UV resonance Raman detection and quantitation of domoic acid in phytoplankton

Cultures of the phytoplankton diatom, Pseudonitzschia multiseries, have been harvested under controlled growth conditions ranging from late logarithmic to late stationary phase (17-58 days). The amount of domoic acid (DA) present in the growth media and in the homogenized cells has been determined by HPLC. Defined samples of media, homogenized cells, whole cells, and whole cells in media have been laser excited at 251 nm for the purpose of selectively exciting intense UV resonance Raman spectra from DA in the samples. Neither media nor cell component spectra from algae seriously interfere with DA spectra. The spectral cross sections for the dominant 1652-cm-1 mode of DA have been determined for 242-, 251-, and 257-nm excitation. Maximum sensitivities are achieved with 251-nm excitation because cross sections for DA are a maximum, and interference from other algal components becomes very small. DA concentrations that have been determined with 251-nm excitation by resonance Raman methods correlate closely with values determined independently with HPLC, especially at higher DA concentrations. The UV resonance Raman analysis of DA in phytoplankton algae is shown to be very sensitive and quantitative as well as rapid and nonintrusive.     

Classification of organic and biological materials with deep ultraviolet excitation

We show that native fluorescence can be used to differentiate classes or groups of organic molecules and biological materials when excitation occurs at specific excitation wavelengths in the deep ultraviolet (UV) region. Native fluorescence excitation-emission maps (EEMs) of pure organic materials, microbiological samples, and environmental background materials were compared using excitation wavelengths between 200-400 nm with emission wavelengths from 270 to 500 nm. These samples included polycyclic aromatic hydrocarbons (PAHs), nitrogen- and sulfur-bearing organic heterocycles, bacterial spores, and bacterial vegetative whole cells (both Gram positive and Gram negative). Each sample was categorized into ten distinct groups based on fluorescence properties. Emission spectra at each of 40 excitation wavelengths were analyzed using principal component analysis (PCA). Optimum excitation wavelengths for differentiating groups were determined using two metrics. We show that deep UV excitation at 235 (+/-2) nm optimally separates all organic and biological groups within our dataset with >90% confidence. For the specific case of separation of bacterial spores from all other samples in the database, excitation at wavelengths less than 250 nm provides maximum separation with >6sigma confidence.     

Second-order advantage achieved with four-way fluorescence excitation-emission-kinetic data processed by parallel factor analysis and trilinear least-squares. Determination of methotrexate and leucovorin in human urine

Four-way fluorescence data recorded by following the kinetic evolution of excitation-emission fluorescence matrices (EEMs) have been analyzed by parallel factor analysis and trilinear least-squares algorithms. These methodologies exploit the second-order advantage of the studied data, allowing analyte concentrations to be estimated even in the presence of an uncalibrated fluorescent background. They were applied to the simultaneous determination of the components of the anticancer combination of methotrexate and leucovorin in human urine samples. Both analytes were converted into highly fluorescent compounds by oxidation with potassium permanganate, and the kinetics of the reaction was continuously monitored by recording full EEM of the samples at different reaction times. A commercial fast scanning spectrofluorometer has been used for the first time to measure the four-way EEM kinetic data. The rapid scanning instrument allows the acquisition of a complete EEM in 12 s at a wavelength scanning speed of 24 000 nm/min. The emission spectra were recorded from 335 to 490 nm at 5-nm intervals, exciting from 255 to 315 nm at 6-nm intervals. Ten successive EEMs were measured at 72-s intervals, to follow the fluorescence kinetic evolution of the mixture components. Good recoveries were obtained in synthetic binary samples and also in spiked urine samples. The excitation, emission, and kinetic time profiles recovered by both chemometric techniques are in good agreement with experimental observations.     

