200

300

400

500

600

700 Vitamin D

α-tocopherol

β-and

Time [min]

Standards

3

δ-tocopherol

γ-tocopherol

Figure 35Analysis of fat-soluble vitamins with UV detection

Water Methanol

Column compart-ment

Auto-sampler



Diode-arraydetector

46

3

Chromatographic conditions for electrochemical detection

The HPLC method presented here was used in the analysisof a vitamin standard.20

-tocopherol

mV

0 2 4 6 8 10Time [min]

Standard118.5

118.0

117.5

117.0

116.5

Figure 36Analysis of a fat-soluble vitamin with electrochemical detection

Auto- sampler



Water

Columncompart-ment

Auto-sampler


Tocopherols cannot be separated completely usingreversed-phase chromatography. However, normal-phasechromatography can separate isocratically all eighttocopherols (T) and tocotrienols (T3 ) naturally occurring infats, oils, and other foodstuffs. Fluorescence detection isrecommended for the analysis of total lipid extractionbecause UV absorbance detection is not selective enough toprevent detection of coeluting peaks.

Analysis of tocopherolson normal-phase

column

Column 125 x 4 mmLichrospher RP18, 5 µm

Mobile phase methanol + 5 g/llithiumperchlorate + 1 g/l acetic acid

Stop time 20 minFlow rate 1 ml/minOven temperature 30 ºCInjection volume 1 µl standardDetector electrochemicalWorking electrode: glassy carbon

Operation mode: amperometryWorking potential: 0.9 VRange: 0.5 µAReferenceelectrode: AgCl/KClResponse time: 8 s

HPLC method performanceLimit of detection 80 pg (injected amount),

S/N = 2Repeatability ofRT over 10 runs < 0.5 %areas over 10 runs < 5 %Linearity 30 pg to 1 ng

Chromatographic conditions for analysis oftocopherols on normal-phase column

The HPLC method presented here was used in the analysisof margarine.

47

Time [min]1 2 3 4 5 6 7

mAU

0

5

10

15

20

FLD

DAD

γ-tocopherol

δ-tocopherol

β-tocopherolα-tocopherol

Figure 37Analysis of tocopherols on normal phase using UV and fluorescencedetection

Time [min]

1 2 3 4 5 6

%F

10

30

50

70

90

77.3 %9.5 %

1.9 %11.2 %

β-tocopherol

α-tocopherol

γ-tocopherol

δ-tocopherolStandard

Margarine

Figure 38Analysis of tocopherol concentration in margarine fat extract withfluorescence detection

Hexane

Column compart-ment

Auto-sampler



Diode-arraydetector


Sample preparation 20 g sample dissolved in 15 ml hexane

Column 100 x 2.1 mmHypersil SI 100, 5 µm

Mobile phase hexane + 2 %isopropanol

Stop time 8 minFlow rate 0.3 ml/minColumn compartment 25 ºCInjection volume 0.5 µlDetector

UV-DAD 295/80 nmFluorescence excitation wavelength

295 nm,emission wavelength330 nm

HPLC method performanceLimit of detection 10–20 ng, S/N = 2for diode-arrayLimit of detection 0.5–2 ng S/N = 2for fluorescenceRepeatability ofRT over 10 runs < 2 %areas over 10 runs < 2 %

Biogenic amines The following amines were analyzed: ammonia, amylamine,1-butylamine, 1,4-diaminobutane, 1,5-diaminopentane,diethylamine, ethanolamine, ethylamine, hexylamine,histamine, isobutylamine, isopropylamine, methylamine,3-methylbutylamine, morpholine, phenethylamine,propylamine, pyrrolidine, and tryptamine.

Free amines are present in various food products andbeverages, including fish, cheese, wine, and beer.

High concentrations of specific amines can have toxicproperties. As a result, several countries have set maximumtolerance levels for these compounds in foodstuffs. HPLC isnow preferred for the analysis of amines in food matricesbecause of its shorter analysis time and relatively simplesample preparation.

Sample preparation

Amines can be extracted from different matrixes usingliquid/liquid extraction or solid-phase extraction followedby derivatization.

48

3



Water Acetonitrile

Column compart-ment

Auto-sampler

Variablewavelengthdetector


The HPLC method presented here was used to analyzeamines in wine.21

49

1 ethanolamine2 ammonia3 methylamine4 ethylamine5 morpholine6 i-propylamine7 propylamine

8 pyrrolidine9 i-butylamine10 1-butylamine11 tryptamine12 diethylamine13 phenethylamine14 3-methylbutylamine

15 amylamine16 1,4-diaminobutane17 1,5-diaminopentane18 hexylamine19 histamine20 heptylamine

(internal standard)

20 40 60

2.0e4

6.0e4

8.0e4

4.0e4

mAU

Time [min]

Standard1

2

3 4

5

6

7 8

9

10

1112

13

14

15

16

17

18

19

20

Figure 39Analysis of amine standard with UV detection after derivatization

21. O. Busto, et al., “Solid phase extraction applied to the determination ofbiogenic amines in wines by HPLC”, Chromatographia, 1994, 38(9/10),571–578.

�

Sample preparation25 ml wine was decolored withpolyvinylpyrrolidoine. After filtration, theamines (5 ml sample, pH = 10.5) werederivatized with 2 ml dansyl chloridesolution (1 %). The reaction solution wascleaned with solid-phase extraction usingC18 cartridges (500 mg). After elutionwith 2 ml ACN, the solution wasconcentrated to 100 µl.

Column 250 x 4.6 mmSpherisorb ODS2, 5 µm

Mobile phase A = water + 5 % ACN =75 %B = ACN (25 %)

Gradient at 5 min 45 % Bat 30 min 45 % Bat 50 min 60 % Bat 55 min 80 % Bat 60 min 80 % B

Stop time 60 minPost time 4 minFlow rate 1 ml/minColumn compartment 60 ºCDetector UV-VWD

250 nm

HPLC method performanceRecovery rate > 85 %Limit of detection 50–150 µg/lMethod repeatability for5 red wine analyses < 5 %Linearity 500 µg/l to 20 mg/l

Amino acids Both primary and secondary amino acids were analyzed inone run.

The amino acid composition of proteins can be used todetermine the origin of meat products and thus to detectadulteration of foodstuffs. Detection of potentially toxicamino acids is also possible through such analysis. Throughthe use of chiral stationary phases as column material, Dand L forms of amino acids can be separated and quanti-fied.

HPLC in combination with automated online derivatizationis now a well-accepted method for detecting amino acidsowing to its short analysis time and relatively simple samplepreparation.

Sample preparation

Hydrolyzation with HCl or enzymatic hydrolysis is used tobreak protein bonds.


The HPLC method presented here was used in the analysisof secondary and primary amino acids in beer withprecolumn derivatization and fluorescence detection.22, 23

50

3



Water Acetonitrile

Column compart-ment

Auto-sampler

Diode- arraydete


ctor

51

ASPGLU

GLNH

ISGLY

ALAARG

TYR

VALM

ET

PRO

LEU

ILE

ASN

SER

CIT

PHELYS

WL switch

Time [min]

mAU

70

60

50

40

30

20

10

2 4 6 8 10 120

γ−AB

A

Figure 40Analysis of amino acids in beer after online derivatization

22. ”Sensitive and reliable amino acid analysis in protein hydrolysatesusing the Agilent 1100 Series”, Agilent Technical Note 5968-5658E, 199923. R. Schuster, “Determination of amino acids in biological, pharmaceutical, plant and food samples by automated precolumnderivatization and HPLC”, J. Chromatogr., 1988, 431, 271–284.

�

Sample preparation filtrationColumn 200 x 2.1 mm

Hypersil ODS, 5 µmMobile phase A = 0.03 M sodium acetate

pH = 7.2 + 0.5% THFB = 0.1 M sodium acetate/ACN (1:4)

Gradientat 0 min 0 % B at 0.45 ml/min flow rateat 9 min 30 % Bat 11 min 50 % B at 0.8 ml/min flow rateat 13 min 50 % Bat 14 min 100 % B at 0.45 ml/min flow rateat 14.1 min at 0.45 ml/min flow rateat 14.2 min at 0.8 ml/min flow rateat 17.9 min at 0.8 ml/min flow rateat 18 .0 min at 0.45ml/min flow rateat 18 min 100 % Bat 19 min 0 % B

Post time 4 minFlow rate 0.45 ml/minColumn compartment 40 ºCInjection volume 1 µl standardDetector

UV -DAD 338 nm and 266 nmFluorescenceExcitation wavelength: 230 nmEmission wavelength: 450 nmat 11.5 minExcitation wavelength: 266 nmEmission wavelength: 310 nmPhotomultiplier gain: 12Response time: 4 s

Injector program for online derivatization1. Draw 3.0 µl from vial 2 (borate buffer)2. Draw 1.0 µl from vial 0 (OPA reagent)3. Draw 0.0 µl from vial 100 (water)4. Draw 1.0 µl from sample5. Draw 0.0 µl from vial 100 (water)6. Mix 7.0 µl (6 cycles)7. Draw 1.0 from vial 1 FMOC reagent8. Draw 0.0 µl from vial 100 (water)9. Mix 8.0 µl (3 cycles)10. Inject

HPLC method performanceLimit of detection DAD < 5 pmol

FLD < 100 fmolRepeatability ofRT over 6 runs < 1 %areas over 6 runs < 5 %Linearity DAD 1 pmol to 4 nmol

Peptides Peptide mapping of phytochrome from dark grown oatseedlings using capillary liquid chromatography

The analyzed phytochrome is a photoreceptor protein that controls light-dependent morphogenesis in plants. Forexample, potato clod forms pale long sprouts if it germi-nates in a dark cellar. However, if this process takes place in the light, a normal plant with green leaves grows andphotosynthesis occurs. Phytochrome proteins are presentin very low concentrations in potato clod, and sample volume and concentration of these proteins is rather lowfollowing sample preparation. In this case, columns or capillaries with a small internal diameter are preferredbecause sensitivity increases with decreasing internal diameter of the column. The use of capillaries with an internal diameter of 100–300 µm enables flow rates as lowas 0.5–4.0 µl/min, which reduces solvent consumption. Such flow rates are well-suited to liquid chromatography-mass spectroscopy (LC/MS) electrospray ionization.

In our experience, the appropriate conversion of standardHPLC equipment to a capillary HPLC system is cost-effectiveand yields the highest performance for running capillarycolumns. For conversion, a flow stream-split device, a35-nL capillary flow cell for the detector, and capillary con-nections between system modules are required. Systemdelay volume should be as low as possible. To meet thedemands of such a system, the Agilent 1100 Series binarypump, which has inherently low delay volume, was selectedas a pumping system. The flow splitter, the capillary flowcell for the detector, and the column were purchased fromLC Packings in Amsterdam.24

With this design, a standard flow rate (for example, 100 or50 µl/min) can be set for the pump. This flow then can bereduced by calibrated splitters between 0.5 and 4 µl/min, forexample. This flow rate is optimal for capillary columnswith an internal diameter of 300 µm.

52

3


Capillary HPLC with UV and MS detection has been used inthe analysis of phytochrome protein from dark grown oatseedlings. Figures 41, 42 and 43 show the UV and total ionchromatogram together with two mass spectra of selectedfragments. The Agilent 1100 Series LC system was usedwithout mixer. All tubings were as short as possible, with aninternal diameter of 75–120 µm id.

Sample preparation

The extracted protein was reduced and alkylated prior todigestion with trypsin.

53

Time [min]40 60 80 100

mAU

20

40

60

80

100

120

Figure 41Capillary LC-MS of a phytochrome tryptic digest (17.5 pmol)—UV trace

Flowsplitdevice


Water iAcetonitr le

Columncompart-ment

Auto-sampler

Massspectrome-ter or VWDdetector

Binarypump +vacuum degasser

Sample tryptic digest ofphytochrome from oatseedlings, 7 pmol/µl

Capillary column 300 µm x 25 cm, C18Mobile phase A = 0.025 % TFA in water

B = 0.02 % TFA in ACNGradient 0.35 % B/minFlow rate 100 µl/min split to

4 µl/minColumn compartment 25 ºCInjection volume 2.5 µlDetector UV-VWD

wavelength 206 nm witha 35-nl, 8-mm flow cell

HPLC method performanceLimit of detection 1 pmolRepeatability ofRT over 10 runs < 0.7 %areas over 6 runs < 1 %

MS data was used for further evaluation. Some of the trypticmass fragments of the phytochrome are signed. As anexample, figure 42 shows two mass spectra.

