The study, published in the journal Biogeosciences by Joaquín Chaves, Crystal Thomas, and Antonio Mannino, examined nearly 20,000 individual water samples analyzed by high-performance liquid chromatography, or HPLC, at NASA’s centralized pigment facility since its establishment in 2011. The facility, which has processed more than 30,000 samples in total from every major ocean basin, exists because NASA carries a mandate to distribute in situ data of the highest quality for calibrating and validating satellite ocean color missions. When a satellite sensor measures the greenness of the sea, that greenness comes chiefly from chlorophyll a and a suite of accessory pigments inside phytoplankton cells. If the ground-based measurements of those pigments are sloppy, the entire validation chain wobbles.

The technical heart of the analysis is the coefficient of variation, or CV%, calculated among replicate samples, predominantly duplicate filters collected from the same water mass and processed independently. Across the full suite of 26 routinely reported pigments, mean precision ranged from a remarkably tight 3.2% for divinyl chlorophyll a, a signature pigment of oceanic cyanobacteria, to 17.1% for chlorophyllide a, a degradation product that serves mainly as a red flag for sample-handling problems rather than a biogeochemical quantity in its own right. Crucially, the study tested the results against benchmarks forged during the SeaWiFS HPLC Analysis Round-Robin Experiments, known as SeaHARRE, which set a precision target of 5% for total chlorophyll a and 8% for the twelve primary pigments most relevant to ocean color validation. Total chlorophyll a came in at 4.3%, comfortably within spec, and ten of the twelve primary pigments also passed. Only diatoxanthin, at 8.6%, and peridinin, at 9.2%, slightly exceeded the bar, likely because both tend to occur at low concentrations where quantification uncertainty grows.

What makes the study genuinely surprising is what did not drive the variability. The team hypothesized that pigment concentration, or the mass of pigment actually injected into the instrument, would be the dominant factor, since analytical methods are expected to degrade near their detection limits. Instead, multivariate regression models incorporating concentration, filtered volume, inferred phytoplankton size structure, and coastal versus oceanic origin explained no more than 3% of the precision variability across the full dataset. In other words, once pigments sit comfortably above their detection thresholds, the validated NASA protocols deliver essentially concentration-independent precision, a testament to the quality assurance plan built on years of intercalibration exercises. The instrument itself, an Agilent system with a C8 column held at 60 degrees Celsius and dual-wavelength detection at 450 and 665 nanometers, achieves injection repeatability averaging just 0.6%, thanks in part to a clever vitamin E internal standard that corrects for variations in extraction volume without interfering with pigment signals.

The picture changed, however, when the researchers stripped out invariant replicates, those duplicate pairs that produced identical concentration values and thus a CV of exactly zero. In this censored dataset, regression models suddenly explained up to 44% of the variability for divinyl chlorophyll b, and concentration emerged as the dominant variable for 22 of 25 pigments. Precision deteriorated toward detection limits for secondary and tertiary pigments, the less abundant compounds that often serve as taxonomic fingerprints for specific phytoplankton groups. The authors caution that this shift partly reflects a statistical artifact: pigments with narrow, low concentration ranges, such as divinyl chlorophyll b, where invariant replicates made up 70% of the sets, are simply more likely to yield identical values by chance, so removing them concentrates the analysis on the rare cases where variability was detectable at all.

One of the most intriguing findings concerns the difference between analytical precision and natural sample heterogeneity. For taxon-specific carotenoids like peridinin, the marker for dinoflagellates, precision worsened at low concentrations when plotted against concentration but showed a much weaker relationship when plotted against the total pigment mass injected. The researchers interpret this asymmetry as evidence of stochastic cell capture: when rare organisms are sparsely scattered through the water, two replicate filters may trap genuinely different numbers of cells, producing variability that reflects the patchiness of the real ocean rather than any flaw in the instrument. Filtering larger volumes of dilute water improves precision precisely because it captures more cells, pointing to sampling statistics, not laboratory sensitivity, as the bottleneck for rare pigments.

Filtration volume itself emerged as a practical lever. For most primary pigments, filtering more than 1000 milliliters of seawater pushed precision below 10%, though the benefit plateaued well below that threshold for many compounds, and a subset including alloxanthin, diatoxanthin, peridinin, and all the tertiary pigments actually showed precision degradation at very large volumes in the censored analysis. The authors suggest a combination of detection limit constraints, where even large volumes cannot lift trace pigments far above the limit of quantification, and possible physical stresses during extended filtration, such as cell lysis under prolonged vacuum. Their recommendations align with NASA’s Ocean Optics Protocols: roughly 0.5 to 1 liter for nutrient-rich waters, and 1 to 4 liters for the oligotrophic open ocean where accessory pigments must be coaxed above detection limits.

Geography told a subtler story. In the full dataset, oceanic samples more than 200 kilometers from shore showed significantly better precision than coastal samples for nearly every pigment, and total chlorophyll a retained that oceanic advantage even in the censored analysis. Yet the team argues this does not mean coastal waters are inherently harder to measure. The SeaHARRE-4 and SeaHARRE-5 intercomparisons, which used exclusively coastal samples from Danish fjords and rivers in New England and Tasmania, found that quality-assured laboratories achieved precision essentially indistinguishable from open-ocean exercises, with total chlorophyll a differences of only about 1.4% to 2.4% among validated methods. The coastal penalty in the NASA dataset more likely reflects differences in field sampling procedures, filtration volumes, or adherence to collection protocols across research groups, factors that remain largely invisible because the necessary metadata were not systematically recorded.

The study’s conclusions carry real weight for the future of ocean color science, particularly as new satellite missions demand ever more stringent calibration and validation. The clearest path to improvement, the authors argue, lies not in the laboratory but on the ship deck: better field replication, careful vacuum pressure monitoring during filtration, immediate preservation in liquid nitrogen, and an unbroken cold chain from collection to analysis. Only about 30% of samples in the dataset were collected as replicates, and 97% of those replicate sets were mere duplicates, which statistically limits how well precision can be characterized. NASA recommends that at least 5% of samples be replicated, but the team urges investigators to exceed that minimum substantially, and to collect triplicate filters where logistics allow. As satellites continue to chart the pulse of the global ocean, this massive audit confirms that the ground truth beneath them is solid, and shows exactly where the next gains in confidence will come from.

Subject of Research: Precision assessment of HPLC phytoplankton pigment analysis for global ocean color satellite validation

Article Title: Precision of phytoplankton pigment analysis by high-performance liquid chromatography: an assessment of the global ocean color validation dataset analyzed by NASA

Article References: Chaves, J. E., Thomas, C. S., & Mannino, A. (2026). Precision of phytoplankton pigment analysis by high-performance liquid chromatography: an assessment of the global ocean color validation dataset analyzed by NASA. Biogeosciences, 23(19), 7043-7065. https://doi.org/10.5194/bg-23-7043-2026

Image Credits: AI Generated

DOI: 10.5194/bg-23-7043-2026

Keywords: phytoplankton, HPLC, chlorophyll a, ocean color, satellite validation, NASA, pigment analysis, SeaHARRE, precision, biogeosciences, coastal ocean, quality assurance