A multi-source portable light emitting diode spectrofluorometer

A portable luminescence spectrofluorometer weighing only 1.5 kg that uses multiple light emitting diodes (LEDs) as excitation sources was developed and evaluated. Excitation using a sequence of seven individual broad-band LED emission sources enabled the generation of excitation-emission spectra using a light weight (<1.5 kg) spectrometer. Limits of detection for rhodamine 6G, rhodamine B, and fluorescein were 2.9, 3.2, and 11.0 nM, respectively. Generation of excitation-emission matrices (EEMs) enabled the analysis of samples containing mixtures of rhodamine B and fluorescein. Buffered saline plant and animal feed extracts were also analyzed using this instrument. These samples included the woody plants Pistacia lentiscus (Evergreen pistache or Mastic) and Philyria latifolia, and the herbaceous species Medicago sativa (alfalfa), Trifolium spp. (clover), and a feed concentrate. Application of multi-way principal component analysis (MPCA) to the resulting three-dimensional data sets enabled discernment among these various diet constituents.     

Chemical characterization and classification of pollen

We report on the in situ characterization of tree pollen molecular composition based on Raman spectroscopy. Different from purification-based analysis, the nondestructive approach allows (i) to analyze various classes of molecules simultaneously at microscopic resolution and (ii) to acquire fingerprint-like chemical information that was used for the classification of pollen from different species. Hierarchical cluster analysis of spectra from fresh pollen samples of 15 species partly related at the genus level and family level indicates separation of species based on the complete Raman spectral signature and yields classification in accord with biological systematics. The results have implications for the further elucidation of pollen biochemistry and also for the development of chemistry-based online pollen identification methods.     

Discrimination of soil-borne fungi using fourier transform infrared attenuated total reflection spectroscopy

Fourier transform infrared (FT-IR) attenuated total reflection (ATR) spectroscopy was used to discriminate five commonly encountered soil-borne fungi that cause severe economic damage to agriculture: Colletotrichum, Fusarium, Pythium, Rhizoctonia, and Verticillium. Contrary to previous studies related to microorganism discrimination using FT-IR-ATR spectroscopy, the pathogen samples were not dried on the ATR crystal, which is a time-consuming operation. Rather, after removing some pathogen filaments from the solution using tweezers, these were placed directly on a flat ATR crystal and pressure was applied using a pressure clamp. Following water subtraction, baseline correction, and normalization of the spectra, principal component analysis was used as a data-reduction step and canonical variate analysis was used for discrimination. Discrimination was performed at the genus level and at the strain level for Colletotrichum. For discrimination between the five fungi at the genus level, the success rate for the validation samples ranged from 75% to 89%. For discrimination between the two Colletotrichum strains, the success rate was 78%. Comparison with spectra of similar fungi dried on the ATR crystal showed that both types of spectra were very similar, indicating that drying the samples on the ATR crystal is not required and can be replaced by mathematical post-processing of the spectra. For routine analyses that involve rapid screening of very large amounts of samples, this approach allows for increasing significantly the number of samples that can be analyzed daily.     

Simultaneous determination of trace cadmium and arsenic in biological samples by hydride generation-double channel atomic fluorescence spectrometry

Hydride generation atomic fluorescence spectrometry (HG-AFS) has been used for determination of hydride-forming elements because of its high sensitivity, simplicity, and low costs, but most of such work has been concentrated on single element analysis, and reports dealing with multielement determination by HG-nondispersive (ND)AFS are rare. In this work, a sensitive HG-NDAFS method was developed for simultaneous determination of trace cadmium and arsenic in biological materials. The conditions for the generation of volatile cadmium and arsenic species from the reaction with KBH4 in aqueous solution were investigated using a double-channel AFS integrated with an intermittent flow reactor. Like thiourea and Co(II), ascorbic acid was found to significantly enhance the generation efficiency of volatile Cd and As species. The interferences of coexisting ions were evaluated. Under optimal conditions, the detection limits for Cd and As were determined to be 10 and 150 ng L(-1), respectively. The precision for 11 replicate determinations at the 1 microg L(-1) Cd level and the 10 microg L(-1) As level were 3.5 and 2.7% (RSD), respectively. The recoveries of spike analytes in the biological samples studied ranged from 94 to 109%. The proposed method was successfully applied to the simultaneous determination of Cd and As in a variety of biological samples.     