54

3

Time [min]

20000

40000

60000

80000

100000

120000

140000

160000

Abun

danc

e

40 50 60 70 80 90 100 110

T46

T92

T15

T12

T14T58

T60-61

T8

T42

Figure 42Capillary LC-MS of a phytochrome tryptic digest (17.5 pmol)—total ionchromatography (TIC)

Abu

ndan

ce

450 550 650 750 850 m/z0

2000

4000

6000

8000

10000

415.4

829.7

T12 (MW = 828.5)

1000

2000

3000

4000

5000

6000

796.6

1194.7

700 900 1100 1300500 m/z

T58 (MW = 2387.2)

Time [min] Time [min]

Abun

danc

e

Figure 43Mass spectra of T12 and T58

24. “Capillary Liquid Chromatography with the Agilent 1100 Series Modulesand Systems for HPLC”, Agilent Technical Note 5965-1351E , 1996.�

Voltages Vcyl -5500, Vend -3500,Vcap -4000, CapEx 150

Scan 400–1800 m/zThreshold 150Sampling 1Stepsize 0.15 amuDrying gas nitrogen, 150 °CNebulizer gas nitrogen, < 20 psi

The Agilent 5989B MS engine was equippedwith an Iris™ Hexapole Ion Guide

55

TheEquipmentBasics

An overview of the hardware and the softwarecomponents neededfor successful HPLC, and an introduction to the analytical techniques that have become routine in food analysis

Part Two

Chapter 4Separation inthe liquid phase

Separationmechanisms

Reversed-phase materials

Ion-exchange materials

Liquid chromatography offers a wide variety of

separation modes and mobile phases for optimizing

your separation system.

Stationary phases can be classified according to themechanism by which they separate molecules:

• partition phases

• adsorption phases

• ion-exchange phases

• size-exclusion phases

Nowadays the most popular column material is reversedphase, in which separation is achieved through partitionand through adsorption by unprotected silanol groups. Inreversed-phase chromatography, the stationary phase isnonpolar (or less polar than in the mobile phase) and theanalytes are retained until eluted with a sufficiently polarsolvent or solvent mixture (in the case of a mobile-phasegradient).

Reversed-phase materials have wide application and a longlifetime. Moreover, these media have good batch-to-batchreproducibility, low equilibration times, high mechanicalstability, and predictable elution times and elution order.Reversed-phase chromatography is frequently used in foodanalysis, as shown in part one of this primer.

Compared with reversed-phase media, ion-exchangematerials have a shorter lifetime, are less mechanicallystable, and take longer to equilibrate. These columns havelimited application in food analysis and are used primarilyfor inorganic cations and anions or for glyphosate.

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59

Size-exclusion chromatography is used for sample cleanupand fractionation and is described in more detail inchapter 5 (“Sample preparation”).

Adsorption chromatography is used for sampling andcleanup. For example, flavonoids from plant material canbe cleaned, fractionated, and enriched on alumina. Otherexamples are given in chapter 5.

Discussions of HPLC methods often revolve around theinternal diameter (id), or bore, of the column to be used.Standard-bore columns have an internal diameter ofapproximately 4 or 5 mm, whereas narrow-bore columnshave an internal diameter of approximately 2 mm. Whenpacked with the same materials as the standard-borecolumn, the narrow-bore column can achieve the sameresolving power with less solvent because the analytes canbe eluted at a lower flow rate (< 0.5 ml/min) than the 2–3ml/min required for standard-bore columns. In addition,narrow-bore columns are 4–6 times more sensitive using theinjection volume required for a standard-bore column (seefigure 44).

Narrow-bore columns nonetheless place higher demands onthe equipment used than standard-bore columns. First, theHPLC pump must yield these low flow rates in a way that isboth reproducible and precise. Second, all capillary connec-tions, that is, from injector to column and from column todetector, must be kept to a minimum. Third, because column frits block more often, guard columns are recommended. An HPLC system designed for narrow-borecolumns (low dead volume and high-performance pumpingsystem) can achieve solvent economies of more than 60 %as well as improve detection limits with the same injectionvolume. Moreover, under the same conditions, a standard-bore column may have higher resolving power.

Size-exclusion gels

Adsorption media

The advent ofnarrow-borecolumns

Time [min]5 10 15 20

% F

0

100

120

140

60

40

20

80

250 x 2.1 mm id column

250 x 4.6 mm id column

Figure 44Effect of bore dimensions onseparation

Influence of columntemperature on separation

Many separations depend not only on the column materialand mobile phases but also on the column temperature. Insuch cases, column temperature stability is the dominatingfactor for the elution order. A thermostatted columncompartment using Peltier control with good ambienttemperature rejection ensures stable chromatographicconditions. Periodic fluctuations in room temperatureduring 24-hour use influence these conditions. Figure 45shows the advantage of Peltier control over conventionalair cooling.

60

70.40

70.60

70.80

71.00

71.20

1 2 3 4 5 6 7 8 9 10Run number

Retention time

Day

Night

Day

Conventional column oven

Agilent 1100 Series thermostattedcolumn compartment

Figure 45Comparison of Peltier and conventional cooling as demonstrated using retention time fluctuations of a peptide peak over a sequence of 10 consecutive tryptic peptide maps

4

Reversed-phase stationary phases are the most popularLC media for the resolution of food mixtures. The use ofnarrow-bore columns can result in gains in sensitivity andreduced solvent consumption. For example, thesecolumns have been applied successfully in the analysis ofaflatoxins and fatty acids.

In brief…

Chapter 5Samplepreparation

Sample preparationsteps

Automation

The isolation of analytes from other matrix

constituents is often a prerequisite for successful

food analysis. The broad selection of cleanup and

enrichment techniques takes into account the many

matrices and compound classes under study.

Sample preparation for HPLC can be broken down into thefollowing main steps:

1. Sampling

CollectionStorage

2. Cleanup/enrichment offline

Homogenization, centrifugation, precipitation,hydrolyzation, liquid/liquid extraction, solid-phaseextraction, ultrasonic bath liquid extraction,supercritical fluid extraction, concentration

3. Cleanup/enrichment online

Guard columnsOnline solid-phase extractionGel-permeation chromatography (GPC)

4. Chemical derivatization

Precolumn, online, or offline(see also discussion of postcolumn derivatization,chapter 9)

Manual extraction, cleaning, and concentration of the sampleprior to transfer to the HPLC instrument is time-consumingand can drain resources. Sample preparation thereforeshould be automated where possible. Nowadays the samplecan be fractionated and/or derivatized automatically.

62

5

63

Supercritical fluid extraction (SFE) systems and automatedsolid-phase extraction equipment also have been interfaceddirectly to liquid chromatographs. Equipment used to auto-mate preparation of HPLC samples includes:• Valves—Valves are used to switch to guard columns and

online solid-phase extraction techniques.25 Switchingvalves are common in HPLC, and some instruments evenhave built-in column compartment valves. With a six-portvalve, for example, the eluant stream can be switchedfrom one column to another to cut out a peak. This peakis then analyzed on the second column.

• SFE interfaces—This technique is rather new, and onlinesystems are under development.26 An offline procedurehas been used successfully in the analysis of vitamin K ininfant formula.27

• Precolumn derivatization—This well-accepted andcommercially available technique28 has been appliedin the analysis of amino acids in beer (see page 50 ff.).Reagents also can be used postcolumn (see page 28).

• Automated solid-phase extraction—This relatively newtechnique is used to analyze bittering compounds inbeer.29

Solid samples, for example chocolate or meat, should behomogenized before such techniques as steam distillation,SFE, or ultrasonic-stimulated liquid extraction areapplied.30

Ultrasonic bath liquid extraction is a very simple extractionmethod. Selectivity is achieved through the use of appropriatesolvents. Antioxidants and preservatives can be extractedwith this technique if the matrix is low in fat.

Solids

Ultrasonic bath liquidextraction

Steam distillation

Uses relatively small quantities of organicsolvents, thereby reducing costs andfacilitating disposal. Extraction times arein minutes rather than hours.

64

5

✔ ✘

Samples high in fat cannot be extracted.

Enables selective extraction of volatilecompounds.

✔ ✘

Extraction times are long and offline.Narrow range of use.

Uses small quantities of organic solvents,thereby reducing costs and facilitatingdisposal. Extraction times are in minutesrather than hours. Can be automated.

✔ ✘

Weak solvating power limits range ofanalytes. Ultrapure fluids for traceanalysis are not always available.

Steam distillation is only used to extract volatilecompounds from solid homogenized matrices. For example,biphenyl and 2-phenylphenol pesticides can be extractedfrom citrus fruits with this technique.31

Supercritical fluidextraction

Until now, supercritical fluid extraction (SFE) was rarelyused in food analysis. However, the input of modern SFEinstruments can be automated with sampling devices. Thismethod is used primarily for GC,26, 32 although LC couplingalso has been performed with SFE.33

65

Liquid-liquid extraction, on- and offline solid-phaseextraction, and GPC are used in the analysis of liquidsamples or extracts from solid samples.

Liquid-liquid extraction is the most common extractionmethod. It requires an appropriate solvent and a separatingfunnel, or a continuous or counter-current distributionapparatus

Simple, with highly selective modifiers(pH, salts, or ion-pairing reagents).

✔ ✘

Requires large amounts of toxic solvents,can emulsify, and is difficult to automate.

Solid-phase extraction Suitable for cleaning clear liquids such as filtered bever-ages, solid-phase extraction (SFE) is simple in principle.The sample is first sucked through a preconditioned car-tridge or disk filled with adsorbents. The solid then trapsthe compounds of interest, which can be extracted laterwith a small amount of an organic eluant. A variety of mate-rials provides a choice of selectivities for use as a fraction-ing tool. Two or more separate cartridges filled with specificadsorption materials can trap individual fractions of thesample.

SPE is one of the fastest-growing sample preparation andcleanup techniques.34 Attempts have been made to auto-mate both the procedure and its interface with the chro-matograph. Systems based on robotics and valves areavailable. Pumping a certain volume of water samplethrough one or more precolumns filled with extractionmaterials will extract and concentrate the compounds ofinterest. After desorption with a suitable solvent, the ana-lytes can be introduced into a liquid or gas chromatographfor identification and quantification. The precolumns are

Liquids

Liquid-liquid extraction

66

exchanged automatically between analyses to preventclogging and memory effects.35 So far this system hasbeen used only to extract pesticides and polynucleararomatics in river water. A different online solid-phaseextraction system has been used to extract and analyzeiso-a-acids in beer.36, 40

5

Uses small amounts of organic solvents,can run several samples at once, and canbe automated.

✔ ✘

Differing batch-to-batch efficiencies canreduce reproducibility. Risk of irreversibleadsorption. Degradation by surfacecatalysis can occur.

Highly reproducible, good automationpossibilities.

✔ ✘

Large amounts of solvents needed,separation efficiency may differ frombatch to batch.

Gel permeationchromatography

Also known as size-exclusion chromatography, gel perme-ation chromatography (GPC) has become a standard tech-nique for isolating compounds of low molecular weightfrom samples that contain compounds of high molecularweight, such as oil or fats. The separation is based on differ-ences in size, with higher molecular weight compoundsretained less than smaller ones. GPC has been used success-fully to separate vitamins A, D, and E from glycerides ininfant formula and clean-up of pesticides in spices (seechapter 2, page 22 ff).37

67

Highly reproducible, good automationpossibilities.

✔ ✘

More complex, and more expensive if avalve is used.

Guard columns A guard column is connected in front of the analyticalcolumn to prevent contamination of the analytical columnby the matrix. Either the guard column can be included inanalytical column design, or both columns can beinterconnected by a valve that, when switched, transfersfractions from the precolumn to the analytical column. Thelatter technique is more flexible and can be used for samplecleanup and enrichment. Alternatively, a backflush valvecan be used to enrich the sample on a precolumn. Reversingthe direction of flow transfers compounds concentratedfrom the precolumn to the analytical column.

Many food analyses are governed by officially recognizedmethods, which often include details on samplepreparation. Recent trends toward automated samplepreparation increase precision by eliminating operatorvariances. Should you adopt a newly developed samplepreparation technique, however, please be aware that themethod must comply with existing good laboratorypractice (GLP) regulations and with accreditationstandards.38

In brief…

68

Chapter 6Injectiontechniques

Characteristics of a good sampleintroduction device

Figure 46A typical 6-portinjection valve

After the sample has been prepared for introduction

onto the LC column, analysis can begin. Judgements

based on analyte concentration require a reliable

quantity of sample volume. The process of

introducing the sample onto the column with

precision syringes can be automated for increased

throughput.39, 40

The main requirements for any sampling device are goodprecision of injection volumes, low memory effects(carry-over of material from one injection to another), andthe ability to draw viscous samples and inject variable vol-umes. Modern sampling systems can further increase pro-ductivity with features such as online precolumnderivatization for selective detection, heating and coolingfor improved stability, and microsampling of material in lowsupply. Some analyses may require corrosive solvents ormobile-phase additives such as 0.1 N HCl or 60 % formicacid. Some vendors supply devices of corrosion-resistanttitanium to solve this problem.

Injection systems often are based on a six-port valve, whichis put through several steps for each injection, as illustratedin figure 46. In the first step, denoted here as load, the sam-ple is either aspired by a vacuum (in automated systems) orexpressed by a syringe plunger (in manual systems) into asample loop, where it rests until the valve is switched toinject. This second step connects the pump and the mobilephase with the column. The contents of the sample loopthen move into the solvent flow path and onto the analyticalcolumn. Because all parts of the system are constantlyflushed during analysis, the remnants of a previous injec-tion are removed before the next injection occurs.

70

6

Normal

Load

Inject

71

The quality of the separation on the column depends on thequality of the injection—a short, sharp injection increasesthe likelihood of short, sharp peaks. The use of a minimumnumber of fittings between the injector and the columnreduces the diffusion of the contents of the sample loop intothe mobile-phase fronts in front of and behind the column.So-called low dead volume fittings with the minimumrequired internal capacity are available. These fittings haveno “dead ends” or unnecessary spaces where solvent andsample can mix.

