December 2010

NASA/TM–2010–215857

The Fourth SeaWiFS HPLC Analysis Round-Robin

Experiment (SeaHARRE-4)

Stanford B. Hooker, Crystal S. Thomas, Laurie Van Heukelem, Louise Schlüter, Mary E. Russ, 

Joséphine Ras, Hervé Claustre, Lesley Clementson, Elisabetta Canuti, Jean-François Berthon, 

Jason Perl, Claire Normandeau, John Cullen, Markus Kienast, and James L. Pinckney
	







 

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National Aeronautics and 

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

December 2010

Stanford B. Hooker

NASA Goddard Space Flight Center, Greenbelt, Maryland

Crystal S. Thomas and Laurie Van Heukelem

UMCES Horn Point Laboratory, Cambridge, Maryland

Louise Schlüter

DHI Water and Environment, Hørsholm, DENMARK

Mary E. Russ

Science Systems and Applications Incorporated, Lanham, Maryland

Joséphine Ras and Hervé Claustre

Laboratoire d’Océanographie de Villefranche, Villefranche-sur-Mer, FRANCE

Lesley Clementson

CSIRO Marine Research, Hobart, AUSTRALIA

Elisabetta Canuti and Jean-François Berthon

JRC/IES/Global Environment Monitoring Unit, Ispra, ITALY

Jason Perl

SDSU Center for Hydro-Optics and Remote Sensing, San Diego, California

Claire Normandeau, John Cullen, and Markus Kienast

Dalhousie University, Halifax, Nova Scotia, CANADA

James L. Pinckney

University of South Carolina, Columbia, South Carolina

NASA/TM–2010–215857

The Fourth SeaWiFS HPLC Analysis Round-Robin

Experiment (SeaHARRE-4)
Available from:

NASA Center for AeroSpace Information National Technical Information Service

7115 Standard Drive 5285 Port Royal Road

	




 	




Hooker et al.

Table of Contents

Prologue .................................................. .............................................. 1

1. SeaHARRE-4 Methods, Data, and Analysis ....................................................... 6

1.1 Introduction ............................................ .......................................... 6

1.2 The Data Set ..................................................................................... 6

1.2.1 The Field Samples ................................................................................ 6

1.2.2 The Laboratory Mix ............................................................................... 7

1.2.3 The Pigments ............................................ .......................................... 8

1.3 The Governing Equations ......................................................................... 11

1.4 Laboratory Methods .............................................................................. 13

1.5 Data Analysis Methods ........................................................................... 15

1.6 Results ........................................................................................... 17

1.6.1 Average Pigment Concentrations .................................................................. 19

1.6.2 Method Precision ................................................................................. 21

1.6.3 Method Accuracy ................................................................................. 23

1.7 Summary and Discussion .......................................................................... 30

1.7.1 Precision ............................................ ............................................. 30

1.7.2 Accuracy ............................................ ............................................. 31

1.7.3 DHI Mix-102 ..................................................................................... 32

1.7.4 Ocean Color Requirements ....................................................................... 32

1.7.5 Performance Metrics ............................................................................. 33

1.7.6 Conclusions and Recommendations ............................................................... 33

2. The CSIRO Method .............................................................................. 34

2.1 Introduction ............................................ .......................................... 34

2.2 Methods .......................................................................................... 34

2.2.1 Spectral Absorption ............................................................................... 34

2.2.2 Spectrophotometric Chlorophyll a ................................................................. 35

2.2.3 HPLC Pigment Analysis .......................................................................... 35

2.3 Extraction............................................ ............................................. 35

2.4 HPLC Analysis ......................................... .......................................... 35

2.5 Calibration ....................................................................................... 36

2.6 Validation ........................................................................................ 36

2.7 Carryover ............................................ ............................................. 37

2.8 Data Products .................................................................................... 37

2.9 Conclusions ....................................................................................... 37

3. The DHI Method ................................................................................ 38

3.1 Introduction ............................................ .......................................... 38

3.2 Extraction ....................................................................................... 38

3.3 HPLC Analysis .................................................................................. 38

3.4 Calibration ............................................ .......................................... 39

3.5 Validation ....................................................................................... 39

3.6 Data Products ......................................... .......................................... 39

3.7 Conclusions ............................................ .......................................... 40

4. The FIO Method ................................................................................ 41

Lead Author’s Note .............................................................................. 41

iii
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table of Contents (cont.)

5. The GSFC Method .............................................................................. 42

5.1 Introduction ............................................ .......................................... 42

5.2 Extraction ....................................................................................... 43

5.3 HPLC Analysis .................................................................................. 43

5.4 Calibration ............................................ .......................................... 43

5.5 Validation ....................................................................................... 44

5.6 Data Products ......................................... .......................................... 44

5.7 Conclusions ............................................ .......................................... 44

6. The HPL Method ................................................................................ 45

6.1 Introduction ............................................ .......................................... 45

6.2 Methodology .................................................................................... 45

6.2.1 Extraction ....................................................................................... 45

6.2.2 HPLC Analysis .................................................................................. 46

6.3 Quality Assurance ............................................................................... 48

6.3.1 Replicate Injections .............................................................................. 48

6.3.2 Carryover ....................................................................................... 49

6.4 Data Reporting .................................................................................. 49

6.4.1 Governing Equation ............................................................................. 49

6.4.2 Data Products ......................................... .......................................... 50

6.5 Discussion ....................................................................................... 50

6.6 Conclusions ............................................ .......................................... 51

7. The JRC Method ................................................................................ 52

7.1 Introduction ............................................ .......................................... 52

7.2 Extraction ....................................................................................... 52

7.3 HPLC Analysis .................................................................................. 53

7.4 Calibration ............................................ .......................................... 53

7.5 Quality Control .................................................................................. 54

7.6 LOD and LOQ .................................................................................. 54

7.7 Data Products ......................................... .......................................... 54

7.8 Conclusions ............................................ .......................................... 55

8. The LOV Method ................................................................................. 56

8.1 Introduction ....................................................................................... 56

8.2 Extraction ........................................................................................ 56

8.3 HPLC Analysis ......................................... .......................................... 57

8.4 Calibration ....................................................................................... 57

8.5 Validation ........................................................................................ 58

8.6 Data Products .................................................................................... 59

8.7 Conclusions ....................................................................................... 59

9. The DalU Method ................................................................................ 60

9.1 Introduction ....................................................................................... 60

9.2 Extraction ........................................................................................ 60

9.3 HPLC Analysis ......................................... .......................................... 60

9.4 Calibration ....................................................................................... 61

9.5 Validation ........................................................................................ 61

9.6 Data Products .................................................................................... 61

9.7 Conclusions ....................................................................................... 61

iv
Hooker et al.

Table of Contents (cont.)

10. The SDSU (CHORS) Method ...................................................................... 62

10.1 Introduction ........................................................................................62

10.2 Extraction ............................................ ............................................. 62

10.3 HPLC Analysis .................................................................................... 62

10.4 Calibration ........................................................................................ 63

10.5 Validation ............................................ ............................................. 63

10.6 Data Products ..................................................................................... 63

10.7 Conclusions ........................................................................................ 64

11. The USC Method .................................................................................. 65

11.1 Introduction ........................................................................................65

11.2 Extraction ............................................ ............................................. 65

11.3 HPLC Analysis .................................................................................... 65

11.4 Calibration ........................................................................................ 66

11.5 Validation ............................................ ............................................. 67

11.6 Data Products ..................................................................................... 67

11.7 Conclusions ........................................................................................ 67

Acknowledgments ......................................... .......................................... 68

Appendix A The SeaHARRE-4 Science Team ........................................................... 68

Appendix B The SCOR WG 78 Pigment Abbreviations ................................................. 69

Appendix C Commercial HPLC Manufacturers and Pigment Suppliers................................... 69

Glossary .............................................................................................. 70

Symbols .................................................. ............................................. 71

References ........................................................................................... 72

v

Hooker et al.

Abstract

Ten international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample.

Although prior Sea-viewing Wide Field-of-view Sensor (SeaWiFS) High Performance Liquid Chromatography

(HPLC) Round-Robin Experiment (SeaHARRE) activities conducted in open-ocean waters covered a wide dynamic range in productivity, and some of the samples were collected in the coastal zone, none of the activities

involved exclusively coastal samples. Consequently, SeaHARRE-4 was organized and executed as a strictly

coastal activity and the field samples were collected from primarily eutrophic waters within the coastal zone of

Denmark. The more restrictive perspective limited the dynamic range in chlorophyll concentration to approximately one and a half orders of magnitude (previous activities covered more than two orders of magnitude). The

method intercomparisons were used for the following objectives: a) estimate the uncertainties in quantitating

individual pigments and higher-order variables formed from sums and ratios; b) confirm if the chlorophyll a

accuracy requirements for ocean color validation activities (approximately 25%, although 15% would allow for

algorithm refinement) can be met in coastal waters; c) establish the reduction in uncertainties as a result of

applying QA procedures; d) show the importance of establishing a properly defined referencing system in the

computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f) demonstrate the

utility of a laboratory mix in understanding method performance. In addition, the remote sensing requirements

for the in situ determination of total chlorophyll a were investigated to determine whether or not the average

uncertainty for this measurement is being satisfied.

PROLOGUE

The first Sea-viewing Wide Field-of-view Sensor (SeaWiFS) High Performance Liquid Chromatography (HPLC)

Round-Robin Experiment (SeaHARRE-1) took place in

1999 (Hooker et al. 2000). It emphasized oligotrophic

and mesotrophic regimes (northwest African upwelling and

the Mediterranean Sea), involved four laboratories using

four different methods (three C8 and one C18), and was

based on 11 duplicates and triplicates (12 triplicates were

planned). The dynamic range in the total chlorophyll a

(TChl a) concentration, denoted TChl a



, spanned 0.044–

2.089 mg m−3.

Field sampling for SeaHARRE-2 took place in 2002

(Hooker et al. 2005) and emphasized mesotrophic and eutrophic regimes (Benguela Current), involved eight laboratories using eight different methods (four C8 and four

C18), although some of the methods were based on the

same general method resulting in five rather distinct methods. Sample distribution involved 12 duplicates (12 triplicates were planned) spanning a 

TChl a



dynamic range

of 0.357–26.185 mg m−3.

Field sampling for SeaHARRE-3 took place in 2004

(Hooker et al. 2009) and emphasized the oligotrophic waters of the South Pacific Ocean central gyre. Additional

samples were collected in mesotrophic waters and in the

higher productivity of the Chilean upwelling. A total of 24

samples were distributed in triplicate covering a TChl a



dynamic range of 0.020–1.366 mg m−3. Seven laboratories

participated, but one of them executed two different methods, so a total of eight methods were intercompared.

Field sampling for SeaHARRE-4 took place in 2006

and was the first activity to emphasize coastal sampling,

in particular the shallow waters associated with near-shore

ecosystems. Unlike prior SeaHARRE field sampling campaigns, which took advantage of already scheduled oceanographic expeditions, the field sampling for SeaHARRE-4

was executed as a separate activity. The samples were

collected from the fjords, estuaries, and bays within the

coastal zone of Denmark.

Ten international laboratories agreed to participate in

SeaHARRE-4 with so-called validated HPLC methods:

1. The Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO);

2. The Danish DHI Institute for Water and Environment (DHI);

3. The American University of South Florida (USF)

Florida Institute of Oceanography (FIO);

4. The American National Aeronautics and Space Administration (NASA) Goddard Space Flight Center

(GSFC);

5. The American Horn Point Laboratory (HPL) University of Maryland Center for Environmental Science (UMCES);

6. The European Joint Research Centre (JRC), which

is located in Italy;

7. The French Laboratoire d’Oc ́eanographie de Villefranche (LOV);

8. The Canadian Dalhousie University (DalU);

1
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

9. The American Center for Hydro-Optics and Remote

Sensing (CHORS) at the San Diego State University

(SDSU); and

10. The American University of South Carolina (USC).

The scientists involved in SeaHARRE-4 are listed in

App. A.

The other laboratories that participated in past SeaHARRE intercomparisons are the Canadian Bedford Institute of Oceanography (BIO), the South African Marine

and Coastal Management (MCM), and the British Plymouth Marine Laboratory (PML). As shown in Table 1,

of all the laboratories involved with SeaHARRE activities, only HPL and LOV have participated in every one,

although CSIRO, DHI, JRC, MCM, and SDSU have participated in three each.

Table 1. The laboratories, with their corresponding countries and assigned one-letter codes, that

have participated in the four SeaHARRE activities

executed to-date.

Laboratory and Country Code SeaHARRE

BIO Canada B 2

CSIRO Australia C 234

DHI Denmark D 234

FIO United States F 4

GSFC United States G 4

HPL United States H 1234

JRC Italy J 1 34

LOV France L 1234

MCM South Africa M 123

DalU Canada N 4

PML United Kingdom P 2

SDSU United States S 234

USC United States U 4

There are advantages in having a recurring set of core

participants within the overall SeaHARRE activity, most

notably because they provide an established capability and

knowledge base that can be counted on during data analysis and workshop discussions (there have been almost as

many workshops as round robins). The experience of the

core analysts has provided invaluable learning opportunities for new analysts and they have helped steer the evolving objectives of each activity. In addition, however, emphasis is placed during the planning stages of each SeaHARRE activity to try and recruit new practitioners because another objective of the SeaHARRE activity is to

provide the broadest investigation of community capabilities as possible.

The aforementioned concept of a validated method requires some additional explanation, because there is no

external process or independent agency that certifies an

HPLC phytoplankton pigment method is validated. The

validation process is currently conceived and executed by

the individual laboratory based on the sampling requirements and research objectives associated with the method.

Consequently, validation occurs largely in isolation and relies heavily on a temporal evaluation of the calibration

procedures, although some laboratories use more sophisticated evaluation criteria. As first demonstrated during

SeaHARRE-1 (Hooker et al. 2000), intercomparing methods is a more robust mechanism for demonstrating the degree of validation for a particular method, and this is a

permanent objective of the SeaHARRE activity.

Method validation procedures are important because

they describe the level of measurement uncertainty associated with reported data products, i.e., individual pigment concentrations, sums, ratios, and indices. In the absence of the aforementioned external process or independent agency, however, validation activities of individual

laboratories have emerged with varying emphases, often

tailored to the specific research conducted by the individual laboratory. The products of validation, therefore, may

not always yield the kind of information useful to intercomparing a diverse set of laboratory results over time or

between laboratories. Consequently, for a more thorough

understanding of measurement uncertainty and its relationship to accuracy in the analysis of field samples, intercalibration exercises are necessary, but the methods of the

participating laboratories are best evaluated according to

a common set of procedures and products.

The culmination of this philosophy of quantitative assessment was the drafting of a set of performance metrics

during SeaHARRE-2 (Hooker et al. 2005), which have been

continuously reviewed and updated (Hooker et al. 2009),

since their inception. The evaluation of the performance

metrics—in particular the corresponding accuracy and precision parameters—resulted in some participants replacing

the methods they were initially using for a single (more

modern) method with superior performance parameters:

the Van Heukelem and Thomas (2001) method. In the

more recent SeaHARRE activities, since SeaHARRE-1,

the maximum diversity in the combination of laboratories and methods was achieved during SeaHARRE-2, and

the least during SeaHARRE-3. Consequently, an emphasis was placed on recruiting new laboratories and methods

for SeaHARRE-4, particularly methods that would help

counterbalance the evolving predominance of C8 methods

over C18 methods (Table 2).

The reduction in method diversity over time was not

expected. There was a strong feeling in the early planning for SeaHARRE-1 that the approach used in the joint

Global Ocean Flux Study (JGOFS 1994)—selecting one

method, in this case the Wright et al. (1991) method,

and making it the protocol—should not be repeated, even

unintentionally, because it stifles creativity. Two principal concerns with having too many practitioners using the

same method was a) a bias in the predominant method

would go undetected, and b) the state of the art would

not continue to evolve. The practical benefit of adopting

2
Hooker et al.

Table 2. The methods used by all of the laboratories in the four HPLC round-robin intercomparisons executed

to-date. The laboratory codes under the citations indicate the method used by a particular laboratory as a

function of the four round robins.

Round Gieskes and Wright et al. Pinckney et al. Vidussi et al. Barlow et al. Van Heukelem and

Robin Kraay (1989)1 (1991)1 (1996)1 (1996)2 (1997)2 Thomas (2001)2

1 J L M H

2 B CDS L M P H

3 J S3 M CDHLS3

4 N S4 F U CDGHJL

1 A C18 column method. 2 A C8 column method. 3 SDSU switched from the Wright et al. (1991) method to the Van Heukelem and Thomas (2001) method, but executed

both, so they could be compared. 4 SDSU switched back to the Wright et al. (1991) method.

a proven method instead of investing an unknown amount

of time and resource in trying to improve a method, however, was simply too alluring. The potential pitfall of

this approach—which is quantified here in many aspects—

is underestimating the difficulty of implementing a new

method with all its attendant detail.

The overall results of SeaHARRE-4 are presented in

Chap. 1 and the individual methods of the 10 laboratories

are presented in Chaps. 2–11, respectively. A summary of

the material presented in each chapter is given below.

1. SeaHARRE-4 Methods, Data, and Analysis

The focus of this study was the estimation of uncertainties in quantifying a diverse set of chlorophyll and carotenoid pigment concentrations for a variety of HPLC methods and related procedures used in the analysis of predominantly coastal waters. The SeaHARRE-4 activity was

designed to investigate the following objectives: a) estimate the uncertainties in quantitating individual pigments

and higher-order variables formed from sums and ratios;

b) confirm if the chlorophyll a accuracy requirements for

ocean color validation activities (approximately 25%, although 15% would allow for algorithm refinement) can be

met in coastal waters; c) establish the reduction in uncertainties as a result of applying QA procedures; d) show

the importance of establishing a properly defined referencing system in the computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f)

demonstrate the utility of a laboratory mix in understanding method performance. All of these objectives were satisfied and the results associated with each are presented.

2. The CSIRO Method

The CSIRO method is a modified version of the Van

Heukelem and Thomas (2001) method (VHT) and has the

capacity to resolve approximately 35 different pigments

with baseline resolutions of divinyl and monovinyl chlorophyll a, and zeaxanthin and lutein. Partial separation of

divinyl and monovinyl chlorophyll b, and chlorophyll c2 and

chlorophyll c1 can also be achieved. The method used for

the samples and standards analyzed for SeaHARRE-4 was

the same method used for SeaHARRE-3. Samples were

extracted over 15–18 hours in an acetone solution before

analysis by HPLC using a C8 column and binary gradient

system with an elevated column temperature. Pigments

were identified by retention time and absorption spectrum

from a photodiode array (PDA) detector. The method is

regularly validated with the use of internal and external

standards and individual pigment calibration. The detection limit of most pigments was within the range of 0.001–

0.005 mg m−3. This method is applicable to the study of

pigment composition and concentration in samples from

all water types including freshwater, estuarine, upwelling

coastal regions, and oligotrophic open ocean, as well as in

the microphytobenthos of shallow coastal regions.

3. The DHI Method

The DHI HPLC method is a modified version of the

HPL method. The method provides good separation of

more than 30 of the most important pigments in freshwater, estuarine, and oceanic environments. Validation steps

include four injections of a chlorophyll a standard to verify

the calibration of the HPLC, use of an internal standard for

correcting evaporation errors, and injection of a mixture of

pigments to verify correct elution and retention times, and

for documenting the precision of the HPLC and response

factor stability. During analysis of the SeaHARRE-4 samples, the method provided satisfactory results on the precision of both mixed pigments and natural samples, and

on the accuracy of TChl a measurements. The accuracy

of PPig, however, was much higher when comparing the

results to SeaHARRE-3, where DHI first used the HPL

method. This increase in uncertainty is ascribed to the

complexity of samples derived from transitional areas such

as the Danish estuaries, where the SeaHARRE-4 samples

were taken.

4. The FIO Method

The FIO method used multiple reversed-phase C18 columns connected in series. The configuration uses a single

3
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

monomeric and two polymeric columns, and was originally

devised to enhance the separation of numerous structurally

similar pigments and degradation products. The combination of the coarse and fine molecular properties of the two

different column types optimizes pigment separation. The

monomeric column provides strong retention and high efficiency, while the polymeric columns provide the selection

for similar compounds. The latter are temperature sensitive and require the use of a column heater. A nonlinear

binary gradient, adapted from Van Heukelem et al. (1992),

was used for pigment separations. Solvent A consisted of

80% methanol:20% ammonium acetate (0.5 M adjusted to

pH 7.2) and solvent B was composed of 80% methanol:20%

acetone. Absorption spectra and chromatograms were acquired using a photodiode array detector. Pigment peaks

were identified by comparing retention times and absorption spectra with standards or culture extracts (depending

on the pigment involved).

5. The GSFC Method

GSFC participated in SeaHARRE-4 as an HPLC novice, with no previous experience in actual HPLC pigment

analysis. The primary objective of the GSFC participation

was to strictly adhere to the established performance metrics for quantitative analysis, as well as the published protocols of the selected method (Van Heukelem and Thomas

2001), to demonstrate whether or not both were sufficiently

robust to allow any practitioner to produce results in keeping with the QA subset. Preparation at GSFC prior to

sample analysis included servicing the instrument, making

solvents, buffers, and standards, and running single- and

multipoint regressions of known standards to create a calibration table and update a spectral library used to identify

pigments in the 36 SeaHARRE unknown samples. Unexpected pressure issues resulted in recalibration and validation, as well as the SeaHARRE samples being analyzed

on the Agilent 1100 HPLC at HPL. Multiple Chl a regression curves were run, and residuals calculated, in order to

identify the dynamic range of the detector, as well as the

overall precision of the instrument. Overall, 35 Chl a standards of varying concentrations were injected with average

residuals of 1.5% for all concentrations. A second measurement of Chl a concentration, using a spectrophotometer and a trichomatic equation was completed at GSFC

using the remaining sample extractions from the HPLC

analysis. GSFC obtained state-of-the-art results, which

established the capability of a novice laboratory to produce high-quality pigment data for use in calibration and

validation exercises associated with remote sensing derivations of global chlorophyll concentrations.

6. The HPL Method

The HPL HPLC method employed by Horn Point Laboratory was developed for use with a variety of water types.

Many pigments important to freshwater, estuarine, and

oceanic systems are baseline resolved and quantitatively

reported, including divinyl and monovinyl chlorophyll a.

The method is built around a C8 HPLC column, and incorporates a methanol-based reversed-phase solvent system, a

simple linear gradient, and an elevated column temperature (60◦C) to achieve separation of the pigments to be

quantitated. The method can provide quantitative results

for up to 25 pigments with qualitative information for additional pigments. Quality assurance measurements are

made during sample analysis to confirm that the method

performance is within expectations. Investigations into the

uncertainties in the method show the 95% confidence limits are estimated as a) 0.5–3.8% for precision of replicate

injections within and across sequences, b) 3.2% for chlorophyll a calibration reproducibility, and c) 5.1% for chlorophyll a method precision, including filter extraction and

analysis.

7. The JRC Method

The HPLC method adopted by the JRC is the Van

Heukelem and Thomas (2001) method, as modified for

SeaHARRE-3 (Van Heukelem and Thomas 2009). This

method has been successfully applied to a wide range of

pigment concentrations from oligotrophic to eutrophic

coastal waters (Van Heukelem and Thomas 2009). Here,

it allowed for the separation and the quantification of 22

different pigments and, in particular, the monovinyl and

divinyl forms of chlorophyll a. The samples are extracted

in a 100% acetone solution including an internal standard

(vitamin E acetate) and analyzed by HPLC using a C8

column with a binary solvent gradient. The different pigments are identified using a diode array detector on the basis of the absorption spectra at two different wavelengths

(450 and 665 nm). The quality control of the data is assured by injecting a chlorophyll a standard at the beginning

of each sequence, in order to check the calibration, as well

as a mixture of pigments in order to check the retention

times, and the system accuracy and precision.

8. The LOV Method

The LOV method, derived from the technique described

by Van Heukelem and Thomas (2001), applies a sensitive

reversed-phase HPLC technique for the determination of

chloropigments and carotenoids within 28 min. The different pigments, extracted in methanol, are detected by diode

array detector (DAD), which allows for automatic identification to be carried out on the basis of absorption spectra. Optical densities are monitored at 450 nm (chloropigments and carotenoids), 667 nm (chlorophyll a and derived

pigments), 770 nm (bacteriochlorophyll a) and 222 nm (vitamin E acetate internal standard). The method provides

good resolution between most pigments, but uncertainties

may arise because of the partial separation of chlorophyll b

and divinyl chlorophyll b, for the resolution of chlorophyll c

pigments, and for the separation of α- and β-carotenes. It

has proven to be efficient over a wide range of trophic conditions, from eutrophic upwelling waters, to the hyperoligotrophic South Pacific Subtropical Gyre. Short-term and

4
Hooker et al.

long-term quality control is monitored regularly to ensure

state-of-the-art analyses. The injection precision of the

method is estimated at 0.3%, and the limits of detection

for most pigments are low (0.019 ng inj−1 for chlorophyll a,

and 0.033 ng inj−1 for carotenoids).

9. The DalU Method

The HPLC pigment technique used at Dalhousie University follows the method developed by Wright et al.

(1991). It is a reversed-phase HPLC procedure (C18 column), based on a tertiary gradient and includes a cooled

autosampler, and photodiode array and fluorescence detectors. Samples are disrupted with a sonic probe in 100%

methanol including an internal standard (vitamin E acetate). The method is validated with the use of internal

and external standards. It does not allow for the separation of divinyl chlorophylls a and b from their respective

monovinyl forms. In addition, chlorophyll c1 and chlorophyll c2 are not separated, and neither is lutein from zeaxanthin; however, it offers good separation of a variety of

pigments in a relatively short period of time (29 min).

10. The SDSU (CHORS) Method

The CHORS method was developed to provide HPLC

phytoplankton pigment analyses for the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program, following

the protocols presented in the Ocean Optics Protocols for

Satellite Ocean Color Sensor Validation (Bidigare et al.

2002). The method (Wright et al. 1991) was designed to

support a wide range of pigment concentrations from waters sampled throughout the world ocean, but it does not

chromatographically separate the divinyl chlorophylls a

and b from their corresponding monovinyl forms. The

Latasa et al. (1996) dichromatic equations were used to

spectrally resolve divinyl chlorophyll a from monovinyl

chlorophyll a. The method uses a reversed-phase C18 column, with a tertiary solvent gradient; a temperaturecontrolled autosampler provides continuous sample injection to maintain a quota of analyzing 4,000 samples per

year. System calibration is routinely monitored and recorded each month to ensure repeatability and consistency

of data products.

11. The USC Method

The USC method was developed to provide a universal

protocol that could be used to analyze freshwater, estuarine, coastal, and ocean habitats, as well as sediment and

microbial mat samples. The method employs a unique

combination of both monomeric and polymeric C18 columns combined with a variable flow binary gradient. This

column configuration was originally devised to enhance

photopigment separations from sediment samples containing numerous (greater than 150) photopigment and pigment degradation products. The combination of columns

provides strong retention and high efficiency (monomeric

columns) while selecting for similar compounds with minor differences in molecular structure (polymeric columns).

The variable flow binary gradient allows baseline separation of most major pigments including lutein and zeaxanthin, and chlorophyll c3. Chlorophylls c1 and c2 plus divinyl chlorophylls a and b are not completely separated.

For HPLC analysis, filters are placed in disposable polypropylene microfuge tubes and lyophilized to remove all

water from the filters. The primary advantages of this

method are long column life (greater than 2,000 injections),

inexpensive and non-hazardous solvents and reagents, no

uncertainty regarding the water retained on the filter, and

reliability across a range of sample types.

5
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 1

SeaHARRE-4 Methods, Data, and Analysis

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Laurie Van Heukelem

UMCES Horn Point Laboratory

Cambridge, Maryland

Louise Schluter  ̈

DHI Water and Environment

Hørsholm, Denmark

Abstract

The focus of this study was the estimation of uncertainties in quantifying a diverse set of chlorophyll and carotenoid pigment concentrations for a variety of HPLC methods and related procedures used in the analysis of

predominantly coastal waters. The SeaHARRE-4 activity was designed to investigate the following objectives: a)

estimate the uncertainties in quantitating individual pigments and higher-order variables formed from sums and

ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation activities (approximately

25%, although 15% would allow for algorithm refinement) can be met in coastal waters; c) establish the reduction

in uncertainties as a result of applying QA procedures; d) show the importance of establishing a properly defined

referencing system in the computation of uncertainties; e) quantify the analytical benefits of performance metrics,

and f) demonstrate the utility of a laboratory mix in understanding method performance. All of these objectives

were satisfied and the results associated with each are presented.

1.1 INTRODUCTION

The results obtained in the first three SeaHARRE activities established a continuing interest in estimating and

understanding the sources of uncertainties associated with

the principal terms in the equation governing the calculation of the concentration (C) of an individual pigment

(Pi) from a field sample. Because prior activities used

open ocean samples, SeaHARRE-4 was organized around

coastal samples.

1.2 THE DATA SET

The SeaHARRE-4 analyses were derived from field samples and a laboratory mixture of natural pigments. The

activity involved 10 laboratories (Table 1) using three different methods (Table 2); a total of six C8 and four C18

methods were executed. In some parts of this document,

abbreviations from the Scientific Committee on Oceanic

Research (SCOR) Working Group (WG) are used for pigment presentations (Appendix B), but the majority of the

analysis results are presented using a more compact lexicon. This lexicon was developed to satisfy the diversity of

presentation requirements spanning text, tables, and formulas. The latter is particularly important to summarizing

the statistical description of the results.

1.2.1 The Field Samples

The SeaHARRE-4 sampling plan emphasized coastal

waters. The samples were collected as part of a dedicated

field campaign in the estuaries and fjords of Danish coastal

waters. Details concerning individual stations where samples were collected are presented in Table 3. The last three

stations (K, L, and M) were collected during a recurring

Danish coastal observation activity and were not part of

the collection of the other samples. This was done to further broaden the types of waters sampled. The resulting

diversity in ecosystems is well described by the range in

salinity, which spanned 8.0–28.0 PSU.

The locations of the sampling stations are shown in

Fig. 1, but only the last 12 were used for SeaHARRE-4. All

samples were collected on 25 mm GF/F filters and stored

in liquid nitrogen as soon as filtration was completed. A

batch of 12 replicates were collected at each station, with

6
Hooker et al.

Table 3. The sampling log for the 13 batches of field samples, which were all collected in triplicate. Samples

were collected for 12 laboratories, so each batch contained 36 filters. The individual filters were identified

alphabetically from A to M, but only B–M were used during SeaHARRE-4 (batch A was retained for another

purpose). The water samples were collected from Niskin bottles during conductivity, temperature, and depth

(CTD) profiles. The sampling depth is shown with the volume of water filtered, Vf , for all filters within a batch.

Station Code Date and Time Longitude Latitude Vf Salinity Water

and Name [GMT] [

◦] [◦] [mL] [PSU] Depth [m]

A Hvalpsund 05 Sep 2006 0707 9.1778 56.7046 300.0 25.2 10.0

B Virksund 05 Sep 2006 0920 9.2954 56.6084 84.5 18.4 7.0

C Skive 05 Sep 2006 1444 9.0660 56.5799 168.4 24.6 5.0

D Mariager 06 Sep 2006 0752 9.9736 56.6627 252.8 16.1 28.5

E Hadsund 06 Sep 2006 0921 10.1914 56.6969 450.0 20.2 5.5

F Randers Fjord 06 Sep 2006 1416 10.2281 56.5232 252.8 8.0 4.0

G Kattegat 06 Sep 2006 1455 10.3564 56.6037 500.0 22.2 6.5

H Horsens Fjord 07 Sep 2006 0706 9.9003 55.8536 500.0 25.7 4.0

I Vejle Fjord 1 07 Sep 2006 0938 9.6837 55.6956 700.0 27.4 10.8

J Vejle Fjord 2 07 Sep 2006 1049 9.5648 55.7023 400.0 28.0 2.0

K Roskilde Fjord 28 Sep 2006 0941 12.0336 55.8862 700.0 17.4 7.0

L Isefjord 28 Sep 2006 0725 11.8262 55.9146 700.0 19.1 9.8

M Ven 03 Oct 2006 0855 12.7492 55.8598 1,500.0 15.4 20.2

four stored in so-called histoprep filter holders and eight in

folded foil packets. Both H and L received foil and histoprep samples, C and G received histopreps only, and the

remaining laboratories received foil packets. The histoprep

samples were collected to investigate if this storage method

might be a source of elevated uncertainties.

Longitude

Latitude

Denmark

Sweden

J

J

J

J

J

J

Odense

Kolding

Aalborg

Aarhus

Copenhagen

Helsingor

Fig. 1. Station locations for SeaHARRE-4 wherein

the 1–13 numeric bullets correspond to stations A–M,

respectively. Depth contours are in meters.

The filters within each batch type were randomly selected for each laboratory and distributed using (liquid

nitrogen) dry shippers. There were no anomalies in the

shipment of the samples—all filters were received properly

frozen by each laboratory.

1.2.2 The Laboratory Mix

A recommendation from the SeaHARRE-2 activity was

to find a source for an algal mixture of the primary pigments. After SeaHARRE-2, DHI successfully produced

a laboratory mix of pigments and made it commercially

available. The mix is made from cultures of different phytoplankton species, and each lot contains approximately

20 different pigments, all of which can be present in oligotrophic oceans: Chl c3, Chl c2, Peri, But, Fuco, Neo,

Pras, Viola, Hex, Diad, Allo, Diato, Zea, Lut, Chl b, Chl a,

ββ-Car, and βε-Car. The content varies slightly in different lots, and may also contain Phide a, Phytin a, Chlide a,

MgDVP, plus Chl c1 and other Chl c-type pigments.

The mixed pigments allow an HPLC analyst to check

detection of, and resolution between, pigments. They can

also be used for quality assurance, for example, monitoring

retention time and response factor stability, verifying the

correct elution and identity of peaks, and for documenting the precision of the HPLC. The mix is not really a

proxy for a natural field sample because they contain less

of some pigments and more of some others, so the relative

abundance is not in keeping with a natural sample.

The mix analyzed during SeaHARRE-4 is denoted DHI

Mix-102. Each laboratory received 10 ampules of the mix

and was requested to make at least three analyses of the

mix, and to use it to whatever quality assurance (QA)

advantage was deemed appropriate. For example, some

analysts make an analysis of the mix at the start of the

field sample analyses and after every 20 samples (with at

least one mix sample analyzed in each sample set of field

samples, e.g., for each complete analysis of an autosampler

compartment). In most cases, more than three analyses

were performed.

7
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

1.2.3 The Pigments

Each participating laboratory established and validated

an HPLC method based on the pigment content of the samples they typically analyze. This is an important point,

because some laboratories were exposed to atypical pigment types or concentrations. The variety of methods

means some pigments were analyzed by only a few methods, whereas others were analyzed by all methods. The

latter constitute a group of pigments that are routinely

useful to many aspects of marine studies and, following

the nomenclature of Claustre et al. (2004), are referred to

here as the primary pigments (PPig).

The utility of the pigments for biogeochemical inquiries,

along with the number of methods that actually quantitated a particular pigment, were used to separate the pigments into four groups:

• The primary pigments are the total chlorophylls

and the carotenoids most commonly used in chemotaxonomic or photophysiological studies in the open

ocean or in coastal waters (Gieskes et al. 1988, Barlow et al. 1993, Claustre et al. 1994, and Bidigare

and Ondrusek 1996);

• The secondary pigments are the individual pigments

used to create a primary pigment composed of separate contributions (e.g., the total chlorophylls);

• The tertiary pigments are those pigments not included in the composition of the primary and secondary pigments for which three or more laboratories provided quantitations; and

• The ancillary pigments are those remaining pigments only analyzed by one or two laboratories.

This nomenclature implies a precedence or ranking of the

pigments, but this is only true from the perspective of the

SeaHARRE activity and marine phytoplankton pigment

research, for which certain pigments are routinely used

more often than others (e.g., chlorophyll a). The primary

reason for establishing a unique vocabulary is to provide a

categorization scheme for grouping the analytical results.

A listing of the secondary, tertiary, and ancillary pigments are given in Table 4. The ancillary pigments are

not used in this study; they are included to summarize the

complete capabilities of each method. Only a subset of

the tertiary pigments deemed representative of the types

of tertiary pigments of interest to the marine phytoplankton community are presented and discussed. Table 4 also

provides the methods used for the quantitation of each pigment, the names and abbreviations of each pigment, and

the corresponding variable forms, which are used to indicate the concentration of each pigment.

All laboratories quantitated the individual primary pigments, which are used to create the higher-order pigment

associations: sums, ratios, and indices (Table 5). The

grouping of pigments to form sums permits the formulation of variables useful to different perspectives. For example, the pool of photosynthetic and photoprotective carotenoids (PSC and PPC, respectively) are useful to photophysiological studies (Bidigare et al. 1987) and the total

amount of accessory (non-chlorophyll a) pigments (TAcc)

are useful in remote sensing investigations (Trees et al.

2000). The ratios derived from these pooled variables,

e.g., PSC/



TChl a



, are dimensionless, and have the advantage of automatically scaling the comparison of results

from different areas and pigment concentrations.