Selective measurement of ultratrace methylmercury in fish by flow injection on-line microcolumn displacement sorption preconcentration and separation coupled with electrothermal atomic absorption spectrometry

A novel nonchromatographic speciation technique for ultratrace methylmercury in biological materials was developed by flow injection microcolumn displacement sorption preconcentration and separation coupled on-line with electrothermal atomic absorption spectrometry (ETAAS). In the developed technique, Cu(II) was first on-line complexed with diethyldithiocarbamate (DDTC), and the resultant Cu-DDTC was presorbed onto a microcolumn packed with the sorbent from a cigarette filter. Selective preconcentration of methylmercury (MeHg) in the presence of Hg(II), ethylmercury (EtHg), and phenylmercury (PhHg) was achieved at pH 6.8 through loading the sample solution onto the microcolumn due to a displacement reaction between MeHg and the presorbed Cu-DDTC. The retained MeHg was subsequently eluted with 50 microL of ethanol and on-line determined by ETAAS. Interferences from coexisting heavy metal ions with lower stability of their DDTC complexes relative to Cu-DDTC were minimized without the need of any masking reagents. No interferences from 5.5 mg L(-1) Cu(II), 4.5 mg L(-1) Cd(II), 2.5 mg L(-1) Cr(III), 3 mg L(-1) Fe(III), 10 mg L(-1) Ni(II), 10 mg L(-1) Pb(II), and at least 25 mg L(-1) Zn(II) were observed for the determination of MeHg at the 50 ng L(-1) level (as Hg). With the consumption of only 3.4 mL of sample solution, an enhancement factor of 75, a detection limit of 6.8 ng L(-1) (as Hg) in the digest (corresponding to 3.4 ng g(-1) in original solid sample for a final 50 mL of digest of 0.1 g of solid material), and a precision (RSD, n = 13) of 2.3% for the determination of methylmercury at the 50 ng L(-1) (as Hg) level were achieved at a sample throughput of 30 samples h(-1). The recoveries of methylmercury spike in real fish samples ranged from 97 to 108%. The developed technique was validated by determination of methylmercury in a certified reference material (DORM-2, dogfish muscle), and was shown to be useful for the determination of methylmercury in real fish samples.     

Photocatalytic degradation-excitation-emission matrix fluorescence for increasing the selectivity of polycyclic aromatic hydrocarbon analyses

The application of photocatalysis enhancement to calibration of fluorescence excitation-emission matrixes (EEMs) with parallel factor (PARAFAC) analysis is described. In this study, three- and four-way PARAFAC analysis was employed to extract the fluorescent species' spectra from overlapping EEMs. Time-dependent photocatalysis degradation of the polycyclic aromatic hydrocarbons (PAHs) was employed to create an additional dimension for analysis. The consequent four-dimension degradation-EEM data cubes have greater selectivity for each PAH than do three-dimension EEM data cubes alone. On a scale of 0 to 1, with 0 being completely collinear spectra and 1 being orthogonal spectra, including the time-dependent measurements increased the selectivity an average of 21%, from 0.73 to 0.87.     

Characterization and matching of oil samples using fluorescence spectroscopy and parallel factor analysis