Simple manual injectors remain popular in somelaboratories because they are inexpensive and becausetheir operation requires little previous experience, which isimportant if the equipment is used infrequently. With aprecision syringe, the operator can fill the sample loop atatmospheric pressure by injecting the contents into theinjection port. A switch of the rotor attached to the valverealigns the valve ports to the inject position. Solvent fromthe pump then flushes the contents of the sample loop ontothe column. Continual flushing during the run keeps theinjection port and valve clear of remnants of previoussamples.

Manual injectors

Inexpensive.

✔ ✘

No automation and no provision for onlinederivatization. Syringe must be cleanedmanually, offline.

Automated injectors

72

Highly reproducible. Can be fullyautomated. Flow maintained over all partsin contact with sample, preventinginaccuracies from intermingling betweenruns.

✔ ✘

Equipment can be costly.

Automated injectors contain a mechanically driven versionof the same six-port valve found in manual injectors.Pneumatic or electrical actuators control the valve as itswitches between steps in the injection cycle. A meteringdevice can handle injection volumes of 0.1–1500 µl. Withsample loops of larger capacity, such a device can inject upto 5 ml. Vials designed to hold microliter volumes can beused to inject as little as 1 µl of a 5-µl sample. Even the waythe needle enters the vial can be controlled with computersoftware: deep down to aspire from the denser of twolayers, or a shallow dip into the supernatant phase. Withthis technique, even viscous samples can be analyzed if theright equipment is used. The time required to extract thesyringe plunger is simply protracted, permitting meniscusmotion of higher reproducibility.

6

Autosampler withsample pretreatmentcapabilities

Autosamplers can provide online precolumn derivatization,dilute small volumes of sample, and add internal standards.You may need to protect unstable species by keeping thesample chilled with a cooling device connected to a flow of refrigerated water or, more conveniently, by Peltier elements. Alternatively, you might want to induce reactionsusing heat applied within the injection device of theautosampler. Commercially available autosamplersoffer all these features.

73

Derivatization

Sample Reagent

Meteringdevice

Samplingunit

6-port valve

Reagent

To waste

From pump

To column

Figure 47Automated precolumn derivatization

The robotic arm of the autosampler transports, in turn, asample vial and several reaction vials under the injectionneedle. The needle is extended by a length of capillary atthe point at which the derivatization reaction takes place.

As discussed later in chapter 8, derivatization may berequired if the analytes lack chromophores and if detectionis not sensitive enough. In this process, a chromophoregroup is added using a derivatization reagent. Derivatizationcan occur either in front of or behind the analytical columnand is used to improve sensitivity and/or selectivity.Precolumn derivatization is preferable because it requiresno additional reagent pump and because reagents can beapportioned to each sample rather than pumped throughcontinuously. Automated precolumn derivatization yieldsexcellent precision. Moreover, it can handle volumes in themicroliter range, which is especially important whensample volume is limited. The principles involved areillustrated in figure 47.

74

The injector draws distinct plugs of sample and derivatizationreagent into the capillary. The back-and-forth movementof the plunger mixes the plugs. With the right software, theautoinjector can be paused for a specified length of time toallow the reaction to proceed to completion. If the reactionrequires several reagents, the autosampler must be programmable, that is, it must be able to draw sequentiallyfrom different reagent vials into one capillary.In this complex sample manipulation, the needle must becleaned between vials, for example by dipping into washvials of distilled water.

Automated sampling systems offer significant advantagesover manual injectors, the most important of which ishigher reproducibility of the injection volume. Samplethroughput also can be increased dramatically. Modernautosamplers are designed for online sample preparationand derivatization. For food analysis, an automatedinjection system is the best choice.

In brief…

6

Chapter 7Mobile phasepumps anddegassers

Characteristics of amodern HPLC pump

Flow ranges

Gradient elution

The pump is the most critical piece of equipment for

successful HPLC. Performance depends strongly on

the flow behavior of the solvent mixture used as

mobile phase—varying solvent flow rates result in

varying retention times and areas. Conclusions

from a calibration run for peak identification or

quantification depend on reproducible data. In this

chapter we discuss multiple aspects of pump

operation, including solvent pretreatment and its

effect on performance.

A modern HPLC pump must have pulse-free flow, highprecision of the flow rates set, a wide flow rate range, andlow dead volume. In addition, it must exhibit control of amaximum operating pressure and of at least two solventsources for mobile-phase gradients, as well as precision andaccuracy in mixing composition for these gradients.

We discuss two gradient pump types: that constructed forflow rates between 0.2 and 10 ml/min (low-pressure gradientformation), and that designed for flow rates between 0.05and 5 ml/min (high-pressure gradient formation).

In separating the multiple constituents of a typical foodsample, HPLC column selectivity with a particular mobilephase is not sufficient to resolve every peak. Changing theeluant strength over the course of the elution by mixingincreasing proportions of a second or third solvent in theflow path above the column improves peak resolution in two

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77

ways. First, resolution is improved without extending theelution period, which prevents long retention times (peaksthat have been retained on the column for a longer period oftime tend to broaden and flatten through diffusion, loweringthe S/N and therefore detection levels). Second, gradientelution sharpens peak widths and shortens run time,enabling more samples to be analyzed within a given timeframe. The solvents that form the gradient in front of thecolumn can be mixed either after the pump has applied highpressure or before, at low pressure.

If mixing takes place after pressure has been applied, ahigh-pressure gradient system results (this is most oftenachieved by combining the output of two isocratic pumps,each dedicated to one solvent).

Gradient formation at highpressure

Ability to form sharp gradient profiles andto change solvents rapidly (100% A to100% B), without degassing, for standardapplications.

✔ ✘

Expensive. An additional mixer for lowestmixing noise at flow rates below 200 µl isneeded for mobile-phase compositions.

Gradient formation at lowpressure

At low pressure, mixing of the gradient solvents occursearly in the flow path before the pump applies pressure, asin the two examples below.

Less expensive than gradient elution. Canmix more than two channels. Low mixingnoise without a dedicated mixer.

✔ ✘

Degassing is necessary for highestreproducibility.

78

In food analysis, pump performance is critical. In theexamples, we describe a low-pressure gradient system and ahigh-pressure gradient system, both of which performaccording to food analytical requirements. The former has asingle dual-piston mechanism for low-pressure gradientformation, whereas the latter has a double dual-pistonmechanism for high-pressure gradient formation. Afterpassing the online vacuum degasser, the mobile phase entersthe first pump chamber through an electronically activatedinlet valve (see figure 48). Active valves resolve the problemof contaminated or sticky ball valves by making the pumpeasy to prime. Output from the first piston chamber flowsthrough a second valve and through a low-volume pulsedampener (with pressure transducer) into a second pistonchamber. Output from the second chamber flows onto thesampling unit and column. The pistons in the pumpchambers are motor driven and operate with a fixed-phase

Pump designs forgradient operation

Low-pressure gradientAgilent 1100 Series pump

7

mAU

0

10

15

20

25

30

20

40

50

Time [min]

0.11%0.15%

0.10%

0.09%0.08%

0.08%

0.09% 0.08%

0.07%

0.08%

0.08% 0.08%0.10%0.09%

0.09%

5 10

Figure 49Retention time precision (% RSD) of 10 injections of a polycyclicaromatic hydrocarbon (PNA) standard sample

Figure 48Low pressure gradient pump

Damper

From solventbottles

Proportioningvalve

Vacuum chamber

Inletvalve

Out-letvalve

To waste

Purgevalve

To samplingunit andcolumn

79

difference of 180°, so that as one delivers mobile phase, theother is refilling. The volume displaced in each stroke can bereduced to optimize flow and composition precision at lowflow rates. With solvent compressibility, compensation, anda low-volume pulse dampener, pulse ripple is minimal,resulting in highly reproducible data for retention times andareas (see figure 49). A wide flow range of up to 10 ml/minand a delay volume of 800–1100 µl support narrow-bore,standard-bore, and semipreparative applications. Foursolvents can be degassed simultaneously with highefficiency.

In this design, gradients are formed by a high-speedproportioning valve that can mix up to four solvents on thelow-pressure side. The valve is synchronized with pistonmovement and mixes the solvents during the intake strokeof the pump. The solvents enter at the bottom of eachchamber and flow up between the piston and the chamberwall, creating turbulences. Compared with conventionalmultisolvent pumps with fixed stroke volumes, pumps withvariable stroke volumes generate highly precise gradients,even at low flow rates (see figure 50).

mAU

80

60

40

20

0

Time [min]0 5 10 15 20

80

60

40

20

0

mAU

0 5 10 15 20

Time [min]

Figure 50Results of a step-gradient composition (0–7%) of a high-pressurepump (left) and of a low-pressure pump (right)

Performance of low-pressure pump designFlow precision < 0.3 % (typically < 0.15 %)

based on retention times of 0.5 and 2.5 ml/min

Flow range 0.2–9.999 ml/minDelay volume ca. 800–1100 µlPressure pulse < 2 % amplitude (typically

< 1 %), 1 ml/min propanol, at all pressures

Composition ± 0.2 % SDprecision at 0.2 and 1 ml/min

80

High-pressure gradientAgilent 1100 Series pump

The Agilent 1100 Series high-pressure gradient pump isbased on a double dual-piston mechanism in which twopumps are connected in series in one housing. This con-figuration takes up minimal bench space and enables veryshort internal and external capillary connections. Both pistons of both individual pumps are servocontrolled inorder to meet chromatographic requirements in gradient formation (see figure 51).

Three factors ensure gradients with high precision at lowflow rates: a delay volume as low as 180–480 µl internalvolume (without mixer), maximum composition stabilityand retention time precision, and a flow range typicallybeginning at 50 µl/min.

The same tracer gradient used to determine compositionprecision and accuracy also was used to determine theripple of the binary pump (see figures 50 and 52). The delayvolume was measured by running a tracer gradient. Largedelay volumes reduce the sharpness of the gradient andtherefore the selectivity of an analysis. They also increasethe run-time cycle, especially at low flow rates.

7

Damper

To sampling unit and column

Inletvalve

Purgevalve

Inletvalve

Outletvalve

Outletvalve

Mixer

Figure 51Schematics of the high-pressure gradient Agilent 1100 Series pump

Performance of high-pressure pumpdesignFlow precision < 0.3 %Flow range 0.05–5 ml/minDelay volume 180–480 µl (600–900 µl

with mixerPressure pulse < 2 % amplitude (typically,

1 %), 1 ml/minisopropanol, at all pressure> 1MPa

Compositionprecision < 0.2 % at 0.1 and

1.0 ml/min

81

When working at the lowest detection limits, it is importantto use a mixer to reduce mixing noise, especially at210–220 nm and with mobile phases containing solventssuch as tetrahydrofuran (THF). Peptide mapping on 1-mmcolumns places stringent demands on the pump becausesmall changes in solvent composition can result in sizeablechanges in retention times. Under gradient conditions at aflow rate of 50 µl/min, the solvent delivery system mustdeliver precisely 1 µl/min per channel. A smooth baselineand nondistorted gradient profiles depend on good mixingand a low delay volume. Figure 53 shows six repetitive runsof a tryptic digest of myoglobin with a retention timeprecision of 0.07–0.5% RSD.

mAU

300

200

100

0

3 4 5

binary pumpwithout mixer 380 µlwith mixer 850 µl

6 8 9 107Time [min]

quaternary pump950 µl

at 5 minstart of gradient

Figure 52Delay volume of high- and low-pressure gradient pumps

82

mAU

Time [min]20 40 60 80 100 120

300

250

200

150

100

50

0

0.53%

0.38%

0.15% 0.08%

0.06% 0.04%

0.04%

0.02%0.04%

0.07%

Figure 53Overlay of six repetitive runs of a tryptic digest of myoglobin in RSD ofRT is as low as 0.07–0.5 %

7

Degassing removes dissolved gases from the mobile phasebefore they are pumped over the column. This processprevents the formation of bubbles in the flow path andeliminates volumetric displacement and gradient mixing,which can hinder performance. Instable flow causesretention on the column and may increase noise and drift onsome flow-sensitive detectors. Most solvents can partiallydissolve gases such as oxygen and thereby harm detectors.Detrimental effects include additional noise and drift in UVdetectors, quenching effects in fluorescence detectors, andhigh background noise from the reduction of dissolvedoxygen in electrochemical detectors used in reductionmode (in oxidation mode, the effect is less dramatic).

Degassing

The oxygen effect is most apparent in the analysis of polycyclic aromatic hydrocarbons (PNAs) withfluorescence detection, as shown in figure 50. The lessoxygen present in the mobile phase, the less quenchingoccurs and the more sensitive the analysis.

In general, one of three degassing techniques is used: on- oroffline vacuum degassing, offline ultrasonic degassing, oronline helium degassing. Online degassing is preferablesince no solvent preparation is required and the gasconcentration is held at a constant, minimal level over along period of time. Online helium and online vacuumdegassing are the most popular methods.

83

Helium degassingNo degassing

Agilent on-line degassing

Fluorescence

Signal heightsfor selected PNAs

12

10

8

6

4

2

10 11 12 13 14

Time [min]

1

2

3 4

5

6

Figure 54The loss of response due to

quenching can be recovered witheither helium or vacuum degassing.