An important pigment sum is the total diagnostic pigments (DP), which was introduced by Claustre (1994) to

estimate a pigment-derived analog to the f-ratio (the ratio

of new-to-total production) developed by Eppley and Peterson (1979). The use of DP was extended by Vidussi et

al. (2001) and Uitz et al. (2006) to derive size-equivalent

indices that roughly correspond to the biomass proportion

factors of pico-, nano-, and microphytoplankton, which are

denoted pPF,



nPF, and mPF, respectively. They are

composed of sums and are ratios, so they should be useful

in reconciling databases from different oceanic regimes.

Together with the individual primary pigments, the

pigment sums, ratios, and indices are presented in Table 5.

Note that TChl a



,



TChl b



, and TChl c

 do not represent individual concentrations—each is a group of pigments roughly characterized by the same absorption spectra (including some degradation products). These sums

allow for the comparison of results originating from HPLC

methods that differ in the way the pigments within the

same family are quantitated (e.g., chlorophyll c types) or

whose extraction procedures might or might not generate

degradation forms (e.g., chlorophyllide a). The sums also

allow for the comparison of methods that differ in their

capability of differentiating monovinyl from divinyl forms.

The symbols used to indicate the concentration of the

so-called primary pigments, which were reported by all of

the laboratories, are as follows:

CTa Total chlorophyll a,

CTb Total chlorophyll b,

CTc Total chlorophyll c,

CC Carotenes,

CA Alloxanthin,

CB 19

-Butanoyloxyfucoxanthin,

CDd Diadinoxanthin,

CDt Diatoxanthin,

CF Fucoxanthin,

CH 19

-Hexanoyloxyfucoxanthin,

CP Peridinin, and

CZ Zeaxanthin.

These are the same 12 pigments given in the topmost portion of Table 5. The first three are the (total) pigment

8
Hooker et al.

Table 4. The secondary (top portion) and tertiary (middle portion) pigments shown with their variable forms,

names, and calculation formulas (if applicable). The absence of allomers and epimers for pigments other than Chl a

is not indicative of a lack of understanding that they might be present—it is simply a reflection that the SeaHARRE

participants have agreed to quantitate and include the allomers and epimers in the definition of Chl a



. The methods

used to quantitate the various pigments are indicated by their one-letter codes. The variable forms, which are used

to indicate the concentration of the pigment, are patterned after the nomenclature established by the SCOR WG 78

(Jeffrey et al. 1997b). Abbreviated pigment forms are shown in parentheses. The presence of Neo+Vio

and Zea+Lut

is to maintain continuity with prior SeaHARRE activities, for which these sums were important.

Variable Method Secondary Pigment Calculation



Chl a

 CD F GHJLNSU Chlorophyll a (Chl a) Including allomers and epimers



DVChl a

 CD GHJL § Divinyl chlorophyll a (DVChl a)



Chlide a

 CD F GHJLNSU Chlorophyllide a (Chlide a)



Chl b

 CD F GHJLNSU Chlorophyll b (Chl b)



Chl c1+c2

 CD F GHJLNSU Chlorophyll c1+c2 (Chl c1+c2) 

Chl c1



+ Chl c2





Chl c3

 CD GHJLNSU Chlorophyll c3 (Chl c3)



βε-Car F SU βε-Carotene† (βε-Car)



ββ-Car F SU ββ-Carotene‡ (ββ-Car)

Variable Method Tertiary Pigment Calculation



Chl c1

 C GH Chlorophyll c1 (Chl c1)



Chl c2

 CD GH SU Chlorophyll c2 (Chl c2)



Lut CD F GHJLNSU Lutein (Lut)



Neo CD F GHJLNSU Neoxanthin (Neo)



Neo+Vio CD F GHJLNSU Neoxanthin and Violaxanthin

(Neo+Viola)



Neo+ Viola



Phide a

 CD HJLNS Phaeophorbide a (Phide a)



Phytin a

 CD GHJLNS Phaeophytin a (Phytin a)



Pras CD F GHJLNSU Prasinoxanthin (Pras)



Viola CD F GHJLNSU Violaxanthin (Viola)



Zea+Lut CD F GHJLNSU Zeaxanthin and Lutein (Zea+Lut) Zea+ Lut



Gyro FH U Gyroxanthin (Gyro)

Variable Method Ancillary Pigment Calculation



DVChl b

 G H Divinyl chlorophyll b (DVChl b)



Myxo D Myxoxanthophyll (Myxo)



MgDVP C F Mg 2,4-divinyl phaeoporphyrin a5

monomethyl ester (MgDVP)



BChl a

 L Bacterial Chlorophyll a (BChl a)



Pyro C Pyro-phaeopigments¶



Phytin b

 C Phaeophytin b (Phytin b)



Anth D U Antheraxanthin (Anthera)



Cantha D Canthaxanthin (Cantha)



Croco F Crocoxanthin (Croco)



Monado U Monadoxanthin (Monado)

§ Method S used the Latasa et al. (1996) simultaneous equations to estimate [DVChl a].

† Also referred to as α-Carotene.

‡ Also referred to as β-Carotene.

¶ Pyro-phaeophorbide a and pyro-phaeophytin a.

9
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 5. The (individual) primary pigments, pigment sums, pigment ratios, and pigment indices shown with their

variable forms, names, and calculation formulas (if applicable). All methods produced all of these variables. The

variable forms, which are used to indicate the concentration of the pigment or pigment association, are patterned

after the nomenclature established by the SCOR Working Group 78 (Jeffrey et al. 1997b). Abbreviated forms for the

pigments are shown in parentheses.

Variable Primary Pigment (PPig) Calculation



TChl a

 Total chlorophyll a† (TChl a) 

Chlide a



+ DVChl a



+ Chl a





TChl b

 Total chlorophyll b† (TChl b) 

DVChl b



+ Chl b





TChl c

 Total chlorophyll c† (TChl c) 

Chl c1



+ Chl c2



+ Chl c3





Caro Carotenes† (Caro) ββ-Car+ βε-Car



Allo Alloxanthin (Allo)



But 19

-Butanoyloxyfucoxanthin (But-fuco)



Diad Diadinoxanthin (Diadino)



Diato Diatoxanthin (Diato)



Fuco Fucoxanthin (Fuco)



Hex 19

-Hexanoyloxyfucoxanthin (Hex-fuco)



Peri Peridinin (Perid)



Zea Zeaxanthin (Zea)

Variable Pigment Sum Calculation



TChl Total Chlorophyll (TChl) TChl a



+ TChl b



+ TChl c





PPC Photoprotective Carotenoids (PPC) Allo+ Diad+ Diato+ Zea+ Caro



PSC Photosynthetic Carotenoids (PSC) But+ Fuco+ Hex+ Peri



PSP Photosynthetic Pigments (PSP) PSC+ TChl



TAcc Total Accessory Pigments (TAcc) PPC+ PSC+ TChl b



+ TChl c





TPig Total Pigments (TPig) TAcc+ TChl a





DP Total Diagnostic Pigments (DP) PSC+ Allo+ Zea+ TChl b



Variable Pigment Ratio Calculation



TAcc/



TChl a

 The 

TAccto TChl a



ratio 

TAcc/



TChl a





TChl a



/



TPig The 

TChl a



to TPigratio 

TChl a



/



TPig



PPC/



TPig The 

PPCto TPigratio 

PPC/



TPig



PSC/



TPig The 

PSCto TPigratio 

PSC/



TPig



PSP/



TPig The 

PSPto TPigratio 

PSP/



TPig

Variable Pigment Index Calculation



mPF Microplankton Proportion Factor‡ (MPF)



Fuco

+



Peri



DP



nPF Nanoplankton Proportion Factor‡ (NPF)



Hex

+



But

+



Allo



DP



pPF Picoplankton Proportion Factor‡ (PPF)



Zea

+



TChl b





DP

† Considered as individual pigments, although computed or equivalently represented as sums by some methods.

‡ As a group, also considered as macrovariables.

10
Hooker et al.

associations for the chlorophylls and the other nine are all

carotenoids, of which only Caro is a sum.

The secondary and tertiary pigments that are also of

interest to this study, in terms of the presentation of some

of the statistical analysis of the results and a historical

perspective for the SeaHARRE activity, are as follows:

Ca Chlorophyll a,

CDa Divinyl chlorophyll a,

CCa Chlorophyllide a,

CL Lutein,

CN Neoxanthin,

CN+V Neoxanthin plus violaxanthin,

CP ba Phaeophorbide a,

CP ta Phaeophytin a,

CP r Prasinoxanthin,

CV Violaxanthin, and

CZ+L Zeaxanthin plus lutein.

These 11 pigments are a mixture of chlorophylls and carotenoids. They are not the full subset of secondary and

tertiary pigment analyzed by three or more laboratories,

but are representative of the most important secondary

pigments for marine studies (the chlorophyll a family of

pigments) plus some of the usually minor pigments that

many methods quantitate (the tertiary carotenoids).

The symbology presented here is used primarily to represent the final pigment concentrations for each field sample, because this is the way most laboratories report their

results, and replicate sampling is not a normal procedure

in field campaigns. The symbology does not include the

concentrations associated with the individual samples that

were used to determine the final sample value.

1.3 THE GOVERNING EQUATIONS

Ignoring the specific details of the basic HPLC processes, because they are presented in detail by Jeffrey et

al. (1997a) and Bidigare et al. (2003), the formulation for

determining pigment concentration begins with the terms

describing the calibration of the HPLC system:

C ̃Pi = AˆPi RPi , (1)

where C ̃Pi is the amount of pigment injected (usually in

units of nanograms), AˆPi is the area of the parent peak

and associated isomers for pigment Pi (usually in milliabsorbance units (denoted mAU) or microvolts as a function of time), and RPi is the response factor. The latter

is the calibration coefficient for the HPLC system, and it

takes on a separate value for each pigment being quantitated. For the general problem, the response factor is

denoted R, but for the specific problem of a particular

pigment, it is denoted RPi . The R values are usually expressed as the amount of pigment divided by the peak area.

The formulation given in (1) is based on a single-point

calibration wherein one or more injections of a calibration

standard at a known concentration is injected onto the

HPLC column. An alternative approach is to create a

dilution series of the pigment standard, inject these one at

a time, and then fit the response of the HPLC system to

a linear function (y = mx + b) using least-squares analysis

(this is also referred to as a multipoint calibration). In this

case, pigment concentration is computed as

C ̃Pi = AˆPi − bi

mi

, (2)

where mi is the slope (equating change in peak area with

change in amount) and bi is the y-intercept.

The formulation presented in (2) can be expressed to

follow (1) as follows:

C ̃Pi = AˆPi



1 − (bi/AˆPi )

mi



, (3)

where the equivalent RPi for (1) is given by the terms in

brackets. If the linear regression is forced through zero,

bi = 0, and (3) becomes

C ̃Pi = AˆPi

mi

, (4)

and RPi = 1/mi (note that the inverse slope is change in

amount divided by change in peak area, which matches

the definition for R). In this context, it is convenient to

reconsider the definition of RPi , which some authors have

done (Bidigare et al. 2003), as the inverse of the original

definition, that is, FPi = 1/RPi and (1) becomes

C ̃Pi = AˆPi

FPi

. (5)

The advantage of this approach is FPi follows directly from

the slope of the linear calibration curve and, for the common case of forcing the slope through zero, FPi = mi. For

the purposes of this study, the majority of the methods

used the original definition of R, so it is retained hereafter.

The governing equation for the determination of pigment concentration can be expressed as

CPi = Vx

Vf

C ̃Pi

Vc

, (6)

where Vx is the extraction volume, Vc is the volume of

sample extract injected onto the HPLC column (measured

in the same units as Vx), and Vf is the volume of water

filtered in the field to create the sample (usually through

a 0.7 μm pore size glass-fiber filter and measured in liters).

The variables used to compute RPi in (1), or the terms

in brackets in (3), follow from the procedures used to determine the concentration of pigment standards, which most

11
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

often are done spectrophotometrically based on principles

of the Lambert-Beer Law. The latter states that the fraction of the incident light at a particular wavelength λ that

is absorbed by a solution depends on the thickness of the

sample, the concentration C of the absorbing compound in

the solution, and the chemical nature of the absorbing compound (Segel 1968). This relationship can be expressed as:

APi (λ) = aPi (λ)lc CPi , (7)

where APi (λ) is absorbance, aPi (λ) is the absorption coefficient (a constant), and lc is the sample thickness in

centimeters (the cuvette pathlength). To compute concentration from a measured absorbance, (7) is rewritten as

CPi = APi (λ)

aPi (λ)lc

, (8)

where the units for CPi depend on the expression of aPi (λ).

For example, if the concentration is expressed in molarity, a becomes the molar absorption coefficient (ε) and if

the concentration is expressed as grams per liter, a is the

specific absorption coefficient (α). Absorption coefficients

vary depending on wavelength and the solvent in which

the compound is suspended, and they are always provided

with the solvent and wavelength used.

Pigment standards used for HPLC calibration are either a) purchased in solution (with concentrations provided by the manufacturer), b) isolated from natural

sources, or c) purchased in solid form. In the latter two

cases, pigments are suspended in the solvents specified for

use with the selected absorption coefficients, which also determines the wavelength used to measure the absorbance

spectrophotometrically. Assuming the specific absorption

coefficient is used, computing the concentration of a pigment standard Si requires the wavelength of maximum absorbance for the pigment, λm (specified with αSi ), plus a

correction measurement for the absorbance of the pigment

at 750 nm:

CSi = ASi (λm) − ASi (750)

αSi (λm)lc

, (9)

where ASi is the absorbance of the internal standard.

The calibration process continues with a volume of the

standard, Vc, being injected onto the HPLC column. This

assumes that the range of peak areas (for the pigment)

over which a linear response can be attained has already

been determined. With that knowledge, it will be known

whether or not the peak area of the standard (when injected undiluted) is within the linear range. For calibration purposes, the standard is injected at the wavelength

and bandwidth used for the quantitation of that pigment.

Chromatographic purity also needs to be assessed and can

be performed at additional wavelengths—most notably the

wavelength specified for use with the absorption coefficient or wavelengths permitting detection of other contaminating pigments. It is rare that a pigment standard is

chromatographically pure, meaning no isomers, allomers,

epimers or other such degradation products are present. It

is desirable that the parent peak (or main peak) represents

no less than 90% of the total of all peaks (excluding the

injection peak). The sum of the parent peak and the area

of the alteration products is denoted as ΣAˆSi .

Returning to the HPLC calibration equation, (1) can

be converted to concentration by including the Vc term:

CSi = AˆSi RPi

Vc

, (10)

and remembering that the same pigment is involved for Si

and Pi (the former is used to make it clear that a measurement is made on the pigment standard). The response

factor is now accessible, but there are two basic procedures

used for determining response factors, which are distinguished by how the peak area information is used and are

denoted as follows:

RΣ

Pi The amount injected onto the column divided by

the total peak area (including the sum of the parent

peak and degradants).

R%

Pi The purity-corrected amount injected onto the column divided by the area of the main (or parent)

peak alone.

With acceptably pure standards, RΣ

Pi is sufficiently similar to R%

Pi so that either approach is valid. In fact, as will

be shown below, they are computationally equivalent.

To derive RΣ

Pi

, the definition from above is applied,

which produces the following:

RΣ

Pi = VcCSi

ΣAˆSi

, (11)

where the numerator on the right side is the amount injected on the column and the denominator is the total

peak area. To make use of the spectrophotometric work

that began the calibration process, (9) is substituted for

CSi in (11), and the terms rearranged to yield:

RΣ

Pi = ASi (λm) − ASi (750)

αSi (λm)lc

Vc

ΣAˆSi

, (12)

and noting that ΣAˆSi can be used directly in (10) for the

peak area term, and then (9) and (10) can be equated to

provide RΣ

Pi

.

To derive R%

Pi

, a formulation for purity needs to be

established, and the typical definition is the ratio of the

main (or parent) peak divided by the sum of the parent

peak plus degradants:

Aˆ%

Si = AˆSi

ΣAˆSi

, (13)

where the numerator is the main peak and the denominator

is the sum of peaks. The definition for R% requires the

12
Hooker et al.

purity-corrected amount injected onto the column, which

is the product of CSiVc Aˆ%

Si

, where the Vc term converts

the concentration to amount, and the purity term provides

the needed correction factor. Using the definition for R%

Pi

produces

R%

Pi = CSi Vc Aˆ%

Si

AˆSi

, (14)

but once (13) is substituted into (14), and (9) is applied,

the relationship becomes:

R%

Pi = ASi (λm) − ASi (750)

αSi (λm)lc

Vc

ΣAˆSi

, (15)

which is equivalent to (12).

Given the equivalence of (12) and (15), it is logical to

wonder why two techniques for calculating response factors

are desirable. It is primarily a function of the need to be

cognizant of the chromatographic purity of standards, for

it is not uncommon for purity to diminish as the standard

ages. In this case, a change in RΣ

Pi may be observed and

can be a direct result of the absorption coefficient used for

the standard not being completely accurate for the alteration products associated with the aged standard. More

importantly, the purity-corrected approach must be used

when the standard is diluted to the point where the alteration products are not detectable and only the main

peak can be integrated. In this case, the amount injected

is CSiVc Aˆ%

Si and the peak area of the standard is AˆSi .

In these instances, it is important to determine chromatographic purity with an undiluted standard that is near the

upper limit of the linear range so that alteration products

are detectable.

The formulations for response factors can be combined

with a typical quantitation equation for pigment concentration (6) to produce a governing equation involving all

the terms associated with computing the concentration of

a particular pigment in an individual sample:

CPi = Vx

Vf

AˆPi



ASi (λm) − ASi (750)

αSi (λm)lc ΣAˆSi



, (16)

where it is assumed Vc is the same for field samples and

laboratory standards, and the terms in brackets represent

the response factor.

Additional complexities occur, because an internal standard can be used to improve the determination of Vx.

There are two common procedures for using an internal

standard, and they are distinguished here by the number

of laboratory steps involved: a) the extraction solvent and

internal standard are contained together in a mixture (prepared beforehand), which is added to the sample in one

step; or b) the extraction solvent and internal standard

are added separately in two steps.

In the one-step approach, a volume of solvent and internal standard is mixed together in a batch, and a small

portion of the mixed volume, Vm, is added to the sample. In the two-step approach, a volume of the extraction

solvent, Ve, is added to the sample followed by a small

volume of internal standard, Vs. The filter, now soaking

in the solvent–standard mixture, is disrupted (most commonly with a sonic probe), clarified (to remove filter and

sample debris), and a volume of the clarified sample extract, Vc, is injected onto the HPLC column.

The internal standard permits a correction for the presence of residual water retained on the filter (plus any variations in extract volume caused by evaporation) by using

a) the peak area of the internal standard when it is injected onto the HPLC column (Aˆc) prior to its addition to

the sample, and b) the peak area of the internal standard

in the sample (Aˆs). In the one-step approach, Aˆc is determined by injecting the solvent–standard mixture onto

the HPLC column, whereas for the two-step approach, the

internal standard is injected directly onto the column. For

the one-step approach, the internal standard is diluted by

the extraction solvent, so Vx1 = VmAˆc1 /Aˆs1 , where the “1”

in the subscripts indicates the one-step methodology. For

the two-step approach, Vx2 = VsAˆc2 /Aˆs2 (the “2” in the

subscripts indicates the two-step methodology).

If an internal standard is not used, an estimate of the

volume of water retained on the filter, Vw, is added to the

volume of extraction solvent, Ve, so Vx= Ve + Vw. For

a 25 mm filter, water retention is usually assumed to be

0.2 mL (Bidigare et al. 2003). Whether or not this is a

realistic value is directly related to the protocols used in

the field. If filters are allowed to sit under vacuum after

all water has been exhausted, they can be dried too much.

Considering a one-step internal standard methodology

for determining Vx, (16) becomes

CPi = Aˆc1

Aˆs1

Vm

Vf

AˆPi



ASi (λm) − ASi (750)

αSi (λm)lc ΣAˆSi



, (17)

and now all terms associated with a rather complicated

protocol are accessible (assuming Vc is a constant). This

means an analyst can begin to assign uncertainties to each

term and ultimately estimate a final uncertainty for the

quantitated concentrations of each pigment. This is not to

imply that any terms not present in the governing equation should be ignored (e.g., the cancellation of Vc for the

assumptions presented here). It is important to scrutinize

each step of the protocol to ensure all parts are properly

understood.

1.4 LABORATORY METHODS

SeaHARRE is based on a global perspective, so it is

likely that some laboratories would receive samples that

were atypical of those for which their HPLC method was

originally intended. For example, it would not necessarily be true that a method developed for oligotrophic samples would perform optimally with eutrophic samples. The

13
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 6. A summary of the extraction specifications for each of the methods. The volume of solvent added

is given in milliliters. Each filter was disrupted for the indicated amount of time, allowed to soak for the

specified number of hours, and then clarified. For this and subsequent presentations, identification of commercial

equipment to adequately specify or document the experimental problem does not imply recommendation or

endorsement, nor does it imply that the equipment identified is necessarily the best available for the purpose.

Meth.

Code

Volume

Added

Extraction

Solvent

Internal

Standard

Mode and Time

of Disruption

Soak

Time [h] Clarification

C 4.2 97.5%

Acetone

Vitamin E

acetate

Sonicating

bath 15 min 15–18 Centrifuge, 0.2 μmTeflon syringe filter

D 3.0 95%

Acetone

Vitamin E

acetate

Sonicating

bath ∼10 min 24 0.45 μm Teflonsyringe filter

F 0.6 90%

Acetone

trans-β-apo8

-carotenal None 24 0.45 μm Teflon

syringe filter

G 1.8 95%

Acetone

Vitamin E

acetate Sonic probe ∼15 s 3–4 0.45 μm Teflonsyringe filter

H 4.2 95%

Acetone

Vitamin E

acetate Sonic probe ∼15 s 4 0.45 μm Teflonsyringe filter

J 2.5 100%

Acetone

Vitamin E

acetate Sonic probe 90 s 4 0.45 μm Teflonsyringe filter

L 3.0 100%

Methanol

Vitamin E

acetate Sonic probe 10 s 1† 0.7 μm GF/Ffilter

N 2.0 100%

Methanol

Vitamin E

acetate Sonic probe 20 s 2 Centrifuge 3 min(13,000 rpm)

S 4.0 100%

Acetone

trans-β-apo8

-carotenal Sonic probe <15 s ≥ 24 Centrifuge 4 min

(5,100 rpm)‡

U 0.6 90%

Acetone

trans-β-apo8

-carotenal None 24 0.45 μm Teflon

syringe filter

† The sum of soaking for 0.5 h, sonicating, and then soaking for another 0.5 h.

‡ Plus a 0.2 μm Teflon membrane filter.

HPLC methods presented here (Chaps. 2–11) are based on

diverse objectives, but are most commonly used with samples from a variety of environmental regimes:

C Based on the Van Heukelem and Thomas (2001)

method and used predominantly with temperate water samples;

D Based on the Van Heukelem and Thomas (2001)

method and used mostly with samples from freshwater, estuaries, and coastal areas;

F Based on the Pinckney et al. (1997) method and

used with a wide range of marine samples;

G Based on the Van Heukelem and Thomas (2001)

method and used primarily for methodological research with a wide variety of aquatic samples;

H Based on the Van Heukelem and Thomas (2001)

method and used with a wide variety of water samples from freshwater lakes, estuarine ecosystems,

and the oligotrophic ocean;

J Based on the Van Heukelem and Thomas (2001)

method and used predominantly for the analysis of

coastal samples;

L Based on the Van Heukelem and Thomas (2001)

method and used initially with Case-1 (open ocean)

samples, but also successfully with Case-2 (coastal)

waters;

N Based on the Wright et al. (1991) method and used

with a wide range of oceanic samples;

S Based on the Wright et al. (1991) method and used

with a wide range of pigment concentrations from

water types throughout the world ocean; and

U Based on the Pinckney et al. (1997) method and

used with a wide range of samples from marine

ecosystems.

Note there are 10 laboratories, but essentially only three

distinctly different methods. It is important to remember,

however, that the implementation of a common method

always results in differences that will distinguish seemingly

identical methods from one another over time.

A summary of the filter extraction procedures is presented in Table 6. All of the methods used acetone as

an extraction solvent, except for L and N, which used

methanol. Sonic disruption predominated, although two

methods (F and U) used none. The soak time for the

extract ranged from 0.5 h to more than 24 h, and clarification was mostly accomplished by filtration with a few

methods including centrifugation in the procedure. The

14
Hooker et al.

Table 7. A summary of the HPLC separation procedures used by the SeaHARRE-4 methods. Column particle

size (Ps) is in units of micrometers, and column length (Lc) and diameter (Dc) are given in millimeters. Column

temperature is denoted as Tc, and wavelength is denoted as λ.

Meth. Stationary Column Detector and Monitoring Wavelength

Code Phase Ps Lc Dc Tc Manufacturer and Model λ [nm]

C C8 3.5 150 4.6 55◦C Waters PDA 996 436

D C8 3.5 150 4.6 60◦C Shimadzu SPD-M10A VP-DAD 222†, 450, and 665

F C18 3.0 100§ 4.6 40◦C Shimadzu SPD-M10A VP 440

G C8 3.5 150 4.6 60◦C Agilent 1100¶ 222†, 450, and 665

H C8 3.5 150 4.6 60◦C Agilent 1100 222†, 450, and 665

J C8 3.5 150 4.6 60◦C Agilent 1100 222†, 450, and 665

L C8 3.5 150 3.0 60◦C Agilent 1100 222†, 440, 667, and 770

N C18 5.0 150 4.6 Room‡ Agilent 1100 436 and 450

S C18 5.0 250 4.6 Room‡ ThermoQuest UV6000 436 and 450

U C18 3.0 100§ 4.6 40◦C Shimadzu SPD-M10A VP 440

† Used for monitoring vitamin E (the internal standard).

‡ Maintained at 18◦C by a specialized air conditioner.

§ The monomeric column is 15 mm.

¶ The G method was executed on the same hardware used by H.

Table 8. A summary of the HPLC solvent systems used with the SeaHARRE-4 methods: MeCN is acetonitrile,

NH4Ac is ammonium acetate, EtOAc is ethyl acetate, MeOH is methanol, and TbAA is tetrabutyl ammonium

acetate. The flow rate is in units of milliliters per minute.

Meth. Injection Flow Mobile Phase Solvent Initial

Code Buffer Rate A BC Conditions

C TbAA:MeOH† 1.1 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

D TbAA:MeOH† 1.1 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

F 1.0 M NH4Ac 0.8‡ 80:20 MeOH:0.5 M NH4Ac§ 80:20 MeOH:Acetone 100% A

G TbAA:MeOH† 1.1 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

H TbAA:MeOH† 1.1 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

J TbAA:MeOH† 1.1 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

L aqueous TbAA¶ 0.55 70:30 28 mM TbAA:MeOH MeOH 95% A:5% B

N 0.5 M NH4Ac 1.0 80:20 MeOH:0.5 M NH4Ac 90:10 MeCN:Water EtOAc 100% A

S Water 1.0 80:20 MeOH:0.5 M NH4Ac 90:10 MeCN:Water EtOAc 100% A

U 1.0 M NH4Ac 0.8‡ 80:20 MeOH:0.5 M NH4Ac§ 80:20 MeOH:Acetone 100% A

† 28 mM TbAA:MeOH in a 90:10 (v:v) mixture, and the TbAA has a 6.5 pH.

‡ Variable flow rate of 0.8–1.5 mL min−1.

§ Adjusted to 7.2 pH.

¶ 28 mM aqueous TbAA with 6.5 pH.

internal standard used by C, D, G, H, J, L, and N was

vitamin E acetate, whereas the F, S, and U methods all

used trans-β-apo-8

-carotenal.

A summary of the HPLC column separation procedures

and solvent systems are given in Tables 7 and 8, respectively. The type of stationary phase divides the methods

into two groups, C8 and C18, with the former predominating. Additional distinctions can be seen with a) column

temperature (N and S18 did not control column temperature while C, D, G, H, J, and L used high temperature control), and b) multiple- versus single-wavelength

monitoring systems (C only used 436 nm). Note also the

diversity in equipment manufacturers. All methods used

an injection buffer, and the majority of the methods were

two-solvent systems, with S18 using a three-solvent system.

The flow rates of the methods are very similar except for

laboratory L, which had a flow rate that is half as much as

the others (a lower flow rate is required with the narrower

internal diameter column used by L).

1.5 DATA ANALYSIS METHODS

This study used a laboratory mix and field samples,

both with unknown concentrations. Each laboratory participated as if the analyses were performed as a result of

normal operations; that is, a single concentration value was

reported by each laboratory for each pigment in each filter.

For subsequent data analyses, solitary pigment concentrations per batch were used and were determined as the average concentration of a pigment across a set of triplicates,

15
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

also referred to as a “sample.” To ensure a consistency in

reporting, all values were converted to concentrations of

milligrams per cubic meter.

In the analytical approach adopted here for field samples, no one laboratory (or result) is presumed more correct

than another—all the methods were considered properly

validated by the individual analysts. Furthermore, there

is no absolute truth for field samples, so an unbiased approach is needed to intercompare the methods. The first

step in developing an unbiased analysis is to calculate the

average concentration, C ̄, for each pigment from each sample as a function of the contributing laboratories or methods:

C ̄Lj

Pi (Sk) = 1

NR



NR

l=1

CLj

Pi (Sk,l), (18)

where Pi identifies the pigment or pigment association (following the symbology established in Sect. 1.2.3); Lj is the

laboratory (or method) code; Sk,l sets the batch (or station) number and replicate number, using the k index for

the former (following Table 3) and l for the latter (l = 1,

2, or 3); and NR is the total number of replicates (3).

In (18), the i index represents an arbitrary ordering of

the pigments, and the j index is used for summing over the

10 laboratory (or method) codes. Although any ordering

for the pigments and methods is permissible, the former

are ordered following their presentation in Table 6; for the

latter, j = 1, 2,...,10 corresponds to the C, D, F, G, H,

J, L, N, S, and U methods, respectively (which is based

on a simple alphabetic ordering of the one-letter codes).

Only one value for each pigment is computed for each

station, and this is generically referred to as a “sample,”

so the number of samples equals the number of stations

(or batches). Averages of a sample across the methods

reporting a particular pigment in a sample are used to

estimate the true value of the pigment for each sample (or

station):

C ̄A

Pi (Sk) = 1

NL



NL

j=1

C ̄Lj

Pi (Sk), (19)

where the superscript A denotes an average across all (applicable) methods, and NL is the number of laboratories

or methods quantitating a pigment. For the primary pigments, NL = 10, but for the secondary and tertiary pigments NL is frequently less than 10 (Table 4).

The unbiased percent difference (UPD), ψ, for each pigment of the individual laboratories with respect to the average values are then calculated for each sample as

ψLj

Pi (Sk) = 100

CLj

Pi (Sk) − C ̄A

Pi

(Sk)

C ̄A

Pi

(Sk) . (20)

Note that the formulation in (20) provides a relative percent difference (RPD), because it is signed: a positive ψ

value indicates the pigment concentration for a particular

laboratory was greater than the average for that pigment

(a negative value indicates the laboratory pigment concentration was less than the average). Although C ̄A

Pi is not

considered truth, it is the reference value or proxy for truth

by which the performance of the methods with respect to

one another are quantified.

When RPD values for methods that do not present any

trend relative to the average consensus are summed, however, there is the risk of destroying some or all of the variance in the data. To preserve an appropriate measurement

of the variance in the data, absolute UPD values, |ψ|, are

averaged over the number of samples (NS) to give the average absolute percent difference (APD) of each laboratory

for each pigment across all the samples:

|ψ ̄|

Lj

Pi = 1

NS



NS

k=1



ψLj

Pi (Sk)



, (21)

where Sk is the kth batch (or station) number (Table 3)

associated with pigment Pi. For the analysis of field samples, NS = 12, but when the analysis is extended to mixed

laboratory samples, NS is less and depends on the number

of times a laboratory analyzed and reported results for the

mixed laboratory sample (e.g., the DHI mix).

Absolute values are used in the overall averages, so positive and negative ψ values do not cancel out and artificially lower the average difference. The latter is particularly important for pigments with low concentrations, but

also in terms of a general philosophy: the primary measure

of dispersion between the methods are the ψ and |ψ ̄| values,

so it is important to ensure they are not underestimated.

Another useful parameter is the average of the APD,

|ψ ̄|, values for a particular pigment across the number of

laboratories or methods (NL) reporting the pigment involved:

|ψ ̄|

A

Pi = 1

NL



NL

j=1

|ψ ̄|

Lj

Pi , (22)

where the A code indicates all the laboratories were averaged (and ψ ̄A

Pi values are formed in a similar fashion from

the UPD values). In general, (22) is only computed for the

primary pigments, so NL = 10.

To examine the replicate data for each method more

closely, the coefficient of variation (CV), ξ, is used, which is

expressed as the percent ratio of the standard deviation in

the replicate (σ) with respect to the average concentration

(C ̄):

ξ

Lj

Pi (Sk) = 100 σLj

Pi (Sk)

C ̄Lj

Pi (Sk)

, (23)

where Sk is the kth sample number, and the number of

replicates is three for all methods. Individual ξ values

are computed for each pigment, for each sample, and for

each method; and then all the ξ values for a particular

16
Hooker et al.

method are averaged to yield an average precision ( ̄ξ) for

the method and pigment:

 ̄ξ

Lj

Pi = 1

N



NS

k=1

ξ

Lj

Pi (Sk). (24)

Subsets of the laboratories (or methods) involved are

also used for different aspects of the analysis. One of the

most important results is the estimation of the uncertainties in the reported data products, which requires an estimate or proxy for the truth. From the perspective of pigment concentration, there is no a priori understanding of

truth with a field sample, so a procedure must be adopted

to determine it. For the SeaHARRE activity, the performance metrics established during SeaHARRE-2 (Hooker et

al. 2005) and expanded during SeaHARRE-3 (Hooker et al.

2009) are used to determine the quality of the results from

the participating laboratories. The methods satisfying the

quantitative level of performance (Table 9) are considered

to have uncertainties sufficiently low to be considered acceptable representatives of truth and are hereafter referred

to as the QA subset. The results from the other methods

are considered to be not validated (NV) at the performance

level associated with the QA subset. The methods in the

NV subset are not used in determining truth.

To compute uncertainties, (19) is modified to include

only the contributions from the QA subset:

C ̄A

Pi (Sk) = 1

NL



NL

j=1

C ̄Lj

Pi (Sk), (25)

where the A code indicates the QA subset, and NL is set

to index over the laboratories within the QA subset. The

UPD values (relative uncertainties) are then computed by

using (25) in (20):

ψLj

Pi (Sk) = 100

CLj

Pi (Sk) − C ̄A

Pi (Sk)

C ̄A

Pi (Sk) , (26)

where the reference value for truth in each calculation is

given by C ̄A

Pi (Sk). APD values are determined using (21).

Summary averages for the performance of the QA and

NV subsets are derived from (22) by setting NL to reflect

the number of laboratories (or methods) within each subset. Although it is a notable achievement to be included

in the QA subset—which is associated with a data quality

level in keeping with calibration and validation activities—

there are many research inquiries that do not require this

level of expertise. A significant advantage of not initially

being in the QA subset is all subsequent evaluations are

truly independent, so a laboratory (or method) that is evaluated against the QA subset and found to have data products in keeping with the quantitative level of performance

has achieved a singularly remarkable result. Indeed, one

of the most useful aspects of the SeaHARRE activity is

to provide the opportunity of any method to be evaluated

against established performance capabilities and criteria.

The formulations presented in (18)–(26) are for the field

samples, but they are applicable to the laboratory standards by redefining the indexing limits and setting Sk to

match the laboratory samples.

1.6 RESULTS

Before presenting any results, it is useful to clarify the

definitions of certain key terms required for arriving at any

statistical description of the various methods. Although

not all of these terms are used in this study explicitly,

they are all defined to provide complete clarification:

• Accuracy is the estimation of how close the result

of the experiment is to the true value.

• Precision is the estimation of how exactly the result

is determined independently of any true value.

• Repeatability, also called within-run precision, is

obtained from a single operator, using the same instrument, and analyzing the same samples from the

same batch.

• Reproducibility, also called between-run precision,

is obtained from different operators, using different

instruments and analyzing separate samples from

the same batch.

Note that alternative definitions and quantifications are

possible, and the ones advocated above are simply the ones

deemed suitable for this study.

Two of the most important variables in the results presented here are accuracy and precision, and a simpler definition for these parameters is:

Accuracy is telling a story truthfully, and precision

is how similarly the story is repeated over and over

again.

For the analytical approach adopted here, the average accuracy is represented by the average APD values across

the 12 samples, |ψ ̄|, and the average precision is given as

the average CV across the 12 samples,  ̄ξ. These are the

principal parameters for determining method performance

and the uncertainties in the methods.

The first step in the analysis of the SeaHARRE data

is to establish the QA subset using the performance metrics (Table 9). This is initially based on the precision obtained with the field samples. A method with an average

precision not satisfying the semiquantitative performance

metric—more than 8% plus 2% for field sample variability

(or approximately 10%)—is excluded from the QA subset

(F and U). In addition, a laboratory with three or more

primary pigments with a precision exceeding routine capabilities (13%) is considered for exclusion (N).