A novel approach for matching oil samples by fluorescence spectroscopy combined with three-way decomposition of spectra is presented. It offers an objective fingerprinting based on the relative composition of polycyclic aromatic compounds (PACs) in oils. The method is complementary to GC-FID for initial screening of oil samples but can also be used for prescreening in the field, onboard ships, using a portable fluorescence spectrometer. Parallel factor analysis (PARAFAC) was applied to fluorescence excitation-emission matrixes (EEMs) of heavy fuel oils (HFOs), light fuel oils, lubricating oils, crude oils, unknown oils, and a sample collected in the spill area two weeks after the Baltic Carrier oil spill (Denmark, 2001). A total of 112 EEMs were decomposed into a five-factor PARAFAC model using excitation wavelengths from 245 to 400 nm and emission wavelengths from 280 to 550 nm. The PARAFAC factors were compared to EEMs of PAC standards with two to five rings, and the comparisons indicate that each of the factors can be related to a mixture of PACs with similar fluorescence characteristics: a mixture of naphthalenes and dibenzothiophenes, fluorenes, phenanthrenes, chrysenes, and five-ring PACs, respectively. Oils were grouped in score plots according to oil type. Except for HFOs and crude oils, the method easily discriminated between the four oil types. Minor overlaps of HFOs and crude oils were observed along all five PARAFAC factors, and the variability of crude oils was large along factor 2 due to a varying content of five-ring PACs. The spill sample was correctly assigned as a HFO with similar PAC pattern as oil from the cargo tank of the Baltic Carrier by comparing the correlation coefficient of scores for the oil spill sample and possible source oils (i.e., oils in the database).     

Toxin screening in phytoplankton: detection and quantitation using MALDI triple quadrupole mass spectrometry

The investigation of a MALDI triple quadrupole instrument for the analysis of spirolide toxins in phytoplankton samples is described in this study. A high-frequency (kHz) laser was employed for MALDI, generating a semicontinuous ion beam, thus taking advantage of the high duty cycle obtained in sensitive triple quadrupole MRM experiments. Initially, several experimental parameters such as type of organic matrix and concentration, solvent composition, and matrix-to-analyte ratio were optimized, and their impact on sensitivity and precision of the obtained ion currents for a reference spirolide, 13-desmethyl-C, was studied. In all quantitative experiments, excellent linearities in the concentration range between 0.01 and 1.75 microg/mL were obtained, with R2 values of 0.99 or higher. The average precision of the quantitative MALDI measurements was 7.4+/-2.4% RSD. No systematic errors were apparent with this method as shown by a direct comparison to an electrospray LC/MS/MS method. Most importantly, the MALDI technique was very fast; each sample spot was analyzed in less than 5 s as compared to several minutes with the electrospray assay. To demonstrate the potential of the MALDI triple quadrupole method, its application to quantitative analysis in several different phytoplankton samples was investigated, including crude extracts and samples from mass-triggered fractionation experiments. 13-Desmethyl spirolide C was successfully quantified in these complex samples at concentration levels from 0.05 to 90.4 microg/mL (prior to dilution to have samples fall within the dynamic range of the method) without extensive sample preparation steps. The versatility of the MALDI triple quadrupole method was also exhibited for the identification of unknown spirolide analogues. Through the use of dedicated linked scan functions such as precursor ion and neutral loss scans, several spirolide compounds were tentatively identified directly from the crude extract, without the usual time-consuming chromatographic preseparation steps. Moreover, high-quality CID spectra were obtained for low-abundant spirolides present in the phytoplankton samples.     

Determination of organic and inorganic carbon in forest soil samples by mid-infrared spectroscopy and partial least squares regression

Analyses of organic and inorganic carbon are of great interest in the field of soil analyses. Soil samples from a national monitoring project were provided for this study, including more than 130 forest sites from Austria. We investigated the humus layers (if present undecomposed litter (L), of mixed samples of F- (intermediate decomposed organic matter) and H-(highly decomposed organic matter) (FH)) and upper mineral soil layers (0-5 and 5-10 cm) of the samples. Mid-infrared spectra were recorded and evaluated by their band areas; subsequently we calculated models with the partial least squares approach. This was done by correlating calculated data of the mid-infrared spectra with gas-volumetrically determined carbonate values and measurements of organic carbon from an elemental analyzer. For carbonate determination, this approach gave satisfying results. For measurements of organic carbon, it was necessary to discriminate into humus layers and mineral soils or even more groups to obtain satisfactory correlations between spectroscopically determined and conventionally measured values. These additional factors were the presence of carbonate, the forest type, and the dominant tree species. In mineral soils, fewer subdivisions were necessary to obtain useful results. In humus layers, groupings of sites with more similar characteristics had to be formed in order to obtain satisfying results. The conclusion is that the chemical background of soil organic matter leading to different proportions of functional groups, especially in the less humified organic matter of the humus layers, plays a key role in analyses with mid-infrared spectroscopy. Keeping this in mind, the present approach has a significant potential for the prediction of properties of forest soil layers, such as, e.g., carbonate and organic carbon contents.     