Requires only a simple regulator. Severalchannels can be purged simultaneouslywithout additional dead volume.

✔ ✘

Expensive. Evaporation of the morevolatile components can changecomposition over time. Oxygen is betterpurged by vacuum degassing.

Helium degassing In helium degassing, gas is constantly bubbled through themobile-phase reservoir. This process saturates the solventand forces other gases to pass into the headspace above.

Vacuum degassing In vacuum degassing, the solvent is passed through amembranous tube made of a special polymer that ispermeable to gas but not to liquids under vacuum. Thepressure differences between the inside and outside of themembrane cause continuous degassing of the solvent. Newonline degassers with low internal volume (< 1 ml) allowfast changeover of mobile phases.

84

7

Less expensive to use and maintain thanhelium degassing. The composition ofpremixed solvents is unaffected, andremoval of oxygen is highly efficient.Several channels can be degassedsimultaneously.

✔ ✘

Increases dead volume and may result inghost peaks, depending on the type oftubing and type of solvent used.

The choice of pump depends on both elution mode(isocratic or gradient) and column diameter (narrow boreor standard bore). Although an isocratic system often issufficient, gradient systems are more flexible. Moreover,their short analysis times make gradient systems ideal forcomplex samples, sharp peaks, resolution of multiplespecies, and automatic system cleansing with additionalonline solvent channel. Agilent 1100 Series pumps are best suited for flow ranges from 0.05 ml/min up to 10 ml/min and can therefore be used with columns thathave an inner diameter of 1 mm to 8 mm. Although many officially recognized methods are based on standardcolumns and flow rates, the trend is toward narrow-borecolumns. These consume less solvent, which also reduceswaste disposal, thus lowering operating costs.

In brief…

Chapter 8Detectors

Most detectors currently used in HPLC also can be

applied in the analysis of food analytes. Each

technique has its advantages and disadvantages.

For example, diode array UV-absorbance detectors

and mass spectrometers provide additional spectral

confirmation, but this factor must be weighed against

cost per analysis when deciding whether to use a

detector routinely.

The ability to use UV spectra to confirm the presence of cer-tain food analytes and their metabolites and derivativesmakes UV absorbance the most popular detection tech-nique. However, for analytical problems requiring high sen-sitivity and selectivity, fluorescence detection is the methodof choice. Although electrochemical detectors are alsohighly sensitive and selective, they are rarely used in foodanalysis. Conductivity detectors, on the other hand, arewell-suited for the sensitive and selective analysis of cationsand anions, and thermal energy detectors are used forhigh-sensitivity determination of nitrosamines down to 10parts per trillion (ppt). Refractive index (RI) detectors areappropriate only if the above-mentioned detectors are notapplicable or if the concentration of analytes is high, orboth.

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Analyticalparameters

Limit of detection and limitof quantification

Selectivity

The most important parameters for food analysis are:

• limit of detection (LOD) and limit of quantification (LOQ)

• linearity

• selectivity

• qualitative information

The LOD and LOQ of an analytical system depend on thenoise and drift of the detection equipment. Absolute detec-tor LOD can be determined by injecting a sample directlyinto the detector. It is often expressed as minimum detect-able level, which is sometimes defined as equal to the noiselevel. However, the LOD depends not only on the detectorbut may also depend on the oxygen content of the mobilephase, the injection system, peak broadening on the col-umn, and temperature differences among system compo-nents. Taking these factors into account, the LOD is definedas 2 to 3 times the noise level. The LOQ is defined as 10 to20 times the noise level. A UV detection system can be usedto measure quantitative amounts down to 500 pg per injec-tion. The LOD can be as low as 100 pg for food compoundssuch as antioxidants if detection wavelengths have beenoptimized to match the extinction coefficients of as manycompounds as possible. Fluorescence and electrochemicaldetectors operate in the very low picogram range. The LODof a mass spectrometer connected to HPLC equipmentdepends on the type of interface used. Instruments withelectrospray interfaces can detect down to the picogramrange. Refractive index detectors normally are appropriateabove 500 ng.

We define the selectivity of a detection system as the abilityto select only those compounds of interest in a complexmatrix using specific compound properties. A detector isselective if it does not respond to coeluting compounds that

88

could interfere with analyte quantification. A UV absorbancedetector can be made selective by setting an appropriatewavelength with a narrow bandwidth for the compound ofinterest. However, the selectivity of detectors based on sucha universal feature is low compared with the selectivity ofdetectors based on fluorescence and electrochemistry.Response characteristics are very selective, shown by alimited number of compounds. Mass spectrometers can beapplied selectively or universally (in total scan mode),depending on the analysis to be performed. RI detectorsare universal by definition.

Detector response can be expressed both as dynamic rangeand as linear dynamic range. Dynamic range is the ratio ofthe maximum and the minimum concentration over whichthe measured property (absorbance, current, and so on) canbe recorded. However, in practice, linear dynamic range—the range of solute concentration over which detectorresponse is linear—is more commonly used. Plotting theresponse of injections of different analyte concentrationagainst their concentrations should give a straight line overpart of the concentration range. Response often is linear foronly one tenth of the full dynamic range. UV detectors arelinear over a range of a maximum of five orders of magni-tude, whereas fluorescence and electrochemical detectorsare linear over a range of two orders of magnitude. Massspectrometers are usually linear over three orders of magni-tude, and RI detectors are linear over a maximum of fourorders of magnitude.

A classical identification tool in chromatography is the massspectrogram, which is recorded by a mass spectrometer. Itsappeal in HPLC, however, is limited owing to the cost ofinterfacing the mass spectrometer equipment. If the spectraof the analytes differ markedly, UV absorbance spectra canbe used for identification using diode array technology.Fluorescence and electrochemical detectors can be usedonly to identify compounds based on their retention times.

Linearity

Qualitative information

8

89

Deuterium lamp

Lens

Cut-off filterHolmium oxide filter

Slit

Mirror 1

Mirror 2

Sample diode

Flow cell

Beam splitter

Reference diode

Grating

Figure 55Conventional variable wavelength detector

UV detectors Figure 55 shows the optical path of a conventional variablewavelength detector. Polychromatic light from a deuteriumlamp is focused onto the entrance slit of a monochromatorusing spherical and planar mirrors. The monochromatorselectively transmits a narrow band of light to the exit slit.The light beam from the exit slit passes through the flowcell and is partially absorbed by the solution in the flow cell.The absorbance of the sample is determined by measuringthe intensity of the light reaching the photodiode withoutthe sample (a blank reference) and comparing it with theintensity of light reaching the detector after passing throughthe sample.

Most variable wavelength detectors split off part of the lightto a second photodiode on the reference side. The referencebeam and the reference photodiode are used to compensatefor light fluctuations from the lamp. For optimum sensitivity,

90

the UV detector can be programmed for each peak withina chromatographic run, which changes the wavelengthautomatically. The variable wavelength detector is designedto record absorbance at a single point in the spectrum at any given point in time. However, in practice, differentwavelengths often must be measured simultaneously, forexample when two compounds cannot be separated chromatographically but have different absorbance maxima.If the entire spectrum of a compound is to be measured,the solvent flow must be stopped in order for a variablewavelength detector to scan the entire range, sincescanning takes longer than elution.

Tungsten lamp

Deuterium lamp

Achromatic lens

Holium oxidefilter

Standardflow cell Programmable

slit

190 nm950 nm

1024-elementdiode array

Figure 56Diode array detector optics

8

Sensitive; can be tuned to the wavelengthmaxima of individual peaks. Someinstruments are equipped with scanningmechanisms with stopped-flow operation.

✔ ✘

Single-wavelength measurement is notalways sufficient. Without spectra, peakscannot be identified.

Diode arraydetectors

Figure 52 shows a schematic diagram of a photodiode arraydetector (DAD). An achromatic lens system focuses poly-

91

chromatic light from the deuterium and tungsten lamps intothe flow cell. The light then disperses on the surface of a dif-fraction grating and falls on the photodiode array. The rangevaries from instrument to instrument. The detector shownhere is used to measure wavelengths from 190 to 950 nmusing the twin-lamp design.

In our example, the array consists of 1024 diodes, each ofwhich measures a different narrow-band spectrum. Measur-ing the variation in light intensity over the entire wavelengthrange yields an absorption spectrum. The bandwidth oflight detected by a diode depends on the width of theentrance slit. In our example, this width can be pro-grammed to selected values from 1 to 16 nm. If very highsensitivity is required, the slit is opened to 16 nm for maxi-mum light throughput. If maximum spectral resolution isneeded, the slit is narrowed to 1 nm. At this setting, the finestructure of benzene can be detected, even at 0.7 mAUfull-scale (mAUFS; see figure 57). Because the relative posi-tions of the sample and the diffraction grating are reversedcompared with a conventional instrument, this configura-tion is often referred to as reversed optics. The most signifi-cant differences between a conventional UV absorbancedetector and a DAD are listed at left.

DADs connected to appropriate data evaluation units helpoptimize wavelengths for different compounds over thecourse of the run. Maxima can be seen easily usingthree-dimensional plots of data, or as absorbance intensityplotted over time at different wavelengths, that is, as anisoabsorbance plot (see figure 58). Figure 55 illustrates theoptimization result for antibiotics. The ability to acquire andstore spectra permits the creation of electronic spectrallibraries, which can be used to identify sample compoundsduring method development.

Three dimensions of data

0.7 mAU0.6

0.4

0.2

0

240 260 280 nm

Figure 57High-resolution spectrum for

benzene in the low absorbancerange

Conventional DAD

Signal 1 8acquisition

Spectra stop flow on-line acquisition

92

Figure 58Isoabsorbance plot

11

meticlorpindolmetronidazol nicarbazine

100

260 300 340 3800

Wavelength [nm]

Abso

rban

ce(s

cale

d)

MetronidazolMeticlorpinolSulfapyridineFurazolidonPyrazonIpronidazolChloramphenicolN-AcetylsufapyridineEthopabatBenzothiazuronNicarbazin

1234567891011

100

80

60

40

20

0

mAU

2010 4030Time [min]

275 nm

315 nm

360 nm

1

2

4

5

6,7

8

9

10

Figure 59Multisignal detection of antibiotic

drugs

Multisignal detection yields optimum sensitivity over a widespectral range. However, the spectral axis in figure 58shows that no single wavelength can detect all antibiotics athighest sensitivity.

8

In light of the complexity of most food samples, the abilityto check peak purity can reduce quantification errors. In themost popular form of peak purity analysis, several spectraacquired during peak elution are compared. Normalized andoverlaid, these spectra can be evaluated with the naked eye,or the computer can produce a comparison. Figure 60shows a peak purity analysis of antibiotics. If a spectrallibrary has been established during method development, itcan be used to confirm peak identity. Analyte spectra can becompared with those stored in the library, either inter-actively or automatically, after each run.

93

Figure 60Peak purity analysis

Figure 61 shows both the quantitative and qualitative resultsof the analysis. Part one of this primer contains severalapplications of UV absorbance DAD detection.

94

Enables maximum peak purity andidentity, measurement of multiplewavelengths, acquisition of absorbancespectra, and spectral library searches.

✔ ✘

DADs are best suited for universal ratherthan sensitive analysis (for whichelectrochemical or fluorescence detection is more appropriate).

8

10 20 30

2

6

10

14

18

Match > 950

1

2

3

4

5

6

7

89

10

11

1 ?-*Metronidazole2 ?-*Meticlorpindol3 Sulfapyridine4 Furazolidone

6 ?-*Ipronidazole

7 Chloramphenicol8 N-Acetylsulfapyridine9 Ethopabate10 Benzothiazuron11 *Nicarbazin5 Pyrazon

Peak Purity Check and Identification

* * * * * R E P O R T * * * * * Operator Name: BERWANGER (s1B Vial/Inj.No.: 0/ 1 (s0BDate & Time: 10 Sep 86 9:17 am Data File Name: LH:LETAA00A Integration File Name: DATA:DEFAULT.I Calibration File Name: DATA:ANTI.Q Quantitation method: ESTD calibrated by Area responseSample Info: DOTIERUNGSVERSUCHE Misc. Info: Method File Name: ANTIBI.M Wavelength from: 230 to: 400 nmLibrary File Name: DATA:ANTIBI.L Library Threshhold: 950Reference Spectrum: Apex Peak Purity Threshold: 950Time window from: 6.0 % to: 2.0 % Smooth Factor: 7Dilution Factor: 1.0 Sample Amount: 0.0 Resp.Fact.uncal.peaks: None

Name Amount Peak-Ret. Cal.-Ret. Lib.-Ret Purity Library Res.