The second step is to use a permutation analysis of the

results versus different selections of which laboratories constitute the reference set for computing uncertainties. For

17
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 9. The current performance metrics (for the four categories established during SeaHARRE-2) for validating the determination of marine pigments using an HPLC method (left to right): concentration (average

precision,  ̄ξ, and accuracy, |ψ ̄|, for TChl a and PPig); pigment sums (also for pigment indices); pigment ratios;

separation (minimum resolution, Rˇs, and average retention time precision,  ̄ξt

R ); injection precision,  ̄ξinj (the

average of an early- and late-eluting pigment standard, e.g., Perid and Chl a); and calibration (average residual,

|ψ ̄|res, for Chl a and the precision of the dilution devices,  ̄ξcal). The PPig and TChl a performance metrics are

based on using the analysis of a laboratory mixture of pigments and replicate field samples with approximately

equal weights applied to each (remembering that uncertainties are assumed to combine in quadrature and that

the latter presupposes the inclusion of replicate filter collection during field sampling). The corresponding values for method H during SeaHARRE-2 are given as an example (selected because SeaHARRE-2 represented an

exhaustive inquiry into method performance). The overall performance of H is considered “state-of-the-art,”

because the average score of the weights is 3.6, (4 + 4 + 4 + 3 + 4 + 3 + 4 + 3 + 3 + 4 + 4 + 4 + 3 + 4)/14.

Performance Weight, TChl a PPig Sums Ratios Sep.† Inj.‡ ( ̄ξinj) Cal.§

Category, and Score  ̄ξ |ψ ̄|  ̄ξ |ψ ̄|  ̄ξ |ψ ̄|  ̄ξ |ψ ̄| Rˇs  ̄ξt

R Perid Chl a |ψ ̄|res  ̄ξcal

1. Routine 0.5 8% 25% 13%40% 8%20% 5% 15% 0.8 0.18% 10% 6% 5% 2.5%

2. Semiquantitative 1.5 5 15 8 25 5 12 3 9 1.0 0.11 6 4 3 1.5

3. Quantitative 2.5 3 10 5 15 3 8 2 6 1.2 0.07 4 2 2 0.9

4. State-of-the-Art 3.5 ≤2 ≤5 ≤3≤10 ≤2 ≤4 ≤1 ≤3 ≥1.5 ≤0.04 ≤2 ≤1 ≤1 ≤0.5

Method H 1 5 2 12 2 5 1 5 1.2 0.02 <1 <1 1.1 0.4

† The Rˇs parameter is the minimum resolution determined from a critical pair for which one of the pigments is a primary

pigment. The retention time precision,  ̄ξt

R , values are based on sequential replicate injections of pigments identified in

a laboratory mix. In the absence of a diverse set of early- through late-eluting pigments, a practical alternative is to

compute  ̄ξt

R based on three sequential injections of Perid, Fuco, Diad, Chl a, and ββ-Car.

‡ The  ̄ξinj terms are calculated from the average of replicate injections of an early- and late-eluting pigment in the same

run. (Perid is chosen to include the possible effects of peak asymmetry, which is not presented as a separate parameter.)

§ The |ψ ̄|res values presented here are based on calibration points within the range of concentrations typical of the

SeaHARRE-2 field samples. To determine this metric for an arbitrary sample set, |ψ ̄|res is computed using those

calibration points within the range of concentrations expected in the field samples to be analyzed.

this inquiry, methods with an established QA capability

(i.e., satisfy the quantitative analysis performance metrics

in Table 9) are intercompared for consistency. The results

from the other methods with respect to the QA laboratories are then evaluated individually and as a group. The

threshold for retention within the QA subset is the average

uncertainty of the primary pigments must be to within 25%

(which is the semiquantitative performance metric) or to

within 5% of the average for the reference group. From an

overall performance perspective, these thresholds are based

on an approximately equal evaluation of both laboratory

standards and field samples, but because the difference between methods is not always as distinctive with laboratory

standards as it is with field samples, greater weight is given

to the results achieved with field samples when it comes

to establishing the QA subset. This procedure removes J

and N for inclusion in the QA subset.

The objective of the second step is to make sure methods close to a QA capability are carefully considered for

inclusion. One of the criteria considered is to investigate

beyond the primary pigments and look at the convergence

of the candidate method with respect to established QA

results with some of the tertiary pigments, like Neo, 

Viola, and Neo+Vio. This is considered important, because method-to-method differences can conceivably produce biases within the referencing system—particularly if

the QA subset is dominated by one particular method—

and one of the most important objectives of the intercomparison activity is to identify biases and resolve them. As

shown in Tables 2 and 7 and discussed in Sect. 1.4, the

majority of the methods used during SeaHARRE-4 were

based on C8 columns, and more specifically, were based on

a single C8 method (Van Heukelem and Thomas 2001).

Finally, the remaining laboratories in the QA subset are

intercompared. Any method with more than three individual pigments exceeding an uncertainty of 25% is normally

removed from the QA subset (if one of the pigments is

TChl a, the allowed maximum uncertainty is 15%), and

a new reference set for all pigments is computed. For

SeaHARRE-4, anomalously poor results for But required

this threshold to be relaxed to 30%. This procedure leaves

only the C, D, G, H, and L. All ensuing results presented

in the follow-on sections are based on these five laboratories as the quality-assured reference set (and are denoted

as the QA subset of methods or laboratories), except as

noted for specialized discussions.

A few aspects to note about the five laboratories in the

QA subset, in terms of the results that will be presented

in subsequent sections, are as follows:

• All of them, except G, participated in SeaHARRE-2

and SeaHARRE-3, and two of them (H and L) participated in SeaHARRE-1;

18
Hooker et al.

• With the exception of G, all routinely analyze a

large number of samples per year and have significant commitments to an established user base;

• All used the same C8 method (Van Heukelem and

Thomas 2001); and

• The participation of G was an experiment to demonstrate what a laboratory that had never done HPLC

analysis was capable of achieving if the method protocols and the performance metrics for quantitative

analysis were strictly followed.

The latter point is particularly relevant because it shows

the power of the performance metrics. The analyst in this

case was an established biogeochemist who had never done

an HPLC analysis, but who was familiar with the concept

of following best practices in the laboratory.

The introduction of the QA subset automatically establishes another subset: the laboratories (or methods) that

are not part of the QA subset are denoted A+, which is

composed of methods F, J, N, S, and U. In comparison,

for the laboratories not in the QA subset:

Only J and S participated in one or more prior

SeaHARRE activities;

Both C8 and C18 methods were used, with different

methods for both column types; and

Sample analysis varied for a large number of users

(S) at the production level of analysis (thousands

of samples per year) to exclusive analyses for a very

small user base (J).

The importance of these distinctions are considered in more

detail during the subsequent presentations of the results.

1.6.1 Average Pigment Concentrations

The analytical process begins with computing the reference or proxy for truth needed for evaluating the analysis

of the field samples by the individual methods, i.e., the

average pigment concentrations C ̄A

Pi in (25) are the reference values and these are computed from the QA subset.

Normally, any pigments with significant coelution or specificity problems are not included in producing the overall

averages, but for SeaHARRE-4 no such limitations existed

for the QA subset.

The average concentrations for the primary pigments

quantitated by the QA subset are presented in Table 10.

A recurring objective of field sampling for SeaHARRE activities is to have a wide dynamic range in 

TChl a



, typically two orders of magnitude, and the table shows this

was partially achieved for SeaHARRE-4. Although the dynamic range in chlorophyll is not as large as desired, the

dynamic range in several of the other primary pigments

exceeds what has been experienced in prior SeaHARRE

activities. The dynamic range in Fuco, for example, is almost two orders of magnitude with elevated concentrations

across the entire range.

Table 10 also shows the laboratories not part of the QA

subset are typified by higher concentrations on average,

which can be on the order of 100% or more (TChl c and

Caro, as well as But and Hex), but not in all cases. For

example, the results for TChl b, TChl c, and Zea are very

similar between the two subsets. Given the objective of

average PPiguncertainties to within 25% and TChl a



uncertainties to within 15%, the preponderance of large

differences represent significant performance challenges.

From a generalized perspective, any pigment with an

average concentration less than 0.050 mg m−3 can be considered to be at a low concentration. Table 10 shows some

of the carotenoids are below this limit with But and Hex

being notably so, and Diato being nearly so. The other carotenoids have average concentrations above this limit and

usually do not fall below it. The persistent low concentrations of But and Hex provide a significant opportunity

for false positives, i.e., a pigment is reported present, when

in fact it is not. Alternatively, a seemingly false positive

pigment result can occur when a method with exceptional

detectability quantifies a result, while other methods cannot detect it; although, the latter is a rare occurrence.

False positives are especially onerous to the computation of uncertainties because the larger false value is differenced with respect to the much smaller reference value,

which yields a relatively large number in the numerator

of (15). The denominator is the much smaller reference

value, so the computed uncertainty is a large number divided by a much smaller number, which frequently yields

an uncertainty of many hundreds of percent. So the large

overestimation of TChl c



, Caro, and But within the A+

subset is going to lead to very large uncertainties with respect to the relatively smaller A values.

A false negative occurs when a laboratory reports a pigment is not present when in fact it is. False negatives are

not as damaging as false positives, because a false small

number is differenced with respect to a larger reference

value, which yields a relatively large number in the numerator of (26). The denominator is the larger reference value,

so the computed uncertainty is a larger number divided by

a slightly larger number, which yields an uncertainty a bit

less than 100%.

The influence of false positives and negatives on method

uncertainty is usually minimal for pigments that are almost

always in an oceanic sample (e.g., Chl a), but they are

particularly important for pigments whose presence and

abundance changes significantly from sample to sample.

The average concentrations of the secondary and tertiary

pigments are presented in Table 11. Although there are

some low results for these pigments, all of them have average concentrations above 0.050 mg m−3 (except DVChl a).

The A+ subset results for the secondary and tertiary pigments are characterized by a mix of lower and higher concentrations with respect to the A subset, but the magnitude of the differences are not as great as was seen with

the PPig results (Table 10).

19
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 10. The average individual PPig concentrations for the QA subset (C, D, G, H, and L) as a function of

the batch sample number for the field samples (in units of milligrams per cubic meter). The overall averages for the

individual pigments for the QA subset, C ̄A

Pi , as well as the range in maximum and minimum values, CˆAPi and CˇAPi ,

respectively, are computed across the 12 samples. Corresponding overall averages for the methods not in the QA subset

are presented in the last three rows and are denoted by the A+ notations.

No. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea

1 42.704 9.971 2.958 2.432 0.137 0.059 0.222 0.857 0.381 10.185 0.097 1.471

2 13.598 0.293 1.424 0.345 0.033 0.021 0.179 0.384 0.039 5.179 0.999 0.146

3 19.244 0.463 2.706 0.458 0.001 0.001 0.288 0.588 0.035 6.145 0.003 0.007

4 2.626 0.530 0.205 0.120 0.007 0.001 0.113 0.075 0.018 0.500 0.021 0.031

5 4.971 0.645 0.187 0.282 0.001 0.001 0.186 0.097 0.007 0.452 0.018 0.199

6 3.944 0.708 0.325 0.137 0.002 0.003 0.162 0.085 0.017 0.702 0.032 0.057

7 5.504 0.433 0.843 0.176 0.020 0.016 0.059 0.266 0.028 1.535 0.867 0.096

8 5.671 0.213 1.022 0.137 0.001 0.020 0.038 0.437 0.041 1.743 1.208 0.044

9 20.836 0.521 1.614 1.008 0.003 0.019 7.438 0.295 0.125 1.049 0.408 0.030

10 3.226 0.314 0.426 0.123 0.002 0.002 0.202 0.134 0.004 0.652 0.380 0.052

11 2.671 0.459 0.305 0.130 0.004 0.006 0.086 0.093 0.001 0.225 0.455 0.204

12 1.896 0.110 0.361 0.061 0.006 0.039 0.060 0.112 0.006 0.611 0.077 0.031

CˆA

Pi 42.704 9.971 2.958 2.432 0.137 0.059 7.438 0.857 0.381 10.185 1.208 1.471

C ̄A

Pi 10.574 1.222 1.031 0.451 0.018 0.015 0.753 0.285 0.059 2.415 0.380 0.197

CˇA

Pi 1.896 0.110 0.187 0.061 0.001 0.001 0.038 0.075 0.001 0.225 0.003 0.007

CˆA+

Pi 51.141 11.724 74.519 21.039 2.166 0.434 9.907 1.748 0.699 20.171 3.696 1.935

C ̄A+

Pi 11.275 1.135 4.221 1.889 0.059 0.033 0.870 0.335 0.036 2.990 0.554 0.187

CˇA+

Pi 1.643 0.001 0.064 0.060 0.001 0.001 0.001 0.079 0.001 0.220 0.001 0.001

Table 11. A subset of the average secondary and tertiary pigment concentrations for the field samples analyzed by

the QA subset. The presentation follows the scheme established in Table 10.

No. 

Chl a

 DVChl a Chlide a 

Lut Neo Neo+Vio Phytin a

 Phide a Pras Viola Zea+Lut

1 40.601 0.001 2.103 2.530 0.473 0.848 7.144 14.833 0.142 0.375 4.001

2 12.867 0.001 0.731 0.015 0.008 0.038 0.632 4.429 0.001 0.030 0.160

3 14.970 0.001 4.274 0.010 0.032 0.103 0.266 1.905 0.007 0.071 0.017

4 2.404 0.001 0.222 0.010 0.057 0.105 0.169 0.316 0.123 0.048 0.040

5 4.822 0.001 0.149 0.162 0.084 0.170 0.190 0.152 0.121 0.087 0.362

6 3.774 0.001 0.170 0.024 0.081 0.148 0.090 0.100 0.181 0.067 0.081

7 4.815 0.001 0.689 0.091 0.061 0.110 0.083 0.283 0.022 0.049 0.187

8 5.095 0.001 0.575 0.022 0.034 0.065 0.043 0.113 0.034 0.031 0.067

9 20.368 0.001 0.474 0.048 0.045 0.130 4.567 0.605 0.032 0.086 0.078

10 2.982 0.001 0.245 0.003 0.041 0.079 0.068 0.091 0.078 0.039 0.055

11 2.587 0.001 0.084 0.023 0.055 0.097 0.029 0.031 0.053 0.043 0.226

12 1.586 0.001 0.310 0.043 0.022 0.041 0.017 0.033 0.023 0.019 0.073

CˆA

Pi 40.601 0.001 4.274 2.530 0.473 0.848 7.144 14.833 0.181 0.375 4.001

C ̄A

Pi 9.739 0.001 0.835 0.248 0.083 0.161 1.108 1.908 0.068 0.079 0.446

CˇA

Pi 1.586 0.001 0.084 0.003 0.008 0.038 0.017 0.031 0.001 0.019 0.017

CˆA+

Pi 49.594 0.001 6.824 7.161 1.406 1.928 5.982 21.667 0.392 0.522 8.824

C ̄A+

Pi 10.125 0.001 0.849 0.400 0.089 0.157 0.829 1.253 0.058 0.067 0.588

CˇA+

Pi 1.180 0.001 0.001 0.001 0.001 0.001 0.023 0.001 0.001 0.001 0.001

Notes: 1. The F, N, S, and U methods are not included in the A+ [DVChl a] results, because these methods did not chromatographically separate DVChl a (S used a simultaneous equation for information purposes only).

2. The A [Phide a] entries do not include values from G, and the A+ [Phytin a] and [Phide a] entries do not include values

from F and U.

20
Hooker et al.

Table 12. The method precision results for the individual PPig  ̄ξ values (coefficients of variation in percent)

across all 12 batches of field samples. The data are presented as a function of the laboratory (or method) with

the last column presenting the overall (horizontal) method average across the pigments. The overall (vertical)

QA subset averages (C, D, G, H, and L) are given in the A entries, and the methods that were not validated

at the QA level (F, J, N, S, and U) in the A+ entries. The lowest precision values for each pigment in the

QA subset constitute a hypothetical best method and are shown in bold typeface, which are summarized for

all pigments by the A- entries in the bottom row. The analyses made by laboratory L on the particulate

absorption filters are indicated by the L results, which are not included in the determination of the QA subset

or any of the summary averages; they are presented separately and are shown in slanted typeface. Exceptions to

the computation of any of the averages are indicated by a special symbol and explained below the table (most

exceptions attempt to deal with the fact that not all methods produce all data products, particularly for the

secondary and tertiary pigments).

Meth. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea Avg.

C 4.3 2.9 3.6 2.8 1.4 1.9 4.2 4.3 8.9 4.6 4.4 4.2 4.0

D 3.6 8.2 4.8 6.0 0.5† 5.1 4.9 5.6 12.2 5.8 4.7 5.9 6.1

G 4.8 5.9 3.4 4.9 0.0† 0.1† 5.7 5.1 4.1 4.3 3.7 6.1 4.8

H 5.8 4.9 5.5 5.9 17.9 4.1 5.4 7.3 8.0 5.0 8.3 4.4 6.9

L 2.8 5.0 4.3 2.8 2.9 2.0 10.9 4.0 7.2 3.6 3.3 5.1 4.5

L 1.8 5.7 2.4 3.1 6.2 1.9 4.5 8.9 5.9 2.6 2.7 4.1 4.2

F 8.6 12.6 61.9 16.6 35.5 39.8 33.5 12.6 28.0 14.3 34.0 26.4 27.0

J 3.5 6.8 11.1 6.1 6.1 4.3 4.7 5.8 22.7 4.0 3.5 6.4 7.1

N 7.5 6.6 9.4 18.6 1.0 3.8 16.3 16.7 9.2 10.2 6.4 5.7 9.3

S 2.6 3.5 6.1 4.1 3.3 6.5 4.9 5.9 14.0 2.5 8.8 5.9 5.7

U 6.6 19.6 12.2 9.5 0.0† 0.2† 15.2 9.0 37.5 8.9 5.9 26.2 15.1

A 4.3 5.4 4.3 4.5 7.4 3.3 6.2 5.3 8.1 4.7 4.9 5.1 5.3

A+ 5.8 9.8 20.1 11.0 11.5 13.6 14.9 10.0 22.3 8.0 11.7 14.1 12.7

A- 2.8 2.9 3.4 2.8 1.4 1.9 4.2 4.0 4.1 3.6 3.3 4.2 3.2

† Artificially low precision, because of a preponderance of false negatives—not included in averages.

1.6.2 Method Precision

Some laboratories use a field sample collected for HPLC

analysis for more than one purpose. For example, it is not

unusual for an HPLC filter to also be used to measure the

particulate absorption of seawater, which has the advantage of providing two measurements from the same water

sampling. LOV follows this practice and there has always

been some concern as to whether or not the additional

handling and different storage of the filter—it is kept in

a small plastic histoprep holder, so it can lay flat within

a protective shell—causes differences in the determination

of pigment concentrations.

Consequently, for SeaHARRE-4, LOV analyzed two

sets of filters (H was supposed to do the same, but was

unable to do so): a) the first set was collected and stored

following normal SeaHARRE practices (i.e., folded into foil

packets), and b) the second set was collected as usual, but

stored in histopreps. Both sets of filters were stored in

liquid nitrogen. The histoprep analyses are designated L

in all of the following presentations of results, and are not

included in the determination of the QA subset or any

of the summary averages—they are presented separately.

Separating the L results is not an a priori determination

that they are different—it is simply done to preserve an

equal weighting of the methods used to determine the reference values for computing uncertainties and to provide

an independent assessment of the LOV histoprep samples.

Method precision for each pigment is estimated by averaging the values computed from the sample triplicates

across all 12 samples, which is denoted by  ̄ξPi . Table 12

presents the method precision for the primary pigments

plus three types of overall precision: a) the average (Avg.)

across all primary pigments for each laboratory, b) the average values for the methods in the A and A+ subsets,

and c) the best precision obtained for each pigment within

the A subset, which is denoted A-. The latter represent

a theoretical best method threshold first tested and found

to be a satisfactory criteria for a state-of-the-art method

during prior SeaHARRE activities.

In most cases, the average method precision results for

the primary pigments show superior precision is associated

with TChl a



, and there is a general worsening of precision

for the other chlorophylls and carotenoids—this is particularly true for the A+ subset. The best average precision in

the A subset is for Hex, which was the primary pigment

present in the lowest average concentration (Table 10). As

shown in SeaHARRE-3 (Hooker et al. 2009), this result

is somewhat artificial, because much of the data was at

the limit of detection, so as long as a laboratory correctly

21
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 13. The  ̄ξ values (coefficients of variation in percent) across all 12 batches of field samples for a subset of

the secondary and tertiary pigments, following the presentation scheme established in Table 12. A blank entry

indicates a particular laboratory (or method) did not quantitate the pigment indicated; none of the averages

include contributions from blank entries.

Meth. 

Chl a

 DVChl a Chlide a 

Lut Neo Neo+Vio Phytin a

 Phide a Pras Viola Zea+Lut

C 4.3 0.0 2.7 3.6 3.8 6.1 1.2 7.6 3.6 4.9 5.5

D 10.4 0.0 22.5 6.4 6.5 8.0 7.9 12.9 3.0 4.7 8.7

G 6.6 0.0 16.2 4.1 4.1 6.7 7.2 1.7 5.4 7.4

H 9.8 0.0 46.2 6.0 4.4 10.0 9.6 7.5 14.7 9.0 7.4

L 2.9 0.0 12.9 3.1 4.0 6.7 3.4 8.6 6.8 5.4 6.0

L 1.9 0.0 8.3 3.9 2.5 19.1 2.1 7.0 3.7 18.9 5.7

F 9.5 42.4 26.4 16.3 53.2 16.5 50.6 37.4

J 4.8 0.0 26.0 15.3 4.5 6.8 19.1 6.8 5.6 5.1 16.6

N 10.4 18.2 6.1 8.0 20.8 6.3 4.7 7.0 19.2 8.3

S 3.6 8.6‡ 18.3 6.3 5.9 10.8 3.8 2.9 9.5 9.0 8.7

U 6.6 25.3 32.6 0.4† 20.9 0.9† 21.3 32.9

A 6.8 0.0 20.1 4.6 4.5 7.5 5.9 9.2 6.0 5.9 7.0

A+ 7.0 4.3 26.0 17.4 8.7 22.5 9.7 4.8 9.6 21.1 20.8

A- 2.9 0.0 2.7 3.1 3.8 6.1 1.2 7.5 1.7 4.7 5.5

† Artificially low precision, because of a preponderance of false negatives—not included in averages.

‡ Derived from a simultaneous equation (Latasa et al. 1996) and provided for information purposes only.

identifies the pigment is absent or minimally observed in

those samples, the precision will be very good.

The A average precisions fall within a narrow range

of outcomes, 4.0–6.9%, with the L results very close to

the best overall average. The C and G results, which like

L are histoprep samples, have six and two of the lowest

precision results, respectively. The C, G, and L results indicate storage in histopreps and absorption measurements

prior to HPLC analysis do not have a detrimental effect

on pigment precision. Despite the tight grouping within

the A averages, each individual method exhibits at least

one anomalously high precision value, e.g., But for H and

Diato for D. These distinctions are important indicators

as to where additional work needs to be done by the individual analysts in particular, and the SeaHARRE activity

in general.

The individual instances of excellent precision for specific methods and pigments within the QA subset (and also

in some of the entries for the other methods), show excellent precision is a recurring outcome across all pigments.

The precision of the selected best results in the QA subset (the bold entries in Table 12) ranged from 1.4–4.2%,

with an overall average of 3.2% (the overall average for

SeaHARRE-3 was 3.4%). The narrow range of precision

excellence, and because it occurs across three methods (C,

G, and L), suggests filter inhomogeneity is not a significant component of the variance, and that methodological

differences account for the majority of the diversity in the

precision results. The fact that the C, L, and L results

have an overall precision very close to the A- average shows

the best method approach is achievable and is a useful indicator of the state of the art.

The A+ average precisions for each primary pigment

show a larger range of outcomes. The J and S results are

similar to the A averages, the N results are slightly worse,

and the F and U results are significantly poorer. This

demonstrates the difficulty of using precision exclusively as

a criteria for evaluating method performance. The point

to remember here is that precision is the starting point,

and it is very difficult for a method to achieve a suitable

accuracy if method precision is poor, but that does not

mean a good precision will ensure good accuracy—it is a

necessary, but not sufficient, criteria.

Table 13 presents the precision obtained by the methods for a subset of the secondary and tertiary pigments

using the format established for Table 12. These results

largely confirm the precision conclusions obtained with the

primary pigments, but there are some differences. The best

precision of the QA subset occurs over a slightly larger

range (1.2–7.5%) and is spread across all five laboratories. The worst results are seen with 

Chlide a



, which was

present in reasonably high abundances (Table 10). Once

again, areas for additional research can be identified by

anomalously poor precision for individual methods. In

this regard, the L results for 

Viola, and by extension



Neo+Vio

, stand out because of significantly degraded values with respect to the L results. Although L has degraded precision for 

Violaand Neo+Vio

, the C and G

results have the lowest or near-lowest precision for both

parameters, which suggests the poorer L values are not a

consequence of histoprep storage. Overall, however, the L

method precision is in keeping with the A averages.

As anticipated from the PPig results, the A+ results

are usually worse than the A results—almost by a factor

22
Hooker et al.

Table 14. The  ̄ξ values (coefficients of variation in percent) for DHI Mix-102 as a function of the method for

the primary pigments using the presentation scheme from Table 12. The lowest  ̄ξ values from the QA subset

are given in the last row, A-.

Meth. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea Avg.

C 0.8 0.5 1.6 1.3 0.9 0.5 0.9 0.7 0.9 0.9 1.0 0.7 0.9

D 0.9 0.9 0.6 0.9 0.9 1.4 0.9 0.4 0.8 1.0 1.4 1.9 1.0

G 0.9 0.7 1.0 1.6 1.3 0.6 1.4 0.6 0.9 1.6 1.1† 0.9 1.1

H 0.9 1.3 1.1 1.1 0.9 0.8 0.7 1.1 0.9 1.3 1.1 1.0 1.0

L 0.1 0.2 0.4 0.2 0.2 0.7 1.2 1.0 0.8 0.7 0.2 0.3 0.5

F 4.4 4.5 13.3 4.4 3.8 4.7 2.5 4.2 3.9 3.6 5.8 4.5 5.0

J 2.7 0.7 1.2 0.6 0.7 1.3 1.2 0.5 0.6 1.2 3.5 0.6 1.2

N 0.2 0.2 0.2 1.3 0.1 1.2 0.2 0.2 0.1 0.3 0.5 0.0‡ 0.4

S 4.0 4.5 9.3 10.8 4.5 4.9 5.1 4.1 5.2 4.5 6.7 4.3 5.7

U 1.3 1.9 7.5 3.4 4.1 3.7 2.8 3.3 1.0 4.6 4.3 2.7 3.4

A 0.7 0.7 0.9 1.0 0.9 0.8 1.0 0.8 0.9 1.1 0.9 1.0 0.9

A+ 2.5 2.3 6.3 4.1 2.6 3.2 2.3 2.5 2.2 2.9 4.1 3.0 3.2

A- 0.1 0.2 0.4 0.2 0.2 0.5 0.7 0.4 0.8 0.7 0.2 0.3 0.4

† Revised GSFC Peri precision if the secondary Peri peak is quantitated in addition to the parent peak.

‡ Artificially low precision, because of a persistent nondetection—not included in averages.

of two on average. This is not true for all A+ methods

and all pigments, however. Many of the A+ results are

within the range of the QA subset, with the recurring exception of the F data. If the F data are excluded from

an A+ overall average, the remaining methods have an average precision that is within about 50% of the A overall

average–so approximately half the variance is coming from

a single method. Comparable reductions are achieved with

many of the individual PPig method precision values if the

same exclusion is applied to the A+ data in Table 12.

Table 14 presents the method precision for the primary

pigments quantitated for DHI Mix-102. The results show

the A subset has better average precision than the A+ subset, although some of the individual methods and pigments

of the latter are superior or are similar to the former (J

and N). The range in average precision for the A subset

is not very large (0.5–1.1%), and the A+ results are distinguished primarily by the three methods (F, S, and to a

lesser extent U) that are notably different with respect to

the A values. Although the three methods with the poorest precision are C18 methods, N is also a C18 method and

the results obtained were excellent.

The DHI mix does not have the full complexity of a

natural sample and the pigment concentrations are significantly elevated with respect to open-ocean surface waters,

particularly for many carotenoids. Identifying peaks in

the mix is easier than in a natural sample, so false positives or negatives are unlikely. Consequently, the precision

obtained with the mix should be closer to the injection

precision than the precision of a field sample. Nonetheless,

as will be shown later, the precision obtained with the mix

is an important QA opportunity, which can provide a lot

of information about method performance.

The A- results (which are a proxy for a theoretical best

method) are always to within 0.7% and have an overall average of 0.4%. This means they are within the 2% performance metric for state-of-the-art injection (Table 9), and

all the QA methods satisfy this metric for every pigment—

as does the N method (except for Zea). The fact that so

many methods achieved precision results close to or within

this value is a notable indicator that using the best results

from the QA subset produces a realistic and achievable

metric for what a method should be capable of achieving.

1.6.3 Method Accuracy

Method accuracy for pigment products are determined

using |ψ ̄|, the average APD between the reported laboratory values and the average concentrations constructed

from the QA subset, that is, (26) is used in (21). Although

the limitations already noted in determining method precision (Sect. 1.6.2) are relevant to understanding accuracy,

most do not actually change the computations. There are

exceptions, however, and the two most important are the

aforementioned false positives and negatives (Sect. 1.6.1),

which are both specificity problems.

Note that the primary difference between false negatives and false positives is the uncertainty of a false negative is bounded (it cannot be more than 100%), whereas

the uncertainty for a false positive is unbounded (it can

be many times more than 100%). In both cases, the actual uncertainty will be somewhat mitigated if the true

concentration of the pigment is close to detection limits,

because the multiplicative factor relating the observation

to the reference value will be a small number. The false

positive situation, however, will usually be the most serious

in terms of average uncertainties.

23
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 15. The |ψ ̄| values (average APD in percent) across all 12 batches of field samples for the primary

pigments following the presentation scheme established in Table 12. Exceptionally large uncertainties with

truncated digits of precision are shown in a red typeface.

Meth. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea Avg.

C 4.5 16.0 31.2 6.8 79.0 78.1 26.7 16.0 56.4 12.5 53.4 21.2 33.5

D 5.4 14.5 30.2 18.5 65.2 45.8 9.2 7.8 30.7 6.0 103.7 17.2 29.5

G 7.8 6.5 9.4 4.4 75.7 61.8 14.4 8.4 66.0 3.3 51.6 21.0 27.5

H 6.8 6.8 16.5 12.3 144.6 57.0 9.1 7.4 64.0 7.9 67.6 15.1 34.6

L 7.4 18.2 14.8 5.8 71.4 44.9 5.8 6.9 32.1 3.3 56.5 20.3 23.9

L 7.5 22.6 14.0 4.2 92.5 45.7 12.4 11.8 31.8 5.0 56.7 20.9 27.1

F 24.6 19.7 55.3 1,318 36,471 122.7 29.8 18.0 86.7 33.2 93.1 56.8 3,194

J 22.7 20.6 13.2 10.1 441.7 66.3 32.1 18.3 32.7 16.7 57.9 30.4 63.6

N 6.9 26.2 12.2 9.0 653.3 897.0 20.0 21.5 94.0 16.0 95.2 271.4 176.9

S 34.1 23.9 32.3 67.3 2,750 3,068 5.1 13.6 30.6 7.5 284.1 55.1 530.9

U 10.7 4.2 1,328 325.2 75.7 64.2 37.1 31.8 65.8 27.0 68.6 32.5 172.6

A 6.4 12.4 20.4 9.6 87.2 57.5 13.0 9.3 49.8 6.6 66.6 19.0 29.8

A+ 19.8 19.0 288.2 345.9 8,078 843.6 24.8 20.7 62.0 20.1 119.8 89.2 827.6

A- 4.5 6.5 9.4 4.4 65.2 44.9 5.8 6.9 30.7 3.3 51.6 15.1 20.7

1.6.3.1 Individual Pigments

The performance metrics for QA (quantitative) performance require an average 

TChl a

 and 

PPig uncertainty to within 10% and 15%, respectively (Table 9). Recalling the allowed variance in establishing the QA subset

(Sect. 1.6)—no more than three individual primary pigments were permitted to exceed an uncertainty of 25% and

the TChl a



uncertainty must be within 15%—the expectation is all QA methods will have PPig uncertainty results

satisfying these criteria.

The individual and summary PPig uncertainties are

presented in Table 15, which shows the QA subset (A

)

comes close to, but does not satisfy, the quantitative performance metric for accuracy—the overall uncertainty is

29.8%. Furthermore, only one of the overall individual

method uncertainties, L, is less than 25% (the semiquantitative performance threshold); although G is within the

2–3% expected variance from natural variability for this

level of performance. The results for TChl a

 are more

promising. All QA laboratories are well within the 15%

threshold, as is the A average. Furthermore, the overall

A average and all the individual A methods have TChl a

uncertainties within the 2–3% sampling variance for the

state-of-the-art performance metric.

The two most problematic pigments within the A subset are But and Hex. If either had an uncertainty more

in keeping with expectations, the overall A average would

be closer to 25% (for SeaHARRE-3, But and Hex had QA

uncertainties of 14.6 and 6.0%, respectively). The results

for Peri are also high, but not as anomalous as for But

and Hex (the QA uncertainty for Peri in SeaHARRE-3

was 30.5%). The values for Diato are also high, but Diato

has been a problematic pigment in the past, e.g., during

SeaHARRE-1 where the average A uncertainty was even

higher. Although there are many But and Hex samples

that are detection limited, this is not true for some of the

Diato samples and most of the Peri samples. Consequently,

the challenges go beyond a single simplistic explanation.

The results from the A+ methods are significantly different from the A subset and are characterized by higher

or significantly higher uncertainties. The overall average

PPig uncertainty (827.6%) does not satisfy any of the performance metrics (Table 9), and neither do any of the

individual methods (although the J method is the closest). The routine performance metric for TChl a is satisfied as an overall average, and the N and U methods

satisfy the quantitative and semiquantitative performance

requirements, respectively, while the F and J methods are

within the routine analysis threshold.

The problematic pigments within the A+ subset are the

same ones seen with the A subset with the addition of

TChl c and Caro. For the latter two, most of the difficulty arises from the F and U results, which are based on

the same method. The implementation of the method at

the two laboratories appears notably different, because the

magnitude of the uncertainties do not covary that closely.

The individual pigment results for the A+ subset are further distinguished by all methods contributing very large

uncertainties to one or more of the problematic pigments

(only J has large uncertainties for only one pigment).

The best possible outcomes from the QA subset, the

A- entries, have an overall average TChl a and PPig uncertainty of 4.5 and 20.7%, respectively. These results are

within the requirements for quantitative and semiquantitative performance, respectively. The L overall PPig average uncertainty also satisfies this metric to within the 2–3%

sampling variance. Note that the invocation of adding a

margin of 2–3% variance for the performance discussions

24
Hooker et al.

is simply a reflection that only field samples are being considered and there is a small amount of variance that comes

from the preparation of field replicates—they are not perfect replicates—and this variance is beyond the control of

the methods being intercompared.

As noted earlier, the J method stands out within the

A+ subset, because it has the lowest overall average uncertainty in the A+ subset. If the But results were not so

anomalous (i.e., closer to the A average), the overall PPig

average uncertainty for J would be within the range of uncertainties for the A subset. What this shows is the value

of a proper referencing system: it highlights which parts

of a method need additional attention and which parts are

performing adequately. The latter qualification is simply a

reminder that although the J method has been intercompared before, SeaHARRE-4 was the first intercomparison

for J after switching to the Van Heukelem and Thomas

(2001) method. Consequently, additional intercomparisons

are needed to verify the findings emerging here.

Within the context of needing more than one intercomparison to provide confidence in the capabilities of a

method, it is worth reviewing the histories of the methods

being intercompared here (Tables 1 and 2):

C Participated in SeaHARRE-2, but switched to the

Van Heukelem and Thomas (2001) method for the

SeaHARRE-3 activity; only the latter results were

part of the QA subset.

D Participated in SeaHARRE-2 and SeaHARRE-3,

and both results were part of the QA subset.

F Had not participated in a prior SeaHARRE activity.

G Had not participated in a prior SeaHARRE activity and participated in SeaHARRE-4 as a novice

practitioner.

H Participated in all prior SeaHARRE activities and

always produced results as part of the QA subset.

J Participated in SeaHARRE-1 and SeaHARRE-3,

and the former results were part of the QA subset.

L Produced results that were part of the QA subset for SeaHARRE-1, but not for SeaHARRE-2;

switched to the Van Heukelem and Thomas (2001)

method for SeaHARRE-3, and results were part of

the QA subset.

N Had not participated in a prior SeaHARRE activity.

S Participated in SeaHARRE-2 with results that were

part of the QA subset; the inability to chromatographically separate Chl a and DVChl a led to the

use of the Van Heukelem and Thomas (2001) method for SeaHARRE-3 along with the original method,

but neither method produced results as part of the

QA subset.

U Had not participated in a prior SeaHARRE activity.

Out of all of these laboratories, H and L are the only

ones to have participated in all prior SeaHARRE activities.