Simultaneous speciation of monomethylmercury and monoethylmercury by aqueous phenylation and purge-and-trap preconcentration followed by atomic spectrometry detection

A new method for the detection of trace levels of organomercury species has been developed by combining the high enrichment capacity of purge and trap with aqueous phenylation derivatization. Phenylation products of monomethylmercury (MeHg) and monoethylmercury (EtHg) were first separated by capillary gas chromatography and then detected by atomic fluorescence spectrometry (AFS) or inductively coupled plasma mass spectrometry (ICPMS). This combination made it possible to simultaneously quantify trace or ultratrace level of MeHg and EtHg in environmental samples. Method detection limits were 0.03 ng/L for both MeHg and EtHg when AFS was used as the detector and 0.02 and 0.01 ng/L for MeHg and EtHg with ICPMS, respectively. Certified reference materials, IAEA-405 and DORM-2, were analyzed and the results were in accordance with certified values. Both MeHg and EtHg were detected in sediment samples collected from the Florida Everglades and a Canadian wetland. This new method has been validated for the direct detection of trace organomercury species in freshwater samples and has the additional benefits of being free from interference by Cl (-) and dissolved organic matter.     

Hydrogeochemistry and arsenic contamination of groundwater in the Ganges Delta Plain, Bangladesh

Geochemical composition and the level of Arsenic (As) contamination of groundwater in the Ganges Delta Plain, southwestern Bangladesh were elucidated. Hydrogeochemical data of tube well samples suggested that the groundwater is mostly Ca-Mg-HCO(3) type with bicarbonate (HCO(3)(-)) as the dominant anion, though other type waters are also observed. In contrast, the elevated EC, Cl(-) and high content of Na(+) relative to Ca(2+), Mg(2+) and K(+) in six groundwater samples suggest their saline origin. Low concentrations of NO(3)(-) and SO(4)(2-), and high concentrations of dissolved organic carbon (DOC), HCO(3)(-) and PO(4)(3-) indicate the reducing conditions of subsurface aquifer where sediments are deposited with abundant organic matter. The total As concentration in the analyzed samples is very high (0.0431-1.352 mg/L) along with high Fe (2.791-17.058 mg/L) and relatively low Mn (0.134-1.972 mg/L) at different depths. Distinct relationship of As with Fe and Mn, and strong correlation with DOC suggests that the biodegradation of organic matter and reductive dissolution of Fe-oxyhydroxide is considered to be the dominant processes to release As in aquifers. Moreover, negative correlation between As and SO(4)(2-) demonstrates the As may not be directly mobilized from sulfide minerals like arsenopyrite.     

Hyphenating multisyringe flow injection lab-on-valve analysis with atomic fluorescence spectrometry for on-line bead injection preconcentration and determination of trace levels of hydride-forming elements in environmental samples

