Precision of phytoplankton pigment analysis by high-performance liquid chromatography: an assessment of the global ocean color validation dataset analyzed by NASA
- 1Science Systems and Applications (United States) (Lanham, United States of America)
- 2Goddard Space Flight Center (Greenbelt, United States of America)
Abstract
Space-borne ocean color sensors capable of measuring phytoplankton pigments, such as chlorophyll a , have greatly expanded our understanding of oceanic biological processes. The ability to generate such measurements in a way that satisfies the requirements of climate-quality data records is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. The National Aeronautics and Space Administration (NASA) has a mandate to collect and distribute in situ data of the highest quality to support data product validation for ocean color missions; hence the agency uses a centralized, quality-assured laboratory to perform high-performance liquid chromatography (HPLC) analysis of pigment samples collected by NASA-affiliated investigators. Since its establishment in 2011, the facility at NASA's Goddard Space Flight Center has processed over 30 000 samples collected in all the major ocean basins. We evaluated the replicate sample precision, measured as the percent coefficient of variation among replicates (CV %) derived predominantly from duplicate analyses, with a very small minority of triplicates and higher-order sets, for total chlorophyll a and all pigments examined to investigate the sources of variability in analytical measurements. Here, primary pigments refer to chlorophylls and carotenoids commonly analyzed in phytoplankton research, secondary pigments are individual compounds aggregated to quantitate the primary pigments, and tertiary pigments are less frequently reported compounds commonly present in smaller amounts. Mean analytical precision, expressed as the mean CV % for each pigment, ranged from 3.2 % (divinyl chlorophyll a ) to 17.1 % (chlorophyllide a ). The analytical precision performance benchmarks for total chlorophyll a (5 %) and primary pigments (8 %), established for legacy ocean color missions, were met for total chlorophyll a and for 10 of 12 primary pigments. Two primary pigments exceeded the 8 % benchmark: diatoxanthin (8.6 %) and peridinin (9.2 %). No performance benchmarks have been established for secondary or tertiary pigments. Precision was evaluated against average sample concentration, pigment mass injected into the HPLC instrument, filtered volume, estimated phytoplankton size-fractions (micro-, nano-, and picoplankton), and sample origin (coastal versus oceanic) using multivariate regression and non-parametric approaches. Neither concentration nor pigment mass appeared as significant drivers of precision variability across their ranges. Precision showed minimal variation across concentration ranges for total chlorophyll a and primary pigments but deteriorated toward detection limits for secondary and tertiary pigments when samples with invariant replicates (CV % = 0) were excluded from analysis. Filtration volumes > 1000 mL generally improved precision, though it degraded at higher volumes for some pigments in censored datasets, possibly attributable to a combination of physical stresses during extended filtration and to detection limit constraints whereby low abundance pigments may still fall near their limit of detection regardless of the volume filtered. For most pigments, sample precision was statistically poorer in coastal versus oceanic samples, though previous interlaboratory comparisons suggest this reflects methodological rather than biogeochemical factors. Multivariate regression models explained ≤ 3.0 % of precision variability in full datasets but up to 44 % when invariant replicates were excluded, indicating that analytical precision is primarily governed by methodological factors rather than systematic dependencies on sample characteristics. The distinction between analytical precision and sample heterogeneity emerged as a possible factor, with increased variability at low concentrations for rare taxa likely reflecting stochastic cell capture during filtration rather than analytical limitations. These findings demonstrate that rigorous quality assurance protocols achieve precision performance suitable for climate-quality ocean color validation, with pre-analytical sample processing and field replication strategies identified as priorities for further improvements.