Laboratories C, D, J, and S have now participated in three

round robins, but C, D, and J are no longer using their

original methods; S switched back to their original method

for SeaHARRE-4.

The participation history of the various methods establishes how difficult it is to a) confidently evaluate a method

using only one intercomparison, b) maintain a QA status

over time, and c) further develop or troubleshoot the capabilities of a method—several analysts simply changed

to a proven method rather than try to refine an existing

method. For the methods considered here, only H has

consistently produced QA results over an extensive (many

year) time span, although C, D, and L are now emerging

with sufficiently long time series of quality control variables. This means comparisons to individual established

methods, or the time series of the results from those methods, help establish confidence in many of the findings presented here.

One of the important results from the intercomparison

of the PPig analysis is how similar the data within each of

the two A and A+ subsets are, and how distinctly different the two subsets are with respect to one another. For

example, each method in the A+ subset has at least one

pigment with uncertainties that are many hundreds of percent, and three have uncertainties exceeding 1,000%. The

A subset has much lower uncertainties, although D and

H have large values for Peri and But, respectively. If the

referencing system was flawed, at least one of the methods

within one of the two groups would appear out of place

with a set of results that would not be in keeping with the

group in which it was placed.

If the referencing system involved all of the methods,

the aforementioned distinctions would become less notable,

because the variance between the populations of results

would be shared between the individual contributors. For

example, the average uncertainty in PPig for the A subset would increase to 38.7%, whereas it would decrease to

67.8% for the A+ subset. Consequently, both sets would

not be within the limits for routine analysis, but the A+

subset would have improved by more than an order of magnitude (the prior value was 827.6%). The effects on TChl a

would be less significant, because the A+ results were not

as dramatically different: the uncertainty for the A subset would increase to 6.8%, and decrease to 17.9% for the

A+ subset. Both results would stay within their respective original quality categories of quantitative and routine

analysis. The significant change for the PPig average uncertainties, however, shows the importance of selecting and

defending a proper referencing system. If the results are

blindly pooled together, the methods with reduced performance metrics are improved at the expense of the higher

performing methods and a false understanding of uncertainties is presented.

This concept of whether or not the referencing system

is properly established is further evaluated by investigating

the uncertainties for the secondary and tertiary pigments,

25
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 16. The |ψ ̄| values (average APD in percent) across all 12 batches of field samples for a subset of the

secondary and tertiary pigments (following the presentation scheme established in Tables 12, 13, and 15).

Meth. 

Chl a

 DVChl a Chlide a 

Lut Neo Neo+Vio Phytin a

 Phide a Pras Viola Zea+Lut

C 9.7 0.0 97.5 42.4 29.4 22.1 87.0 82.5 34.0 18.8 23.9

D 9.8 0.0 91.2 25.6 70.2 30.2 62.1 40.3 45.5 17.0 17.9

G 13.4 0.0 57.8 37.3 30.6 18.4 25.0 38.5 12.3 20.4

H 8.5 0.0 27.3 35.0 28.6 11.3 24.7 39.3 51.6 9.6 16.1

L 9.0 0.0 40.6 43.6 37.4 18.1 38.5 34.8 77.2 15.3 24.6

L 10.6 0.0 35.6 40.9 38.7 22.8 40.6 81.5 54.1 20.3 22.3

F 34.9 38.7 209.6 71.7 48.8 66.7 51.7 48.5

J 25.6 0.0 21.1 179.4 80.5 27.2 28.7 74.3 1,330 6.8 82.1

N 10.5 0.0 107.4 93.0 78.0 45.5 74.1 82.3 553.2 42.0 109.4

S 36.7 78,461† 42.8 154.5 534.9 170.8 23.8 88.8 2,148 53.5 70.2

U 10.8 90.0 141.3 91.8 90.3 78.1 87.1 44.7

A 10.1 0.0 62.9 36.8 39.3 20.0 47.5 49.2 49.4 14.6 20.6

A+ 23.7 39,231 60.0 155.6 171.4 76.5 42.2 81.8 835.2 48.2 71.0

A- 8.5 0.0 27.3 25.6 28.6 11.3 24.7 34.8 34.0 9.6 16.1

† Derived from a simultaneous equation (Latasa et al. 1996) and provided for information purposes only.

which are presented in Table 16. Unlike the PPig results,

these data are not supplied by all the methods, so some

of the results cannot be used at the same level of efficacy.

The A uncertainties are usually significantly lower than

the corresponding A+ values, but not in all cases. For

example, note the good J results for Chlide a and Viola,

as well as the good S results for Phytin a.

Despite some good results within the A+ subset, the

general distinction between the A and A+ results is each

of the A+ methods have one or more pigments for which

the uncertainty is anomalously poor, both with respect to

the A methods and to the other A+ methods:

F Lut;

J Lut and Pras;

N Chlide a and Pras; and

S DVChl a, Neo, Neo+Vio, and Pras; and

U Lut.

Although DVChl a is listed above, it is important to note

that S provided the associated data for information purposes only, and higher uncertainties were expected based

on the results from SeaHARRE-2 (Hooker et al. 2005).

The presence of the anomalously high uncertainties in

the A+ subset further reinforces the need for a properly

established referencing system. A separate check on the

capabilities of the methods and, in particular, the veracity of establishing two subsets of analyses (A and A+), is

provided by the results from the DHI mix. With respect

to field samples, the DHI mix is distinguished by higher

concentrations (larger peaks) and less coeluting contaminants. This means the pigments are easier to quantify and

quantitate, so the results should almost be at the highest quality level a method can achieve. In practice what

this means is any method should quantitate the DHI mix

at one level of performance better than expected for field

samples.

A review of the governing equations, (1) and (6), reveals why results for the DHI Mix should be better: fewer

variables are needed to compute the concentrations of pigments in the DHI Mix relative to a field sample, because

the filtration volume (Vf ) and extraction volume (Vx) are

not applicable to the former. The variables in common are

injection volume (Vc), pigment peak area (AˆPi ), and the

calibration response factor (RPi ). For the QA subset, the

expectation is the results will satisfy the state-of-the-art

performance metric on average, and for many of the individual pigments. The A+ subset is expected to be at a

lower level of performance (on average and for many individual pigments), but should be within the 15% threshold.

Given an investigative perspective, uncertainties in Vc,

for example, are in part described by the imprecision of

replicate injections of the DHI Mix (Sect. 1.6.2 and Table 14). Uncertainty sources affecting AˆPi differ somewhat

between field sample and DHI Mix analyses. For example, effects of filter inhomogeneity and the efficiency with

which pigments are extracted from cells are unique to field

samples and contribute to interlaboratory differences. For

methods with a restricted limit of linearity (or nonlinear

methods), however, the DHI Mix at full strength can produce erroneous results and dilution with validated dilution

devices may be needed so peak areas fall within the limit

of linearity for the method.

Method uncertainties from the DHI Mix-102 analyses

are presented in Table 17. The QA subset has overall

TChl a and PPig uncertainties of 4.2% and 4.6%, respectively, which are within the performance specifications for

state-of-the-art analyses (Table 9). The QA subset is also

distinguished by a small range in the overall PPig averages

26
Hooker et al.

Table 17. The |ψ ̄| values (average APD in percent) for DHI Mix-102 as a function of the HPLC method for

the primary pigments using the presentation scheme established in Tables 12, 13, and 15. The uncertainties are

computed using the average concentrations of the pigments determined by the QA subset as the reference in

the uncertainty calculations.

Meth. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea Average

C 6.5 5.7 24.4 5.5 2.8 5.7 4.7 0.7 0.9 1.6 3.8 0.6 5.2

D 6.2 2.0 8.0 6.0 8.5 6.6 1.5 7.7 1.8 3.1 5.4 17.1 6.1

G 2.7 5.0 5.6 4.7 2.4 0.9 5.6 2.5 1.4 2.3 0.0 5.4 3.2

H 1.6 10.2 4.4 0.3 6.9 3.3 3.3 5.0 3.7 4.2 4.4 9.3 4.7

L 3.9 7.5 6.3 4.5 1.1 1.6 1.0 0.5 4.2 5.0 4.7 3.1 3.6

F 5.2 13.9 39.3 998.7 30.1 26.6 7.2 17.4 29.5 28.2 11.8 19.7 102.3

J 12.7 26.4 4.0 9.9 1.4 8.7 14.6 1.6 24.8 2.4 10.3 0.1 9.7

N 11.6 6.3 20.0 29.5 6.2 20.0 12.8 22.3 0.5 2.6 17.5 99.8 20.8

S 5.6 4.6 4.8 11.8 8.3 9.5 13.3 1.5 6.1 3.4 19.3 7.8 8.0

U 2.3 19.4 606.6 149.4 9.0 4.6 1.9 0.2 9.2 4.1 6.2 6.7 68.3

A 4.2 6.1 9.7 4.2 4.3 3.6 3.2 3.3 2.4 3.2 3.7 7.1 4.6

A+ 7.5 14.1 134.9 239.9 11.0 13.9 10.0 8.6 14.0 8.1 13.0 26.8 41.8

A- 1.6 2.0 4.4 0.3 1.1 0.9 1.0 0.5 0.9 1.6 0.0 0.6 1.2

of 2.9%. The low value of the theoretical best method,

1.2%, shows how many high-quality results were achieved

for the individual pigments.

All of the overall A average PPig uncertainties for DHI

Mix-102 are within the state-of-the-art performance metric (Table 9). In terms of the individual methods and individual pigments, virtually all of the results are within,

or close to, the state-of-the-art performance metric. The

best method entries are spread across all five methods.

The small number of notable exceptions are TChl c for C,

Zea for D, and TChl b for H.

The difference between the A uncertainties for robust

field samples (i.e., those without quantitation problems)

and their corresponding uncertainties in the DHI Mix-102

analyses can be used to estimate the contribution of sampling variance to the uncertainty budgets. For example,

the difference for TChl a is 2.2% and the difference for

Fuco is 3.4%. This range of differences establishes a variance estimate of approximately 2–3% in field sample filtering (which is similar to the filtering variance experienced

during SeaHARRE-2 and SeaHARRE-3).

The overall A+ averages for the DHI Mix-102 analyses

are 7.5% for TChl a and 41.8% for PPig; the former are

within expectations, but the latter are significantly not.

Closer inspection shows the J and S methods are performing as expected, however, and with the exception of

the Zea results, the N method is very nearly doing so. The

F and U methods each have at least one pigment for which

the results are sufficiently anomalous as to prevent higher

quality results. Again, these kinds of distinctions reinforce

why a proper referencing system is so important.

The uncertainties for the analysis of secondary and tertiary pigments within DHI Mix-102 are presented in Table 18. These data further reinforce the results already

presented with the field samples and the PPig results for

the DHI mix: a) the QA subset almost always has significantly lower overall uncertainties than the A+ subset

(Chlide a is the notable exception) and is usually at a stateof-the-art level of performance; b) the distribution of the

best method results are spread across more than one QA

method (although C predominates); and c) there are numerous examples of A+ methods achieving state-of-the-art

performance, but this is countered by other instances of

elevated uncertainties, some of which are significant (e.g.,

Lut for J and N).

1.6.3.2 Pigment Sums

Prior SeaHARRE activities established a functional relationship in pigment uncertainties: PPig overall uncertainties decreased significantly as individual pigments were

summed. This is a direct reflection of a) how summing cancels the highs and lows associated with the biases in the

individual pigments, and b) more abundant pigments are

more important to the sums and they are usually quantitated with lower uncertainties (i.e., smaller biases), because they are not detection limited. If an abundant pigment is also a problematic pigment, summing will frequently not ameliorate the uncertainties involved.

In this cascade towards lower uncertainties, a method

having problems with a class of pigments (e.g., the carotenoids), is expected to have elevated uncertainties for sums

predominated by that class of pigments (e.g., PPC). These

elevated uncertainties can easily influence other sums if the

pigments involved are particularly abundant. For example,

chlorophyll a is usually the most abundant pigment in marine ecosystems, so if there is a problem with the quantitation of this pigment, there will be elevated uncertainties

in the formulation of TChl or TPig.

27
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 18. The |ψ ̄| values (average APD in percent) across the DHI Mix-102 analyses for a subset of the

secondary and tertiary pigments (following the presentation scheme established in Tables 12, 13, and 15).

Meth. 

Chl a

 DVChl a Chlide a 

Lut Neo Neo+Vio Phytin a

 Phide a Pras Viola Zea+Lut

C 4.7 10.7 20.1 0.7 0.1 0.1 59.5 1.7 0.4 0.7

D 4.4 13.8 68.3 5.4 4.5 4.2 0.6 3.7 10.7

G 2.8 1.3 1.1 8.1 6.3 188.3 0.9 3.7 1.8

H 1.9 0.7 1.5 3.5 2.1 2.7 63.2 75.3 0.1 3.6 6.1

L 4.4 2.5 10.1 3.7 5.6 4.9 65.6 75.3 1.9 4.0 3.5

F 30.3 30.5 33.2 33.2 22.0 45.3 6.3 9.1

J 14.7 6.9 25.8 117.8 2.0 5.5 63.0 6.6 10.5 64.1

N 54.1 3.6 99.9 1.8 9.7 99.9

S 3.5 10.3† 33.7 4.6 14.3 3.0 6.1

U 42.6 1.8 39.4 0.8 4.0

A 3.6 5.8 25.0 2.9 4.1 3.6 94.1 75.3 1.0 3.1 4.6

A+ 29.0 8.6 23.4 51.5 15.3 11.3 63.0 21.5 6.0 36.6

A- 1.9 0.7 1.5 0.7 0.1 0.1 59.5 75.3 0.1 0.4 0.7

† Derived from a simultaneous equation (Latasa et al. 1996) and provided for information purposes only.

Table 19. The |ψ ̄| values (average APD in percent) across all 12 batches of field samples as a function of the

laboratory method for the pigment sums (following the presentation scheme established in Tables 12, 13, and

15). The PPig |ψ ̄| values for field samples (Table 15) are given in the first column for easy comparison. Method

averages for the pigment sums are given in the last column.

Meth. 

PPig TChl PPC PSC PSP TCaro TAcc TPig DP Avg.

C 33.5 4.8 10.1 13.6 4.3 11.7 4.7 4.2 10.3 8.0

D 29.5 4.5 4.2 9.2 3.1 6.2 6.0 3.1 8.6 5.6

G 27.5 6.8 3.3 7.0 6.7 4.8 4.0 5.9 5.5 5.5

H 34.6 6.8 7.8 9.1 6.8 9.0 7.2 6.8 7.0 7.6

L 23.9 7.7 5.7 4.9 6.3 5.7 5.5 6.2 6.4 6.0

L 27.1 8.4 6.5 4.9 6.9 5.2 5.8 6.7 6.3 6.3

F 3,194 25.3 336.5 32.0 16.6 112.1 67.2 14.6 16.1 77.5

J 63.6 18.3 15.8 16.3 18.3 17.4 11.6 18.0 11.9 15.9

N 176.9 7.0 14.7 18.6 7.2 12.8 10.0 7.3 14.7 11.5

S 530.9 33.2 30.3 12.4 29.3 18.7 21.3 28.8 15.5 23.7

U 172.6 117.7 107.6 26.8 97.9 52.9 241.0 98.8 17.7 95.0

A 29.8 6.1 6.2 8.8 5.4 7.5 5.5 5.2 7.6 6.5

A+ 827.6 40.3 101.0 21.2 33.8 42.8 70.2 33.5 15.2 44.7

A- 20.7 4.5 3.3 4.9 3.1 4.8 4.0 3.1 5.5 4.2

The uncertainties in the pigment sums for the field samples are presented in Table 19. The overall averages from

the QA subset show a decrease in average uncertainties

from PPig to pigment sums of 29.8% to 6.5%. The range of

the uncertainties within the individual sums is frequently

rather small, with the exception of some of the C results.

The uncertainties in the individual pigment sums are usually less than 8%, as are the overall averages for the individual sums or laboratories, which is the performance level

for quantitative analysis. The range of the individual averages are rather similar (they differ by a maximum of only

2.5%). The best method results are spread across three

of the QA methods with G predominating. The difference

between the overall A- and A averages is 1.3%.

The A+ subset shows a more dramatic decrease in uncertainties from the overall PPig average of 827.6% to

44.7%. The individual method decreases are also large

with F decreasing the most. Such substantial decreases

establish the utility of using sums in databases to minimize uncertainties, particularly if the source data has an

unknown quality, but some caution is needed: with the

exception of the N method, the overall averages are not

to within 12%, the threshold for semiquantitative analysis

(Table 9). In addition, many of the individual uncertainties and laboratory averages exceed 20%, the threshold for

routine analysis. For uncertainties with sums, the latter

is an indication of significant biases in the method. For

example, the problems with the individual carotenoids for

28
Hooker et al.

Table 20. The |ψ ̄| values (average APD in percent) across all 12 batches of field samples as a function of

the laboratory method for the pigment ratios and indices (following the presentation scheme established in

Tables 12, 13, and 15).

Lab.

Method



TAcc



TChl a





PSC



TCaro



PPC



TCaro



TChl



TCaro



PPC



TPig



PSP



TPig



TChl a





TPig

Avg.

Ratio



pPF nPF mPF Avg.

Index

C 4.1 2.4 4.6 15.3 9.8 0.9 1.6 5.5 14.4 10.7 5.4 10.2

D 9.3 3.3 4.9 7.2 4.5 0.4 3.6 4.7 5.9 9.6 2.2 5.9

G 6.6 3.0 5.1 6.6 8.0 0.9 2.6 4.7 5.7 8.6 1.9 5.4

H 3.6 1.3 2.6 5.5 3.1 0.3 1.4 2.5 8.4 9.6 2.9 6.9

L 4.9 1.9 2.3 7.2 4.0 0.3 1.9 3.2 12.2 8.1 4.9 8.4

L 5.7 3.1 4.2 7.7 5.4 0.5 2.3 4.1 14.7 11.6 5.0 10.4

F 125.7 40.4 105.9 63.8 283.6 24.7 31.6 96.5 22.3 91.2 16.9 43.5

J 12.6 2.8 4.5 6.9 4.8 0.5 5.3 5.3 23.8 29.9 7.4 20.4

N 9.5 7.1 12.1 13.0 13.0 1.3 3.7 8.5 12.9 13.9 6.4 11.1

S 11.4 6.2 10.9 16.1 10.9 1.4 5.0 8.8 13.6 47.4 9.4 23.5

U 220.2 17.0 36.9 49.0 11.5 1.1 46.1 54.5 12.7 31.0 9.3 17.7

A 5.7 2.4 3.9 8.4 5.9 0.6 2.2 4.1 9.3 9.3 3.5 7.4

A+ 75.9 14.7 34.1 29.7 64.8 5.8 18.3 34.8 17.1 42.7 9.9 23.2

A- 3.6 1.3 2.3 5.5 3.1 0.3 1.4 2.5 5.7 8.1 1.9 5.3

the F method produce anomalously large uncertainties for

PPC and TCaro, and the large uncertainties in TChl c results in a large TChl uncertainty.

1.6.3.3 Pigment Ratios and Indices

The aforementioned functional relationship in uncertainties established by prior SeaHARRE activities extended beyond pigment sums and into higher-order data products: PPig overall uncertainties decreased as individual

pigments were summed, decreased further when pigment

ratios were formed, and then increased slightly with the

formation of pigment indices. The latter are a combination of sums and ratios (Table 6), so the small increase is

expected to be on the order of the uncertainty in pigment

sums (or less).

The uncertainties in pigment ratios and indices for the

SeaHARRE-4 field samples are presented in Table 20. The

QA subset has overall average uncertainties of 4.1% and

7.4% for the ratios and indices, respectively. Both results are to within their respective anticipated performance

thresholds for quantitative analysis, which are to within

6% and 8%, respectively (Table 9). The individual A

method uncertainties for the ratios are almost always within performance limits and span a narrow range. The notable exception are the C results for TChl/TCaro and

PPC/TPig, which exceed the 6% threshold. The individual method uncertainties for the indices are quite similar

and are within, or close to, expectations, except for the

pPF results for C and L.

The uncertainties in the A+ pigment ratios and indices

provide additional clarity about the unique problems with

the methods. As a group, the overall average A+ uncertainties for ratios and indices are much higher than the

corresponding QA subset values, particularly for the ratios, and the values are above the performance thresholds

even for routine analysis. Although the overall average decreases in the progression from PPig, to sums, to ratios, it

does not increase with the ratios. This deviation from the

expected functional form of the uncertainties has been an

indicator of methodological (Hooker et al. 2009) or sampling problems (Hooker et al. 2005) in the past.

The individual J, N, and S overall averages do not

exhibit a deviation from the expected functional form of

the uncertainties—they behave as expected. The average

uncertainties for the ratios puts J at a quantitative level

of performance, while N and S are at the semiquantitative

level; for the indices, J and S are close to the routine performance level, while N is at the semiquantitative level.

The F method never satisfies a performance threshold—

even for the PSP/TPig ratio, which is one of the least

sensitive ratios. The U does satisfy some performance levels for some ratios and indices, and has an overall average

uncertainty for the indices that is at the routine level of

performance.

The more abundant a pigment is naturally, the more

important it is to the net uncertainty of a ratio or index,

but not in all cases. As noted in prior SeaHARRE activities, problematic pigments can elevate uncertainties in

ratios. This is particularly notable if the problematic pigment or pigments appear exclusively in the numerator or

the denominator. If the sources of uncertainty appear in

both the numerator and denominator, uncertainties can

increase, decrease, or be nullified depending on the biases

29
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Fig. 2. Overall performance results for the A+ and A (QA) subsets (light and dark bars, respectively) for all

four SeaHARRE (SH) activities: a) method precision, with the approximate 2% variance associated with the

preparation of the field samples shown as a dotted line, and b) accuracy, with the 15% quantitative and 25%

semiquantitative performance metrics for PPig shown as dotted and dashed lines, respectively.

the uncertainties represent (i.e., overestimation versus underestimation) and the magnitudes involved.

1.7 SUMMARY AND DISCUSSION

The diversity of objectives for the SeaHARRE-4 activity, along with the large number of separate analyses

involved, make it appealing to summarize and discuss the

most important aspects of the results in one place. The discussion presented here is not intended to be a substitute

for reading the greater detail presented in the preceding

sections, and follows the original presentation of the objectives (Sect. 1.1) and much of the organizational scheme

used to present the results (Sect. 1.6).

1.7.1 Precision

A recurring aspect of the results presented here has

been to discuss the importance of a proper referencing

system for establishing method uncertainties. This has

been emphasized, because in round robins involving natural samples, there is no a priori understanding of truth. A

foundation of the SeaHARRE activity is that truth can be

estimated by assuming a properly validated HPLC method

is capable of providing a good estimate of truth, and the

deviations from truth are mostly due to small sources of

random errors, so the pooled estimate of truth from several methods should tend towards a realistic proxy value of

truth. The potential pitfall in this logic is if a method that

has not been properly validated is included in the methods used to estimate the referencing system. There is no

evidence in the results presented that the QA subset was

corrupted by an improperly validated method.

Consequently, an important attribute of the subset of

methods used as the referencing system for computing uncertainties is that they have rather uniform results across

the broadest suite of data products possible. The standard deviation in the uncertainties within the QA subset

averaged 1.4% for TChl a, 10.5% for PPig, 1.1% for pigment sums, 1.2% for pigment ratios, and 1.9% for pigment

indices. The corresponding values for the A+ subset were

11.0%, 1,551.1%, 38.7%, 40.1%, and 12.2%, respectively.

The latter represents approximately a 6- to 150-fold increase in variance with respect to the former, and is one

of the distinctive mechanisms for showing the difference

between the two subsets. This is not to say all methods

within the A+ subset are associated with the same levels of

variance. As has already been shown, there are numerous

examples of excellent results from a subset of A+ methods

and for a subset or variety of pigment data products.

The precision of the individual methods is another important indicator of the distinct differences between the

A and A+ subsets. Figure 2a shows the average precision

of the two subsets as a function of the primary pigments

grouped as three chlorophylls, the nine carotenoids, and

the overall average. To establish a wider context, summary

data are shown for all four SeaHARRE activities executed

to-date. The precision of the A subset for SeaHARRE-4

30
Hooker et al.

is largely indistinguishable from the first three activities.

The SeaHARRE-4 A+ results are characterized by being

more imprecise on average and for all cases shown except

TChl b.

There are examples for which the two subsets in Fig. 2a

have similar precision, for example, the TChl a results are

not widely different. The majority of the data, however,

shows the QA subset has distinctly better precision, and

the overall A average is about 4.7% better on average

than the A+ average. The latter represents almost the

entire performance budget for the PPig precision metric

for quantitative analysis (5%). Given that precision is the

first step in the uncertainty budget, it also represents onethird of the PPig accuracy metric for quantitative analysis,

so it is a significant difference.

1.7.2 Accuracy

The most significant difference between the A and A+

subsets is in the accuracy (uncertainty) of the derived

data products, which is shown in Fig. 2b for all four SeaHARRE activities. A substantial decrease in uncertainties

from the A+ to A subset is seen in all data products, but

very notably for the individual pigments (the largest decrease is for the SeaHARRE-4 PPig results). In fact, the

QA methods are within the approximately 2% sampling

variance for the 10% and 15% quantitative analysis requirements for TChl a and PPig, except for SeaHARRE-4,

which are a bit above this threshold. The A+ subset frequently does not satisfy the TChl a and PPig semiquantitative thresholds (15% and 25%, respectively), particularly

for the SeaHARRE-3 and SeaHARRE-4 results.

With the exception of the PPig results obtained during

SeaHARRE-4, the A accuracies for all pigment categories

within each SeaHARRE activity are rather similar. The

closest agreement is seen for TChl a, which is important,

because it is currently the most significant pigment for

ocean color remote sensing. The A+ results are typified by

much greater variability with each pigment category—even

for TChl a.

The most troubling aspect of the SeaHARRE-4 A+ results is the absence of the established functional form of the

uncertainties—that is, the decrease in uncertainties from

PPig to sums to ratios, followed by a small increase with

the indices—is seen in all past SeaHARRE activities, but

not in SeaHARRE-4. Prior SeaHARRE investigations suggested this represents a corruption of the natural relationships between the pigments (Hooker et al. 2005 and 2009).

A likely explanation for the corruption is the presence of

significant biases in one or more of the pigment data products, which can occur if a method is put into service without proper validation or if a quality assurance plan is not

implemented and rigorously applied over time.

As already noted, the four SeaHARRE activities executed to-date span a wide dynamic range in trophic systems, e.g., the TChl a concentration range is approximately

0.020–42.704 mg m−3, which represents a little more than

four decades in concentration. The sampling for the first

three activities involved oceanic regimes emphasizing the

mesotrophic Mediterranean Sea, the eutrophic Benguela

Current, and the oligotrophic South Pacific gyre, respectively. The SeaHARRE-4 activity emphasized eutrophic

Danish coastal waters (fjords and estuaries). Note the international extent of the sampling was conducted.

It is also important to remember that the composition of each SeaHARRE activity changes over time as the

overall objectives evolve. The largest number of new analysts participating in a round robin occurred during the

SeaHARRE-2 and SeaHARRE-4 exercises, and the greatest diversity in the individual methods occurred during

SeaHARRE-2 (Table 2). Some qualifications regarding the

results need to be remembered, because the largest variances in the A+ results frequently come from a minority of

methods. For some activities, this was caused by known

hardware problems, but in other cases it was simply caused

by methods whose performance was compromised by unknown or improperly investigated problems that led to degraded data products.

Additional details regarding the uncertainty in individual primary pigments for the A and A+ subsets across all

four SeaHARRE activities are presented in Table 21, and

within the perspective of a generalized overview, some notable results are as follows:

• The lowest uncertainty for both the A and A+ subsets is for TChl a, which is largely invariant to water

type for the A data.

• The only carotenoid with an uncertainty to within

state-of-the-art PPig performance (to within 10%),

is Fuco for the A subset, and it is also largely invariant to water type.

• The highest uncertainty for both the A and A+

subsets is for But, which has a lot of variability

within each subset.

• In between the highest and lowest uncertainty for

both the A and A+ subsets, Diato, Peri, Hex, and

TChl c emerge as problematic pigments.

• The ranking within the chlorophyll uncertainties is

the same for the A and A+ subsets; the lowest

uncertainty is for TChl a, followed by TChl b, and

TChl c.

• The lowest average uncertainties for the A and A+

subsets are associated with oligotrophic and mesotrophic waters, respectively. The latter corresponds

to SeaHARRE-1, which had the fewest number of

participants and the closest agreement between the

A and A+ classifications.

• The highest average uncertainties for both the A

and A+ subsets are associated with coastal waters.

31
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 21. The |ψ ̄| values (average APD in percent) for field samples across all four SeaHARRE activities

for the primary pigments following the presentation scheme established in Tables 12, 13, and 15. The lowest

individual pigment uncertainties across the four SeaHARRE activities and within the A subset are shown in

bold typeface and summarized in the A- entries.

Meth. 

TChl a

 TChl b TChl c 

Caro But Hex Allo Diad Diato Fuco Peri Zea Avg.

A SH-1 7.0 14.0 26.5 17.6 23.6 24.8 38.9 16.0 55.8 8.8 13.0 11.4 21.5

A SH-2 5.9 16.5 21.8 16.8 30.6 9.5 20.3 8.7 20.6 4.7 15.4 21.4 16.0

A SH-3 6.3 13.9 14.9 13.2 14.6 6.0 4.2 5.0 17.8 10.6 30.5 9.6 12.2

A SH-4 6.4 12.4 20.4 9.6 87.2 57.5 13.0 9.3 49.8 6.6 66.6 19.0 29.8

A+ SH-1 7.9 18.0 32.7 20.2 29.5 24.8 38.9 24.9 59.0 11.5 32.3 21.5 26.8

A+ SH-2 17.2 20.8 25.6 23.5 63.7 40.4 95.4 30.5 49.3 39.1 56.9 44.3 42.2

A+ SH-3 33.1 36.8 22.4 24.3 112.6 31.1 111.5 22.0 64.3 58.7 112.1 13.7 53.6

A+ SH-4 19.8 19.0 288.2 345.9 8,078 843.6 24.8 20.7 62.0 20.1 119.8 89.2 827.6

A Avg. 6.4 14.2 20.9 14.3 39.0 24.5 19.1 9.7 36.0 7.7 31.4 15.3 19.9

A+ Avg. 19.5 23.7 92.2 103.5 2,071 235.0 67.6 24.5 58.7 32.4 80.3 42.2 237.5

A- 5.9 12.4 14.9 9.6 14.6 6.0 4.2 5.0 17.8 4.7 13.0 9.6 9.8

• The lowest individual pigment uncertainties within

the A subset are spread across all four SeaHARRE

activities, but SeaHARRE-3 predominates with the

greatest number of best results.

• The lowest individual pigment uncertainties within

the A subset and across the four SeaHARRE activities establish a best method average of 9.8%, which

is within the state-of-the-art performance metric for

PPig accuracy (Table 9).

• The problematic pigments within the A- results are

almost exactly the same as noted above using the A

and A+ joint results; the difference is the exclusion

of Hex and the inclusion of TChl b.

• The difference between the A- overall average uncertainty (9.8%) and the best A overall result for

an individual SeaHARRE activity (12.2%) is within

the 2–3% sampling variability that has been estimated for each round robin.

The importance of some of these findings are discussed in

the following sections.

1.7.3 DHI Mix-102

The concept of using the natural relationships between

pigments to discern problems with a method is difficult

to apply to the DHI Mix-102 results, which are derived

from an artificial mixing of pigments from cultured stocks.

Nonetheless, the reduction in uncertainties as pigments are

summed and then ratioed should occur, and the uncertainties should be considerably lower than in natural samples

because of the (mostly) artificially high abundance of the

pigments in the mix, plus Vx and Vf do not interfere, i.e.,

the 15% threshold should always be satisfied and a QA

method should have higher-order uncertainties on the order of 5% or less.

A summary of the average uncertainties for the A and

A+ results for DHI Mix-102 is presented in Table 22. The

results for the QA subset satisfy the expected performance

thresholds and exhibit a decreasing relationship similar to

the functional form presented in Fig. 2b, and includes a

small increase in uncertainties associated with the indices.

The lowest values are close to the precision of the individual methods, which have an average value of approximately

0.9% for the DHI mix, so the ability to distinguish them

further is not really possible.

Table 22. The average uncertainties in percent for

DHI Mix-102 as a function of the A and A+ subsets.

Subset PPig Sums Ratios Indices

A 4.6 2.8 2.5 3.1

A+ 41.8 25.0 23.9 8.3

The A+ subset has an average precision for the DHI Mix

of about 3.2%, so there are no resolution issues for the entries in Table 22. With the exception of the results for the

indices, the A+ subset results a) exceed the 15% threshold;

and b) do not follow the expected functional form, both

in terms of the relationships and the magnitudes. Uncertainties do decrease in the progression from the primary

pigments to the pigment ratios, but do not increase for the

pigment indices. The magnitude and aberrant functional

form of the uncertainties are further evidence of one or

more corrupted methods within the A+ subset.

1.7.4 Ocean Color Requirements

The invariance of TChl a



uncertainties to water type

for the A subset and the fact that it has the lowest overall

uncertainty for both the A and A+ subsets are important

results for the remote sensing problem set. Equally important is the average uncertainty for the A and A+ subsets are less than 15 and 25%, respectively. This implies

32
Hooker et al.

much of the worldwide contributions of TChl a

 values

are, on average, compliant with the SeaWiFS calibration

and validation specification, and contributions from QA

laboratories can probably be used in algorithm refinement

exercises.

The difficulty with the above compliance statement is

the range of variance that has been established for methods that are not part of the QA subset can be significant,

and most algorithm validation work—particularly in the

early stages of validating a new algorithm—proceed more

effectively with higher-quality data. The same is true for

the very important work of first establishing a new algorithm. Being able to partition databases between A and

A+ contributions would make establishing and refining an

algorithm easier to do.

1.7.5 Performance Metrics

The participation of laboratory G was an experiment to

demonstrate what a laboratory that had never done HPLC

analysis was capable of achieving if the Van Heukelem and

Thomas (2001) protocols and the performance metrics for

quantitative analysis were strictly followed. The analyst in

this case was an established biogeochemist who had never

done an HPLC analysis, but who was familiar with the concept of following best practices in the laboratory. The fact

that the G results were in the A subset and were repeatedly some of the best results within that subset demonstrates how adherence to protocols and performance metrics can result in significantly lower uncertainties in the

production of data products from field samples, even for

novice practitioners. It also shows the performance metrics

are achievable and realistically set.

1.7.6 Conclusions and Recommendations

The SeaHARRE-4 activity was designed to investigate

the following objectives: a) estimate the uncertainties in

quantitating individual pigments and higher-order variables formed from sums and ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation

activities (approximately 25%, although 15% would allow

for algorithm refinement) can be met in coastal waters; c)

establish the reduction in uncertainties as a result of applying QA procedures; d) show the importance of establishing

a properly defined referencing system in the computation

of uncertainties; e) quantify the analytical benefits of performance metrics; and f) demonstrate the utility of a laboratory mix in understanding method performance. All of

these objectives were satisfied and the most salient aspects

involved are as follows:

• Estimates of the uncertainties in quantitating individual pigments and higher-order variables formed from

sums and ratios show the latter provide a significant

opportunity to reduce uncertainties in larger databases

(Fig. 2). In addition, the results showed that the use of

histopreps for sample storage does not produce a significant degradation in the uncertainties (or precision)

with respect to foil packet storage. In fact, some of the

most superior results were obtained for the histoprep

samples.

• The chlorophyll a accuracy requirements for ocean color

validation activities are significantly satisfied in coastal

waters, but some additional investigation is needed to

reduce uncertainties when detection by absorption spectra is sufficiently degraded that analysts cannot reasonably be expected to make similar choices as to the

presence or absence of a pigment (the so-called twosentence rule† is a starting point for this work).

• The reduction in uncertainties as a result of applying QA procedures is demonstrated by the significantly

lower uncertainties associated with the QA subset

across all four SeaHARRE activities executed to-date

(Table 21).

• The importance of establishing a properly defined referencing system in the computation of uncertainties is

revealed by the large difference between the A and A+

subsets, because if the partition had not been properly

defined, the larger variance of the A+ subset (most notably F and S) would have been spread across all the

methods.

• The analytical benefits of the performance metrics are

shown by the excellent results achieved with method

G (Tables 15–20), which involved a first-time HPLC

analyst that was guided primarily by strict adherence

to the performance metrics.

• The utility of the laboratory mix was demonstrated by

how the differences between the A and A+ subsets are

still seen in the average uncertainties for DHI Mix-102

(Table 22) even though the mix is significantly easier to

analyze than a field sample (no extraction procedures).

The SeaHARRE-4 results were more difficult to integrate, because they contained more unknown pigments

than prior SeaHARRE activities. This was probably due

to the stations being in eutrophic and estuarine environments. Frequently, the content in the samples were most

likely a mixture of freshwater and marine algae, which

means they were more complicated to analyze than samples from high salinity areas. By itself this is a challenging

analysis scenario, but for an analyst who is not used to

these samples, it is doubly challenging, because interpretation is usually more reliable if experience is also a factor.

Consequently, a likely reason for the QA subset increase

in uncertainties for SeaHARRE-4 was having so many analysts confronting such a complex sample set for the first

time.