[ng/l] [min] [min] [min] Matchfactor

________________________________________________________________________________

Sulfapyridine 10.31 A 12.183 12.143 12.159 999 1000 0.9

Furazolidone 4.54 A 16.096 16.024 16.028 992 984 1.3

Pyrazon 13.72 A 19.024 18.987 19.000 1000 1000 1.7

N-Acetylsulfapyidine 14.66 A 23.307 23.282 23.282 976 1000 1.1

Ethopabat *up 13.40 A 23.874 23.840 23.848 911 996 2.3

Benzthiazuron 12.80 A 24.047 24.024 24.029 998 1000 0.7

Nicarbazin *up 3.00 A 32.733 32.722 32.709 336 984 1.2

========

72.41

Part 2: Quantitation, peak purity check and peak identification

Part 1: General information

Figure 61Quantitative and qualitative results forthe analysis of antibiotic drugs

95

Fluorescencedetectors

Fluorescence is a specific type of luminescence that iscreated when certain molecules emit energy previouslyabsorbed during a period of illumination. Luminescencedetectors have higher selectivity than, for example, UVdetectors because not all molecules that absorb light alsoemit it. Fluorescence detectors are more sensitive thanabsorbance detectors owing to lower background noise.Most fluorescence detectors are configured such thatfluorescent light is recorded at an angle (often at a rightangle) to the incident light beam. This geometry reduces thelikelihood that stray incident light will interfere as abackground signal and ensures maximum S/N for sensitivedetection levels.

The new optical design of the Agilent 1100 Series fluores-cence detector is illustrated in figure 62. A Xenon flashlamp is used to offer the highest light intensities for exci-tation in the UV range. The flash lamp ignites only formicroseconds to provide light energy. Each flash causesfluorescence in the flow cell and generates an individualdata point for the chromatogram. Since the lamp is notpowered on during most of the detector operating time, itoffers a lifetime of several thousand hours. No warmuptime is needed to get a stable baseline. A holographic grat-ing is used as a monochromator to disperse the polychro-matic light of the Xenon lamp. The desired wavelength isthen focused on the flow cell for optimum excitation. Tominimize stray light from the excitation side of the detec-tor, the optics are configured such that the emitted light isrecorded at a 90 degree angle to the incident light beam.Another holographic grating is used as the emission mono-chromator. Both monochromators have optimized lightthroughput in the visible range.

A photomultiplier tube is the optimum choice to measurethe low light intensity of the emitted fluorescence light.Since flash lamps have inherent fluctuations with respectto flash-to-flash intensity, a reference system based on a

Figure 62Schematics of a fluorescence

detector

Xenon flash lamp

Lens

Mirror

Excitationmonochromator

Sample

Photodiode

Lens

Photomultiplier

Emissionmonochromator

96

photodiode measures the intensity of the excitation andtriggers a compensation of the detector signal.

Since the vast majority of emission maxima are above 280 nm, a cut-off filter (not shown) prevents stray lightbelow this wavelength to enter the light path to the emis-sion monochromator. The fixed cut-off filter and band-width (20 nm) avoid the hardware checks and documenta-tion work that is involved with an instrument that hasexchangeable filters and slits.

The excitation and emission monochromators can switchbetween signal and spectral mode. In signal mode they aremoved to specific positions that encode for the desiredwavelengths, as with a traditional detector. This modeoffers the lowest limits of detection since all data pointsare generated at a single excitation and emission wavelength.

A scan of both the excitation and the emission spectra canbe helpful in method development. However, only detectorswith motor-driven gratings on both sides can perform sucha scan. Some of these detectors also can transfer this datato a data evaluation computer and store spectra in datafiles. Once the optimum excitation and emissionwavelength has been determined using scanned spectra,detectors with grating optics can be programmed to switchbetween these wavelengths during the run.

The spectral mode is used to obtain multi-signal or spec-tral information. The ignition of the flash lamp is synchro-nized with the rotation of the gratings, either the excita-tion or emission monochromator. The motor technologyfor the gratings is a long-life design as commonly used inhigh-speed PC disk drive hardware. Whenever the gratinghas reached the correct position during a revolution, theXenon lamp is ignited to send a flash. The flash duration isbelow two microseconds while the revolution of the grat-ing takes less than 14 milliseconds. Because of the rotat-ing monochromators, the loss in sensitivity in the spectral

8

Online spectral measurementsand multisignal acquisition

Cut-off filter

Signal/spectral mode

mode is much lower compared to conventional dual-wave-length detection with UV detectors.

PNA analysis, for example, can be performed with simulta-neous multi wavelength detection instead of wavelength-switching. With four different wavelengths for emission,all 15 PNAs can be monitored (figure 63).

97

Multisignal

1 excitation WL at 260 nm4 emission WL at 350, 420,

440 and 500 nm

Ex=260, Em=350

Ex=260, Em=420

Ex=260, Em=440

Ex=260, Em=500

Ex=275, Em=350, TTReference chromatogram with switching events

0 5 10 15 20 25

LU

0

20

40

60

80

100

120

140

160

180

Time [min]

12

3

5

6

78

9

10

11

12

13 14

154

1 Naphthalene2 Acenaphthene3 Fluorene4 Phenanthrene5 Anthracene6 Fluoranthene7 Pyrene

8 Benz(a)anthracene9 Chrysene10 Benzo(b)fluoranthene11 Benzo(k)fluoranthene12 Benz(a)pyrene13 Dibenzo(a,h)anthracene14 Benzo(g,h,i)perylene15 Indeno(1,2,3-cd)pyrene

1 2 3 4 5

Figure 63Simultaneous multi wavelength detection for PNA-analysis The upper trace was received with traditional wavelength switching.

Ex/Em = 260/420 nmEx/Em = 270/440 nmEx/Em = 260/420 nmEx/Em = 290/430 nmEx/Em = 250/550 nm

12

3

4

5

Electrochemicaldetectors

Electrochemical detection techniques are based on theelectrical charge transfer that occurs when electrons aregiven up by a molecule during oxidation or absorbed by amolecule during reduction. This oxidation or reductiontakes place on the surface of a so-called working electrode.Whether a compound is reduced or oxidized and the speedof the reaction depend on the potential difference betweenthe working electrode and the solution containing thecompounds. From the activation energies and redoxpotentials expressed by the Nernst equation, reaction speedcan be determined. The resulting current is proportional tothe number of reactions occurring at the electrode, which inturn is an indicator of the concentration of the compound ofinterest at the surface.

In the detection process, three electrodes are used: theworking electrode, in which the reaction takes place; thecounter electrode, which applies the potential differencebetween mobile phase and the working electrode; and thereference electrode, which compensates for any change ineluant conductivity (see figure 64). The reference electrodereadings feed back to the counter electrode in order to keepthe potential difference constant during peak elution ascurrent flows through the working electrode.

98

8

Highly specific. Flash lamps eliminatedrawback of baseline drift from heattransfer. Fluorescent tagging improvesdetection limits.

✔ ✘

Fluorescence spectra are not commonlyused to confirm peak identity.

Reference

electrodeWorking

electrode

Cell

V

+

Reference electrode

Counter electrode

Workingelectrode

Cell

V

-+

Figure 64Three-electrode electrochemical

detector

Detector response results from amplification of the electronflow and its subsequent conversion to a signal. Extremelylow currents representing analyte quantities in thepicogram range and below can be measured with today’sadvanced electronics. Although electrochemical detectioncan detect only those substances that can be electrolyzed,this limitation is actually an advantage when applied tocomplicated food matrices because it improves selectivity.To determine the optimum working electrode potential, therelationship between detector response (current) andpotential applied (voltage) must be plotted for eachcompound as a current-voltage (CV) curve, as shown infigure 65. At a potential less than E1, oxidation cannot occurbecause the supply of energy is insufficient. Increasing thepotential to E1/2 will electrolyze 50 % of all molecules at thesurface of the electrode. Maximum response requires apotential just above E2. This potential is known as thelimiting current because any further increase in voltage willlimit detection by raising noise.

Several materials are used in working electrodes, the mostcommon of which is glassy carbon. These materials alsoinclude gold (for sugars and alcohols), platinum (for chlo-rite, sulfite, hydrazine, and hydrogen peroxide), silver (forhalogens), copper (for amino acids), mercury (in reductivemode for thiosulfate), and combined mercury-gold (inreductive mode for nitrogenous organic compounds).

Numerous cell designs have been described in theliterature. The majority can be classified as one of threeprincipal types: thin-layer design, wall-jet design, andporous flow-through design (see figure 66). The porousflow-through cell design differs significantly from the othertwo in that coulometric detection ensures 100 % reactionyield on the surface of the electrode. The other designsallow an efficiency of only 1–10 % by amperometricdetection. However, amperometric detection is usually themore sensitive technique and is preferred over coulometric

99

Current

Optimum potential

0.4 0.6 0.8 1.0Potential [V]

E1/2

E2

E1

Figure 65Current-voltage relationship

Electrode materials

Flow cell aspects

detection. electrochemical detectors can employ 1-µlflow cells and are well-suited to narrow-bore HPLC.

100

8

Reference electrode

Auxilliary electrode

Porous flow-throughThin layer Wall jet

Working electrode

Reference electrode


Reference electrode


Working electrodeWorking electrode

Figure 66Thin-layer design, wall-jet design, and porous flow-through design

Until recently, the electrochemical technique was consid-ered difficult to apply and not stable enough for routineanalysis. However, recent improvements have made the useof these detectors routine, for example in the analysis ofcatecholamines in clinical research and routine testing labo-ratories. When applied between runs or even during peakelution (for example in sugar analysis using gold electrodes),self-cleaning routines based on pulsed amperometryimprove stability (see figure 67).

Although an optimum potential for a mixture of compoundscan be determined by evaluating the voltamograms for eachcompound, these optimizing steps can be automated usingcertain electrochemical detectors in so-called auto-incrementmode. The HPLC equipment runs a series of injections overa range of increasing potentials (defined by start and endpotentials and increment parameter), as shown in figure 68.A drift sensor helps ensure that a specified threshold ismaintained before the next analysis begins (see figure 69).

Automation features

Figure 67Cleaning of working electrode

oxidativecleaning (+1.3 V)

workingpotential (1.2 V)

reductive cleaning (-0.1 V)Pote

ntia

l [V]

Figure 68Autoincrement mode

0.80.9

1.01.1

1.21.3

1.4

4 6 8 10 12Time [ms]

3-Nitrophenolp-Chloro m-cresol

V

Should the electrode surface of the flow cell becomeseverely contaminated, as is likely for food matrixes, thecell must be disassembled and the electrode removed andcleaned in a strong acid or other suitable cleaning agent.Modern detectors are designed for ease of access and disas-sembly. Part one of this primer contains several applica-tions of electrochemical detection.

101

Figure 69Drift trigger

Curr

ent

Falling current -detector not ready

Current steady - detector triggers next injection

Threshold set by drift trigger parameter

BaselineTime [min]

Figure 70Suitability of MS interfaces

Polarity/solubility in water

Mol

ecul

ar w

eigh

t

GC/MS

Particle

Thermo-

beam

spray

Electrospray

Mass spectrometers The identification of complex samples presents a problemfor LC analysis. Coeluting compounds generally can beidentified using UV absorbance detection with diode arraytechnology, but this method may not be specific enoughwhere spectra differences are low. Detection techniquessuch as fluorescence may offer higher specificity than UVdetection, but if many different compounds are to be ana-lyzed, these techniques also may not yield desired results.With mass spectroscopy (MS), several different analyteclasses in a wide variety of sample types can be identifiedwith greater certainty. Although GC/MS is a well-establishedtechnique for food analysis, LC/MS is only now emerging asa useful tool in this area. A GC-based analysis is appropriateonly for those food compounds that are volatile and ther-mally stable (see figure 70). However, many compounds arenonvolatile, extremely polar, or thermally labile. Such com-pounds often can be separated successfully with LC, andthe development of improved interfaces has made LC/MSmore popular.

Mass spectrometers nevertheless are more easily interfacedwith GC equipment than with LC equipment. The table atleft lists the different operational conditions of LC and MS.Early efforts to interface LC with MS used direct liquidinjection and moving-belt interfaces, but these methodsproved ineffective and unreliable. In the 1980s, thermosprayand particle beam interfaces improved both the range ofapplicability and the reliability of LC/MS. However, low sen-sitivity, the narrow mass and polarity range of analytes, andfrequent maintenance requirements limited the effective-ness of these interfaces. More recently, two atmosphericpressure ionization (API) interfaces—electrospray andatmospheric pressure chemical ionization (APCI)—havereplaced almost completely thermospray and particle beamtechniques. These interfaces have a broad range of analytemolecular weights and polarities, high sensitivity, improvedusability, and reduced maintenance needs. Selection of theappropriate LC/MS interface for an application depends onfactors such as the polarity, molecular weight, and thermallability of the analyte.

In electrospray, effluent is directed through a nebulizingneedle into a high-voltage field where charged droplets areformed (see figure 71). The charged droplets are then dried

102

8

API interfaces

+++ +

++

+

+ + + +++

+

HPLC inlet

NebulizerSkimmers Octopole

Fragmentationzone (CID)

LensesQuadrupole

Capillary

Figure 71API-electrospray LC/MS interface

HPLC MSHigh pressure High vacuumliquid phase requiredseparation

Produces large Typical MSquantities of vacuum systemsvolatilized solvent designed for low(100–1000 ml/min ml/min gas loadgas)*

No mass range Depends onlimitation masss/charge

and mass rangeof analyzer

Can use Prefers volatileinorganic buffers buffers

* About 1000-fold increase going from liquid to gasphase with typical LC solvent

and, as they shrink, analyte ions are desorbed. The ions are transported to the mass analyzer through a series ofvacuum stages and ion-focusing elements.