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BibTeX
@article{chaves2026precision,
title = {{Precision of phytoplankton pigment analysis by high-performance liquid chromatography: an assessment of the global ocean color validation dataset analyzed by NASA}},
author = {Joaquín E. Chaves and Crystal S. Thomas and Antonio Mannino},
journal = {Biogeosciences},
year = {2026},
month = oct,
doi = {10.5194/bg-23-7043-2026},
url = {https://bg.copernicus.org/articles/23/7043/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Precision of phytoplankton pigment analysis by high-performance liquid chromatography: an assessment of the global ocean color validation dataset analyzed by NASA
AU - Joaquín E. Chaves
AU - Crystal S. Thomas
AU - Antonio Mannino
PY - 2026
DA - 2026/10/08
JO - Biogeosciences
DO - 10.5194/bg-23-7043-2026
UR - https://bg.copernicus.org/articles/23/7043/2026/
AB - Space-borne ocean color sensors capable of measuring phytoplankton pigments, such as chlorophyll a , have greatly expanded our understanding of oceanic biological processes. The ability to generate such measurements in a way that satisfies the requirements of climate-quality data records is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. The National Aeronautics and Space Administration (NASA) has a mandate to collect and distribute in situ data of the highest quality to support data product validation for ocean color missions; hence the agency uses a centralized, quality-assured laboratory to perform high-performance liquid chromatography (HPLC) analysis of pigment samples collected by NASA-affiliated investigators. Since its establishment in 2011, the facility at NASA's Goddard Space Flight Center has processed over 30 000 samples collected in all the major ocean basins. We evaluated the replicate sample precision, measured as the percent coefficient of variation among replicates (CV %) derived predominantly from duplicate analyses, with a very small minority of triplicates and higher-order sets, for total chlorophyll a and all pigments examined to investigate the sources of variability in analytical measurements. Here, primary pigments refer to chlorophylls and carotenoids commonly analyzed in phytoplankton research, secondary pigments are individual compounds aggregated to quantitate the primary pigments, and tertiary pigments are less frequently reported compounds commonly present in smaller amounts. Mean analytical precision, expressed as the mean CV % for each pigment, ranged from 3.2 % (divinyl chlorophyll a ) to 17.1 % (chlorophyllide a ). The analytical precision performance benchmarks for total chlorophyll a (5 %) and primary pigments (8 %), established for legacy ocean color missions, were met for total chlorophyll a and for 10 of 12 primary pigments. Two primary pigments exceeded the 8 % benchmark: diatoxanthin (8.6 %) and peridinin (9.2 %). No performance benchmarks have been established for secondary or tertiary pigments. Precision was evaluated against average sample concentration, pigment mass injected into the HPLC instrument, filtered volume, estimated phytoplankton size-fractions (micro-, nano-, and picoplankton), and sample origin (coastal versus oceanic) using multivariate regression and non-parametric approaches. Neither concentration nor pigment mass appeared as significant drivers of precision variability across their ranges. Precision showed minimal variation across concentration ranges for total chlorophyll a and primary pigments but deteriorated toward detection limits for secondary and tertiary pigments when samples with invariant replicates (CV % = 0) were excluded from analysis. Filtration volumes > 1000 mL generally improved precision, though it degraded at higher volumes for some pigments in censored datasets, possibly attributable to a combination of physical stresses during extended filtration and to detection limit constraints whereby low abundance pigments may still fall near their limit of detection regardless of the volume filtered. For most pigments, sample precision was statistically poorer in coastal versus oceanic samples, though previous interlaboratory comparisons suggest this reflects methodological rather than biogeochemical factors. Multivariate regression models explained ≤ 3.0 % of precision variability in full datasets but up to 44 % when invariant replicates were excluded, indicating that analytical precision is primarily governed by methodological factors rather than systematic dependencies on sample characteristics. The distinction between analytical precision and sample heterogeneity emerged as a possible factor, with increased variability at low concentrations for rare taxa likely reflecting stochastic cell capture during filtration rather than analytical limitations. These findings demonstrate that rigorous quality assurance protocols achieve precision performance suitable for climate-quality ocean color validation, with pre-analytical sample processing and field replication strategies identified as priorities for further improvements.
SN - 1726-4189
ER -