† The two-sentence rule is as follows (Hooker et al. 2009): If a

peak is good and it can be proved to not be the pigment for

that retention time, do not report it; otherwise report it. If

a peak is bad and it cannot be disproved to be the correct

pigment, report it; otherwise do not report it.

33
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 2

The CSIRO Method

Lesley Clementson

CSIRO Marine Research

Hobart, Australia

Abstract

The CSIRO method is a modified version of the Van Heukelem and Thomas (2001) method (VHT) and has

the capacity to resolve approximately 35 different pigments with baseline resolutions of divinyl and monovinyl

chlorophyll a, and zeaxanthin and lutein. Partial separation of divinyl and monovinyl chlorophyll b, and chlorophyll c2 and chlorophyll c1 can also be achieved. The method used for the samples and standards analyzed

for SeaHARRE-4 was the same method used for SeaHARRE-3. Samples were extracted over 15–18 hours in

an acetone solution before analysis by HPLC using a C8 column and binary gradient system with an elevated

column temperature. Pigments were identified by retention time and absorption spectrum from a photodiode

array (PDA) detector. The method is regularly validated with the use of internal and external standards

and individual pigment calibration. The detection limit of most pigments was within the range of 0.001–

0.005 mg m−3. This method is applicable to the study of pigment composition and concentration in samples

from all water types including freshwater, estuarine, upwelling coastal regions, and oligotrophic open ocean, as

well as in the microphytobenthos of shallow coastal regions.

2.1 INTRODUCTION

For SeaHARRE-4, CSIRO was asked to analyze the

samples to determine the total particulate absorption coefficient, the pigment composition and concentration by

HPLC, and the spectrophotometric total chlorophyll a concentration. On 6 December 2006, 12 triplicate samples

were received, flat in histopreps (Fisher), together with 10

vials of DHI mixed standards on dry ice. The samples were

immediately transferred to liquid nitrogen for storage until

the start of HPLC analysis. The standards were stored in

a −20◦C freezer.

Because only one sample was received for three different analyses, the samples were analyzed in sets of 12 (four

groups of triplicate samples). All of the HPLC analyses

were completed from 26–30 March 2007, inclusive. The

samples were removed from liquid nitrogen and stored on

ice in the dark to thaw. Once thawed, an ultraviolet–

visible (UV/Vis) spectrophotometer, equipped with an integrating sphere, was used to scan the samples from 200–

900 nm. These measurements were used to determine the

optical density of the total particulate matter on each filter. The filters were then extracted for pigment analysis.

The final extracts were measured at four wavelengths in

a UV/Vis spectrophotometer to determine the total chlorophyll a concentration before analysis by HPLC to determine pigment concentration for a wide variety of pigments.

2.2 METHODS

Three different methods were used by CSIRO to complete the SeaHARRE-4 work plan: a) spectral absorption,

b) spectrophotometric chlorophyll a, and c) HPLC pigment

analysis. Brief summaries of the first two are presented in

the following two sections. The remainder of the material

that is presented deals with the HPLC pigment analysis

method.

2.2.1 Spectral Absorption

Optical density spectra for total particulate matter were

obtained using a GBC 916 UV/Vis dual beam spectrophotometer equipped with an integrating sphere. Quartz

glass plates were used to hold the sample and blank filters

against the integrating sphere. The optical density of the

total particulate matter of each sample was obtained using

a blank filter as a reference (from the same batch number as

the sample filters) wetted with filtered seawater (0.2 μm)

and scanned from 200–900 nm with a spectral resolution

of 1.3 nm. The optical density scans were converted to absorption spectra by first normalizing the scans to zero at

750 nm and then correcting for the path length amplification using the coefficients of Mitchell (1990). Particulate

spectra were smoothed using a running box-car filter with

a width of 10 nm.

34
Hooker et al.

2.2.2 Spectrophotometric Chlorophylla

The absorbance of the pigment extract (see details in

the next section) was measured using a GBC 916 UV/Vis

spectrophotometer with 40 mm path length optical glass

microcells. Absorbance was read at wavelengths 750, 664,

647, and 630 nm. The absorbance at 750 nm was subtracted from the absorbance at each of the other three

wavelengths and substituted into the equations of Jeffrey

and Humphrey (1975).



Chl a



e = 11.85A664 − 1.54A647 − 0.08A630

lc

, (27)



Chl b



e = 21.03A647 − 5.43A664 − 2.66A630

lc

, (28)

and



Chl c



e = 24.52A630 − 1.67A664 − 7.60A647

lc

, (29)

where e indicates the extract, A is the corrected absorbance, and lc is the path length of the cuvette in centimeters.

The concentration of each chlorophyll pigment in the

sample in micrograms per liter was obtained by the following equation:



Chl x



s = Ve

Vf



Chl x



e, (30)

where s indicates the sample, Ve is the volume of extract

in milliliters, and Vf is the volume of seawater filtered in

liters.

2.2.3 HPLC Pigment Analysis

The CSIRO method separated pigments on a C8 column using a two-solvent gradient system. Pigments were

verified by the retention time and absorption spectra (using a PDA detector) of each chromatographic peak and

quantified by the detector signal at 436 nm. Analysis time

was 31 min per sample with a further 5 min injection delay

to ensure no carryover between samples. Separation was

achieved for most pigments, the exceptions being ββ- and

βε-carotene that coelute. In samples where one of the two

carotenes is dominant, however, the two pigments can be

separated by their absorption spectra.

Additional separation problems routinely occurred between chlorophyll c2, MgDVP, chlorophyll c1, and chlorophyllide a, for which baseline resolution cannot always be

achieved. It is not common for all four pigments to be

present in any one particular chromatogram, however,

thereby allowing for good resolution between chlorophyll c2

and chlorophyll c1, and partial resolution between chlorophyll c1 and chlorophyllide a when both were present.

While baseline resolution of divinyl and monovinyl chlorophyll a was achieved, only partial separation of divinyl

and monovinyl chlorophyll b can be achieved.

2.3 EXTRACTION

To extract the pigments, the thawed filters were cut

into three or four pieces and covered with 100% acetone

(3 mL) in a 10 mL centrifuge tube. Scissor and forcep

blades were cleaned between samples. The tube was covered with parafilm and vortexed for about 30 s, followed

by sonication for 15 min in an ice-water bath in the dark.

The samples were then kept in the dark at 4◦C for approximately 15 h. After this time, 200 μL water was added to

the acetone such that the extract mixture was 90:10 acetone:water (vol:vol), including the water held in the filter

from the sample filtering process, and sonicated once more

for 15 min in an ice-water bath in the dark.

The extract was transferred to a Biorad column, (a

small column containing a scintered glass disc) sitting in a

clean centrifuge tube. The original centrifuge tube was

rinsed twice with 0.5 mL 90:10 acetone:water, with the

rinses added to the column. The column and centrifuge

tube were centrifuged for 5 min at 2,500 rpm and −2◦C to

separate the filter paper from the extract. At this stage,

the final extract volumes were recorded from the centrifuge

tube graduations.

The centrifuged extracts were passed through a 0.2 μm

Teflon syringe filter (Advantec), which had been rinsed

with acetone and air, directly into a 2 mL amber HPLC

vial. The remaining extract from each sample remained in

a centrifuge tube, covered with parafilm, and was stored

at −20◦C until the HPLC analysis had been successfully

completed.

2.4 HPLC ANALYSIS

The CSIRO hardware was based on a Waters–Alliance

HPLC system, comprising a 2695XE separations module

with a column heater and a refrigerated autosampler, plus

a model 2996 PDA. The column temperature was 55◦C

and the refrigerated autosampler was set to 4◦C.

Immediately prior to injection, the sample extract was

mixed with a buffer solution (90:10 28 mM aqueous tetrabutyl ammonium acetate, TbAA, pH 6.5:methanol) within

the sample loop. The injector was programmed by the software to draw up alternating microliter volumes of buffer

and sample in the following order: 150, 75, 75, 75, and 150

starting with the buffer.

After injection, pigments were separated using a Zorbax Eclipse XDB C8 stainless steel 150×4.6 mm internal

diameter (ID) column with 3.5 μm particle size (Agilent

Technologies) and a gradient elution procedure as shown

in Table 23. The gradient was held in an isocratic mode

from 11–15 min to improve the resolution between violaxanthin and 19

-hexanoyloxyfucoxanthin. The flow rate was

1.1 mL min−1. The separated pigments were detected at

436 nm and identified against standard spectra using Waters Empower software. Concentrations of chlorophyll a,

chlorophyll b, and ββ-carotene in sample chromatograms

35
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

were determined from Sigma-Aldrich (St. Louis, Missouri)

standards, while all other pigment concentrations were determined from DHI standards (Hørsholm, Denmark). The

analysis time of each sample was 31 min with an additional

5 min injection delay of the next sample to ensure there is

no carryover between samples.

Table 23. The gradient elution program for the

CSIRO laboratory method as executed during the

SeaHARRE-4 activity. Solvent A is 70:30 28 mM

TbAA (pH 6.5):methanol, and solvent B is 100%

methanol.

Time [min] A [%] B [%]

0 95 5

11 45 55

15 45 55

22 5 95

29 5 95

31 95 5

Peak integration and identification was initially performed by the automated features of Waters Empower software, which produces an electronic report. Each sample

was manually inspected for correct integration markers and

identification of pigments. For a few samples, where the

pigment concentration was very low, baselines were corrected manually to optimize integration.

2.5 CALIBRATION

As noted earlier, calibration standards of chlorophyll a,

chlorophyll b, and ββ-carotene were obtained from SigmaAldrich, while all other pigment standards were obtained

from DHI. Standards were not available for all pigments

reported. CSIRO did not have standards for MgDVP and

chlorophyll c1.

The concentration of all standard stock solutions was

determined using a GBC 916 UV/Vis dual-beam spectrophotometer with a 2 nm bandwidth. An absorption

spectrum of each pigment was recorded from 350–900 nm.

From these stock solutions, a series of 4–6 standard solutions were prepared and analyzed both spectrophotometrically and by HPLC. Calibration curves were obtained with

coefficient of determination, r2, values never less than 0.99

and response factors (RF) for each pigment were determined from these calibration curves.

The concentration of each pigment was calculated using the absorption coefficient from the established literature (Jeffrey et al. 1997b) together with the absorption

measured at the corresponding wavelength. Absorption coefficients, wavelengths, and solvents used for each pigment

are listed in Table 24. The absorbance at the wavelength

used, nominally the wavelength of maximum absorbance,

is corrected for any absorption measured at 750 nm.

Table 24. Absorption coefficient (α) values in liters

per gram per centimeter used with the CSIRO

method for the pigments listed as a function of wavelength (λ). The rightmost column provides the literature reference.

Pigment Solvent λ α Ref.

Peri 100% Ethanol 472.0 4.00 †

But 100% Ethanol 446.0 160.00 §

Fuco 100% Ethanol 449.0 160.00 §

Hex 100% Ethanol 447.0 160.00 §

Neo 100% Ethanol 439.0 224.30 §

Pras 100% Ethanol 454.0 160.00 §

Viola 100% Ethanol 443.0 255.00 §

Diad 100% Ethanol 446.0 262.00 §

Allo 100% Ethanol 453.0 262.00 §

Diato 100% Ethanol 449.0 262.00 §

Lut 100% Ethanol 445.0 255.00 §

Zea 100% Ethanol 450.0 254.00 §

Cantha 100% Ethanol 476.0 207.50 §

Gyro. diester 100% Ethanol 445.0 262.00 §

Asta 100% Acetone 482.0 210.00 †

βε-Car 100% Acetone 448.0 270.00 §

ββ-Car 100% Acetone 454.0 250.00 †

Chlide a 90% Acetone 664.0 127.00 §

Chl b 90% Acetone 647.0 51.36 †

DVChl a 90% Acetone 664.3 87.67 §

MVChl a 90% Acetone 664.0 87.67 †

Chl c3 90% Acetone 453.0 346.00 §

Chl c2 90% Acetone 443.8 374.00 §

Phytin b 90% Acetone 657.0 31.80 †

Phytin a 90% Acetone 667.0 51.20 †

Phide a 90% Acetone 667.0 74.20 §

† Jeffrey et al. (1997b) § DHI (Hørsholm, Denmark)

2.6 VALIDATION

At the start of every set of samples analyzed by HPLC,

a pigment mixture was qualitatively analyzed to determine

if there was any movement in the retention time of approximately 30 pigments. A mixture of known concentrations of

astaxanthin, chlorophyll a, chlorophyll b, and ββ-carotene

was also analyzed to determine that the HPLC system, including the column, was working appropriately. Between 7

March and 1 May 2007, this pigment mixture was analyzed

20 times yielding a precision (percent CV) of 1.47, 1.84,

1.18, and 1.74 for astaxanthin, chlorophyll a, chlorophyll b,

and ββ-carotene respectively. Multipoint calibrations of

chlorophyll a, chlorophyll b, and ββ-carotene are done approximately every three months, while calibrations of a

selection of other pigments are done approximately once

every 12–18 months.

In the case of the SeaHARRE-4 experiment, a mixed

pigment standard, supplied by DHI (Denmark) was analyzed three times within a set of 12 samples analyzed, resulting in a total of nine injections. The precision (percent

36
Hooker et al.

CV) of the nine injections was <1.0 for all major pigments

and many of the minor pigments.

2.7 CARRYOVER

After having analyzed several thousand field samples,

carryover between the samples had not been seen. However, the concentration of the pigments in the DHI-supplied

mixed standard were so much higher than the field samples that very small peaks of DVChl a, MVChl a, and ββcarotene were seen in the chromatogram of the injection

immediately following the standard. To avoid contamination of the first of the triplicate field samples, the DHImixed standard injection was always followed by an acetone blank. Percent carryover from the standard to the

blank was <0.25% for both DVChl a and MVChl a, and

<0.5% for ββ-carotene of the concentration of the individual pigments in the DHI standard mix. If the blank

had not followed the standard, the carryover would have

equated to an approximate increase in concentration of 1%

for the first of the B and C samples, to 3% for the first of

the F samples (Table 3). Because DVChl a was not present

in any of the SeaHARRE-4 samples, the carryover of this

pigment into the next sample to be analyzed would have

resulted in large errors for DVChl a.

2.8 DATA PRODUCTS

Waters Empower software created an electronic file in

which each chromatographic peak had its retention time,

peak area, and peak height recorded together with initial

pigment identification. Once the chromatograms had been

manually checked, the peak areas were transferred to an

Excel spreadsheet in which the pigment concentrations are

calculated using the appropriate RF:

C

Pi = AˆPiRPi , (31)

where C

Pi is the amount of pigment injected (units are

nanograms per injection); AˆPi is the area of the chromatographic peak corresponding to the pigment Pi; and RPi is

the response factor for the pigment Pi. The concentration

of the pigment Pi in the sample was then determined using

the following equation:

CPi = Vx

Vf

Df

Vc

C

Pi , (32)

where Vx is the final extraction volume (in microliters), Vf

is the volume of sample filtered (in milliliters), Vc is the

volume of sample extract injected onto the HPLC column

(in microliters), and Df is the dilution factor. The dilution

factor was rarely used and was only applied if the color

of the extract was dark green and it was likely that the

sample chlorophyll a concentration would be outside the

linear range that was used for the calibration of chlorophyll a.

For pigments MgDVP and chlorophyll c1, the RF value

determined from the calibration curve for chlorophyll c2

was used for quantitation.

2.9 CONCLUSIONS

Since mid-2004, CSIRO changed its HPLC method for

routine analysis of pigments from the Wright et al. (1991)

method to a slightly modified version of the Van Heukelem

and Thomas (2001) method. The main reason for changing the method was to have one method that could analyze complete samples from different regions—tropical and

temperate oceanic, coastal, estuarine, and freshwater. The

CSIRO method is now able to resolve the DV and MV

forms of chlorophyll a, and lutein from zeaxanthin. Resolution between chlorophyll c2 and chlorophyll c1 still remains

problematic. Accurate identification and quantification of

all pigments is important in determining phytoplankton

community composition from pigment composition. The

method has been proven to provide a good balance between accuracy of pigment composition and concentration,

and sample throughput.

37
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 3

The DHI Method

Louise Schluter  ̈

DHI Water and Environment

Hørsholm, Denmark

Abstract

The DHI HPLC method is a modified version of the HPL method. The method provides good separation of

more than 30 of the most important pigments in freshwater, estuarine, and oceanic environments. Validation

steps include four injections of a chlorophyll a standard to verify the calibration of the HPLC, use of an internal

standard for correcting evaporation errors, and injection of a mixture of pigments to verify correct elution and

retention times, and for documenting the precision of the HPLC and response factor stability. During analysis

of the SeaHARRE-4 samples, the method provided satisfactory results on the precision of both mixed pigments

and natural samples, and on the accuracy of TChl a measurements. The accuracy of PPig, however, was much

higher when comparing the results to SeaHARRE-3, where DHI first used the HPL method. This increase in

uncertainty is ascribed to the complexity of samples derived from transitional areas such as the Danish estuaries,

where the SeaHARRE-4 samples were taken.

3.1 INTRODUCTION

For analyzing the SeaHARRE-4 samples, DHI used a

modified version of the Van Heukelem and Thomas (2001)

method (VHT). (In SeaHARRE-2, the Wright et al. (1991)

method was used, but in SeaHARRE-3, DHI participated

with the newly adapted VHT method.) The advantages

of the VHT compared to the Wright et al. (1991) method

are primarily a much better chlorophyll c separation, and

that DVChl a is separated from MVChl a. Unfortunately,

when adapted to the DHI HPLC, the VHT method was,

however, not providing the expected excellent results for

SeaHARRE-3 samples when considering the precision of

the results. Subsequently, troubleshooting using DHImixed pigments located a fault in the autoinjector. Furthermore, it was found that the HPLC vials used were not

tight, which caused solvent evaporation. This emphasizes

the usefulness of pigment mixtures and the necessity of QA

for detecting method problems that have impact on the results. DHI mixed pigments have become a part of the DHI

QA program, because they are well suited for documenting the precision of the HPLC. Furthermore, the mixed

pigments are used to check that all pigments are eluted,

detected, and separated, and that the retention time and

response factors are stable. DHI holds a Danish Accreditation and Metrology Fund (DANAK) accreditation for

carrying out accredited measurements of pigment concentration in aquatic environments. DHI performs pigment

analyses by HPLC in accordance with ISO 17025†, accredited by DANAK, which is handling the administration of

accreditation and metrology in Denmark.

3.2 EXTRACTION

The SeaHARRE-4 filters were stored at 80◦C until

analysis. The filters were extracted in 3 mL 95% acetone containing approximately 0.025 μg mL−1 vitamin E

acetate (Van Heukelem and Thomas 2005) as the internal

standard. The samples were sonicated in a sonication bath,

precooled with ice to approximately 4◦C, for 10 min, placed

at 4◦C for 24 h, and mixed on a vortex mixer. The filters

and cell debris were filtered from the extracts using disposable syringes and 0.2 μm Teflon syringe filters directly

into HPLC vials, and the vials were placed in the cooling rack of the HPLC together with a parallel set of vials

with the injection buffer (90:10, 28 mM aqueous TbAA,

pH 6.5:methanol).

3.3 HPLC ANALYSIS

The DHI HPLC system is a Shimadzu LC-10ADVP

HPLC composed of one pump (LC-10ADVP), PDA detector (SPD-M10A VP), SCL-10ADVP System controller

† ISO 17025 is an international standard (published by the International Organization for Standardization) that specifies

the general requirements for the competence to carry out

tests and calibrations.

38
Hooker et al.

with LC Solution software version 1.24 SP1, temperature

controlled autosampler (set at 4◦C), a column oven (CTO10ASVP) (set at 60◦C), and a degasser. The samples

were mixed with buffer by the autoinjector by programming it to withdraw 150 μL buffer, 72 μL sample, 57 μL

buffer, 71 μL samples, 150 μL buffer, and inject the entire amount (500 μL in total, sample volume injected was

143 μL) onto the column. The method used for HPLC

analysis was the VHT method, where solvent B was methanol, and solvent A was (70:30) methanol:28 mM aqueous

TbAA, pH 6.4 (Table 25). The column was an Eclipse XDB

C8, 4.6×150 mm (Agilent Technologies), the flow rate was

1.1 mL min−1, and the temperature of the column oven was

set to 60◦C.

Table 25. The gradient system used with the DHI

method. Solvent A is 70:30 methanol:28 mM aqueous TbAA, pH 6.4, and solvent B is 100% methanol.

Step Time A [%] B [%]

Start 0 95 5

2 5 95 5

3 27 5 95

4 34 5 95

5 35 0 100

6 38 0 100

End 39.5 95 5

Mixed pigments (DHI Mix-102) were analyzed with the

samples: eight in total were randomly distributed in between the samples, followed by a blank (extraction solvent

with vitamin E).

Chlorophyllide a, phaeophytin a, phaeophorbide a, divinyl chlorophyll a, and monovinyl chlorophyll a were determined at 665 nm; the internal standard at 222 nm; and

the rest of the pigments were determined at 450 nm. Peak

identities were routinely confirmed by online PDA analysis.

3.4 CALIBRATION

The HPLC was calibrated with pigment standards from

DHI (Denmark), prior to analysis of the SeaHARRE-4

samples. Four pigment standards were mixed, and a series of six dilutions were made of each standard mixture:

three different concentrations at the range of expected concentrations of the natural samples, and three different concentrations at low concentrations near the limit of quantitation (LOQ) and limit of detection (LOD). The linearity

of the series was verified, and the response factors were

calculated from the regression forced through zero.

The concentrations of the calibration standards were

determined using a Shimadzu UV-2401PC dual-beam,

monochromator-type spectrophotometer, which is subjected to a regular set of quality control procedures. The

absorption coefficients used are shown in Table 26. Selected batch numbers of the standards are controlled for

purity and concentration by an independent laboratory.

Table 26. Absorption coefficient (α) values in liters

per gram per centimeter used with the DHI method

for the pigments listed as a function of wavelength

(λ).

Pigment Solvent λ α

Chl c3 90% Acetone 452.9 346.00

Chl c2 90% Acetone 443.8 374.00

Chlide a 90% Acetone 664.0 127.00

Peri 100% Ethanol 472.0 132.50

Phide a 90% Acetone 667.0 74.20

But 100% Ethanol 446.0 160.00

Fuco 100% Ethanol 449.0 160.00

Neo 100% Ethanol 439.0 224.30

Pras 100% Ethanol 454.0 160.00

Viola 100% Ethanol 443.0 255.00

Hex 100% Ethanol 447.0 160.00

Diad 100% Ethanol 446.0 262.00

Allo 100% Ethanol 453.0 262.00

Myxo 100% Acetone 478.0 216.00

Diato 100% Ethanol 449.0 262.00

Zea 100% Ethanol 450.0 254.00

Lut 100% Ethanol 445.0 255.00

Cantha 100% Ethanol 476.0 207.50

Chl b 90% Acetone 646.8 51.36

DVChl a 90% Acetone 664.0 87.67

MVChl a 90% Acetone 664.3 87.67

Phytin a 90% Acetone 667.0 51.20

β-Caro 100% Ethanol 453.0 262.00

3.5 VALIDATION

DHI holds a DANAK accreditation for carrying out

accredited measurements of pigment concentration in the

aquatic environment. DHI performs pigment analyses by

HPLC in accordance with ISO 17025 (accredited by DANAK). Validation follows the DHI Standard Operating

Procedure (SOP) No. 30/852:01: “Accredited measurements of pigment concentrations in the aquatic environment.” Validation steps include four injections of a chlorophyll a standard to verify the calibration of the HPLC,

use of an internal standard for correcting evaporation errors, and injection of a mixture of pigments (DHI mixed

pigments) to verify correct elution, retention times, and

for documenting the precision of the HPLC and response

factor stability.

3.6 DATA PRODUCTS

The peak areas and pigment identities were transferred

to an Excel file, and based on the response factors, the

pigment concentrations were calculated:

CPi = Vx

Vf

Aˆc

Aˆs

AˆPi

Vc

RPi , (33)

39
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

where AˆPi and RPi are the peak area and the response

factor of pigment Pi, respectively, Vx is the extraction volume, Vf is the volume of sample filtered, Vc is the amount

of sample injected, Aˆc is the peak area of the internal standard in the extraction solvent, and Aˆs is the peak area of

the internal standard in the sample.

The effective LOD and LOQ were calculated as described in the SeaHARRE-2 report (Hooker et al. 2005) for

all pigments. Results were submitted in separate spreadsheets with zero values indicating that a pigment was not

detected, and results where the values below LOD were

replaced by the effective LOD values, while values below

LOQ were replaced by the effective LOQ values.

3.7 CONCLUSIONS

The method used at DHI for the SeaHARRE-4 analyses was the VHT method, which in SeaHARRE-2 and

SeaHARRE-3 was shown to provide ‘state-of-the-art’ results. An average precision of 1.0% was attained at DHI

when determined by DHI mixed pigments. Because the

variability of natural samples where the filtered volume

and the extraction procedures are applied, uncertainties—

as well as the resulting precision of the SeaHARRE-4

samples—were higher, i.e., PPig ξ (CV) of 6.1%. The overall uncertainty attained in the analysis of field samples

were, on average, 5.4% and 29.5% for TChl a and PPig,

respectively. While the uncertainty of the DHI TChl a was

comparable to the results obtained in SeaHARRE-3, the

uncertainty of PPig was much higher (7.8% in SeaHARRE3). This increase in uncertainty was seen for all laboratories (Table 21, Chap. 1), and the major problem can be

ascribed to the complexity of the samples.

Samples from transitional areas, such as the estuaries

(where the samples for the present SeaHARRE-4 activity

were taken), contain a complex mixture of freshwater and

marine algae of which some undergo degradation due to the

changes in the environment, e.g., salinity gradients. Such

samples pose a particular challenge in the HPLC analyses

because they contain relatively many pigments (freshwater specific pigments as well), and increased amounts of

partly degraded pigments. These derivatives may coelute

and interfere with the quantification of the nondegraded

pigments; therefore, problems with false positives and false

negatives may be larger in such samples, because the baseline is sprinkled with small peaks of uncertain origin.

Acknowledgments. Merete Allerup is greatly acknowledged for skillful technical assistance.

40
Hooker et al.

Chapter 4

The FIO Method

Stanford B. Hooker (for David Millie 1)

1USF/Florida Institute of Oceanography

Saint Petersburg, Florida

Abstract

The FIO method used multiple reversed-phase C18 columns connected in series. The configuration uses a single

monomeric and two polymeric columns, and was originally devised to enhance the separation of numerous

structurally similar pigments and degradation products. The combination of the coarse and fine molecular

properties of the two different column types optimizes pigment separation. The monomeric column provides

strong retention and high efficiency, while the polymeric columns provide the selection for similar compounds.

The latter are temperature sensitive and require the use of a column heater. A nonlinear binary gradient, adapted

from Van Heukelem et al. (1992), was used for pigment separations. Solvent A consisted of 80% methanol:20%

ammonium acetate (0.5 M adjusted to pH 7.2) and solvent B was composed of 80% methanol:20% acetone.

Absorption spectra and chromatograms were acquired using a photodiode array detector. Pigment peaks were

identified by comparing retention times and absorption spectra with standards or culture extracts (depending

on the pigment involved).

Lead Author’s Note

The SeaHARRE activity was conceived as an opportunity for the HPLC community to investigate problems with

quantifying pigments extracted from aquatic phytoplankton and algae. In particular, the activity was established

to estimate the uncertainties in the derivation of standard

data products associated with chlorophylls a, b, and c, plus

a diversity of carotenoids. The main perspective was the

uncertainty in field samples collected primarily—but not

exclusively—from the marine environment. Such samples

do not have an a priori understanding of truth, so proxy

values must be determined from a rigorous application of

performance metrics to the candidate analyses.

The basic approach is to rely on community volunteers

to provide the field samples needed to address the objectives established for each activity, and a larger group of

volunteers are relied on for the subsequent HPLC analyses

using validated methods. The sample sets are collected as

part of either dedicated activities or in conjunction with

an already scheduled field campaign. In either case, considerable extra effort and attentiveness is needed to collect

all the samples in the requisite number of replicates. At

each step of the process, one or more volunteers step up

for the good of the community and the SeaHARRE activity to ensure the highest quality samples are obtained and

distributed.

Much of the dialogue for evolving the activity is established during workshops that are open to the SeaHARRE

participants and the wider community. The workshops are

usually held after the analysis of field samples have been

completed, so there have been almost as many workshops

as field campaigns. The volunteer HPLC analysts are recruited from a core group with established capabilities plus

a subset of new practitioners. The latter are a combination of entirely new analysts and recent participants who

have expressed an interest in remaining a part of the overall process. The union of these diverse sets of analysts

presumably provides a valid snap shot of community capabilities and diversity during each SeaHARRE activity.

All participants agree to an open documentation process, where all laboratories and methods are presented

without anonymity. The forums for presenting the results includes the workshops, scientific conferences, technical reports, and peer-reviewed publications. The most

detailed information for community-wide consumption is

in the technical reports, so at some level they are the

most precious. SeaHARRE activities need active participation and full disclosure from all participants, in order

that other community members can glean useful information. Repeated efforts were made to obtain a description

of the FIO method, but no documentation was provided

before the completion of this report. The FIO chapter abstract and this note were provided by the lead author of

the report. The abstract is based on details concerning

the method that are available in Pinckney et al. (1996 and

2001); additional information is available in Chap. 11.

41
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 5

The GSFC Method

Mary E. Russ

Science Systems and Applications, Inc.

Lanham, Maryland

Abstract

GSFC participated in SeaHARRE-4 as an HPLC novice, with no previous experience in actual HPLC pigment

analysis. The primary objective of the GSFC participation was to strictly adhere to the established performance

metrics for quantitative analysis, as well as the published protocols of the selected method (Van Heukelem

and Thomas 2001), to demonstrate whether or not both were sufficiently robust to allow any practitioner

to produce results in keeping with the QA subset. Preparation at GSFC prior to sample analysis included

servicing the instrument, making solvents, buffers, and standards, and running single- and multipoint regressions

of known standards to create a calibration table and update a spectral library used to identify pigments in

the 36 SeaHARRE unknown samples. Unexpected pressure issues resulted in recalibration and validation, as

well as the SeaHARRE samples being analyzed on the Agilent 1100 HPLC at HPL. Multiple Chl a regression

curves were run, and residuals calculated, in order to identify the dynamic range of the detector, as well as

the overall precision of the instrument. Overall, 35 Chl a standards of varying concentrations were injected

with average residuals of 1.5% for all concentrations. A second measurement of Chl a concentration, using a

spectrophotometer and a trichomatic equation was completed at GSFC using the remaining sample extractions

from the HPLC analysis. GSFC obtained state-of-the-art results, which established the capability of a novice

laboratory to produce high-quality pigment data for use in calibration and validation exercises associated with

remote sensing derivations of global chlorophyll concentrations.

5.1 INTRODUCTION

The SeaHARRE-4 samples were shipped from Denmark by DHI to GSFC on 4 December 4 2006, and arrived

at GSFC on 6 December 2006. All samples were placed in

a −80◦C freezer until analysis began, which was completed

in September 2007. Analysis for the GSFC samples were to

be performed on an Agilent 1100 Series HPLC using the

Van Heukelem and Thomas (2001) method. The GSFC

HPLC instrument had not been used for approximately 2 y,

however, so an extensive preliminary work plan was formulated (Sect. 5.3) to calibrate and validate this instrument.

Even with this effort, several unexpected pressure issues of

known and unknown causes resulted in recalibration and

validation runs, as well as the GSFC samples being ultimately analyzed on an Agilent 1100 HPLC at HPL.

An elevated pressure during the initial start-up procedure (i.e., purging of the instrument, with the pump

valve open at a flow rate of 15 mL min−1), exposed the

first pressure problem. This pressure issue was easily corrected with a change of the pump filter frit. An increasing

pressure at initial conditions (i.e., 95% solvent A and 5%

solvent B, at a flow rate of 1.1 mL min−1) was the second pressure issue. From the initial start-up of the instrument on 22 June through 17 July, initial pressure remained

approximately 150 bar. From 19–26 July, initial pressure

slightly increased (156–196 bar), and then decreased with

the changing of the pump frit on 26 July (146 and 149 bar

on 6 and 7 August, respectively). The pressure issue with

the initial conditions returned on 10 August and eventually

reached maximum pressure at 200 bar on 13 August.

An assessment of the instrument by Agilent, based on

the description of the problem via teleconferences, resulted

in a diagnosis of contamination throughout the system.

The solution recommended by Agilent was to replace the

column, most of the tubing, and several major pump parts,

and then to purge the system for a day with a mixture

of organic solvents. These steps were to be followed by a

thorough inspection of the system by an authorized Agilent

technician.

Because of time constraints, and with no guarantee that

the suggested solution to the pressure issue would result in

the GSFC system being operable, the decision was made

to take all necessary supplies, standards, and samples (via

dry shipper), to HPL for a week to rerun calibration and

validation injections, and perform the analysis of the sam42
Hooker et al.

ples on an Agilent 1100 HPLC that was known to be functioning properly.

5.2 EXTRACTION

Extraction of the 36 SeaHARRE-4 samples was performed at HPL, and followed the HPL extraction method.

Samples were extracted over three days (17–19 September) in three random batches of 12. Each filter was placed

in a solution of −20◦C chilled 100 μL water and 2.5 mL

of acetone for approximately 1 h. Next, the chilled samples were sonicated to completely macerate the filter, and

then placed back in the −20◦C freezer for 3.5–4.0 h. After this time period, sample slurries were individually filtered through a 0.45 μm pore size polytetrafluoroethylene

(PTFE)syringe cartridge filter into a 7 mL glass amber

scintillation vial. Filtered sample extracts were then vortex mixed, and approximately 500 μL of extract were transferred into an HPLC vial for overnight HPLC analysis. The

remaining extracts were stored in the −20◦C freezer, and

returned to GSFC for spectrophotometric chlorophyll a

analysis (Sect. 5.6).

5.3 HPLC ANALYSIS

Before beginning the SeaHARRE-4 sample analysis on

the GSFC HPLC, several steps were required because of

the instrument being idle for a long period of time. All solvent bottles were cleaned and dried, and all glass solvent

frits were replaced with new ones. A new Eclipse XDB

C8 4.6 × 150 mm 3.5 μm column was placed in the instrument, and all solvent lines, system tubing, and the column

were purged with a 70:30 methanol and water solution. All

pipettes, syringes, and dispensers were calibrated. Finally,

the following solutions were prepared for QA and QC purposes during sample analysis: a) a vitamin E solution for

use as an internal and working standard; b) the injection

buffer composed of 90:10 of 28 mM TbAA and methanol; c)

solvent A, a solution of 70:30 methanol and 28 mM TbAA;

and d) a Chl a standard.

The original HPL method gradient and instrument parameters were transferred directly to the GSFC HPLC.

The HPL injector program, however, needed to be modified to accommodate the injection of 525 μL of sample and

buffer to the GSFC hardware, which used a 100 μL syringe

head and a multidraw loop. An 18-step injector program

was designed, providing maximum draws of 100 μL or less,

with a draw speed of 130 μL min−1 and an eject speed of

250 μL min−1, for a total injector program time of approximately 10 min.

Once the injector program was in place and tested

with acetone blanks, a series of samples from DHI Mix102 and -103 were analyzed to determine instrument retention times for all pigments. From this analysis, 2 min

were added to the overall run time to accommodate capturing carotene, the last pigment to elute off the column.

With the retention times established, eight pure culture

samples (Tahitian isochrysis, Emiliania huxleyi, Pycnococcus, Pelagococcus, Prorocentrum, Duneliella, cryptophyte,

and mutant corn) were extracted and analyzed. These

samples were designed to evaluate the GSFC instrument

performance by checking elution of early- (Chl c) and lateeluting (carotene) peaks, the chromatography of less common peaks (DVChl a and DVChl b) and coeluting peaks

(Chlide a and Chl c1), and the resolution of critical pigment pairs (Zea and Lut, as well as Viola and Hex).

Multiple Chl a regression curves were run, and residuals calculated, in order to identify the dynamic range of

the detector, as well as the overall precision of the instrument. The Chl a standard was produced by the dissolution of crystallized Fluka (25730) Chl a in 90% acetone. Subsequent HPLC analysis determined the purity of

the standard to be 98.2%. Five-point regressions, which

signified concentrations ranging from 0.017–1.264 mg L−1

(2.533–186.194 ng inj−1), were performed.

Overall, 35 Chl a standards of varying concentrations

were injected with average residuals of 1.5% for all concentrations, and an average response factor of 0.2988 (with an

average standard deviation of 0.005). This information,

combined with triplicate single-point runs of individual

DHI pigment standards, formulated the calibration table,

which was used to update the HPL spectral library designed to identify unknown pigments in the SeaHARRE-4

samples.

At this point in the instrument calibration and validation process, the unresolved pressure issues at initial conditions rendered the completion of the SeaHARRE-4 samples on the GSFC HPLC impossible. The remaining analyses, except for the spectrophotometer work (Sect. 5.6), was

performed at HPL by the GSFC participant using GSFC

supplies and standards (except where noted) along with

the nearly identical Agilent 1100 HPLC at that facility.