Electrospray ionization can produce multiply charged ionsof macromolecular analytes such as proteins and peptides.Because mass analyzers separate ions based on mass-to-charge ratio (m/z), lower-cost mass spectrometers withmass ranges of several thousand m/z can be used to analyzecompounds in excess of 150,000 daltons. The primary use ofelectrospray has been the analysis of compounds of highermolecular weight. However, this technique also has beenapplied successfully to small polar molecules. Fig. 72 showsa separation of carbamate pesticides using electrospray.

103

HPLC inletNebulizer

Skimmers Octopole

Capillary

Corona needle

Fragmentationzone (CID) QuadrupoleLenses

+ ++ +

+

Figure 73APCI LC/MS interface

Time [min]0 10 20

Abun

danc

e

1 Aldicarb sulfoxide 2 Aldicarb sulfone 3 Methomyl 4 3-hydroxycarbofuran

5 Aldicarb 6 Carbofuran 7 Carbaryl 8 Methiocarb1 2

3

4 5

6 78

Figure 72Carbamate analysis

APCI also can be used to analyze moderate polarityanalytes. As in electrospray, APCI ionization occurs atatmospheric pressure via a chemical ionization process (see figure73).

Refractive indexdetectors

Refractive index (RI) detection is based on the difference inRI between the solution in the sample cell and the puremobile-phase solution in the reference cell. Because thecomposition of the eluents must remain fixed throughoutthe analysis, this detector is not suitable for gradient analysis.Four main types of RI detectors are available: deflectionaccording to Snell’s law, reflection according to Fresnel’slaw, interference, and Christiansen effect. The first, whichuses the dual-cell design, is by far the most popular.However, the nearly designed Agilent 1100 Series refractiveindex detector allows detection limits to the low ng range.Because RI detectors lack sensitivity and exhibit a tendencyto drift owing to temperature changes, they are used prima-rily in the analysis of carbohydrates and nonaromatic acids.

104

<- [M + NH4]+

Abundance

100000

80000

60000

20000

40000

603 639 987

400 600 1000800m/z

Figure 74Mass spectrum of the fatty acid

triolein (C18:1, [cis]-9)molecular weight = 884.781

molecular formula = C57H104O6

8

APCI requires some compound volatility and is less suitablefor highly thermally labile compounds. Figure 74 shows atypical triglyceride mass spectrum. Both the degree ofunsaturation and the length of the fatty acid side chains canbe determined from the [M + NH4] + ion, which correspondsto mass M + 18. In-source CID experiments also can behelpful in determining the fatty acid composition of chro-matographic peaks. Full-scan methods allow easy identifi-cation at the low nanogram level. If more precisequantitation is required, selected ion mode (SIM) can beused to obtain detection limits at the low picogram level.

Polar and semipolar compounds up to150,000 daltons can be analyzed. Highlysensitive. Strong molecular ions.Fragments, depending on in-source CIDparameters.

✔ ✘

Data analysis for complex heterogeneousmixtures of multiply charged analytes isnot straightforward. Matrix can interferewith the ionization process.

Universal detector.

✔ ✘

Low sensitivity, no gradient operation.

105

The following table reviews the detection techniquesdiscussed in this chapter—your decision ideally shouldreflect a balance between desired results and financialresources.

Detector Sensitivity Selectivity Advantages Applications

UV variable + - Low cost, Organic acids, fattywavelength universal acids after derivatization,

inorganic anions

UV-DAD + + Peak purity Antioxidants,confirmation preservatives, flavors,

colorants, antiparasiticdrugs, mycotoxins,pesticides, vitamins,amines afterderivatization

Fluorescence ++ + High sensitivity Artificial sweeteners,mycotoxins, vitamins,carbamates, glyphosate

Electro- ++ + High sensitivity Vitamins, inorganicchemical anions

Mass spectro- - ++ Identity, Carbamates, lipidsmeter scan structure

Mass spectro- ++ ++ High selectivity Pesticides, proteinsmeter SIM

RI - - Universal Carbohydrates,nonaromatic acids

In brief…

106

Chapter 9Derivatizationchemistries

Addition of UV-visiblechromophores

When analyte concentrations are particularly low,

sample handling equipment for chemical derivatization

can enhance the sensitivity and selectivity of results.

As discussed in chapter 6, such equipment is

available both pre- and postcolumn. In this chapter,

we detail the chemistries that can be applied to food

compounds and list the detection techniques for

which they are best suited.

Labeling compounds with reagents that enable UV absorp-tion is one of the most popular derivatization techniques.The reagent should be selected such that the absorptionmaximum of the reaction product exhibits not onlyimproved sensitivity but also good selectivity. This combi-nation reduces matrix effects resulting from the reagent,from by-products, or from the original matrix. The followingtable lists common compounds and reactions. In part one ofthis primer we give examples of compound derivatization,including that of fatty acids and amino acids.

Target compound Reagent λ

Alcohols -OH phenylisocyanate 250 nm

Oxidizable sulfur SO32- 2,2’-dithiobis (5-nitro-pyridine) 320 nm

compounds

Fatty acids -COOH p-bromophenacyl bromide 258 nm2-naphthacyl bromide 250 nm

Aldehydes and -CO-COOH, 2,4-dinitrophenyl hydrazine 365 nmketones =C=O, and -CHO

Primary amines -NH2 ο-phthalaldehyde (OPA) 340 nm

Primary and NHR 9-fluorenylmethyl chloroformate 256 nmsecondary amines (FMOC)

108

9

109

Fluorescence is a highly sensitive and selective detectiontechnique. Adding fluorescent properties to the molecule ofinterest is of particular benefit in food analysis, in whichcomponents must be detected at very low concentrations.The following table lists common fluorescent tags. In partone of this primer we give examples for carbamates41 andglyphosate.42

Target compound Tagging reagent λ

Alcohols -OH phenylisocyanate λex 230 nm, λem 315 nm

Primary amines -NH2 o-phthalaldehyde λex 230 nm, l em 455 nm(OPA)

Primary and NHR 9-fluorenylmethyl, λex 230 nm, l em 315 nmsecondary amines chloroformate

(FMOC)

Precolumn techniques can be run either offline or online,but postcolumn techniques should be run online formaximum accuracy. In postcolumn derivatization, reagentscan be added only through supplementary equipment (seefigure 75) such as pumps. Mixing and heating devices alsomay be required. Increasing the dead volume behind thecolumn in this way will result in peak broadening. Althoughthis broadening may have no effect on standard-borecolumns with flow rates above 1 ml/min, postcolumnderivatization is not suitable for narrow-bore HPLC.

Addition of a fluorescent tag

Precolumn or postcolumn?

Water Methanol

Column compart-ment

Auto-

Pickeringsystem

sampler



Fluorescencedetector

Figure 75Pickering postcolumn

derivatization equipment for theanalysis of carbamates

110

Both pre- and postcolumn derivatization techniques can beautomated with modern HPLC equipment. The single-stepmechanical functions of an autoinjector or autosampler canbe programmed prior to analysis and stored in an injectorprogram (see left). These functions include aspiration of thesample and of the derivatization agent, and mixing.Precolumn derivatization is fully compatible withnarrow-bore HPLC and can result in fivefold improvementsin S/N, with much lower solvent consumption than thatfrom standard-bore methods. The analysis of fatty acids inpart one of this primer illustrates this principle.

Automatic derivatization

9

Derivatization improves detectability oftrace species. It can be automated andintegrated online within the analysis.Many chemistries have been developedfor routine use both pre- and postcolumn.

✔ ✘

Additional investment in equipment.

1 Draw 1.0 µl from vial 122 Draw 0 µl from vial 03 Draw 1.0 µl from vial 84 Draw 0 µl from vial 05 Draw 1.0 µl from sample6 Draw 0 µl from vial 07 Mix 8 cycles8 Draw 1.0 µl from vial 129 Inject

Derivatization offers enhanced analytical response, whichis of benefit in food analysis. Chemical modifications canbe automated either before or after separation of thecompounds under study. In precolumn derivatization,autoinjectors with sample pretreatment capabilities (seechapter 6) are used, whereas in postcolumn derivatiza-tion, additional reagent pumps are plumbed to the chro-matograph upstream of the detector. The latter approachadds dead volume and therefore is not suitable for thenarrow-bore column technique described in chapter 4.

In brief…

Chapter 10Data collectionand evaluation techniques

Regardless which detection system you choose for your

laboratory, the analytical data generated by the instrument

must be evaluated. Various computing equipment is available

for this task. The costs depend on the reporting requirements

and on the degree of automation required.

Depending on individual requirements, increasingly complextechniques are available to evaluate chromatographic data: at the simplest level are strip chart recorders, followed byintegrators, personal computer–based software packagesand, finally, the more advanced networked data systems,commonly referred to as NDS. Although official methodspublished by the U.S. Environmental Protection Agency(EPA) and by Germany’s Deutsche Industrienorm (DIN)provide detailed information about calculation proceduresand results, they give no recommendations for equipment.

Strip chart recorders traditionally have been used in connec-tion with instruments that record values over a period of time.The recorder traces the measurement response on scaledpaper to yield a rudimentary result. In the age of electronicdata transfer, such physical records have been largely sur-passed by data handling equipment preprogrammed to makedecisions, for example to reject peaks that lie outside a cer-tain time window.

112

10

Inexpensive.

✔ ✘

No record of retention times, noquantitative results on-line, no automaticbaseline reset between runs, noelectronic storage.

Strip chartrecorders

113

Integrators offer several advantages over strip chart record-ers and consequently are becoming the minimum standardfor data evaluation. Integrators provide a full-scale chro-matographic plot and multiple report formats. Area percent,normalization, and external and internal standard calcula-tions are basic features of almost all modern integrators.Annotated reports list amounts, retention times, calculationtype (peak areas or heights), and integration parameters aswell as the date and time of measurement. Advanced fea-tures may provide for automated drawing of the baselinesduring postrun replotting and for the plotting of calibrationcurves showing detector response. For unattended analysesin which several runs are performed in series, integratorsnormally are equipped with a remote control connected tothe autosampler in the system. Most models can also storeraw data for replotting or reintegration at a later date. Someinstruments have computer programming capabilities andcan perform more advanced customized statistical calcula-tions using the BASIC programming language, for example.Multichannel integrators are available for some analyticalmethods requiring two or more detection signals.

Inexpensive. Facilitates reporting ofretention times, quantitative results, andautomatic baseline resets.

✔ ✘

No instrument control or reportcustomization.

Integrators

114

In recent years personal computers (PCs) have becomeincreasingly popular as data analysis tools in analytical lab-oratories. PCs offer more flexibility and better data storagecapabilities than traditional storage methods. Moreover,on-line functions such as word processing, spreadsheetanalyses, and database operations can be performed simul-taneously (see figure 76). Through computer networks, lab-oratory instruments can be interconnected to enable thecentral archival of data and the sharing of printer resources.Client/server-based software extends these capabilities bydistributing the processing across multiple processing unitsand by minimizing the time spent validating software.With PCs, all aspects of the HPLC system can be accessedusing a single keyboard and mouse. Parameters for all mod-ules, including pump, detector, and autosampler, can beentered in the software program, saved to disk, and printedfor documentation. Some HPLC software programs includediagnostic test procedures, instrument calibration proce-dures, and extensive instrument logbooks, all of which canfacilitate the validation processes of various regulatoryagencies. Such complementary functions, although not

Personal computers

10

Figure 76Cross sample reports regression analyses, trend charts and other calculations consolidate sample data, enhancing the overall productivity and efficiency of the laboratory

115

directly related to the control of the equipment, are moreeasily built into a software program than into the equipmentitself. In fact, many GLP/GMP features are added to everynew version of the software programs sold with HPLCequipment (see figure 77). For example, in some chroma-tography software, the raw data files can store more thanjust signal data. A binary check-sum protected file storesinstrument parameters (system pressure, temperature, flow,and solvent percent) as well as all aspects of the analyticalmethod, including integration events, calibration settings,and a date-stamped logbook of events as they occurred dur-ing the run. Additionally, with spectral libraries, compoundscan be identified not only on the basis of their elution pro-file but also according to their spectral characteristics. Suchprocedures can be fully automated to reduce analysis timeand user interaction.

Figure 77Maintenance and diagnosis screen

A single PC running the appropriate chromatography soft-ware can process data from several detectors simulta-neously. This feature is particularly useful in analyses inwhich sensitivity and selectivity must be optimized to differ-ent matrices and concentrations. For example, in the analy-sis of polynuclear aromatic hydrocarbons, UV absorbanceand fluorescence detection are applied in series. The PCdisplays graphically the chromatographic signals and spec-tra, enabling detailed interpretation of the data. Softwarepurity algorithms can be used to help determine peakhomo-geneity, even for coeluting peaks.

Flexible software programs can report data in both stan-dard and customized formats. For example, some chroma-tography software can be programmed to yield results onpeak purity and identification by spectra or, for more complex analyses, to generate system suitability reports.Any computer-generated report can be printed or storedelectronically for inclusion in other documents. PCs arewell-suited for the modification of calibration tables and forthe reanalysis of integration events and data. The softwaremust record such recalculation procedures so that the analysis can be traced to a particular set of parameters inaccordance with GLP/GMP principles.