In this work the third generation of flow injection analysis, that is, the so-called micro-lab-on-valve (microLOV) approach, is proposed for the first time for the separation, preconcentration, and monitoring of metalloids as hyphenated with atomic fluorescence spectrometry (AFS). This was made feasible by interfacing the micromachined LOV-module with AFS by a multisyringe flowing stream network for on-line postcolumn derivatization of the eluate aimed at generation of hydride species. The potential of this new hyphenated technique for environmental assays was ascertained via determination of ultratrace level concentrations of total inorganic arsenic in freshwater. Employing quantitative preoxidation of As(III) to As(V) in the samples by means of permanganate, the method involves preconcentration of arsenate at pH 10 on a renewable anion exchanger, namely, Q-Sepharose, packed in a LOV microcolumn. The analyte species is afterward stripped out and concurrently prereduced by a 300 microL eluent plug containing 6 mol L(-)1 HCl and 10% KI. The eluate is downstream merged with a metered volume of sodium tetrahydroborate (0.3% w/v) for generation of arsine, which is subsequently quantified by AFS. The flow system facilitates on-column reduction of the retained arsenic with no need for application of programmable stopped flow. Yet, the high concentration of reductant and extreme pH conditions for elution hinder the sorbent to be reused due to gradual deactivation of the functional moieties, so that maximum benefit can be taken from the application of the bead renewable strategy. The proposed procedure is characterized by a high tolerance to metal species and interfering hydride-forming elements. In fact, ratios of Se(IV) to As < or = 5000 and Sb(V) to As < or = 500 are tolerated at the 10% interference level. Under the optimized experimental conditions, a detection limit (3sigma) of 0.02 ng mL(-1) As, a dynamic linear range of 0.05-2.0 ng mL(-1) As (by tailoring the AFS gain), an enrichment factor of 8.8 for arsenate, and a precision better than 6.0% at the 0.1 ng mL-1 level were obtained for the bead-injection mode whenever the loading sample volume was affixed at 3.0 mL. The reliability and accuracy of the automated procedure was ascertained by determining total inorganic arsenic in both spiked environmental waters and certified reference materials of variable matrix complexity (TMDA-54.3 and ERM-CA010) at the low ng mL(-1) level. No significant differences were found between the experimental results and the certified values at a significance level of 0.05.     

New method for pollen identification by FT-IR spectroscopy

A new methodology for identification of pollen was developed based on FT-IR spectroscopy. Pollen samples of twenty different plant species were collected and the diffuse reflectance infrared Fourier transform (DRIFTS) and KBr pellet spectra were recorded. Libraries of spectra were created. Spectra of unknown plant origin pollen were recorded and compared with those of the corresponding pollen library and the match value was measured automatically using the appropriate software (OMINC ver. 3.1). From the same pollen samples, microscopic slides were prepared and the photographs of the pollen grains were used as a second comparison method. Using light microscopy, the pollen identification is usually limited to the family or generic name, while FT-IR spectroscopy can distinguish species belonging to the same genus. This method is simple and fast, and when the DRIFTS technique is used the sample is not destroyed.     

On-line near-infrared spectrometer to monitor urea removal in real time during hemodialysis

The ex vivo removal of urea during hemodialysis treatments is monitored in real time with a noninvasive near-infrared spectrometer. The spectrometer uses a temperature-controlled acousto optical tunable filter (AOFT) in conjunction with a thermoelectrically cooled extended wavelength InGaAs detector to provide spectra with a 20 cm(-1) resolution over the combination region (4000-5000 cm(-1)) of the near-infrared spectrum. Spectra are signal averaged over 15 seconds to provide root mean square noise levels of 24 micro-absorbance units for 100% lines generated over the 4600-4500 cm(-1) spectral range. Combination spectra of the spent dialysate stream are collected in real-time as a portion of this stream passes through a sample holder constructed from a 1.1 mm inner diameter tube of Teflon. Real-time spectra are collected during 17 individual dialysis sessions over a period of 10 days. Reference samples were extracted periodically during each session to generate 87 unique samples with corresponding reference concentrations for urea, glucose, lactate, and creatinine. A series of calibration models are generated for urea by using the partial least squares (PLS) algorithm and each model is optimized in terms of number of factors and spectral range. The best calibration model gives a standard error of prediction (SEP) of 0.30 mM based on a random splitting of spectra generated from all 87 reference samples collected across the 17 dialysis sessions. PLS models were also developed by using spectra collected in early sessions to predict urea concentrations from spectra collected in subsequent sessions. SEP values for these prospective models range from 0.37 mM to 0.52 mM. Although higher than when spectra are pooled from all 17 sessions, these prospective SEP values are acceptable for monitoring the hemodialysis process. Selectivity for urea is demonstrated and the selectivity properties of the PLS calibration models are characterized with a pure component selectivity analysis.     