5.4 CALIBRATION

Upon arrival at HPL and the inspection of the dry

shipped vials of GSFC standards, it was found that two

standards—Fluka Chl a and Fuco—were damaged in shipment, and were therefore, unusable. The HPL Fluka Chl a

and an HPL Fuco standard based on culture extractions

were used for the GSFC calibrations. Four calibration

curves for Chl a were run, two regressions on the first day

(17 September) and two regressions on the last day (19

September), with Chl a concentrations ranging from 0.014–

1.002 mg L−1 (1.9–146.1 ng inj−1). The average residuals

were always less than 1%, and ranged from 0.81%

(0.014 mg L−1) to 0.13% (1.002 mg L−1). The average response factor was 0.288 (ξ = 0.540).

Single point individual DHI standards, and the HPL fucoxanthin standard were also interspersed throughout the

sample runs, in duplicate, to have sufficient data to create a calibration table and update the spectral library,

43
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

or later chromatogram interpretation and data analysis

calculations of SeaHARRE-4 sample pigment concentrations. The absorption coefficients (α) used with the GSFC

method are presented in Table 27.

Table 27. The α values used by the GSFC method

for a variety of pigments as a function of λ. The

units for α are liters per gram per centimeter and

the units for λ are nanometers.

Pigment Solvent λ α

Chl c3 90% Acetone 452.9 346.00

Chl c2 90% Acetone 443.8 374.00

Peri 100% Ethanol 472.0 132.50

But 100% Ethanol 446.0 160.00

Fuco 100% Ethanol 449.0 160.00

Neo 100% Ethanol 439.0 224.30

Pras 100% Ethanol 454.0 160.00

viola 100% Ethanol 443.0 255.00

Hex 100% Ethanol 447.0 160.00

Diad 100% Ethanol 446.0 262.00

Allo 100% Ethanol 453.0 262.00

Diato 100% Ethanol 449.0 262.00

Zea 100% Ethanol 450.0 254.00

Lut 100% Ethanol 455.0 255.00

Chl b 90% Acetone 646.8 51.36

DVChl a 90% Acetone 664.3 87.67

Chl a 90% Acetone 664.0 87.67

Phaeo a 90% Acetone 667.0 51.20

ββ-Car 100% Acetone 454.0 250.00

5.5 VALIDATION

For both the validation of samples, and to verify instrument precision, during the three days of SeaHARRE-4

sample runs, both Chl a standards (0.547 mg L−1 or

79.7 ng inj−1) and vitamin E injections were interspersed

throughout each batch every four to six samples. Vitamin E standards had an average area of 3,171.7 mAU

(ξ = 0.2%), and Chl a had an average area of 277.8 mAU

(ξ = 0.4%) for all three runs.

5.6 DATA PRODUCTS

With limited past experience in pigment chromatogram

interpretation, a set of reprocessing guidelines were devised

prior to data analysis to provide the most consistency.

First, a set of integration parameters was established based

on the most number of primary peaks initially identified

and labeled via retention times. Second, library spectral peak matches were attempted for these time-identified

peaks, with large and well-formed peaks investigated first;

small and well-formed peaks second; and small and poorlyformed peaks were looked at last. The chromatogram was

then examined for pigment peaks not labeled via integration parameters and retention times. Little resizing of peak

areas was performed, and peaks not quantified, but identified by the software, were removed. Finally, reports for

each sample were consolidated and printed.

A spreadsheet was then created in Excel, and individual pigment concentrations (in units of micrograms per

liter) were quantified via the following equation:

CPi = Vx

Vf

AˆPi

Vc

RPi , (34)

where AˆPi is the area of pigment Pi; RPi is the response

factor; Vx is the extraction volume in liters; Vf is the filtration volume in liters; and Vc is the injection volume

in milliliters. Furthermore, because of the fact that the

method used for pigment analysis did not separate Chl c1

and Chlide a, the quantitation of these two pigments was

determined using a set of simultaneous equations (Hooker

et al. 2000). For each pigment triplicate, the average, standard deviation, and CV were calculated.

An additional calculation of Chl a was accomplished using a spectrophotometer and the trichromatic equation of

Humphrey and Jeffrey (1997). After HPLC pigment analysis at HPL, all remaining SeaHARRE-4 pigment extracts

were carefully wrapped and then placed in a dry shipper

and brought back to GSFC. Upon arrival, all extracts were

read on a PerkinElmer Lambda 35 spectrophotometer, and

absorption at 630, 647, 664, and 750 nm were recorded.

Absorption at 750 nm was used as a baseline and was

subtracted from the other three wavelengths. These adjusted absorption measurements were used to calculate



SChla



for each of the 36 SeaHARRE-4 pigment samples

using the following equation:



SChla



= 11.85A(664) − 1.54A(647) − 0.08A(630). (35)

5.7 CONCLUSIONS

Initially, the 36 SeaHARRE-4 samples were to be analyzed at GSFC, using the Van Heukelem and Thomas

(2001) method, on an Agilent 1100 HPLC. Unresolved

pressure issues, however, created an obstacle to this plan.

With the calibration and validation of the GSFC instrument complete, the pressure issues became insurmountable; recalibration, validation, and analysis of the

SeaHARRE-4 samples were, therefore, performed at HPL

using GSFC supplies and standards. A second measurement of Chl a concentration, using a spectrophotometer

and a trichomatic equation, was completed at GSFC using

the remaining sample extractions from the HPLC analysis. Finally, state-of-the-art results by the GSFC HPLC

novice participant, highlighted the importance of establishing guideline performance metrics for biogeochemical

methods.

44
Hooker et al.

Chapter 6

The HPL Method

Crystal S. Thomas

Laurie Van Heukelem

UMCES Horn Point Laboratory

Cambridge, Maryland

Abstract

The HPL HPLC method employed by Horn Point Laboratory was developed for use with a variety of water types.

Many pigments important to freshwater, estuarine, and oceanic systems are baseline resolved and quantitatively

reported, including divinyl and monovinyl chlorophyll a. The method is built around a C8 HPLC column,

and incorporates a methanol-based reversed-phase solvent system, a simple linear gradient, and an elevated

column temperature (60◦C) to achieve separation of the pigments to be quantitated. The method can provide

quantitative results for up to 25 pigments with qualitative information for additional pigments. Quality assurance

measurements are made during sample analysis to confirm that the method performance is within expectations.

Investigations into the uncertainties in the method show the 95% confidence limits are estimated as a) 0.5–

3.8% for precision of replicate injections within and across sequences, b) 3.2% for chlorophyll a calibration

reproducibility, and c) 5.1% for chlorophyll a method precision, including filter extraction and analysis.

6.1 Introduction

The HPL HPLC method (Van Heukelem and Thomas

2001) and modifications to it have been extensively described in previous SeaHARRE reports (Hooker et al. 2005

and 2009). The HPL method uses a C8 column and a

reversed-phase, methanol-based, gradient solvent system.

A linear gradient is used because segmented gradients offered no advantages—and increased baseline instability—

which can interfere with the quantitation of pigments, particularly those in low concentrations. Elevated column

temperature is used to facilitate separation selectivity.

High column temperature, however, shortens the useful

column lifetime and special handling should be considered

(Wolcott et al. 2000). The HPL procedures are occasionally modified as new types of samples and activities lead

to new understandings, as have been the case with the

SeaHARRE activities.

6.2 Methodology

HPLC methodology includes descriptions of sample extraction procedures, quality assurance (which includes calculation equations), and HPLC analysis, which is further

subdivided into procedures for injection, pigment separation, detection, calibration, and pigment identification.

Data products and data reporting practices specific to the

SeaHARRE-4 activity are also described.

The SeaHARRE-4 samples were received frozen in liquid nitrogen dry shippers the week of 21 February 2007.

The filters were immediately placed in a freezer at −80◦C

until processed in March 2007. DHI pigment standards,

including the Mix-102 standard, were received well frozen

on dry ice the week of 21 February and held at HPL in a

−25◦C freezer until analyzed.

6.2.1 Extraction

At HPL, the ‘default’ volumes used during sample extraction are 2.5 mL 100% acetone and 100 μL water. These

volumes are sometimes adjusted depending on the individual sample set. Several different extraction volumes have

been previously tested and validated. During SeaHARRE4, the volumes were adjusted to 4.0 mL 100% acetone and

160 μL water, after noting that the filters appeared visibly

darker than normal (and therefore more concentrated). Increasing the extraction volume also ensured that sufficient

sample extract would be available for spectrophotometric

analysis.

The procedures for extractions were as follows:

1. A frozen filter sample was placed in a thick-walled

12 mL glass centrifuge tube.

2. The extraction solvent, 100% HPLC-grade acetone

(J.T. Baker 9002-03, Phillipsburg, New Jersey) containing DL-α-tocopherol acetate (vitamin E acetate,

45
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Sigma-Aldrich 95250, St. Louis, Missouri) in a concentration of approximately 0.02 mg mL−1 was kept

in a 1 L brown glass bottle. The bottle was removed

from a −15◦C freezer and brought to room temperature. A 4.0 mL aliquot of room-temperature extraction solvent was added to a centrifuge tube with a

glass volumetric pipette that had been calibrated

gravimetrically with 100% acetone.

3. An automatic pipette was used to deliver 0.16 mL

of deionized water to the tube.

4. To prevent evaporation, the top of the centrifuge

tube was covered with Parafilm immediately after

the acetone and water were added.

5. The tube was placed in an ice bath shielded from the

light as soon as the top was covered with Parafilm.

After all filters in a set were processed following steps 1–5:

6. Samples in the ice bath were placed in a −25◦C

freezer for at least 1 h.

7. Samples were removed from the freezer. Each sample filter was individually disrupted for approximately 20 s with a Branson 450 Sonifier (Danbury,

Connecticut) equipped with a 0.125 in microtip sonic probe, using control settings that resulted in approximately a 30–40W output.

8. The filter extracts were re-covered with Parafilm

and stored in a −25◦C freezer for 3–4 h.

9. Samples were removed from the freezer. The filter slurry of each sample was then transferred to a

clean 5 mL disposable syringe with a Luer-Lok tip

(Becton-Dickinson 309603). The slurry was clarified by pushing it through a PTFE Titan HPLC

syringe cartridge filter attached to each Luer-Lok

syringe. The pore size of all filters used for clarification was 0.45 μm, and the diameter was 17 mm

(Sun SRI 44504-NP, Rockwood, Tennessee). The

clarified extract was collected in clear, 7 mL scintillation vials with cork-backed, foil-lined screw caps

(Fisher Scientific 03-337-26, Pittsburgh, Pennsylvania).

After all the samples extracted in a day were clarified

(steps 6–9), the final sample preparation procedures were

as follows:

10. The sample extract, contained in a 7 mL scintillation vial, was vortexed gently for approximately 1 s.

Using an autopipette, approximately 0.5 mL was

transferred to an amber HPLC vial (National Scientific C4011-6W, Rockwood, Tennessee) and capped

with a PTFE and silicone snap cap (National Scientific C4011-54B). A clean, unused tip was used

with each extract.

11. The vials were placed in the HPLC temperaturecontrolled autosampler (TCAS) compartment, set

at 4◦C, and analyzed within approximately 24 h.

12. The remaining unused sample extracts were recapped and stored at −15◦C until they were used

for spectrophotometric analysis.

6.2.2 HPLC Analysis

The filter extracts and standards were analyzed using a

fully automated Agilent 1100 HPLC equipped with a quaternary pump, programmable autoinjector, TCAS, Peltier

temperature-controlled column oven compartment, PDA

detector, and ChemStation software revision A.10.02 (all

from Agilent Technologies, Inc., Santa Clara, California).

6.2.2.1 Injection

The HPL HPLC has been modified with a metering

device and sample loop capable of drawing up to 900 μL.

The injector is programmed to draw successive aliquots of

sample extract and buffer into the sample loop. A mix

function was tested during SeaHARRE-3, but because it

offered no apparent advantages, HPL returned to the injector program used in SeaHARRE-2 (Hooker et al. 2005).

Several steps have been identified at HPL that contribute to excellent injector precision, and are therefore

always followed:

a. Place sample and buffer vials in the TCAS at least

1 h prior to starting analyses;

b. Disregard the first injection of a sequence;

c. Maintain a sufficient and constant column reequilibration volume between injections;

d. Use vial and cap combinations that have been tested

and proven to prevent evaporation (Hooker et al.

2009);

e. Use injection draw speeds that prevent a vacuum

from forming when sample is withdrawn from the

vial; and

f. Limit the vial residence time in the TCAS to approximately 24 h or less.

The injection buffer solution is 28 mM TbAA (pH 6.5)

and methanol, mixed 90:10 (vol:vol), respectively. This solution is filtered in batches through an Acrodisc 25 mm syringe filter with a 1 μm glass fiber membrane (Pall 4523T,

East Hills, New York). Snap caps on the buffer and sample vials are formulated of layered PTFE and silicone, but

caps used with buffer vials are preslit (National Scientific

C4011-59) to facilitate accurate draw volumes of the more

viscous buffer mixture. Snap caps on sample vials are not

preslit, to prevent evaporation of the sample.

Rather than use a large reservoir from which to draw

buffer, buffer is put in the TCAS in the same type of

HPLC vials as samples. Each HPLC vial contains enough

buffer for four separate injections. Using these smaller

buffer reservoirs helps control potential contamination of

the buffer by sample extract, as well as minimize the impacts of this type of carryover if it were to occur. The

46
Hooker et al.

needle is also dipped in a vial of 100% acetone (with caps

with Teflon septa, National Scientific C4011-52R) after

each time the needle draws from a sample vial, in order to

help control carryover. Occasionally, peak splitting with

chlorophylls c1, c2, and c3 is encountered, and MgDVP is

similarly affected if present.

6.2.2.2 Separation

The separation conditions used in SeaHARRE-4 were

the same as those used in SeaHARRE-2 and -3. Solvent A is formulated (vol:vol) from HPLC-grade methanol (Fisher Scientific A452-4, Fair Lawn, New Jersey) and

28 mM TbAA (pH 6.5) in a ratio of 70:30, respectively.

The aqueous TbAA solution is made by diluting 0.4 M

tetrabutyl ammonium hydroxide (J.T. Baker V365-7) with

high-purity deionized water (HPLC-grade equivalent) and

adjusting the pH to 6.5 with acetic acid.

Solvent A is thoroughly mixed and then filtered through

a 0.2 μm pore size, 47 mm diameter nylon membrane filter

(Millipore GNWP04700, Billerica, Massachusetts). The

number of batches of solvent A needed to complete the

work associated with one week of analyses are combined

in a large glass carboy, so all solvent A to be used in a

week is homogeneous. This procedure promotes day-today retention time stability. This container is kept on a

stir plate at a very low setting to prevent layering from

occurring in the solvent container over the course of the

week. Any solvent A not fully consumed within the week

is either discarded or refiltered and combined with the next

batch of solvent A, to avoid potential precipitates forming

and clogging the column.

Table 28. The HPL pump gradient used during

SeaHARRE-4. Solvent A is 70:30 methanol:28 mM

TbAA (pH 6.5), solvent B is methanol, and solvent

C is acetone. (After SeaHARRE-3, Solvent C was

added as a rinse to help alleviate carryover.)

Time A [%] B [%] C [%] Flow

0 95 5 0 1.1

22.00 5 95 0 1.1

24.50 5 95 0 1.1

24.75 5 65 30 1.3

25.75 5 65 30 1.3

25.85 5 65 30 1.1

26.10 95 5 0 1.1

29.10 95 5 0 1.1

The pump gradient used in SeaHARRE-4 is presented

in Table 28. The total run time, including the injector

program, from the beginning of one injection to the next,

is 44.9 min. A total of 15.2 mL of the solvents at the initial

condition flows through the column in between the time of

the completion of one sample injection and the injection of

the next sample. Column temperature is set at 60.0◦C

±0.8◦C. The HPLC column is a Zorbax Eclipse XDBC8, 3.5 μm particle size, 4.6×150 mm2 (Agilent 963967-

906, Santa Clara, California). The column is used without

a guard column or prefilter, because those have been tested

at HPL and offered no advantages.

6.2.2.3 Detection

Chromatograms are plotted using the 450 and 665 nm

wavelengths (each with a 20 nm bandwidth), as well as at

222 nm with a 10 nm bandwidth. Tungsten and deuterium

lamps are both used and absorbance spectra are collected

between 350–750 nm, with a range step and slit width of

2 nm. The flow cell capacity is 13 μL and the pathlength

is 1 cm.

The wavelength at 222 nm is used exclusively for quantitation of the internal standard. This wavelength is not

associated with the maximum response for vitamin E, but

it allows good detection and minimizes baseline drift. The

baseline drift is caused by solvent effects of the gradient

and is approximately −3 mAU min−1. The signal height

of vitamin E at the concentration used is approximately

600 mAU, and sufficiently high so that baseline drift does

not interfere with accurate peak area determinations. The

vitamin E solution is formulated at a concentration such

that the resulting peak height corresponds to about twothirds of the height threshold where the response becomes

nonlinear.

6.2.2.4 Calibration

The retention times of pigments to be quantified, and

pigments with a potential to interfere with the quantitation

process, were originally documented using algal monocultures and standards (Van Heukelem and Thomas 2001).

This information is summarized in the SeaHARRE-3 report, Table 31, as well as additional details on chromatographic problems that can cause large uncertainties for

some pigments in natural samples (Hooker et al. 2009).

The HPLC was calibrated with both purchased standards and those isolated at HPL. Concentrations of pigment standards were determined with the absorption coefficients given in Table 29. For standards that were purchased from DHI, the spectrophotometrically determined

concentrations provided by DHI were used to compute the

response factors observed from their standards at HPL.

The spectrophotometer used for determining the concentrations of standards isolated at HPL, or purchased

from Sigma-Aldrich or Carotenature and dissolved at HPL,

was a Shimadzu 2401-PC (Columbia, Maryland), with a

bandwidth of either 1 or 2 nm, a medium sampling rate,

1 nm sampling interval, and turbidity correction at 750 nm.

Absorbance of stock standards is typically between 0.2–

0.8, a range recommended by Marker et al. (1980) for best

spectrophotometric accuracy.

47
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 29. The HPL α values (in units of liters

per gram per centimeter), used for spectrophotometrically measuring pigment concentrations. Also

shown are the solvents and maximum wavelengths

(λm) specified for use with α values. Absorption

coefficients and reference wavelengths used at HPL

match those used at DHI. The units for λm are

nanometers. Standards isolated at HPL, or purchased from DHI, Sigma-Aldrich or Carotenature,

are denoted H, D, S, and C respectively, in the

source column.

Pigment Solvent λm α Source

Chl c3 90% Acetone 453 346.00 H D

Chl c2 90% Acetone 444 374.00 H

Chl c1 90% Acetone 443 318.00 H

Chlide a 90% Acetone 664 127.00 D

Phide a 90% Acetone 667 74.20 D

Peri 100% Ethanol 475 132.50 H D

But 100% Ethanol 447 160.00 D

Fuco 100% Ethanol 449 160.00 H

Neo 100% Ethanol 439 227.00 H

Pras 100% Ethanol 438 160.00 H

Viola 100% Ethanol 443 255.00 D

Hex 100% Ethanol 447 160.00 D

Diad 100% Ethanol 446 262.00 D

Allo 100% Ethanol 453 262.00 H

Diato 100% Ethanol 449 262.00 H

Zea 100% Ethanol 450 254.00 H

Lut 100% Ethanol 445 255.00 D

DVChl b 100% Acetone 645 52.50 H

Chl b 90% Acetone 647 51.36 H D

DVChl a 90% Acetone 664 87.67 H

Chl a 90% Acetone 664 87.67 S

Phytin a 100% Acetone 667 51.20 H

ββ-Car 100% Acetone 454 250.00 H C

Single-point response factors are generally used at HPL,

because previously it has been demonstrated that the samples being analyzed were within the linear range and, in

addition, the linear regressions associated with the multipoint calibration curves exhibited y-intercept values very

near zero. The values of the response factors being used are

based on averages obtained from using the same method

for many years. The validity of the average response factors is checked frequently, and the uncertainties for calibration checks are expected to be within 5%. This uncertainty represents the cumulative effects of spectrophotometric determinations of stock standard concentrations,

dilution, and the subsequent HPLC analyses. Uncertainties greater than 5% are investigated and, if necessary, response factors in the calibration table are changed.

Discrete calibration standards were not available for

all of the pigments quantitated during the SeaHARRE-4

activity, including:

• Chlide a;

• A chlorophyll c3-like pigment which elutes immediately after chlorophyll c3 and was summed with

chlorophyll c3;

• Four pigments with Phide a spectra that elute after the retention time of the Phide a standard purchased from DHI (quantitated with the response

factor from DHI Phide a standard);

• Chl a and DVChl a allomers and epimers (quantitated as part of total Chl a); and

• A Phytin a epimer (quantitated with Phytin a response factor).

Because HPL had no discrete standards for these pigments, retention times were updated as they were observed

in the DHI retention time mix or in natural samples (as

identified with in-line visible absorbance spectra).

During the analysis of SeaHARRE-4 samples, retention

times were documented on a daily basis using DHI Mix102. This mix was injected near the beginning of a sequence and then approximately once every 24 h thereafter.

Pigment identification in natural samples was based primarily on retention time; absorbance spectral match with

known standards was also used when possible (e.g., where

the signal was adequate to produce usable absorbance spectra for peaks in sample extracts). In other words, if a pigment appeared at a retention time for a particular standard, but the absorbance spectrum was clearly inconsistent

with what should be apparent for that standard, the pigment was reported as not present (i.e., a limiting value was

assigned).

Pigments with an SNR of 4 or less (at the wavelength

used for their quantitation) were considered “not present”

(i.e., a limiting value was assigned).

If a symmetrical, well-shaped peak appeared at the retention time of a standard, with an SNR ≥ 4, but the

SNR was too low to confirm or reject pigment identity

on the basis of absorbance spectra, the pigment was still

quantitated and reported. Small peaks that were clearly

contaminated with an interference peak, as evidenced by

peak shape distortion, were reported with a limiting value

(this most frequently occurred with Diato).

6.3 Quality Assurance

The quality assurance discussion addresses replicate injections and carryover.

6.3.1 Replicate Injections

The average precision of replicate injections of the internal standard (ISTD) was 0.41% for dates during and

immediately following the analysis of SeaHARRE-4 field

samples.

As part of standard procedures, duplicate sample extract injections are performed daily. Aliquots of the extract

of the first sample to be analyzed in a sequence of injections are added to two HPLC vials, then both vials are

48
Hooker et al.

placed in the TCAS at the same time, along with all other

sample extracts prepared on that day (referred to here as

the “daily sample set”). The first vial (of the two vials

that contain the same sample extract) is the first injection

of the daily sample set (but not the first injection of the

sequence), and the second vial is injected after all other

samples in the daily sample set have been injected.

The timing of the duplicate injections may differ by

as much as 20–30 h. For SeaHARRE-4 samples, only one

sample extract was injected two times in the manner described, therefore, data are included for other duplicate

extract injections that were made on the same sequence as

the SeaHARRE-4 field samples. The CV (in percent) was

determined for TChl a, as well as the primary pigments

(which were averaged and reported as an overall average

PPig CV). For these replicate injections, which represent

samples extracted on 5, 6, 7, 8, and 9 March 2007, the

CV of TChl a was 0.31, 0.01, 0.28, 0.56, and 0.04%, respectively; the corresponding CV for PPig was 2.15, 3.88,

6.02, 1.64, and 1.88%, for the respective dates. The overall average CV for TChl a was 0.24% and for PPig it was

3.11%.

Four separate vials of the DHI Mix-102 were used for

quality assessment. In all cases, when making HPLC injections, the contents of a DHI Mix-102 vial was dispersed

into one or more HPLC vials (500 μL per vial); only one

injection was performed from each HPLC vial. Both intravial injections (i.e., multiple injections from the contents of one vial of DHI Mix) and intervial injections (one

injection each from contents of multiple DHI Mix vials)

were made. Three intravial injections were performed on 4

March 2007, for which the CV was 0.2% (TChl a) and 0.2%

(PPig); and six intervial injections were performed from 7–

8 March 2007, for which the CV was 0.7% (TChl a) and

1.0% (PPig).

6.3.2 Carryover

In the HPL SeaHARRE-3 chapter, it was noted that

HPL experienced substantial carryover immediately following SeaHARRE-3, which was alleviated by adding an

acetone rinse to the solvent gradient (Table 28). During SeaHARRE-4, carryover for pigments was monitored

by inspecting chromatograms for extraneous pigments of

any internal standard or single standard injection. Carryover of ISTD was monitored by inspecting chromatograms

that followed an ISTD injection, if the proceeding injection

would not normally contain ISTD (such as a Chl a quality control, QC, or retention time mix). No carryover was

observed during SeaHARRE-4.

6.4 Data Reporting

Pigments denoted as “not found” or ones with an SNR

that is less than four were reported with a limiting value

(0.0001 mg m−3). Concentrations were rounded to four

digits to the right of the decimal.

6.4.1 Governing Equation

Previously, HPL used multiple equations during the

pigment calculation process. (See the SeaHARRE-2 and

SeaHARRE-3 reports, Hooker et al. 2005 and 2009, respectively, for the equations and descriptions thereof.) Some

of these equations are reiterated here. The amount of pigment injected (C ̃Pi ) was calculated as

C ̃Pi = AˆPi RPi , (36)

where AˆPi is the area of the parent peak (and associated

isomers) and RPi is the response factor (calibration factor).

To calculate the concentration of a pigment in a natural

sample (CPi ),

CPi = Vx

Vf

C ̃Pi

Vc

, (37)

was used, where Vx is the extraction volume, Vc is the

volume of sample extract injected onto the HPLC column,

and Vf is the filtration volume.

Using a ‘one-step’ addition approach, an internal standard was used to correct Vx for residual water retained on

the filter paper (plus any variations in volume caused by

evaporation):

Vx1 = Aˆc1

Aˆs1

Vm, (38)

where Aˆc1 is the peak area of the internal standard (within

the internal standard batch mixture) when it is injected

onto the HPLC column prior to its addition to the sample

(determined using a one-step internal standard methodology); Aˆs1 is the peak area of the internal standard in the

sample; and Vm is the volume of extraction solvent (with

internal standard) added to each sample filter.

While all of these basic equations are still in use, these

equations have been merged with other basic calculation

equations into one governing equation:

CPi = Aˆc1

Aˆs1

Vm

Vf

AˆPi



ASi (λm) − ASi (750)

αSi (λm)lcΣAˆsi

	

, (39)

where αSi is the absorption coefficient for the pigment

standard Si associated with the pigment of interest Pi, λm

is the reference wavelength associated with the absorption

coefficient, lc is the pathlength of the spectrophotometer

cuvette (usually 1 cm), and ASi is the spectrophotometric

absorbance value of the pigment standard (Sect. 1.3).

It can be noted that some of the variables from the previous equations do not appear in the governing equation.

It is not that the variables are no longer of importance,

but rather that the variables drop out or cancel (from the

numerator and denominator) once multiple formulas with

some of the same variables are combined. Quality control

measurements are still made to ensure the accuracy and

precision of such variables.

49
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

6.4.2 Data Products

The data products reported with the HPL method include: a) individual pigments, b) pigment sums (these are

individually quantified pigments summed together), and c)

pigments resulting from one or more unresolved pigments

that are quantified collectively using a response factor for

the most frequently abundant pigment at that retention

time (e.g., Caro and Chl c2).

Pigment standards frequently contain small isomers

that are usually less than 10% of the total peak area for

that standard. It is rather likely that isomers are also

present in natural samples. Most often, however, these isomers are undetectable, because their peak areas are small

relative to the parent peak, or they coelute with the main

peak of a more dominant pigment than the parent pigment.

Only isomers for MVChl a, DVChl a, Phytin a, and Peri

are routinely quantitated for the HPL method, although

the potential of isomers for coelution is described in Table 11 of Hooker et al. (2005). Isomers for Chl b have also

been observed. In the SeaHARRE-4 samples, a relatively

large peak was observed eluting near the main Peri peak.

The retention time of this peak, however, did not match

what was expected for the Peri isomer, therefore, it was

not quantitated as part of Peri. Some other SeaHARRE-4

participants did identify this peak as the Peri isomer, so

in these instances the Peri concentration reported by HPL

would be lower than the average.

In SeaHARRE-4, the total area of all MVChl a allomers

and epimers, plus the main Chl a peak, were summed; the

nanograms per injection was determined by multiplying

the resulting total peak area times the Chl a response factor. No DVChl a was observed in the SeaHARRE-4 samples, but DVChl a was in DHI Mix-102.

6.5 Discussion

Previous SeaHARRE HPL method chapters have discussed problems of pigment quantitation encountered by

HPL (Hooker 2005 and 2009). Here, the discussion is limited to the problems that most probably contributed to

degradation of accuracy with SeaHARRE-4 samples. During SeaHARRE-4, using a “can’t say no” de-facto acceptance criteria, HPL did not reject small peaks (SNR ≤

4) that had no, or inconclusive, spectra. These acceptances likely explain some of HPL’s false-positive results

relative to other A laboratories, if they either rejected or

did not integrate these small peaks. Similarly, there were

some small Peri peaks that only yielded a spectral match if

manual referencing were used. Differences among the laboratories’ quantitative analysis procedures and differences

in available software features, or the use of such, can lead

to differences in quantitation, particularly of small peaks.

In SeaHARRE-4, all A laboratories, including HPL,

experienced undesirable average inaccuracy (> 25% APD)

for But, Hex, Diato, and Peri, with an overall A average

APD for these pigments of 65%. This behavior was largely

a result of laboratories differing regarding whether a pigment was reported as present or not at the 12 sampling

locations. The number of sites for which A laboratories

reached a consensus of agreement for each of these four

pigments ranged between one and six, depending on pigment. In contrast, for the other eight primary pigments, A

laboratories agreed unanimously in all but three instances

(one site for Allo and two for Zea). For each of these other

eight primary pigments, the A average accuracy was always 20% or less; the overall average among A labs was

12%. These data emphasize the need for implementing

measures that reduce the instances of false-negative and

false-positive results (see Chap. 1 for definitions).

Pigments that are only weakly present in a sample extract (e.g., the SNRs are low) are detected by some laboratories, but may not be detected by others, and they are

subject to differences in reporting practices. The “twosentence rule” was intended to minimize such inconsistencies (Hooker et al. 2009), but it is evident that reporting practices in SeaHARRE-4 were still inconsistent when

SNRs were low. For example, in SeaHARRE-4, 48 reporting opportunities existed for the pigments But, Hex, Diato,

and Peri. Laboratories G and H reported these pigments,

collectively, as present in 23% and 75% of instances, respectively, despite the fact that both laboratories conducted

analyses with the same analysis method (Van Heukelem

and Thomas 2001) on the same HPLC. Considering the

specific example of But (for which the HPL average APD

was 144.6%), HPL had five false-positive results. In each

false-positive instance, the SNR was 11 or less. Because

an SNR of this magnitude does not yield adequate absorption spectra, these peaks that were at the But retention

time were reported by HPL (to be in compliance with the

two-sentence rule) because they could not be proved to be

other than But. This problem is not unique to HPL; any

laboratory that is less aggressive in rejecting small peaks

in a SeaHARRE activity is at risk of a higher frequency of

false-positive results.

A “true” false-positive result would occur if a laboratory reported a pigment as present when the identity of

the pigment was not supported by the absorption spectra

and/or retention time. As SNR decreases, there is deterioration in the absorption spectra and there is a point at

which interpretation of spectra becomes too ambiguous to

make a determination. This so-called point-of-ambiguity

varies with pigment, method, and spectral features of the

chromatography software. To elaborate using the specific

example of Peri in SeaHARRE-4—for which average A

APD was 65%—the first six sites exhibited much higher

than normal APDs (A average APD = 118%), but the last

six sites did not (average A APD = 12%). It is notable

that the Peri peak height at the last six sites was sufficiently high to yield adequate spectra (at HPL SNR was

>200), but the peak height was relatively low at the first

six sites (SNRs ranged from 13–70 at HPL). An SNR of 70

50
Hooker et al.

is typically sufficient to yield unambiguous Peri spectra at

HPL, but in the HPL Peri result for site 1 (for which HPL

had a “false-positive” result and an APD of 398%), an

unambiguous positive-identification spectra was only obtainable by disabling the “automatic referencing” feature

of the software.

Most HPLC reprocessing software packages have the

built-in capability to override automatic referencing during

spectral analysis with a manual referencing function. This

function allows analysts to select their own pair of reference

points in the chromatogram before checking spectra for the

peak of interest (typically points immediately before and

after the peak of interest are chosen).

The utility of manual referencing when checking lowlevel spectra is undeniable, but should be used with prudence. It is improbable that even the same user can recreate the exact referencing conditions more than once, and

even a minor change in referencing can lead to a difference

in spectral interpretation. If an analyst uses a combination of automatic referencing and the two-sentence rule to

interpret chromatograms, it is likely that the analyst may

reach the conclusion of “can’t say the pigment is not there”

with many low SNR peaks. The use of manual referencing might provide some clarity on some of these spectral

interpretations. It is likely, therefore, that the analyst will

be able to come to a greater number of definitive “yes/no”

assessments as opposed to a “can’t say no” de-facto acceptance of a peak identity. This difference could cause

an analyst’s results to diverge with those of other analysts

who use only automatic referencing, or who interpret their

manual referencing results differently. The difference can

even lead to variability in interpreting the spectrum of the

same peak by the same analyst on multiple occasions, given

that it is unlikely that the analyst will be able to select the

same reference points (which must be selected each time

the peak is inspected) multiple times. Manual referencing

is a valuable tool, but has the potential to introduce more

false positives and negatives to one’s results.

6.6 Conclusions

The HPLC method used at HPL has been in use since

1999 and is capable of providing quantitative results for up

to 25 different phytoplankton pigments. HPL documented

the elution position and absorbance spectra of 58 pigments

in a spectral library that can be used during the analysis

of samples to assist pigment identification. HPLC pigment

analysis is conducted at HPL within the framework of a

detailed quality assurance plan. Limitations of the method

are regularly reassessed as more diverse water types are analyzed. Such limitations cannot be known until an analysis

method is used with all possible combinations of samples—

a process that is not possible during initial method validation. As such, unforeseen coelution problems were encountered, which required HPL to disregard some pigments

that were originally intended for quantitation.

Following SeaHARRE-4, several changes in the reporting practices of HPL were made and are summarized herein.

Chromatographic peaks representing Chl c2, Chl c1, and

MgDVP are now quantified as one entity, referred to as

Chl c12, because MgDVP, also a Chl c pigment, is frequently found in oligotrophic samples and interferes with

accurate quantitation of both Chl c2 and Chl c1. Pigments

are now categorized as either primary, secondary, tertiary,

or ancillary—terms defined and used within the SeaHARRE activities.

Digits of precision have been reduced from four places

(e.g., 0.0001) to three (e.g., 0.001). This action is consistent with recommendations of other SeaHARRE pigment

analysts. Pigments are rarely quantifiable at concentrations less than 0.0005 μg L−1, and, in fact, these low concentrations are often associated with uncertainties of similar magnitude. As an example, the average standard deviation of pigments in mesotrophic and oligotrophic samples is on the order of 0.0005 μg L−1, as determined from

replicate injections of sample extracts—a quality control

analysis performed daily with all samples.

A new null value of 0.0009999 μg L−1 is now used to

represent pigments that are “not detected,” as well as

pigments that are present, but with concentrations less

than 0.0005 μg L−1. To put this in perspective, for primary pigments, the average limits of detection (SNR =

3) and quantitation (SNR = 10) for filtration and extraction volumes typical of oligotrophic samples are 0.0004 and

0.0013 μg L−1, respectively. A value of 0.0009999, while it

would give the appearance of a concentration of 0.001, is

easily discernible from a value that would represent a concentration less than 0.0014, but greater than 0.0005 μg L−1

(the range of values that would round to 0.001 μg L−1).

The null value is inserted after results have been rounded

to three digits and higher-order data products have been

computed.

51
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 7

The JRC Method

Elisabetta Canuti

Jean-Franc ̧ois Berthon

Institute for Environment and Sustainability, Global Environment Monitoring Unit

Joint Research Centre of the European Commission

Ispra, Italy

Abstract

The HPLC method adopted by the JRC is the Van Heukelem and Thomas (2001) method, as modified for

SeaHARRE-3 (Van Heukelem and Thomas 2009). This method has been successfully applied to a wide range of

pigment concentrations from oligotrophic to eutrophic coastal waters (Van Heukelem and Thomas 2009). Here,

it allowed for the separation and the quantification of 22 different pigments and, in particular, the monovinyl

and divinyl forms of chlorophyll a. The samples are extracted in a 100% acetone solution including an internal

standard (vitamin E acetate) and analyzed by HPLC using a C8 column with a binary solvent gradient. The

different pigments are identified using a diode array detector on the basis of the absorption spectra at two

different wavelengths (450 and 665 nm). The quality control of the data is assured by injecting a chlorophyll a

standard at the beginning of each sequence, in order to check the calibration, as well as a mixture of pigments

in order to check the retention times, and the system accuracy and precision.