A computer can automate entire sequences of unattendedanalyses in which chromatographic conditions differ fromrun to run. Steps to shut down the HPLC equipment alsocan be programmed if the software includes features forturning off the pump, thermostatted column compartment,and detector lamp after completion of the sequence. If theHPLC equipment malfunctions, the software reacts to pro-tect the instrumentation, prevent loss of solvents, and avoidunnecessary lamp illumination time. A good software appli-cation should be able to turn off the pump, thermostattedcolumn compartment, and detector lamp in the event of aleak or a faulty injection. System suitability tests also can beincorporated in a sequence. When performed on a regular

116

10

basis, such tests can validate assumptions about perfor-mance of the analytical system and help verify results.

117

Enables control of multiple instruments.Additional software can be used formany other tasks. Provides for better datastorage and archival.

✔ ✘

Requires more bench space forperipherals such as printers or plotters.

Integrates multiple techniques andinstruments from multiple vendors. Savesbench space and computer processingresources. Access to network utilitiessuch as e-mail.

✔ ✘

Data processing features may not matchthose of dedicated data analysis softwareapplications.

Local area networks A laboratory running food analyses frequently requires multiple instruments from multiple instrument vendors forsample analysis. Although the integrators and PC systemsdescribed above can evaluate data at analytical instrumentstations throughout the laboratory, this data must be col-lected centrally—over a network, for example—in order togenerate a single report for multiple analytical techniques.Local area networks (LANs) offer several advantages inaddition to shared data processing (see figure 78). Central-ized printing saves bench space and reduces equipmentexpenses, and centralized file security through a singlecomputer—the server—accelerates data backup. Standardnetwork software and hardware cannot handle data filesfrom diverse analytical instrument vendors. The analyticalsoftware therefore should have file conversion utilitiesbased on the Analytical Instrument Association ANDI fileformat (*.cdf).

Figure 78A laboratory LAN —

connecting instruments andcollating analytical results

Shared printingperipherals

Networked data systems

The Agilent ChemStation remote access and data storagemodules combine isolated islands of data into a powerfulclient/server networked information system. Each AgilentChemStation becomes a network client. It is possible tooversee and control all laboratory operations securely andeasily from any computer on the network. The progress ofeach analysis is monitored to ensure the quality of theresults the first time the sample is analyzed. Appropriateaction can be taken with the access remote capability from wherever you happen to be if the performance looks suspect. Laboratory data is automatically stored on onecentralized and secure server system.

118

10

Which data handling technique is most effective and eco-nomical for your laboratory depends on several factors:• the size of the laboratory• the role of the laboratory in the organization• industrial testing, public safety testing, and so on• the demands on sample throughput• the range of analytes under studyFor laboratories with few instruments and low samplethroughput, integrator systems normally suffice, althougha PC may be more appropriate for automated operation ofmultiple HPLC instruments. A client/server networked datasystem helps consolidate documentation and validationprocesses for multiple techniques and instruments frommultiple vendors.

In brief…

Chapter 11Factors thatdetermineperformance in HPLC

The analysis of food samples places high demands on

HPLC equipment, notably in the areas of performance, stability,

and reliability. Modern evaluation software enables you to

determine the suitability of a particular piece of HPLC

equipment for analysis. The factors that influence the outcome

of a measurement thus can be identified before results are

published to confirm assumptions made during analysis or to

draw attention to erroneous data.

In this chapter we focus on those instrument-relatedparameters that strongly influence the limit of detection(LOD) and the limit of quantification (LOQ). We alsodiscuss the accuracy, precision, and qualitative informationthat an HPLC system can provide. Some vendors addressthe performance of specific instrumentation in technicalnotes.43 Such notes include detailed performance testprocedures and results for individual modules as well as forcomplete HPLC systems.

120

11

121

The principle determinant of the LOD in HPLC is theresponse of the detector to the compound of interest. Theresponse factor thus depends primarily on the choice ofdetection technique. However, regardless of the quality ofthe detector, the LOD or LOQ remains a function of peakheight. This height can sink if the peak is allowed todisperse within the surrounding liquid in the flow path. Allparts of the flow path in front of the detector thereforemust be designed to limit broadening and flattening of theresponse.

A minimum of narrow capillaries between injector andcolumn and from column to detector helps keep deadvolume low. With low injection volumes, separationefficiency of the column can be utilized to the maximum,thereby improving peak height. In other words, the lowerthe column volume, the lower the peak volume eluted.Other factors that influence peak dispersion include pumpperformance, degassing efficiency, capacity factor (k’), andcolumn particle size. Any improvements can be registeredby calculating the S/N of the analyte. Indeed, the noise ofthe detector should be tested regularly in this way to ensurethat performance is maintained. Dead volume of thecomplete injection system can be determined by firstinjecting a tracer mobile-phase additive into the flow pathwith the column disconnected and then recording the timethis additive takes to reach the detector at a particular flowrate. The flow cell volume of the detector should be as lowas possible, whereas its pathlength should be as long aspossible, according to Beer’s law.

Maximizing analyte response is not sufficient to ensuregood results, however, since the level of background noisefrom the detector can counter any gains made. In particular,the performance of the pump in combination with certainsolvents can increase detector noise level, as described inchapter 7. Degassing is necessary in order to avoid gas

Limit of detectionand limit ofquantification

122

bubbles, which can cause noise or spikes, or oxygenquenching in fluorescence.

High k’ values result from higher elution volume or fromlonger retention time. These values are accompanied bybroader peak width and smaller peak height, that is, peakswith longer retention times have poorer S/N. The use ofdifferent columns, different mobile phases, and differentflow rates can improve S/N. Packing material also directlyinfluences peak dispersion; for example, smaller-sizedparticles reduce peak dispersion.

Accuracy is the degree of agreement between test resultsand true values. It is influenced by the analytical method,the extraction procedure used, and the choice of column ordetector. Prior to the adoption of any HPLC method for rou-tine use, the degree of agreement with an established refer-ence method should be determined, or a control run shouldbe performed with a known quantity of spiked samplematrix. In practice, however, the degree of agreement willnever reach 100 %. This mismatch can be corrected by cali-bration with standards of known concentration and, basedon these results, by calculating the accurate results from anunknown sample. Inclusion of an external or internal stan-dard calibration procedure ensures accuracy in food analysis.The precision of a method is the degree of agreementamong individual test results when an analysis is appliedrepeatedly to multiple samplings. Precision is measured byinjecting a series of standards and then calculating the rela-tive standard deviation of retention times and areas or peakheights. Precision may be measured at three levels: repeat-ability, intermediate precision, and reproducibility. Repeat-ability is associated with an analysis performed in onelaboratory by one operator using a single piece of equipmentover a relatively short time period. Intermediate precision is

11

Accuracy andprecision

123

the long-term variability of the measurement processfor a method performed within one laboratory but on differ-ent days. Reproducibility applies to an analysis performedin more than one laboratory. Any HPLC method used infood analysis should be tested for both repeatability andreproducibility.

The precision of a method is strongly influenced by theperformance of the HPLC instrumentation. Repeatability offlow rates, gradient formation, and injection volumes canaffect precision, as can response stability of the detector,aging of the column, and temperature stability of thecolumn oven. The equipment should be inspected on aregular basis using the test methods recommended by thesupplier to ensure reliability, high performance, and goodanalytical results.

HPLC analytes can be identified on the basis of theirretention times and either their UV-visible or mass spectra.Compounds, on the other hand, are identified primarilyaccording to the degree of agreement between retentiontimes recorded using calibration standards and thoseobtained from the sample. Unfortunately, co-eluting peakscan falsify results obtained with samples containingunknowns, especially for food matrices such as meat,vegetables, or beverages. In such cases, samples often canbe identified using UV-visible spectral information. A diodearray detection system enables online acquisition, and anumber of software packages offer automatic evaluation,for example for the analysis of polynuclear aromatichydrocarbons (PNAs) and pesticides.41

Qualitative information

Referencesand Index

Part Three

References

14. W. Specht, “Organochlor- und Organo-phosphor-Verbindungen sowie stickstoffhaltige sowie anderePflanzenschutzmittel”, DFG-Methodensammlung, 1982, 19.

15. ”A new approach to lower limits of detectionand easy spectral analysis”, Agilent Primer 5968-9346E, 2000.

16. R. Schuster, “A comparison of pre-and post-column sample treatment forthe analysis of glyphosate”,Agilent Application Note5091-3621E, 1992.

17. A.G. Huesgen, R. Schuster, ”Analysisof selected anions with HPLC andelectrochemical detection”,Agilent Application Note5091-1815E, 1991.

18. “Determination of triglycerides invegetable oils”, EC Regulation No.L248, 28ff.

19. L.M. Nollet, Food Analysis by HPLCNew York, 1992.

20. A.G. Huesgen, R. Schuster, “Analysisof selected vitamins with HPLC andelectrochemical detection”,Agilent Application Note5091-3194E, 1992.

21. O. Busto, et al. “Solid phaseextraction applied to thedetermination of biogenic amines inwines by HPLC”, Chromatographia,1994, 38(9/10), 571–578.

22. “Sensitive and reliable amino acid analysis in protein hydrolysates using the Agilent 1100 Series”, Agilent Technical Note, 5968-5658E, 2000

23. R. Schuster, “Determination of aminoacids in biological, pharmaceutical,plant and food samples by automatedprecolumn derivatisation and HPLC”,J. Chromatogr., 1988, 431, 271–284.

24. Capillary Liquid Chromatography withthe Agilent 1100 Series Modules andSystems for HPLC”, AgilentTechnical Note 5965-1351E, 1996.

01. D.N. Heiger, “High PerformanceCapillary Electrophesis–AnIntroduction”, Agilent Primer5968-9936E, 2000.

02. CD-ROM ”CE Partner”, Agilent publication 5968-9893E

03. CD-ROM ”CE Guidebook”, Agilent publication 5968-9892E

04. Official Methods of Analysis, FoodCompositions; Additives, NaturalContaminants, 15th ed; AOAC:Arlington, VA, 1990, Vol. 2.

05. A.M. Di Pietra, et al., “HPLC analysisof aspartame and saccharin inpharma- ceutical and dietaryformulations”, Chromatographia,1990, 30, 215–219.

06. A.G. Huesgen, R. Schuster, “Sensitiveanalysis of synthetic colors usingHPLC and diode-array detection at190–950 nm”, Agilent Application Note 5964-3559E, 1995.

7. A. Herrmann, et al., “Rapid control ofvanilla-containing products usingHPLC”, J. Chromatogr., 1982, 246,313–316.

08. Official Methods of Analysis;W. Horwitz, Ed.; 14th ed.; AOAC:Arlington, VA, 1984; secs 12.018–12.021.

09. H. Malisch, et al., “Determination ofresidues of chemotherapeutic andantiparasitic drugs in food stuffs ofanomaly origin with HPLC and UV-Visdiode-array detection”, J. Liq.Chromatogr., 1988, 11 (13), 2801–2827.

10. EC Guideline 86/428 EWG 1985.

11. M.H. Thomas, J. Assoc. Off. Anal.;1989, 72 (4) 564.

12. Farrington et. al., “Food Additives andContaminants”, 1991, Vol. 8, No. 1,55-64”.

13. Lebensmittel- undBedarfsgegenständegesetz,Paragraph 35, Germany.

126

38. W.O. Landen Jr., J. Assoc. Off. Anal.Chem., 1985, 68, 183.

39. L. Huber, “Good laboratory practice forHPLC, CE and UV-Visible spectroscopy”,Agilent Primer, 5968-6193E, 2000

40. R. L. Grob, M. A. Kaiser,“Environmental problem solving usinggas and liquid chromatography”, J. Chromatogr. ,1982, 21.

41. A. G. Huesgen et al., “Polynucleararomatic hydrocarbons by HPLC”,Agilent Application Note,5091-7260E, 1992.

42. R. Schuster, “A comparison of pre-and postolumn sample treatment forthe analysis of glyphosate”,Agilent Application Note,5091-3621E, 1992.

43. H. Godel, “Performancecharacteristics of the HP 1100 Seriesmodules and systems for HPLC,”Agilent Technical Note,5965-1352E, 1996.

25. R. W. Frei and K. Zech, “Selectivesample handling and detection inHPLC”, J. Chromatogr. 1988, 39A.

26. D. R. Gere et al., “Bridging theautomation gap between samplepreparation and analysis: an overviewof SFE, GC, GC/MSD and HPLCapplied to several types ofenvironmental samples”,J. Chromatogr. Sci., 1993, July.

27. M.A. Schneidermann, et al., J. Assoc.Off. Anal. Chem., 1988, 71, 815.

28. R.Schuster, “A comparison of pre- andpostolumn sample treatment for theanalysis of glyphosate”,Agilent Application Note5091-3621E, 1992.

29. M. Verzele et al., J. Am. Soc. Brew.Chem., 1981, 39, 67.

30. W.M. Stephen, “Clean-up techniquesfor pesticides in fatty foods”, Anal.Chim. Acta, 1990, 236, 77–82.

31. J.E. Farrow, et al., Analyst 102, 752

32. H. Schulenberg-Schell et al., Posterpresentation at the 3rd InternationalCapillary ChromatographyConference, Riva del Garda, 1993.

33. S. K. Poole et al., “Sample preparationfor chromatographic separations: anoverview”, Anal. Chim. Acta, 1990,236, 3–42.