Speciation of dissolved iron(III) and iron(II) in water by on-line coupling of flow injection separation and preconcentration with inductively coupled plasma mass spectrometry

A method has been developed for the speciation of trace dissolved Fe(II) and Fe(II) in water by on-line coupling of flow injection separation and preconcentration with inductively coupled plasma mass spectrometry (ICPMS). Selective determination of Fe(III) in the presence of Fe(II) was made possible by on-line formation and sorption of the Fe(III)-pyrrolidinecarbodithioate (PDC) complex in a PTFE knotted reactor over a sample acidity range of 0.07-0.4 mol L(-1) HCl, elution with 1 mol L(-1) HNO3, and detection by ICPMS. Over a sample acidity range of 0.001-0.004 mol L(-1) HCl, the sum of Fe(III) and Fe(II), i.e., Fe(III + II), could be determined without the need for preoxidation of Fe(II) to Fe(III). The concentration of Fe(II) was obtained as the difference between those of Fe(III + II) and Fe(III). With a sample flow rate of 5 mL min(-1) and a 30-s preconcentration time, an enhancement factor of 12, a retention efficiency of 80%, and a detection limit (3s) of 0.08 microg L(-1) were obtained at a sampling frequency of 21 samples h(-1). The relative standard deviation (n = 11) was 2.9% at the 10 microg L(-1) Fe(III) level. Recoveries of spiked Fe(III) and Fe(II) in local tap water, river water, and groundwater samples ranged from 95% to 103%. The concentrations of Fe(III) and Fe(II) in synthetic aqueous mixtures obtained by the proposed method were in good agreement with the spiked values. The result for total iron concentration in the river water reference material SLRS-3 was in good agreement with the certified value. The method was successfully applied to the determination of trace dissolved Fe(III) and Fe(II) in local tap water, river water, and groundwater samples.     

Statistical analysis of absorption spectra of phytoplankton and of pigment concentrations observed during three POMME cruises using a neural network clustering method

We present a neural network methodology for clustering large data sets into pertinent groups. We applied this methodology to analyze the phytoplankton absorption spectra data gathered by the Laboratoire d'Océanographie de Villefranche. We first partitioned the data into 100 classes by means of a self-organizing map (SOM) and then we clustered these classes into 6 significant groups. We focused our analysis on three POMME campaigns. We were able to interpret the absorption spectra of the samples taken in the first oceanic optical layer during these campaigns, in terms of seasonal variability. We showed that spectra from the PROSOPE Mediterranean campaign, which was conducted in a different region, were strongly similar to those of the POMME-3 campaign. This analysis led us to propose regional empirical relationships, linking phytoplankton absorption spectra to pigment concentrations, that perform better than the previously derived overall relation.     

Surface-enhanced Raman spectroscopy of soft-landed polyatomic ions and molecules

Surface-enhanced Raman spectroscopy (SERS) was used to detect and characterize polyatomic cations and molecules that were electrosprayed into the gas phase and soft-landed in vacuum on plasma-treated silver substrates. Organic dyes such as crystal violet and Rhodamine B, the nucleobase cytosine, and nucleosides cytidine and 2'-deoxycytidine were immobilized by soft landing on plasma-treated metal surfaces at kinetic energies ranging from near thermal to 200 eV. While enhancing Raman scattering 10(5)-10(6)-fold, the metal surface effectively quenches the fluorescence that does not interfere with the Raman spectra. SERS spectra from submonolayer amounts of soft-landed compounds were sufficiently intense and reproducible to allow identification of Raman active vibrational modes for structure assignment. Soft-landed species appear to be microsolvated on the surface and bound via ion pairing or pi-complexation to the Ag atoms and ions in the surface oxide layer. Comparison of spectra from soft-landed and solution samples indicates that the molecules survive soft landing without significant chemical damage even when they strike the surface at hyperthermal collision energies.