7.1 INTRODUCTION

The HPLC method adopted by the JRC in 2007 and

first tested during the present SeaHARRE-4 exercise is

the Van Heukelem and Thomas (2001) method (VHT), as

modified for SeaHARRE-3 (Van Heukelem and Thomas

2009). This method allows for the separation and the

quantification of a larger number of taxonomically relevant

pigments than the previously used Wright et al. (1991)

method. In particular, the VHT method permits the chromatographic separation of the monovinyl and divinyl forms

of chlorophyll a. The VHT method has been successfully

applied to a wide range of pigment concentrations ranging

from the oligotrophic central South Pacific Ocean sampling

conducted for SeaHARRE-3 (Hooker et al. 2009) to the

eutrophic coastal South African waters for SeaHARRE-2

(Hooker et al. 2005).

The main changes introduced with respect to Wright

et al. (1991) are related to the extraction procedure, the

column characteristics, and the mobile phase. The extraction time is shortened (4 h instead 24 h) and the samples

are extracted in less solvent together with a different internal standard (vitamin E acetate). The filter used for the

extract clarification has a lower surface area and allows for

a more efficient recovery of the sample elute.

The column phase changed from C18 to C8 with a

length decreasing from 250–150 mm. The particle size decreased from 5 μm to 3.5 μm, thus inducing a better peak

resolution. The change of mobile phase results in a very

regular baseline not requiring a blank subtraction before

the peak quantification.

The adoption of the VHT method resulted in an increase of method stability and repeatability, and shortened

the analysis time.

7.2 EXTRACTION

The SeaHARRE-4 samples were received on 24 January

2007 and were stored at −80◦C until they were analyzed

(15–19 October 2007). The routine extraction procedure

used for 47 mm GF/F filters was adapted, in terms of extraction volume used, to the 25 mm GF/F delivered for the

SeaHARRE-4 exercise. All pipettes used in the extraction

were gravimetrically calibrated using the same solvent used

in the extraction procedure, as well as a precision balance

(A200S, Sartorius Analytic).

The sample extraction procedure consisted of the following steps:

1. To start, 2.5 mL of a 250 mg mL−1 concentration of

vitamin E acetate (Fluka) dissolved in 100% acetone

(HPLC grade, Merck) were put, using a calibrated pipette (Dispensette 0–10 mL Brandt), into a 10 mL polypropylene plastic tube (Falcon) of 14 mL. Then, 100 μL

of bidistilled water, produced using a Milli-Q system

manufactured by Millipore (Billerica, Massachusetts),

52
Hooker et al.

were added using a calibrated pipette (Eppendorf). Accounting for the water retained on the 25 mm filter

(Wright et al. 1991), the samples were extracted in a

86% acetone solution. The plastic tubes were placed

for 30 min at −20◦C.

2. The samples were cut into small pieces within the tubes.

Each tube, after the samples were added, was capped

and made airtight with parafilm, and soaked at −20◦C

for 1 h. The content of the tubes was disrupted by sonication using a Sonicator SonoPlus model GM2070 manufactured by Bandelin electronic (Berlin, Germany).

The sonication lasted 90 s with the tube immersed in

ice (approximately 0◦C) in order to avoid the sample warming. The power was set at 50% (approximately 35W), the pulsed cycle was set to 5 (at approximately 0.5 pulse s−1), the time was 1 min, and the

probe immersion was 10–15 mm. The sonicator probe

was cleaned with wipes and acetone after each sample.

After sonication, the tubes were capped and closed with

parafilm. The samples were then soaked at −20◦C for

4 h.

3. The samples were clarified by transferring the contents

of the tubes into a plastic syringe (Plastibrand), connected to a Millex-FH filter, 0.45 μL (Millipore). The

elute was collected in 4 mL amber vials. The 4 mL

amber vials were mixed and an amount of approximately 1.5 mL was transferred by glass pipette into

HPLC 2 mL amber vials. Mixing was accomplished

using a Vortex Reax 2000 manufactured by Heidolph

Brinkmann, LLC (Elk Grove Village, Illinois).

Finally, the sample extracts contained in the HPLC vials

were transferred to the prechilled HPLC autosampler for

HPLC analysis.

7.3 HPLC ANALYSIS

The HPLC system used for the analysis is an HPLC

1100 series Agilent Technologies running ChemStation software (B.01.03). The HPLC system is assembled with a microdegasser, a quaternary pump, a temperature-controlled

autosampler compartment (set at 4◦C), a programmable

autoinjector (900 μL syringe and 900 μL injection loop), a

temperature-controlled column oven compartment (set at

60◦C), and a DAD.

The samples were maintained at 4◦C in the autosampler in 2 mL amber vials with rubber caps, waiting for

analysis. Each sample was mixed in the injector loop,

alternated with the buffer, following the sequence in Table 30; the final amount injected onto the column was

375 μL. The column was a Zorbax Eclipse XDB-C8, which

has a 3.5 μm particle size, 150 mm length, and a diameter

of 4.6 mm, and is manufactured by Agilent Technologies

(Santa Clara, California). No precolumn was used.

Table 30. The JRC HPLC injector program. The

buffer solution is 90:10 (vol.) of 28 mM TbAA and

methanol, respectively. The Metering Device Speed

(MDS) is in units of microliters per minute, and the

needles were washed in 90% acetone.

Step Injector Action MDS

1 Draw 150 μL from buffer 500

2 Draw 75 μL from sample 130

3 Needle rinse (Acetone 90%)

4 Draw 75 μL from buffer 130

5 Draw 75 μL from sample 130

6 Needle rinse (Acetone 90%)

7 Draw 150 μL from buffer 500

8 Inject loop contents onto column

The gradient adopted is the three solvents gradient

adopted by Van Heukelem and Thomas in SeaHARRE-3.

Solvent A was a solution 70:30 volume of methanol (HPLC

grade, Merck) and 28 mM TbAA (pH 6.5). The 28 mM

solution was obtained by diluting 0.4 M TbAA hydroxide

tritant (HPLC reagent, J.T. Baker) with bidistilled water

(Milli-Q system, Millipore). The pH was adjusted to 6.5

by adding acetic acid.

Solvent A was filtered (mild vacuum) through a 0.2

filter of nitrocellulose (GNWP Millipore) and stocked in

5 L amber bottles waiting for the analysis: Solvent A was

not stocked longer than two weeks in order to avoid algal

growth. Solvent B was methanol (HPLC grade, Merck),

and Solvent C is acetone (HPLC grade, Merck). The

HPLC gradient is described in Table 31.

Table 31. The gradient system used with the JRC

method. Solvent A is 70:30 methanol:28 mM TbAA

(pH 6.5), solvent B is methanol, and solvent C is

acetone; the flow is in units of milliliters per minute.

Time A [%] B [%] C [%] Flow

0 95 5 0

22.00 5 95 0 1.1

24.50 5 95 0 1.1

24.75 5 65 30 1.3

25.75 5 65 30 1.3

25.85 5 65 30 1.3

26.10 95 5 0 1.1

29.10 95 5 0 1.1

The DAD measured absorbance at the 450, 665, and

222 nm wavelengths, with a bandwidth of 5 nm. Note that

the 222 nm wavelength was used only for quantifying the

internal standard.

7.4 CALIBRATION

When the new column was installed (June 2007), the

system was calibrated over a 22 pigment standards set

(DHI, Denmark; Fluka for chlorophylls a and b) including

53
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

all the pigments quantified. For each pigment, a multipoint calibration curve was determined based on nine dilutions. The dilutions were made from the standard using precalibrated syringes (Hamilton) while trying to minimize evaporation of the solvent. The syringes used for

preparing the dilution were gravimetrically calibrated using the same solvent used for the dilution, as well as a precision balance (A200S, Sartorius Analytic). The calibration

curve points were distributed between the expected LOD

and the standard concentration. After injection into the

HPLC system, the concentration of the standard and of

its dilutions were checked using a dual-beam monochrometer spectrophotometer (Lambda 12, PerkinElmer). The

content of each vial was transferred into a quartz cuvette,

and two scan spectra were collected over the range 350–

700 nm (2 nm bandwidth). The determination of the pigment concentration of each dilution was made considering

the specific absorption coefficient indicated by DHI for the

standard (Table 32) and the absorption measured at the

corresponding wavelength.

Table 32. Absorption coefficient (α) values from

DHI certificates as used with the JRC method for

the pigments listed as a function of wavelength (λ).

Pigment Solvent λ α

Chl c3 90% Acetone 453.0 374.00

Chl c1 + c2 90% Acetone 443.0 262.00

Chlide a 90% Acetone 664.0 127.00

Phide a 90% Acetone 667.0 74.20

Peri Ethanol 472.0 132.50

But Ethanol 446.0 160.00

Fuco Ethanol 449.0 160.00

Neo Ethanol 439.0 224.30

Pras Ethanol 454.0 160.00

Viola Ethanol 443.0 255.00

Hex Ethanol 447.0 160.00

Diad Ethanol 446.0 262.00

Allo Ethanol 453.0 262.00

Diato Ethanol 449.0 262.00

Zea Ethanol 450.0 254.00

Lut Ethanol 445.0 255.00

Chl b 90% Acetone 646.0 51.36

DVChl a 90% Acetone 664.3 87.76

MVChl a 90% Acetone 664.3 87.76

Phytin a 90% Acetone 667.0 51.20

α-Caro 100% Acetone 448.0 270.00

The HPLC results and the standard concentration were

corrected for pigment purity on the basis of the spectrophotometric data. The response factor for each pigment was

determined from a linear fit performed on this multipoint

calibration curve.

After the SeaHARRE-4 exercise, the HPLC instrument

was recalibrated using the monovinyl chlorophylls a and b

standards from DHI. The SeaHARRE-4 samples were reanalyzed after this second calibration. On average, the

concentration of monovinyl chlorophyll a in the requantified samples was 14% lower than the value obtained with

the Fluka standard, whereas the monovinyl chlorophyll b

was 13% higher than the value obtained with the Fluka

standard.

7.5 QUALITY CONTROL

Some quality control procedures were standardized for

each sequence of analysis.

1. At the beginning of each sequence, a solution of

1 mg L−1 of chlorophyll a (Fluka) was analyzed;

2. An injection of a mix standard was performed every 10 analyses to check the retention time and the

analysis reproducibility;

3. After the first injection of the mix standard, an internal standard was injected for checking the carryover;

4. The first sample injected at the beginning of the

sequence was injected at the end to check for any

degradation or variation in quantification.

All the data relative to the quality control, together with

the data relative to the noise control for each sequence,

were statistically recorded.

7.6 LOD AND LOQ

The LOD and LOQ were experimentally determined by

creating a dilution series for each analyzed pigment with

known concentrations corresponding to 3 and 10 times the

SNR. Subsequent to this system verification, during the

routine analysis, the LOD was set as four times the SNR

relative to the sequence. Because the SNR is expected to

change with the instrument condition, the SNR is calculated separately for each sequence and is determined by the

average of the SNR sampled at different time intervals after the first injection of the internal standard. Regarding

the SeaHARRE-4 sequences, the effective LOD was varied from 0.0003–0.0028 mg m−3 for the pigment quantified

at 450 nm, and from 0.0004–0.004 mg m−3 for the pigment

quantified at 665 nm.

7.7 DATA PRODUCTS

The chromatographic information (peak area, peak

height, retention time, and compound amount) relative to

every sample was exported from the ChemStation Software (Agilent) and transferred into an Excel spreadsheet.

Pigment concentrations were calculated as:

CPi = Vx

Vf

Aˆc

Aˆs

AˆPi

Vc

RPi , (40)

54
Hooker et al.

where AˆPi and RPi are the peak area and the response

factor of pigment Pi, respectively; Vx is the extraction volume; Vf is the volume of filtered sample; Vc is the amount

of sample injected onto the column; Ac is the peak area of

the internal standard in the extraction solvent; and As is

the peak area of the internal standard in the sample.

7.8 CONCLUSIONS

Since the SeaHARRE-3 activity, the JRC changed the

HPLC method that was being used and adopted the Van

Heukelem and Thomas (2009) method. This allowed the

separation and the quantification of a larger number of

taxonomically relevant pigments than the previously used

Wright et al. (1991) method. In particular, the new method

permitted the separation of the monovinyl and divinyl

forms of chlorophyll a, plus lutein and zeaxanthin. During SeaHARRE-4, the effective LOD varied from 0.0003–

0.0028 mg m−3 for pigments quantified at 450 nm, and from

0.0004–0.004 mg m−3 for pigments quantified at 665 nm.

Acknowledgments: Laurie Van Heukelem, Crystal

Thomas, Louise Schl ̈uter, and Jos ́ephine Ras are greatly

acknowledged for their support and advice during the set

up of the new method.

55
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 8

The LOV Method

Josephine Ras  ́

Herve Claustre  ́

LOV Observatoire Oc ́eanologique de Villefranche

Villefranche-sur-Mer, France

Abstract

The LOV method, derived from the technique described by Van Heukelem and Thomas (2001), applies a

sensitive reversed-phase HPLC technique for the determination of chloropigments and carotenoids within 28 min.

The different pigments, extracted in methanol, are detected by diode array detector (DAD), which allows for

automatic identification to be carried out on the basis of absorption spectra. Optical densities are monitored at

450 nm (chloropigments and carotenoids), 667 nm (chlorophyll a and derived pigments), 770 nm (bacteriochlorophyll a) and 222 nm (vitamin E acetate internal standard). The method provides good resolution between most

pigments, but uncertainties may arise because of the partial separation of chlorophyll b and divinyl chlorophyll b,

for the resolution of chlorophyll c pigments, and for the separation of α- and β-carotenes. It has proven to be

efficient over a wide range of trophic conditions, from eutrophic upwelling waters, to the hyperoligotrophic South

Pacific Subtropical Gyre. Short-term and long-term quality control is monitored regularly to ensure state-ofthe-art analyses. The injection precision of the method is estimated at 0.3%, and the limits of detection for

most pigments are low (0.019 ng inj−1 for chlorophyll a, and 0.033 ng inj−1 for carotenoids).

8.1 INTRODUCTION

The present method applied at the LOV is derived

from the method described by Van Heukelem and Thomas

(2001), with modifications aimed at increasing the sensitivity. It is a reversed-phase HPLC technique (C8 column),

based on a binary gradient and allows for the determination of most chloropigments (including degradation products) and carotenoids, which are extracted in 100% methanol and analyzed within 28 min. Detection is carried out

at four wavelengths:

450 nm for carotenoids and chlorophylls b and c;

667 nm for chlorophyll a and derived products;

770 nm for bacteriochlorophyll a, and

222 nm for the internal standard (vitamin E acetate).

A very good resolution is achieved for most pigments

(Rs < 1.5), although only partial resolution (Rs < 1) can

be obtained for chlorophyll b and divinyl chlorophyll b and

chlorophyll c2, chlorophyll c1, and MgDVP. Coeluting pairs

include chlorophyllide a and chlorophyll c1 (but they are

quantified at different wavelengths), as well as βε-carotene

and ββ-carotene. Pigment identification is based both on

absorption spectra and retention time.

8.2 EXTRACTION

The SeaHARRE-4 in situ samples (stored and transported in liquid nitrogen) were stored at −80◦C until analysis. The filters were extracted and analyzed between the

25 June and 2 July 2007.

The extraction process involved the following steps:

1. The 25 mm GF/F filter was placed into a 10 mL

disposable Falcon tube.

2. A 3 mL volume of 100% methanol, including an internal standard (vitamin E acetate, Sigma-Aldrich),

was added to each tube using an Eppendorf pipette,

while making sure that the filter was completely

covered. The tube was closed with an airtight cap.

3. The samples were placed in a −20◦C freezer for a

minimum of 30 min.

4. The filters were then disrupted using an ultrasonic

probe (Bandelin Sonopuls HD2200† for 10 s maximum. The probe was rinsed with methanol and

then wiped between each sample. In order to preserve the pigments from heating due to ultrasounds,

the tubes were placed in an ice-filled beaker during

sonication.

† Bandelin Electronic (Berlin, Germany).

56
Hooker et al.

5. The tubes were returned to the freezer for another

30 min minimum.

6. The samples were clarified by vacuum filtration

through GF/F (0.7 μm particle retention size,

25 mm diameter) filters using a Millipore‡ filtration unit. A glass tube (cleaned with methanol and

wiped between each sample) was used to press the

sample slurry. The filtrate was collected in 10 mL

Falcon tubes, and closed with airtight caps.

7. Clarified extracts were stored at −20◦C until HPLC

analysis (within 24 h).

8.3 HPLC ANALYSIS

Pigment analyses were carried out on a complete Agilent Technologies 1100 series HPLC system, which is made

up of the following components:

• Degasser;

• Binary pump;

• Automated sampler, including Peltier temperature

control (set at 4◦C) and a programmable autoinjector with sample preparation prior to injection;

• programmable column oven compartment;

• DAD; and

• ChemStation for LC (A.09.03).

The sample extracts and standards were transferred

into 2 mL glass vials using disposable glass Pasteur pipettes. The vials were then placed in the autosampler

at 4◦C for less than 24 h. Sample preparation (mixture

between buffer (28 mM aqueous TbAA) and sample on a

1:1 basis) was carried out in the 500 μL loop just before

injection, with alternating volumes of buffer and sample

in order to favor mixing in the loop. The total injection volume was 250 μL. Although this injection mixture

is optimized for methanolic extracts, standard solutions in

ethanol or acetone, which are used for calibration, do not

present the peak fronting problems that were encountered

during SeaHARRE-2.

In order to increase sensitivity, the modifications to

the Van Heukelem and Thomas (2001) method included

injection onto a narrow diameter, “solvent saving,” Zorbax Eclipse XDB-C8 column (3×150 mm, 3.5 μm), and a

0.55 μL min−1 flow rate. The fact that the pigments were

in methanol also allowed for a larger injection volume. The

column temperature was maintained at 60◦C.

Separation was based on a linear gradient between a

70:30 methanol-to-TbAA 28 mM mixture and a 100%

methanol solution (solvent A and B respectively), ranging

from 10–95% B in 22 min, followed by an isocratic hold at

95% B for 5 min more. At the end of the run, the mobile

phase returned to initial conditions (10% B) for a column

equilibration time of 5 min (Table 33).

‡ Millipore (Billerica, Massachusetts).

Table 33. The gradient used for the LOV method.

The time is in minutes, and the percentages of solvents A and B are given in the last two columns.

Step Time A [%] B [%]

Start 0 90 10

2 22 5 95

3 27 5 95

4 28 90 10

End 33 90 10

Detection was carried out at three different wavelengths

(10 nm bandwidths): 450 nm for all carotenoids, chlorophylls c and b; 667 nm for divinyl chlorophyll a, chlorophyll a, and associated allomers and epimers, as well as

chlorophyllide a and phaeopigments; and 770 nm for bacteriochlorophyll a. The internal standard was detected at

222 nm where there is no interference from phytoplankton pigments. For all signals, a reference at 850 nm was

applied to compensate for fluctuations caused by baseline

absorbance.

The offline version of the ChemStation software was

used for verification and eventual correction of the peak

integrations in each chromatogram. Automatic spectral

identification was also applied and then checked; only then

would the individual pigment concentrations be calculated

using a Visual Basic program under Excel.

8.4 CALIBRATION

A calibration was performed in July 2007, shortly after

the analysis of the SeaHARRE-4 samples. The concentrations for nine pigment standards (Peri, But, Fuco, Hex,

Allo, Zea, Pras, chlorophyll a, and bacteriochlorophyll a)

provided by DHI International Agency for 14C determination and Sigma-Aldrich, were determined by spectrophotometry using a PerkinElmer Lambda 19 dual-beam spectrophotometer (2 nm slit, 400–800 nm spectral range, with

a correction at 700 nm). The multipoint calibration curves

were composed of 4–10 points, and the corresponding response factors at 440, 667, and 770 nm were determined by

HPLC analysis of each standard solution.

The response factors for divinyl chlorophyll a and divinyl chlorophyll b were computed from the following:

Knowing the specific absorption coefficients of chlorophyll a (or chlorophyll b);

Accounting for the absorption of chlorophyll a and

divinyl chlorophyll a (or chlorophyll b and divinyl

chlorophyll b) at 667 nm when the spectra are both

normalized at their red maxima; and

Considering that both pigments have the same molar absorption coefficient at this red maximum.

The same process was used for determining the Chlide a

absorption coefficient relative to chlorophyll a. For the

remaining pigments, their specific absorption coefficients

57
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Table 34. The α values (in liters per gram per centimeter), associated with their respective wavelengths (λ,

in nanometers), used in the LOV method for a variety of pigments that are listed in the same order as their

retention times (tR).

Pigment Solvent λ α tR [min] Reference

Chl c3 90% Acetone 630.6 42.60 4.33 As for Chl c2

Chl c2 90% Acetone 630.6 42.60 5.83 DHI

Mg DVP 90% Acetone 630.6 42.60 5.86 As for Chl c2

Chl c1 90% Acetone 630.6 42.60 5.90 DHI

Chlide a 90% Acetone 664.0 127.00 5.90 Jeffrey et al. 1997

Phide a 90% Acetone 667.0 74.20 7.30 Jeffrey et al. 1997

Peri 100% Ethanol 472.0 132.50 8.97 DHI

But 100% Ethanol 446.0 160.00 11.91 DHI

Fuco 100% Ethanol 449.0 160.00 12.16 DHI

Neo 100% Ethanol 437.0 224.30 12.86 DHI

Pras 100% Ethanol 454.0 160.00 13.10 DHI

Viola 100% Ethanol 441.0 255.00 13.49 DHI

Hex 100% Ethanol 447.0 160.00 13.75 DHI

Diad 100% Ethanol 446.0 262.00 14.80 DHI

Allo 100% Ethanol 453.0 262.00 16.30 DHI

Diato 100% Ethanol 452.0 262.00 16.80 DHI

Zea 100% Ethanol 450.0 254.00 17.34 DHI

Lut Diethyl Ether 445.0 248.00 17.53 Jeffrey et al. 1997

BChl a 100% Acetone 770.0 54.67 21.60 Oelze 1985

DVChl b 90% Acetone 646.8 51.47 21.61 Derived from Chl b

Chl b 90% Acetone 646.8 51.36 21.72 DHI

DVChl a 90% Acetone 664.3 87.87 23.49 Derived from Chl a

Chl a 90% Acetone 664.3 87.67 23.68 DHI

Phytin a 90% Acetone 667.0 51.20 25.22 Jeffrey et al. 1997

βε-Car 100% Ethanol 453.0 262.00 26.32 As for ββ-Car.

ββ-Car 100% Ethanol 453.0 262.00 26.38 DHI

were either derived from previous calibrations or from the

literature (Jeffrey et al. 1997a). The absorption coefficients

for the LOV standard pigments are listed in Table 34.

Because βε-Car and ββ-Car coelute, the peak was first

identified spectrally. The spectral shape, therefore, pointed

to either one dominant pigment or the other and it was

quantified as such.

8.5 VALIDATION

Short-term quality control (during a sequence run) was

monitored using the methanol-plus-internal standard solution, which was injected twice at the beginning of the sequence and once after 10 sample injections. This was done

to verify retention time reproducibility, peak area precision

(should be less than 1%), and instrument stability during

the analytical sequence. The first two injections of the

sequence, however, were discarded because they generally

tended to lack reproducibility. For troubleshooting purposes, the pressure signal was also monitored during the

analyses.

The identification of individual pigments was manually

checked by retention time comparison and observation of

the absorption spectra using the ChemStation spectral library. This pigment library comprises the retention times

and spectral information of different pigments obtained

from the analysis of standard solutions or identified phytoplankton cultures.

Long-term quality control is carried out using a mixed

pigment standard supplied by DHI. This standard is regularly injected, at least in triplicate, to monitor the quality

of the column and of the instrument performance. This is

represented by a number of parameters, including a) the

initial backpressure, b) the noise level at 450 and 667 nm,

c) the injection precision of chlorophyll a and fucoxanthin,

d) the accuracy of these pigments, e) their plate numbers,

peak widths, and retention times, and f) the resolution for

two critical pairs (DVChl a–Chl a and But–Fuco). Signs

of deterioration of the column can, therefore, be rapidly

detected. Generally, a column is changed every 2,000 samples, although they have shown to last even longer.

The calibration of the volumetric measuring devices

(pipettes, syringes, etc.) is carried out annually. These

data are used to provide the performance metrics that

were determined during the previous SeaHARRE-2 exercise (Table 42 in Hooker et al. 2005). In this way, the

58
Hooker et al.

objective is to evaluate and maintain the state-of-the-art

level of analysis at the LOV.

If a technical problem should prevent the analysis of already extracted samples within the 24 h limit, the extracts

are stored under nitrogen gas and placed in a −80◦C freezer

until routine analysis is re-established.

8.6 DATA PRODUCTS

The ChemStation for LC program produces a spreadsheet file for each sample comprising the pigment identification, retention times, peak areas, peak heights, peak

widths, and other chromatographic information. This file

is used in a Visual Basic program to extract the peak

areas and names, and then to calculate the internal standard corrected concentrations, C (in milligrams per cubic

meter) of each pigment Pi, as in the following equation:

CPi = Aˆ

Pi

Vf

RPi , (41)

where Aˆ

Pi is the corrected peak area (in mAU), RPi is

the pigment response factor [mg (mAU)−1] and Vf is the

volume of water filtered (in cubic meters). The Aˆ

Pi term

is computed as:

Aˆ

Pi = Aˆc1

Aˆs1

AˆPi , (42)

where AˆPi is the uncorrected peak area (mAU), Aˆc1 is the

reference area (in mAU) of the internal standard (established as the average of internal injections over a single

day) and Aˆs1 is the area of the internal standard in the

sample.

8.7 CONCLUSIONS

During this exercise, the LOV method has proven to be

well adapted to the high chlorophyll, particle-rich, coastal

samples. Generally, a very good resolution was obtained

for most pigments, although uncertainties may arise for the

resolution of chlorophyll c pigments or βε-Car and ββ-Car,

which tend to coelute. Problems did occur because of the

presence of many unidentified small peaks that sometimes

influenced integration, for example, neoxanthin. This also

pointed to a lack of consistency that existed in reporting

or not reporting the very small peaks. The limits of detection are estimated to be 0.019 ng inj−1 for chlorophyll a and

0.033 ng inj−1 for carotenoids. Effective LOD is not mentioned this time because of the high variability in filtration

volumes for these samples.

59
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 9

The DalU Method

Claire Normandeau, John Cullen, and Markus Kienast

Dalhousie University

Halifax, Canada

Abstract

The HPLC pigment technique used at Dalhousie University follows the method developed by Wright et al.

(1991). It is a reversed-phase HPLC procedure (C18 column), based on a tertiary gradient and includes a cooled

autosampler, and photodiode array and fluorescence detectors. Samples are disrupted with a sonic probe in

100% methanol including an internal standard (vitamin E acetate). The method is validated with the use of

internal and external standards. It does not allow for the separation of divinyl chlorophylls a and b from their

respective monovinyl forms. In addition, chlorophyll c1 and chlorophyll c2 are not separated, and neither is

lutein from zeaxanthin; however, it offers good separation of a variety of pigments in a relatively short period

of time (29 min).

9.1 INTRODUCTION

The Dalhousie University protocol follows the method

detailed in Wright et al. (1991). It is a reversed-phase

HPLC procedure using a C18 column), which is based

on a tertiary gradient. Chlorophyll c1 and chlorophyll c2

are not separated, and neither is lutein from zeaxanthin.

Chlorophyllide a coelutes with chlorophyll c2, but the identification and

quantification can be done on different detectors; therefore, the interference between the two pigments is avoided.

It does not allow the separation of divinyl chlorophylls a

and b from monovinyl chlorophylls a and b, however, this

does not interfere with the routine analysis conducted at

Dalhousie University because most phytoplankton samples analyzed come from temperate coastal waters where

the producer of divinyl chlorophylls, i.e., Prochlorococcus,

is not abundant. Prochlorococcus has not been found in

the well-studied Nova Scotian inlet, Bedford Basin (Li and

Dickie 2001).

9.2 EXTRACTION

The SeaHARRE-4 samples were received on 16 January

2007, stored immediately in liquid nitrogen, and analysis

was started on 30 March 2007. All procedures were carried out under dim light and samples were kept on ice.

Only 12 samples per batch were extracted at a time, which

minimized the risk for pigment degradation while samples

sat in the autosampler. Filters were taken out of liquid

nitrogen, cut in to three pieces and put in a 4 mL amber

glass vial; 2 mL of extraction solvent was added to the vials

with a gravimetrically calibrated automatic pipette. This

solvent consisted of 100% methanol with approximately

0.125 mg L−1 vitamin E acetate internal standard. After

tightly capping the vials, the samples were stored for 2 h

in a −20◦C freezer. After this time period, samples were

transferred into a 10 mL BD syringe, the tip of which was

closed with Parafilm before sonicating them on pulse mode

for 20 s with a sonicator probe. Samples were vortexed for

5 s and transferred into a 2.5 mL Eppendorf centrifuge tube

and centrifuged at 13,000 rpm for 3 min. The supernatant

was transferred into a 2 mL autosampler vial and stored at

−20◦ until all samples were ready to be analyzed.

9.3 HPLC ANALYSIS

The Agilent 1100 series HPLC system consisted of a

cooled autosampler (4◦C), quaternary pump, and photodiode array and fluorescence detectors. Immediately prior

to injection, 100 μL of sample was mixed three times with

40 μL of buffer solution within the 500 μL sample loop.

The buffer solution consisted of 0.5 M ammonium acetate

(pH 7.2). A total volume of 140 μL was injected in the

HPLC system. Pigments were separated with a Zorbax

Eclipse XDB-C18 150 mm×4.6 mm column with a 5 μm

particle size (Agilent Technologies). The column temperature was not controlled by a thermostat, and pigments

were separated at ambient temperature. The flow rate

was 1 mL min−1 and the gradient elution program is given

in Table 35.

60
Hooker et al.

Table 35. The gradient elution program for the

DalU method (Wright et al. 1991). The time is in

minutes, and the percentages of solvents A, B, and

C are given in the last three columns where solvent

A is 80:20 100% methanol:0.5 M ammonium acetate

(pH 7.2); solvent B is 90:10 100% acetonitrile:MilliQ water; and solvent C is 100% ethyl acetate.

Time [min] A [%] B [%] C [%]

0 100 0 0

4 0 100 0

18 0 20 80

21 0 100 0

24 100 0 0

29 100 0 0

Peak integration was initially performed by Agilent

ChemStation software, and all peaks were manually identified by retention time and spectra signature comparison

with known pigment standards. Absorption peaks of chlorophyll a and phaeopigments were detected at 436 nm, and

carotenoids were detected at 450 nm.

9.4 CALIBRATION

All standards, except for chlorophyll a, were provided

by DHI. Concentration of the chlorophyll a standard

(Sigma-Aldrich) stock solution was determined using a

Cary 3 UV/Vis dualbeam spectrophotometer with a 2 nm

bandwidth. The absorption spectrum was recorded between 300–800 nm. The chlorophyll a concentration was

calculated using a specific absorption coefficient of 79.95 L

g−1cm−1 at 665.2 nm for a solution of 100% methanol

(Porra et al. 1989). Any absorption measured at 750 nm

was subtracted from the absorption measured at 665.2 nm.

Concentrations provided by DHI for all other stock standard pigment solutions were used to calculate concentrations for the 4–6 points dilution series. Dilutions were prepared with gravimetrically calibrated automatic pipettes

and Hamilton glass syringes.

More dilutions at low concentrations for chlorophyll a

and fucoxanthin permitted calculation of the relative limits

of detection (LOD) and quantification (LOQ) for all pigments (Hooker et al. 2005). Signal-to-noise ratios (SNRs)

of 3 and 10 were used for the LOD and LOQ, respectively.

The detection limit for most pigments ranged from 0.5–

1.1 μg L−1 per injection, and 1.3–1.9 μg L−1 for the LOQ.

All calibration curves were linear regressions of area versus concentrations forced through zero. Their correlation

coefficients (r2) were always better than 0.99 and generally, absolute percent residuals were no more than 2% as

recommended by Hooker et al. (2005).

9.5 VALIDATION

At the beginning of an HPLC sequence run, four injections preceded the sample set. The first injection was

of 100% methanol. This first chromatogram was discarded

and served as the instrument “warm-up.” Next, a chlorophyll a standard solution was used to verify the stability in

the response factor of this pigment. Then, a mixed standard solution (that was provided by DHI) was injected to

ensure good retention time and pigment separation. Finally, the vitamin E acetate internal standard was used

in the quantification equation. After the 12 samples were

injected, the internal standard, mixed pigment standard,

and chlorophyll a standard were reinjected to ensure that

no degradation or retention time shift occurred during the

sequence.

9.6 DATA PRODUCTS

The concentration (CPi in micrograms per liter) of each

pigment in the sample was determined using the following

equation:

CPi = Vx

Vf

Aˆc

Aˆs

AˆPi

FPi

, (43)

where the inverse response factor FPi is the slope obtained

by plotting the peak area with the concentrations of a specific pigment standard injected; AˆPi is the peak area; Vx

is the extraction volume (in milliliters); Vf is the volume

of sample filtered (in milliliters); Aˆc is the peak area of

the internal standard when it is injected onto the HPLC

column; and Aˆs is the peak area of the internal standard

in the sample.

Standard deviation and unbiased percent differences

were calculated on all replicates and were used as quality control measures. High deviants were revisited to ensure that no errors in pigment identification, integration,

or quantification were present. Concentration values less

than the LOQ were not reported and were replaced by the

respective LOQ values for the pigment.

In the SeaHARRE-4 samples, partial coelution was frequent between 19

-hexanoloxyfucoxanthin, prasinoxanthin,

and violaxanthin, especially when peak areas were large.

In the samples routinely processed at Dalhousie University, prasinoxanthin is generally absent, or is in very low

concentrations; thus, coelution with this group of pigments

is not a problem.

9.7 CONCLUSIONS

This SeaHARRE exercise demonstrated that the

reversed-phase HPLC method used by Dalhousie University is a useful method for routine analysis of pigments as

long as the separation of divinyl chlorophyll a and b from

monovinyl chlorophylls a and b, and lutein from zeaxanthin

is not critical to the research objectives. Indeed, it provides good resolution of most marine pigments, as well as

consistent and repeatable pigment compositions and concentrations.

61
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Chapter 10

The SDSU (CHORS) Method

Jason Perl

SDSU Center for Hydro-Optics and Remote Sensing

San Diego, California

Abstract

The CHORS method was developed to provide HPLC phytoplankton pigment analyses for the NASA Sensor

Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program, following

the protocols presented in the Ocean Optics Protocols for Satellite Ocean Color Sensor Validation (Bidigare et

al. 2002). The method (Wright et al. 1991) was designed to support a wide range of pigment concentrations

from waters sampled throughout the world ocean, but it does not chromatographically separate the divinyl

chlorophylls a and b from their corresponding monovinyl forms. The Latasa et al. (1996) dichromatic equations

were used to spectrally resolve divinyl chlorophyll a from monovinyl chlorophyll a. The method uses a reversedphase C18 column, with a tertiary solvent gradient; a temperature-controlled autosampler provides continuous

sample injection to maintain a quota of analyzing 4,000 samples per year. System calibration is routinely

monitored and recorded each month to ensure repeatability and consistency of data products.

10.1 INTRODUCTION

The current focus of HPLC analysis at CHORS is to

characterize phytoplankton pigments in the water column

collected as part of SIMBIOS field campaigns. The method

follows the HPLC protocols established in the Ocean Optics Protocols for Satellite Ocean Color Sensor Validation

(Bidigare et al. 2002). The chromatographic analyses do

not separate monovinyl and divinyl chlorophyll a; instead,

these pigments are quantified using dichromatic equations

at 436 and 450 nm.

Because of the large number of samples processed, approximately 4,000 or more per year, the CHORS HPLC

laboratory procedures have been streamlined to accommodate the variety and quantity of water samples collected by

the SIMBIOS research community. By using larger HPLC

solvent reservoirs, multiple sample tube racks, and running

the system 24 h a day, the CHORS laboratory can accommodate 500 samples a month, with the system running

continuously over a 3–4 week period.

10.2 EXTRACTION

The SeaHARRE-4 samples were stored in liquid nitrogen pending extraction and analysis upon receipt at

CHORS. The filters were extracted in 4.0 mL of 100% acetone using a Brinkmann Bottletop Dispenser (with a coefficient of variation of 0.321%). An internal pigment standard, trans-β-apo-8

-carotenal, was added to the acetone

extract prior to pipetting the 4.0 mL, to correct for any

extraction volume changes during sample processing.

After 24 h of extraction in a freezer (maintained at

−20◦C), the samples were sonicated for 10 s using an ultrasonic microprobe tip at a 60% duty cycle. The samples were then extracted for an additional 24 h (stored in a

freezer at −20◦C). Glass-fiber particles, generated during

filter sonication, were removed from the extract by centrifuging the samples at 5,100 rpm for 4 min and then subsequently filtering the extract using 0.2 μm PTFE in-line

filters.

10.3 HPLC ANALYSIS

The equipment used with the CHORS method is as

follows:

• ThermoQuest HPLC system with membrane degasser and P4000 quaternary pump;

• AS3000 temperature-controlled autosampler;

• UV6000 PDA detector (scanning 436 and 450 nm);

• FL3000 fluorescence detector; and

• System controller with ChromQuest (v3.0) software.