34. R. E. Majors, “Sample preparationperspectives: Automation of solidphase extraction”, LC-GC Int. 1993, 6/6.

35. E. R. Brouwer et al., “Determination ofpolar pollutants in river water usingan on-line liquid chromatographicpreconcentration system,”Chromatographia, 1991, 32, 445.

36. I. McMurrough, et al., J. Am. Soc.Brew. Chem., 1988.

37. K. K. Unger, Handbuch für Anfängerund Praktiker, 1989, Git Verlag,Germany.

127

128

129

Index

bitter compounds, 12, 14bromophenacyl bromide, 38butocarboxim, 28butocarboxim sulfone, 28butocarboxim sulfoxide, 28butter, 38butyric acid, 38

Ccalibration

curves, 113settings, 115tables, 116

capacity factor, 121capillary electrophoresis, Vcapillary liquid chromatography, 52carbamates, 26,103,109carbaryl, 28carbendazim, 27carbofuran, 28carbohydrates, III, 40, 41Carrez, 7, 14cell design (electrochemical)

porous flow-through, 99, 100thin-layer, 99, 100wall-jet, 98, 100

cellobiose, 39cereals, 19, 20cheese, 48chemical residues, 16chemotherapeutics, 16chewing gum, 5chiral drug, Vchloramphenicol, 15chlorite, 99chlorpyripho-ethyl, 27chromophore, 38, 108citric acid, 2, 3, 43cleanup, 54client/server-based software, 114cognac, 13collision induced dissociation (CID), 19colorants, III, 10column

guard, 59, 67narrow-bore, 59standard-bore, 59temperature, 60

adsorption chromatography, 59adulteration, 35aflatoxins, 21, 22, 23, 60alcohols, 108alcoholysis, 45aldehydes, 108aldicarb, 28aldicarb sulfone, 28aldicarb sulfoxide, 28alducarb, 28alkaline hydrolysis, 45amines, 48

primary, 108secondary, 108

amino acids, V, 50, 99ammonia, 48AMPA, 29amperometric detection, 98amylamine, 48animal feed, 18, 21, 22, 44anions, 33

inorganic, 32antibiotics, IIIantioxidants, III, 4, 63apples, 21, 22artificial sweeteners, III, 8ascorbic acid, 4aspartame, 8atmospheric pressure chemical ionization

(APCI), 102 - 104autoincrement mode, 100automated injector, 72autosampler, 72, 109

Bbackflash valve, 67bacteria, 15BASIC programming language, 112beer, 48, 50Beer's law, 121benzoic acid, 6benzothiazuron, 16BHA butylated hydroxyanisole, 4BHT butylated hydroxytoluene, 4biogenic amines, 48biotin, 43biphenyl, 84bisphenol A (BADGE), 24

Numerics1,4-diaminobutan, 481 5-diaminopentane, 481-butylamine, 481-naphthol, 282,2'-dithiobis (5-nitro-pyridine), 1082,4-dinitrophenyl hydrazine, 1082-naphthacyl bromide, 1082-phenylphenol, 583-hydroxycarbofuran, 283-ketocarbofuran, 283-methylbutylamine, 489-fluorenylmethyl chloroformate

(FMOC), 108

Aabsorption spectrum, 91accreditation standards, 59accuracy, 120, 122acesulfam, 8acetic acid, 2acids

3,3'-thiodipropionic, 4acetic, 2adipic, 2amino, 50ascorbic, 4benzoic, 5butyric, 38citric, 2, 3, 43fatty, 35, 38, 60,108folic, 43fumaric, 2lactic, 2malic, 2mercapto-propionic (MPA), 9nordihydroguaiaretic, 4oxalic, 3panthothenic, 43phosphoric, 2propionic, 2, 5sorbic, 2, 6succinic, 2tartaric, 2

acidulants, 2, 3additives, IIIadipic acid, 2

130

131

fluorescence detection, 109fluorescence detector, 87, 95, 105fluorescent tag, 109folic acid, 43folpet, 27Food and Drug Administration (FDA), Vfood colors, 10fragmentation, 19fructose, 40fruit juices, 6fruits, 28fumaric acid, 2fumonisins, 19fungi, 15, 21furazolidone, 15

Ggalactose, 40gel permeation chromatography (GPC),27, 66glassy carbon, 99GLP/GMP principles, 114glucose, 40glycerol, 3glyphosate, 26, 29gold, 99good laboratory practice (GLP), 67gradient

elution, 76formation, 77high pressure, 80low-pressure, 78

guard column, 59, 67

Hhalogens, 99hesperidin, 12, 14hexylamine, 48histamine, 48hormones, IIIhumulon, 12hydrazine, 99hydrogen peroxide, 99hydrolysis, 38hydroperoxides, 35, 36

direct solvent extraction, 45drift, 87drift trigger, 101drinking water, 26, 33dual-lamp design, 10dual-piston mechanism, 78dyes, Vdynamic range, 88

Eeggs, 16,17electrochemical detector, 86, 87, 98, 105electroconductivity detector, 32electrospray ionization, 102, 103elution order, 60emission, 96, 97emission grating, 95enzymatic hydrolysis, 45essential oils, 12ethanol, 3ethanolamine, 48ethiofencarb, 28ethiofencarb sulfone, 28ethiofencarb sulfoxide, 28ethopabat, 16ethylamine, 48excitation, 96, 97excitation grating, 95extinction coefficients, 87extraction

liquid-liquid, 65solid-phase, 63, 65supercritical fluid, 64

Ffats, 35, 37, 38fatty acids, 35, 38, 60, 108fertilizers, IIIfigs, 21, 22fish, 48flavors, III, 12flour, 21, 30flow

precision, 79ranges, 76rates, 76

compressibility, 79computer networks, 114computing equipment, 112conductivity detector, 86copper, 99corn, 41coulometric detection, 98counter electrode, 98cross sample reports, 114

Ddairy products, 22dansyl chloride, 49data

evaluation, 112generation, 112storage, 114

dead volume, 59, 71, 121DEG, 3degassing, 82

helium, 83ultrasonic, 83vacuum, 83, 84

derivatization, 73chemical, 62, 108postcolumn, 109, 110precolumn, 109, 110

detectionamperometric, 98coulometric, 99

detector, 86-105conductivity, 86diode array, 86, 90, 105electrochemical, 86, 87, 98, 105electroconductivity, 32fluorescence, 87, 95, 105mass spectrometer, 86, 88, 101, 105refractive index, 86, 87, 104response, 88thermal energy, 86UV, 89, 90variable wavelength, 89, 90, 105

deuterium lamp, 10, 90, 92DG dodecyl gallate, 4diagnostic test, 114diethylamine, 48diode array detector, 87, 91diquat, 26

132

NN-acetyl metabolite, 15naringenin, 12, 14narrow-bore column, 59natural sweeteners, IIINernst equation, 98networked data systems, (NDS), 112, 118nicarbazin, 16nitrites, 32nitro compounds, 27nitrofurans, 16NOGA nordihydroguaiaretic acid, 4noise, 87, 122normalization, 113normal-phase column, 46, 47nuts, 21, 22

Ooat seedlings, 52, 53ochratoxin A, 21, 22OG octyl gallate, 4oils, 35 - 38one-lamp design, 10online spectral measurements, 96o-phthalaldehyde (OPA), 9, 108orange juice, 14organic acids, Voxalic acid, 3oxamyl, 28oxidizable sulfur compounds, 108oxytetracycline, 18

Ppantothenic acid, 43paprika, 27paraquat, 26partition phases, 58Patent blue, 10patuline, 21, 22p-bromophenacyl bromide, 108peak

co-eluting, 123dispersion, 121, 122elution, 93identity, 93, 94purity, 93, 94

limit of detection (LOG), 87, 120, 121limit of quantification (LOQ), 87, 120, 121linearity, 87, 88lipids, 35liquid-liquid extraction, 65local area network (LAN), 117long-term variability, 123luminescence, 95lupulon, 12

Mmalic acid, 2maltose, 40mannitol, 40manual injector, 71margarine, 38, 47mass spectra, 53, 54mass spectrometer, V, 86, 88, 101, 105meat, 16, 63memory effect, 70mercaptobunzothiazol, 26mercapto-propionic acid, 9mercury, 99mercury-gold, 99methabenzthiazuron, 26methanol, 3methiocarb, 28methiocarb sulfone, 28methiocarb sulfoxide, 28methomyl, 28methylamine, 48meticlorpindol, 16metronidazol, 16microbial growth, 6microorganism, 6microsampling, 70milk, 16, 21, 22mixing noise, 81molecular weight, 66monochromator, 89morpholine, 48moving-belt interface (MS), 102multichannel integrators, 113multisignal, 97multisignal detection, 92mycotoxins, 21

Iindirect UV-detection, 33injection volumes, 70 injector

automated, 72manual, 71program, 110

inorganic anions, 32inorganic ions, Vinstrument

calibration, 114logbooks, 114parameters, 115

integrationevents, 115

parameters, 113 integrators, 112 , 113interface (MS)

moving belt, 102particle beam, 102thermospray, 102

intermediate precision, 122iodide, 34ion-exchange chromatography, 10ion-exchange phases, 58ionox-100

4-hydroxymethyl-2,6-di(tert-butyl) phenoI, 4

ion-pairing reversed-phasechromatography,10, 11

ipronidazol, 16isoabsorbance plot, 91, 92isobutylamine, 48isopropylamine, 48

Kketones, 108

Llactic acid, 2lactose, 42LC/MS, 52, 101, 102LC/MSD, 19, 24lemonade, 41light intensity, 91

133

steam distillation, 64sterols, 35strip chart recorders, 112succinic acid, 2sucrose, 40suitability reports, 110sulfapyridine, 16sulfite, 99sulfonamides, 16sulfur dioxide, 6supercritical fluid extraction (SFE), IV,

63, 64surfactants, Vsweeteners, 8switching valves, 63system suitability, 116

Ttable salt, 34tartaric acid, 2TBHQ mono-tert-butylhydroquinone, 4TDPA 3,3'-thiodipropionic acid, 4tetracyclines, 18tetrahydrofurane, 35THBP 2,4,5-trihydroxybutyrophenone, 4thermal

energy detector, 86thermal stability, IVthin-layer chromatography (TLC), 21thiofanox, 28thiofanox sulfone, 28thiofanox sulfoxide, 28thiosulfate, 99tocopherols, 4, 45 - 47tocotrienols, 46tolerance levels, IIItotal ion chromatography, 53, 54toxicity, 8toxins, 19tracer, 80, 121trend charts, 114triazines, 26triglycerides, 35 - 39trypsin, 53tryptamine, 48tungsten lamp, 10, 91

Rraffinose, 40redox potentials, 98reference electrode, 98refractive index detector, 86, 87, 104regression analysis, 114reintegration, 113repeatability, 122reproducibility, 122residues, 16, 26reversed optics, 91reversed phase, 58riboflavin 5' phosphate, 43

Ssaccharin, 8, 43salad, 27salad dressing, 7sample

cleanup, 59preparation, 62pretreatment, 72, 110volume, 72

sampling device, 70scanning, 96selected ion mode (SIM), 105selectivity, 87separation, 58sequences, 116silver, 99size-exclusion chromatography, 66slit, 91smoked sausage, 32soft drinks, 8solid-phase extraction, 65sorbic acid, 2, 6sorbitol, 39spectral

libraries, 115resolution, 91

spices, 21, 22, 27spikes, 122spreadsheet, 114standard

external, 113internal, 113

standard-bore column, 59

Peltier control, 60peptides, 52performance test, 122personal computers, 114pesticides, III, V, 26, 58petrol ether, 35, 37PG propyl gallate, 4PHB-ethyl, 6PHB-methyl, 6PHB-propyl, 6phenethylamine, 48phenylisocyanate, 108phenylurea-herbicides, 26phosphoric acid, 2photodiode, 89

array, 91photomultiplier tube, 97photoreceptor protein, 52phytochrome proteins, 52pistachio nuts, 23platinum, 99polycyclic aromatic hydrocarbons, 96pork muscle, 18postcolumn derivatization, 28, 29, 109, 110potassium ferrocyanide, 14precision, 120, 122precolumn derivatization, 109, 110precolumns, 65preservatives, III, 6, 7, 63procymidon, 27propionic acid, 2, 6propoxur, 28propylamine, 48protein precipitation, 14proteins, 18protozoa, 16pulse ripple, 79pump

high-pressure gradient, 80low-pressure gradient, 78

pumps, 76-84pungency compounds, 12pyrazon, 15pyrrolidine, 48

Qqualitative information, 87, 88, 120, 123quenching effects, 82Quinolin yellow, 10

134

Uultrasonic bath liquid extraction, 63UV absorbance, 86UV detector, 89, 90

Vvalidation processes, 113vanillin, 12, 13variable volumes, 70variable wavelength detector, 89, 90vegetables, 26, 28vinclozolin, 27viruses, 15viscous samples, 60vitamins, V, 4, 35, 42, 44, 66

drink, 43fat-soluble, 42, 46natural, IIIstandard, 46synthetic, IIItablets, 42, 43water-soluble, 42, 43

vodka, 2

Wwavelength switching, 96wine, 2, 7, 48wool-fiber method, 10working electrode, 98

Xxenon flash lamp, 95

Zzearalenone, 21, 22zinc sulfate, 14

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HPLC in Food Analyis