The HPLC gradient program was the same one specified in

the Ocean Optics Protocols for pigment analysis (Bidigare

et al. 2002). Pigments were separated on a reversed-phase,

Waters Spherisorb ODS-2 (5 μm) C18 column (250 mm long

with a 4.6 mm internal diameter), using a three-solvent

gradient system and a 1.0 mL min−1 flow rate (Table 36).

62
Hooker et al.

A ThermoQuest P4000 pump and an AS3000 Autosampler

(maintained at 4◦C) were used for processing all samples.

Each sample extract was mixed (605 mL:195 mL of extract

to water), and 100 mL of this mixture was injected onto

the HPLC column.

Table 36. The tertiary gradient elution system

used with the CHORS HPLC method. Solvent A

is 80:20 methanol:0.5 M ammonium acetate; solvent

B is 90:10 acetonitrile:water; and solvent C is ethyl

acetate.

Step Time A [%] B [%] C [%]

Start 0.0 100 0 0

2 2.0 0 100 0

3 2.6 0 90 10

4 13.6 0 65 35

5 20.0 0 31 69

6 22.0 0 100 0

End 25.0 100 0 0

The separation of the various pigments requires approximately 25 min with the pigment peaks being detected

by an absorption detector: a ThermoQuest UV6000 scanning DAD (190–800 nm at 1 nm resolution). Pigments were

monitored at 436 and 450 nm, with peak retention time or

spectrophotometric recognition used to assign peak identification. In addition, a ThermoQuest FL3000 scanning

fluorescence detector was used to detect the various chlorophyll degradation products, which occur at lower concentrations.

Although the absorption peaks for monovinyl and divinyl chlorophyll a coelute, each compound absorbs differently at 436 and 450 nm, so it was possible to correct for the

divinyl chlorophyll a contribution by monitoring changes in

the 450/436 ratio as a function of changes in the divinyl

percentage (Latasa et al. 1996).

Accuracy for each pigment compound was based on

the availability of pigment standards and the selection of

pigment-specific absorption coefficients. The standard fluorometric method of Hølm-Hansen et al. (1965) was used to

calculate chlorophyll and phaeopigment concentrations on

an aliquot (100 μL) of the pigment extract. These concentrations were also corrected for extraction volume changes

using the internal standard. The Ocean Optics Protocols

(Trees et al. 2003) for fluorometric chlorophyll a was also

followed.

10.4 CALIBRATION

The HPLC pigment calibration standards were purchased from Sigma-Aldrich and DHI. System calibrations

were performed to determine individual standard response

factors for each compound. Each pigment response factor

was determined using a multipoint calibration. The concentration of the standards were provided by DHI, or verified spectrophotometrically (for chlorophyll a and chlorophyll b) using published absorption coefficients (Table 37).

The coefficient of determination for the chlorophyll a calibration curve was r2 = 0.999. The coefficient of variation

for the internal standard average was about 3.8%.

Table 37. The α values used with the CHORS

method for a variety of pigments as a function of λ.

The units for α are liters per gram per centimeter,

and the units for λ are nanometers.

Pigment Solvent λ α

Chlide a 90% Acetone 664.0 127.00†

Chl c3 90% Acetone 452.9 346.00†

Chl c2 90% Acetone 630.9 40.40†

Peri 100% Ethanol 472.0 132.50†

But 100% Ethanol 446.0 160.00†

Fuco 100% Ethanol 449.0 160.00†

Neo 100% Ethanol 439.0 224.30†

Hex 100% Ethanol 447.0 160.00†

Pras 100% Ethanol 454.0 160.00†

Viola 100% Ethanol 443.0 255.00†

Diad 100% Ethanol 446.0 262.00†

Allo 100% Ethanol 453.0 262.00†

Diato 100% Ethanol 449.0 262.00†

Lut 100% Ethanol 445.0 255.00†

Zea 100% Ethanol 450.0 254.00†

Chl b 90% Acetone 646.6 51.36‡

MVChl a 90% Acetone 663.5 87.67‡

DVChl a 90% Acetone 664.3 87.67†

Phytin a 90% Acetone 667.0 51.20†

βε-Car 100% Acetone 448.0 270.00†

ββ-Car 100% Ethanol 453.0 262.00†

† DHI Water and Environment

‡ Jeffrey et al. (1997a)

10.5 VALIDATION

The integration of pigment peaks was performed using ChromQuest (v3.0) software, and manually checked

to ensure each peak was properly integrated. Retention

times and spectral signatures of the standards were used

to verify peak identification. Peak areas were quantified

using software-aided integration. Response factors generated during the system calibration were used for final

concentration calculations.

10.6 DATA PRODUCTS

Each sample data file included the integrated peak area,

which was used with the pigment response factors to compute pigment concentration:

CPi = Vm

Vf

Vc

Vs

Aˆc1

Aˆs1

AˆPi /FPi , (44)

where Vm is the volume of extract (solvent plus standard)

added (in milliliters); Vf is the volume of sea water filtered

63
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

(in liters); Vc is the volume of sample extract injected onto

the column; Vs is the volume of standard injected to determine the inverse response factor, FPi ; Aˆc1 is the average

peak area of 25 internal standard injections; Aˆs1 is the

peak area of the internal standard in the sample; and AˆPi

is the peak area of pigment Pi. For the CHORS method,

Vc = Vs, so (1001) can be simplified to:

CPi = Vm

Vf

Aˆc1

Aˆs1

AˆPi

FPi

. (45)

The following pigments are reported:

• Chlorophyllide a,

• Chlorophyll c3,

• Chlorophyll c2,

• Chlorophyll c1+c2,

• Peridinin,

• 19

-Butanoyloxyfucoxanthin,

• Fucoxanthin,

• 19

-Hexanoyloxyfucoxanthin,

• Prasinoxanthin,

• Violaxanthin,

• Diadinoxanthin,

• Alloxanthin,

• Diatoxanthin,

• Lutein,

• Zeaxanthin,

• Chlorophyll b,

• Chlorophyll a,

• βε-Carotene,

• ββ-Carotene,

• Monovinyl chlorophyll a,

• Divinyl chlorophyll a,

• Total chlorophyll a,

• Fluorometric chlorophyll, and

• Fluorometric phaeopigments.

Chlorophyll a is computed from the absorbance at 436 nm,

assuming no divinyl chlorophyll a is present with a single response factor. Total chlorophyll a is computed as

the sum of monovinyl chlorophyll a, divinyl chlorophyll a,

chlorophyllide a, chlorophyll a allomer, and chlorophyll a

epimer. Divinyl chlorophyll a is not chromatographically

separated; it is computed using the Latasa et al. (1996)

simultaneous equations.

10.7 CONCLUSIONS

The CHORS method provides consistent and repeatable HPLC and fluorometric pigment concentrations in

support of the SIMBIOS project, and accommodates the

high number of samples, and timely turnaround of final

data products. Overall, bulk pigment properties of the

community structure can be determined for a variety of

oceanographic water types.

64
Hooker et al.

Chapter 11

The USC Method

James L. Pinckney

University of South Carolina

Columbia, South Carolina

Abstract

The USC method was developed to provide a universal protocol that could be used to analyze freshwater,

estuarine, coastal, and ocean habitats, as well as sediment and microbial mat samples. The method employs

a unique combination of both monomeric and polymeric C18 columns combined with a variable flow binary

gradient. This column configuration was originally devised to enhance photopigment separations from sediment samples containing numerous (greater than 150) photopigment and pigment degradation products. The

combination of columns provides strong retention and high efficiency (monomeric columns) while selecting for

similar compounds with minor differences in molecular structure (polymeric columns). The variable flow binary

gradient allows baseline separation of most major pigments including lutein and zeaxanthin, and chlorophyll c3.

Chlorophylls c1 and c2 plus divinyl chlorophylls a and b are not completely separated. For HPLC analysis, filters are placed in disposable polypropylene microfuge tubes and lyophilized to remove all water from the filters.

The primary advantages of this method are long column life (greater than 2,000 injections), inexpensive and

non-hazardous solvents and reagents, no uncertainty regarding the water retained on the filter, and reliability

across a range of sample types.

11.1 INTRODUCTION

The HPLC method used at USC for photopigment separations is derived from the Van Heukelem et al. (1992 and

1994) and Pinckney et al. (1996) protocols. Two different

reversed-phase C18 columns are connected in series. A single monomeric guard column is followed by a monomeric

reversed-phase C18 column and a polymeric reversed-phase

C18 column. This column configuration was originally

devised to enhance photopigment separations from sediment samples containing numerous (greater than 150) photopigment and pigment degradation products. Monomeric

columns provide strong retention and high efficiency, while

polymeric columns select for similar compounds with minor differences in molecular structure (Van Heukelem et

al. 1992 and Jeffrey et al. 1997b).

In addition to providing for an increase in the number

of theoretical plates, the combination of both monomeric

and polymeric columns optimizes photopigment separations based on two different molecular properties (coarse

and fine structure). This method allows for the baseline

separation of most major pigments including lutein and

zeaxanthin, as well as chlorophyll c3. Chlorophylls c1 and

c2, however, are not completely separated. Divinyl chlorophylls a and b are not completely resolved, but occur

as “shoulders” on the monovinyl chlorophylls a and b and

can be visually identified in chromatograms.

11.2 EXTRACTION

The SeaHARRE-4 samples were immediately stored in

a −80◦C freezer upon receipt. For HPLC analysis, filters were placed in disposable polypropylene microfuge

tubes (2 mL) and lyophilized (−50◦C, 0.57 mbar, 12 h; Labconco FreeZone 2.5) to remove all water from the filters.

After lyophilization, filters were cut into six equal sections and placed in microfuge tubes. Samples were extracted in 90% acetone (600 μL), and stored at −20◦C

for 18–20 h. Each sample also received 50 μL of the synthetic carotenoid trans-β-apo-8

-carotenal (Sigma-Aldrich,

10810) in 90% acetone as an internal standard using a gastight syringe (Hamilton) and click dispenser (Hamilton,

PB600-1). After extraction, the extract was clarified using a 0.45 μm PTFE filter (Gelman Acrodisc). A known

volume of the extract (400 μL) was then dispensed into

amber glass autosampler vials (2.0 mL) and sealed with

PTFE-silicone caps.

11.3 HPLC ANALYSIS

The instrumentation was manufactured by Shimadzu

and was part of their Validation and Productivity (VP)

series. It consisted of a binary gradient pump (dual LC10-

AT and controller SCL-10A), temperature-controlled autosampler (SIL10-A) with a 500 μL injection loop, column

65
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

oven (CTO-10AS), and PDA (SPD-M10A with a 200–

800 nm range). For the PDA, spectra (380–700 nm) were

obtained at 2 s intervals for the duration of each run and

photopigment peaks were quantified at 440±4 nm.

Two different reversed-phase C18 columns were connected in series. A single monomeric guard column (Rainin

Microsorb, 0.46 × 1.5 cm, 3 μm packing) was followed by a

monomeric reversed-phase C18 column (Varian MicrosorbMV 100-3, 0.46 × 10 cm, 3 μm packing) and a polymeric

reversed-phase C18 column (Vydac 201TP54, 0.46×25 cm,

5 μm packing). The column oven maintained a constant

40◦C for the duration of the gradient.

A nonlinear binary gradient, which was adapted from

Van Heukelem et al. (1992), was used for pigment separations (Table 38). Solvent A consisted of 80% methanol

and 20% ammonium acetate (0.5 M adjusted to pH 7.2),

and solvent B was composed of 80% methanol and 20%

acetone (Table 38). Solvents were degassed with an in-line

degasser (Shimadzu DGU 14A). All solvents were HPLCgrade and chemicals were analytical grade.

Table 38. The gradient used with the USC method.

The time is in minutes, the flow rate is in milliliters

per minute, and the percentages of solvents A and

B are given in the last two columns.

Step Time Flow A [%] B [%]

Start 0 0.80 100 0

2 0.5 0.80 50 50

3 35 1.25 0 100

4 36 1.50 0 100

5 37 0.80 0 100

6 38 0.80 100 0

End 50 0.80 100 0

Just prior to the HPLC run, an ion-pairing (IP) solution (1 M ammonium acetate) was added to the vial in a

ratio of four parts extract to one part ammonium acetate.

Prior work has shown there is negligible pigment degradation within 12 h of adding the IP solution if the sample is

placed in a refrigerated autosampler (4.0◦C). The IP solution, however, should not be added to the sample if the

time until sample analysis is greater than 18 h.

11.4 CALIBRATION

Peaks were identified based on retention time and spectral matches with pigment spectra obtained from DHI standards (Table 39). Peak areas were quantified using Shimadzu SP1 v7.2.1 software. The PDA was calibrated using a multipoint calibration procedure for a range of injection volumes (25–300 μL) of pigment standards. Regressions were performed using known pigment concentration (y) versus integrated peak area (x), and were of the

form y = mx + b, where m is the slope and b is the yintercept.

Table 39. The α values used by the USC method

for a variety of pigments as a function of λ. The

units for α are liters per gram per centimeter and

the units for λ are nanometers. All solvents are at

a 100% purity unless indicated otherwise. Not all

of the pigments listed were identified and reported

for SeaHARRE-4.

Pigment Solvent λ α

ββ-Car Acetone 454 250.00

βε-Car Acetone 448 270.00

βψ-Car Pet Ether 459 318.00

εε-Car Pet Ether 440 290.00

ψψ-Car Acetone 474 344.60

Allo Acetone 454 250.00

Anth Ethanol 446 235.00

Asta Hexane 468 210.00

BChl a Ace./Meth. 771 59.40

But Acetone 445 147.00

Cantha Pet Ether 466 220.00

Chl a 90% Acetone 664 87.67

Chl b 90% Acetone 647 51.36

Chl c12 90% Acetone 631 42.60

Chl c3 90% Acetone 453 346.00

Chlide a 90% Acetone 664 127.00

Chlide b 90% Acetone 645 74.07

Croco Ethanol 443 250.00

Diadchr Acetone 428 250.00

Diad Methanol 445 225.00

Diato Acetone 452 210.00

Dino Acetone 442 210.00

DVChl a 90% Acetone 664 87.67

DVChl b 90% Acetone 647 51.36

Echin Pet Ether 458 215.80

Fuco Acetone 443 166.00

Gyro Ethanol 445 262.00

Hex Acetone 445 142.00

Lut Ethanol 445 255.00

MgDVP Methanol 623 58.90

Monado Diethyl Ether 446 250.00

Myxo Acetone 478 216.00

Neo Ethanol 438 227.00

P-457 Acetone 457 164.00

Peri Acetone 466 134.00

Phide a 90% Acetone 667 74.20

Phide b 90% Acetone 657 46.37

Phytin a 90% Acetone 667 51.20

Phytin b 90% Acetone 657 31.80

Pras Diethyl Ether 446 250.00

Pyrophytin Diethyl Ether 667 60.29

Siphx Acetone 445 250.00

Siphn Ethanol 462 192.00

Vauch Acetone 444 250.00

Viola Acetone 442 240.00

Zea Acetone 452 234.00

66
Hooker et al.

All regressions had a coefficient of determination of

r2 > 0.98. The slope of the fitted line was used as the

response factor for all pigment concentration calculations.

The concentrations of pigments for which standards were

unavailable were estimated using the ratio method outlined

in Jeffrey et al. (1997b).

11.5 VALIDATION

Carotenal blanks (trans-β-apo-8-carotenal in 90% acetone) were run after every 10 samples to verify peak time

reproducibility, peak area precision, and instrument performance during the sequence run. Peaks were identified

based on retention time and comparison of absorbance

spectra with a spectral library derived from pure pigment

standards (DHI). Long-term quality control was achieved

by analyzing pure standards for chlorophyll a and the DHI

mix at monthly intervals. Instrument performance was

measured and compared with previous measures to determine changes in performance metrics. Volumetric measuring devices were checked weekly.

11.6 DATA PRODUCTS

Pigment concentrations were calculated for each identifiable peak using the following equation:

CPi = RI

Vc

Vm

Vf

Aˆc

Aˆs

AˆPi RPi , (46)

where CPi is the pigment concentration in micrograms per

liter; AˆPi is the pigment peak area; RPi is the response

factor; Vc is the injection volume in microliters; Vm is the

total extract volume (volume of added acetone plus volume

of internal standard in milliliters); RI is the ratio of the

volume of ion-pairing (IP) solution plus Vm divided by Vm;

Vf is the volume of seawater filtered (in liters); Aˆc is the

average peak area for carotenal standards; and Aˆs is the

peak area of carotenal in the sample.

11.7 CONCLUSIONS

This method has been employed by USC for approximately 15 y to analyze a broad spectrum of sample types

from marine and freshwater habitats. The execution of the

method is straightforward and involves minimum manipulation of the samples and extracts, is relatively inexpensive,

and does not generate hazardous waste products. The primary weakness of the method is the inability to completely

separate chlorophylls c1 and c2, and divinyl chlorophylls a

and b.

67
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Acknowledgments

The SeaHARRE-4 activity was sponsored by the SeaWiFS and

MODIS Projects along with the individual institutes representing the 10 laboratories that participated. The expertise of the

DHI shipping office was instrumental in the successful delivery

of many sample sets, and the professional contributions of Birgit Gavilan were particularly helpful. The preparation of the

manuscript and its final level of completeness benefitted significantly from the technical editing expertise of Elaine Firestone,

whose attentiveness to detail, and her good cheer, are greatly

appreciated.

Appendices

A. The SeaHARRE-4 Science Team

B. The SCOR WG 78 Pigment Abbreviations

C. Commercial HPLC Manufacturers and Pigment Suppliers

Appendix A

The SeaHARRE-4 Science Team

The science team is presented alphabetically.

Merete Allerup

DHI Water and Environment

Agern All ́e 5

DK-2970 Hørsholm, DENMARK

Voice: 45–4–516–9558

Fax: 45–4–516–9292

Net: mea@dhigroup.com

Jean-Fran ̧cois Berthon

JRC/IES/GEM T.P. 272

I–21020 Ispra (VA) ITALY

Voice: 39–0–332–785–525

Fax: 39–0–332–789–034

Net: jean-francois.berthon@jrc.ec.europa.eu

Elisabetta Canuti

JRC/IES/GEM T.P. 272

I–21020 Ispra (VA) ITALY

Voice: 39–0–332–785–221

Fax: 39–0–332–789–034

Net: elisabetta.canuti@jrc.ec.europa.eu

Herv ́e Claustre

Laboratoire d’Oc ́eanographie de Villefranche

B.P. 08, 06238 Villefranche-sur-Mer, FRANCE

Voice: 33–4–93–76–3729

Fax: 33–4–93–76–3739

Net: claustre@obs-vlfr.fr

Lesley Clementson

CSIRO Marine Research

Castray Esplanade

Hobart, Tasmania, AUSTRALIA, 7000

Voice: 61–3–6232–5337

Fax: 61–3–6232–5000

Net: lesley.clementson@csiro.au

Stanford Hooker

NASA/GSFC/Code 614.8

Greenbelt, MD 20771

Voice: 301–286–9503

Fax: 301–286–0268

Net: stanford.b.hooker@nasa.gov

David Millie

USF/FMRI/FIO

100 Eighth Avenue SE

Saint Petersburg, FL 33701

Voice: 727–896–8626

Fax: 727–550–4222

Net: david.millie@myfwc.com

Claire Normandeau

Dalhousie University

Oceanography Department

1355 Oxford Street

Halifax, Nova Scotia, CANADA B3H 4J1

Voice: 902–494–6326

Fax: 902–494–3877

Net: c.normandeau@dal.ca

Jason Perl

SDSU/CHORS

6505 Alvardo Road, Suite 206

San Diego, CA 92120

Voice: 619–594–3868

Fax: 619–594–8670

Net: jperl@chors.sdsu.edu

James Pinckney

Univ. South Carolina

Dept. of Biological Sciences

Columbia, SC 29208

Voice: 803–777–7133

Fax: 803–777–4002

Net: pinckney@sc.edu

Jos ́ephine Ras

Laboratoire d’Oc ́eanographie de Villefranche

B.P. 08, 06238 Villefranche-sur-Mer, FRANCE

Voice: 33–4–93–76–3729

Fax: 33–4–93–76–3739

Net: jras@obs-vlfr.fr

Mary Russ

NASA/GSFC/Code 614.8

Greenbelt, MD 20771

Voice: 301–286–9503

Fax: 301–286–0268

Net: mary.e.russ@nasa.gov

Louise Schl ̈uter

DHI Water and Environment

Agern All ́e 5

DK-2970 Hørsholm, DENMARK

Voice: 45–4–516–9557

Fax: 45–4–516–9292

Net: lsc@dhigroup.com

Crystal Thomas

UMCES/Horn Point Laboratory

P.O. Box 775

Cambridge, MD 21613

Voice: 410–221–8291

Fax: 410–221–8490

Net: cthomas@umces.edu

Charles Trees

SDSU/CHORS

6505 Alvarado Road, Suite 206

San Diego, CA 92120

Voice: 619–594–2241

Fax: 619–594–8670

Net: ctrees@chors.sdsu.edu

68
Hooker et al.

Laurie Van Heukelem

UMCES/Horn Point Laboratory

P.O. Box 775

Cambridge, MD 21613

Voice: 410–221–8480

Fax: 410–221–8490

Net: laurievh@umces.edu

Appendix B

The SCOR WG 78 Pigment Abbreviations

The chlorophyll pigments used in this report and their SCOR

WG 78 abbreviations are presented alphabetically:

Chl a Chlorophyll a,

Chl aChlorophyll a epimer,

Chl b Chlorophyll b,

Chl b

Chlorophyll b epimer,

Chl c1 Chlorophyll c1,

Chl c2 Chlorophyll c2,

Chl c3 Chlorophyll c3,

Chlide a Chlorophyllide a,

DVChl a Divinyl chlorophyll a,

DVChl aDivinyl chlorophyll a epimer,

DVChl b Divinyl chlorophyll b,

DVChl b

Divinyl chlorophyll b epimer,

Phide Phaeophorbide a, and

Phytin a Phaeophytin a.

The carotenoid pigments and their SCOR WG 78 abbreviations are presented alphabetically (with their trivial names in

parentheses):

Allo Alloxanthin,

Anth Antheraxanthin,

Asta Astaxanthin,

But-fuco 19

-Butanoyloxyfucoxanthin,

Cantha Canthaxanthin,

Croco Crocoxanthin,

Diadchr Diadinochrome (Diadinochrome I and II),

Diadino Diadinoxanthin,

Diato Diatoxanthin,

Dino Dinoxanthin,

Fuco Fucoxanthin,

Hex-fuco 19

-Hexanoyloxyfucoxanthin,

Lut Lutein,

MgDVP Mg 2,4-divinyl phaeoporphyrin a5 monomethyl

ester,

Monado Monadoxanthin,

Myxo Myxoxanthophyll,

Neo Neoxanthin,

Perid Peridinin,

Pras Prasinoxanthin,

Viola Violaxanthin,

Zea Zeaxanthin,

ββ-Car ββ-Carotene (β-Carotene), and

βε-Car βε-Carotene (α-Carotene).

Appendix C

Commercial HPLC Manufacturers and Pigment Suppliers

The commercial HPLC manufacturers and pigment suppliers

discussed in this report are presented alphabetically.

Agilent Technologies, Inc.1

2850 Centreville Road

Wilmington, DE 19808

Voice: 800–227–9770

Fax: 800–519–6047

Net: http://www.agilent.com/chem

Branson Ultrasonics Corporation

41 Eagle Road

Danbury, CT 06810

Voice: 203–796–0400

Fax: 203–796–0320

Net: http://www.bransoncleaning.com

Carl Roth GmbH and Company

Schoemperlenstraße

1-5 D-76185 Karlsruhe

GERMANY

Voice: 49–800–569–9000

Fax: 49–721–560–6149

Net: http://www.carl-roth.de

DHI Water and Environment2

Agern All ́e 5,

DK–2970 Hørsholm

DENMARK

Voice: 45–45–16–9665

Fax: 45–45–16–9292

Net: c14@dhi.dk

Fluka Chemical Corporation3

1001 West St. Paul Avenue

Milwaukee, WI 53233

Voice: 414–273–3850

Fax: 414–273–4979

Net: flukausa@sial.com

Hewlett-Packard Company

3000 Hanover Street

Palo Alto, CA 94304–1185

Voice: 650–587–1501

Fax: 650–857–5518

Net: http://www.hp.com

Hitachi Instruments, Inc.

5100 Franklin Drive

Pleasanton, CA 94588-3355

Voice: 925–218–2800

Fax: 925–218–2900

Net: http://www.hitachi-hta.com

Scientific Resources, Inc.

P.O. Box 957297

Duluth, GA 30095–7297

Voice: 800–637–7948

Fax: 770–476–4571

1 Formerly the Hewlett-Packard Analytical Division.

2 Formerly the VKI Water Quality Institute.

3 Part of Sigma-Aldrich.

69
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Shimadzu Scientific Instruments

7102 Riverwood Drive

Columbia, MD 21046–1245

Phone Number: 800–477–1227

Fax Number: 410–381–1222

Sigma-Aldrich Company4

3050 Spruce Street

St. Louis, MO 63103

Voice: 314–771–5765

Fax: 314–771–5757

Net: sigma@sial.com

ThermoQuest5

355 River Oaks Parkway

San Jose, CA 95134–1991

Voice: 408–526–1100

Fax: 408–965–6810

Net: http://www.thermoquest.com

Glossary

APD Absolute Percent Difference

BIO Bedford Institute of Oceanography (Canada)

CHORS Center for Hydro-Optics and Remote Sensing

CSIRO Commonwealth Scientific and Industrial Research Organisation (Australia)

CTD Conductivity, Temperature, and Depth

CV Coefficient of Variation

DAD Diode Array Detector

DANACK Danish Accreditation and Metrology Fund

DalU Dalhousie University (Canada)

DHI Not an acronym, but the abbreviation for the

DHI Water and Environment Institute (Denmark).

DP (Total) Diagnostic Pigments

EtOAc Ethyl Acetate (alternate abbreviation)

FIO Florida Institute of Oceanography

GF/F Not an acronym, but a type of glass fiber filter.

GNWP Not an acronym, but a filter code.

GSFC Goddard Space Flight Center

HPL Horn Point Laboratory

HPLC High Performance Liquid Chromatography

JGOFS Joint Global Ocean Flux Study

JRC Joint Research Centre (Italy)

ID Internal Diameter

IP Ion-Pairing

ISO International Organization for Standardization

ISTD Internal Standard

LOD Limit of Detection

LOQ Limit of Quantitation

LOV Laboratoire d’Oc ́eanographie de Villefranche

(Oceanographic Laboratory of Villefranche,

France)

4 Formerly Sigma Chemical.

5 Formerly Thermo Separation Products.

MCM Marine and Coastal Management (South Africa)

MeCN Acetonitrile (alternate abbreviation)

MDS Metering Device Speed

MODIS Moderate Resolution Imaging Spectroradiometer

MPF Microplankton Proportion Factor

NASA National Aeronautics and Space Administration

NPF Nanoplankton Proportion Factor

NV Not Validated

PDA Photodiode Array

PML Plymouth Marine Laboratory (United Kingdom)

PPC Photoprotective Carotenoids

PPF Picoplankton Proportion Factor

PPig Primary Pigments

PSC Photosynthetic Carotenoids

PSP Photosynthetic Pigments

PTFE Polytetrafluoroethylene

QA Quality Assurance

QC Quality Control

RPD Relative Percent Difference

RF Response Factor

SCOR Scientific Committee on Oceanographic Research

SDSU San Diego State University

SeaHARRE SeaWiFS HPLC Analysis Round-Robin Experiment

SeaHARRE-1 The first SeaHARRE

SeaHARRE-2 The second SeaHARRE

SeaHARRE-3 The third SeaHARRE

SeaHARRE-4 The fourth SeaHARRE

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SIMBIOS Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies

SNR Signal-to-Noise Ratio

SOP Standard Operating Procedure

TAcc Total Accessory Pigments

TbAA Tetrabutyl Ammonium Acetate

TCaro Total Carotenoids

TCAS Temperature-Controlled Autosampler

TChl Total Chlorophyll

TPig Total Pigments

UMCES University of Maryland Center for Environmental Science

UPD Unbiased Percent Difference

USC University of South Carolina

USF University of South Florida

UV Ultraviolet

VHT Van Heukelem and Thomas (2001) method

Vis Visible

VP Validation and Productivity

WG Working Group

70
Hooker et al.

Symbols

a The specific absorption coefficient.

A This is used to denote the average of all the methods.

A(λ) Absorbance.

A The methods within the QA subset.

A+ The methods not within the QA subset, which are

also referred to as the NV methods (not validated

at the QA level of performance).

A- The set of best results (e.g., lowest uncertainties or

precisions) from a group of methods.

Aˆc The peak area of the internal standard when it is

injected onto the HPLC column.

Aˆc1 The Aˆc determined using a one-step internal standard methodology.

Aˆc2 The Aˆc determined using a two-step internal standard methodology.

APi The absorbance of the pigment.

AˆPi The area of the parent peak and associated isomers

for pigment Pi.

Aˆ

Pi The corrected peak area (in units of milli-absorbance

units).

aPi (λ) Absorption coefficient of a pigment (a constant).

Aˆs The peak area of the internal standard in the sample.

Aˆs1 The Aˆs determined using a one-step internal standard methodology.

Aˆs2 The Aˆs determined using a two-step internal standard methodology.

ASi The absorbance of the internal standard measured

on the spectrophotometer.

AˆSi The peak area of the internal standard measured on

the HPLC.

bi The y-intercept of a linear equation.

C The CSIRO method, or the concentration of a pigment (depending on usage).

C ̄ The average concentration of a particular pigment.

Ca The concentration of chlorophyll a.

CA The concentration of alloxanthin.

CPi The concentration of a particular pigment.

C ̃Pi The amount of pigment injected for pigment Pi,

usually in units of nanograms.

C ̄A

Pi The average concentration of a particular pigment

across all methods.

CˆA

Pi The maximum concentration of pigment Pi across

all 24 samples.

C ̄A

Pi The overall averages for the individual pigments for

the QA subset.

C ̄A+

Pi The overall averages for the individual pigments for

the methods not in the QA subset.

CˆA+

Pi The average concentration of a particular pigment

across all methods for the not in the QA subset.

CˇA+

Pi The minimum concentration of pigment Pi across

all 24 samples not in the QA subset.

CˇA

Pi The minimum concentration of pigment Pi across

all 24 samples.

CB The concentration of 19

-butanoyloxyfucoxanthin.

CC The concentration of the carotenes.

CCa The concentration of chlorophyllide a.

CDa The concentration of divinyl chlorophyll a.

CDd The concentration of diadinoxanthin.

CDt The concentration of diatoxanthin.

CF The concentration of fucoxanthin.

CH The concentration of 19

-hexanoyloxyfucoxanthin.

CL The concentration of lutein.

CN The concentration of neoxanthin.

CN+V The concentration of neoxanthin plus violaxanthin.

CP The concentration of peridinin.

CP ba The concentration of phaeophorbide a.

CPi The concentration of a particular pigment.

C

Pi The amount pigment injected.

C ̃Pi The amount of pigment injected for pigment Pi,

usually in units of nanograms.

C ̄Pi The average concentration for pigment Pi.

CP r The concentration of prasinoxanthin.

CP ta The concentration of phaeophytin a.

CSi The concentration of pigment standard for pigment

Pi.

CTa The concentration of total chlorophyll a.

CTb The concentration of total chlorophyll b.

CTc The concentration of total chlorophyll c.

CV The concentration of violaxanthin.

CZ The concentration of zeaxanthin.

CZ+L The concentration of zeaxanthin plus lutein.

D The DHI method.

Dc The column diameter.

Df A dilution factor.

e Extract.

F The FIO method.

FPi The inverse response factor for pigment Pi, i.e.,

1/RPi .

G The GSFC method.

H The HPL method.

i An array index.

j An array index.

J The JRC method.

k An index indicating the station number.

l An index indicating the replicate number.

L The LOV method.

L The histoprep analyses.

lc The pathlength of the cuvette.

Lc The column length.

Lj The laboratory or method code.

mi The slope of a linear equation (equating change in

peak area with change in amount).

N The DalU method.

NL The number of laboratories quantitating a pigment.

NR The total number of replicates: 3 for M and 2 for

all other methods.

NS The number of samples.

Pi A particular pigment (referenced using index i).

Ps The column particle size.

r2 The coefficient of determination.

R The response factor (from a generalized perspective).

R% The purity corrected response factor.

RI The ratio of the volume of IP solution plus Vm divided by Vm.

71
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

RPi The response factor for pigment Pi, usually expressed as the amount of pigment divided by the

peak area.

RΣ

Pi The amount injected onto the column divided by

the total peak area (including the sum of the parent

peak and degradants).

R%

Pi The purity-corrected amount injected onto the column divided by the area of the main (or parent)

peak alone.

Rs The resolution (or separation) between peaks.

Rˇs The minimum resolution determined from a critical pair for which one of the pigments is a primary

pigment.

s The sample.

S The (SDSU) CHORS method.

Si The pigment standard for pigment Pi.

Sk The kth station or sample number.

Sk,l The station or sample number set by k, and the

replicate number set by l.

Tc The column temperature.

[TChl a] The concentration of total chlorophyll a.

tR The retention time.

U The USC method.

Vc The volume of sample extract injected onto the

HPLC column.

Ve The volume of the extraction solvent.

Vf The volume of water filtered in the field to create

the sample.

Vm The volume of extraction solvent (containing internal standard) added to a filter.

Vs The internal standard.

Vx The extraction volume.

VxThe extraction volume in milliliters.

Vx1 The extraction volume computed using a one-step

internal standard methodology.

Vx2 The extraction volume computed using a two-step

internal standard methodology.

[Vit E] The concentration of vitamin E (in grams per milliliter) in the extraction solvent plus internal standard.

α Specific absorption coefficient a.

αSi The absorption coefficient for the pigment of interest.

ε The molar absorption coefficient at the specified

wavelength for the pigment λPi .

λ The spectral wavelength.

λm The maximum wavelength.

ξ The coefficient of variation.

 ̄ξ The average precision.  ̄ξcal The average CV for gravimetric calibration of dilution devices.  ̄ξinj The injector precision.  ̄ξPi The average precision for pigment Pi.  ̄ξt

R The CV of retention time.

σ The standard deviation.

ΣAˆSi The sum of the parent peak and the area of the

alteration products.

ψ ̄A

Pi The average of the RPD values for a particular pigment across the number of laboratories or methods

(NL) reporting the pigment involved.

|ψ| The absolute UPD.

|ψ ̄|

A

Pi The average of the APD, |ψ ̄|, values for a particular pigment across the number of laboratories or

methods (NL) reporting the pigment involved.

|ψ ̄| The average APD.

|ψ ̄|res The average of the absolute residuals.

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31-12-2010 Technical Memorandum

The Fourth SeaWiFS HPLC Analysis Round-Robin

Experiment (SeaHARRE-4)

NNX09AN94G

Stanford B. Hooker, Crystal S. Thomas, Laurie Van Heukelem, Louise

Schlüter, Mary E. Russ, Joséphine Ras, Hervé Claustre, Lesley Clementson,

Elisabetta Canuti, Jean-François Berthon, Jason Perl, Claire Normandeau,

John Cullen, Markus Kienast, and James L. Pinckney

NASA Calibration and Validation Office (CVO)

BWtech, 1450 S. Rolling Rd., Suite 4.001

Halethorpe, MD 21227

National Aeronautics and Space Administration

Washington, DC 20546-0001

TM-2010-215857

Unclassified-Unlimited, Subject Category: 25, 48

Report available from the NASA Center for Aerospace Information, 7115 Standard Drive, Hanover, MD 21076. (443)757-5802

L. Van Heukelem, C.S. Thomas: UMCES/Horn Point Lab, Cambridge, MD; H. Claustre & J. Ras: LOV Observatoire Océanologique de Villifranche,

Villefranche-sur-Mer, France; L. Schlüter: DHI Water & Environment, Hørsholm, Denmark; M. Russ, Science Systems and Applications, Inc., Lanham MD; L. Clementson: CSIRO Marine

Research, Hobart, Australia; E. Canutti & J.F. Berthon: JRC/IES/Global Monitoring Unit, Ispra, Italy; J. Perl: SDSU Center for Hydro-Optics and Remote Sensing, San Diego, CA; C.

Nomandeau, J. Cullen, & M. Kienast: Dalhousie University, Halifax, Nova Scotia, Canada; and J.L. Pinckney: Univ. of South Carolina, Columbia, SC

Ten international laboratories specializing in the determination of marine pigment concentrations using high performance liquid

chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample. The method intercomparisons were

used for the following objectives: a) estimate the uncertainties in quantitating individual pigments and higher-order variables formed

from sums and ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation activities (approximately 25%,

although 15% would allow for algorithm refinement) can be met in coastal waters; c) establish the reduction in uncertainties as a

result of applying quality assurance procedures; d) show the importance of establishing a properly defined referencing system in the

computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f) demonstrate the utility of a laboratory

mix in understanding method performance. In addition, the remote sensing requirements for the in situ determination of total

chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied.

SeaWiFS, High Performance Liquid Chromatography, HPLC, analysis, round-robin, pigment, chlorophyll, method

 Unclassified Unclassified Unclassified

Unclassified

75

Stanford B. Hooker

(410) 533-6451