Qualitative and Quantitative Analysis of Three-Dimensional Fluorescence Spectra by Improved Parallel Factor Analysis with Internal Standard Sample Embedding.

The strategy of parallel factor analysis, combined with the internal standard method, has been increasingly applied to the qualitative and quantitative analysis of three-dimensional fluorescence spectra of unknown mixed fluorophores. Nevertheless, the disparity in the number of fluorophores included in the internal standard sample set and the number included in test samples may impact the qualitative and quantitative outcomes of parallel factor analysis. In this work, we systematically established the framework of the parallel factor analysis with internal standard sample embedding (ISSE-PARAFAC) strategy. We applied this framework to six datasets representing two scenarios and a real dataset and conducted a detailed discussion on the effects of the disparity between the number of fluorophores in the internal standard sample set and the number in the test set on both qualitative and quantitative results. Additionally, we introduced an enhancement to PARAFAC by aggregating fluorophores with similar emission wavelengths, corresponding to the peaks of emission loadings (spectra) obtained from PARAFAC, as a single fluorophore. This aggregation aimed to mitigate the strong correlation between similar fluorophores. The results imply that the presence of irrelevant fluorophores in the internal standard sample set, whether increased or decreased, does not significantly affect the qualitative and quantitative analysis of target fluorophores in the test set. Moreover, we demonstrated that the improved parallel factor analysis with internal standard sample embedding not only fully decomposes the uncorrelated mixed fluorophores for qualitative analysis but also allows the established linear concentration model for fluorescent components to predict the corresponding fluorophore concentration of test samples, enabling quantitative analysis at the ppm level (mg/L).

Rapid determination of benzo[a]pyrene by membrane enrichment coupled with solid-phase constant-wavelength synchronous fluorescence spectrometry.

Normal methods for benzo[a]pyrene (BaP) determination, including gas chromatography-mass spectrometry and liquid chromatography with fluorescence detection, involve expensive instruments and complex separation and purification processes. Based on membrane enrichment, coupled with solid-phase constant-wavelength synchronous fluorescence spectrometry, a simple, fast, sensitive method was proposed for the determination of BaP in water samples. A Nylon membrane was used as the solid-phase extraction material for enrichment. After enrichment, a constant-wavelength synchronous fluorescence spectrum was scanned directly on the membrane-concentrated BaP without elution. Spectral measurement and enrichment conditions were optimized. Under optimum conditions, when using 150 mL sample solutions, the relationship between fluorescence intensity and BaP concentrations in the 0.05-10.00 µg L(-1) range could be fitted by binomial function with an R(2) value of 0.9973. Limit of detection (LOD) was calculated to be 0.0137 µg L(-1) . The volume of the sample solution was increased to 1000 mL to test if the method could be applied to determine lower BaP concentrations. A linear relationship still existed in the range 2.0-20.0 ng L(-1) BaP with an R(2) value of 0.9895, and a LOD of 2.4 ng L(-1) . The method was also used to measure the BaP concentration in several natural water samples, and recoveries were in the 90-110% range with relative standard deviations (RSDs) in the 0.58-7.93% range. Copyright © 2016 John Wiley & Sons, Ltd.

[Influence of sample loading and test conditions on NIR veracity and study of analysis error source].

The influence of sample test conditions on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Deducing analysis error was achieved by model self-emendation when a global NIR model was set up. Without regarding the influence of loading samples and test conditions, the test repetition error, re-loading error and samples tightness error, which were brought by instrument S/N, accounted for 50%, 30% and 20% of the total error, respectively. Depressing sample could reduce errors brought by sample tightness. Changes in test conditions could bring more analysis error, which was larger than the total of repetition error. These results theoretically explain the influence of sample test conditions on the NIR analysis veracity, which can provide basic theory data for farther improvement of homemade instrument and offer a new idea for resolving this problem.

[Influence of sample annum and distribution of chemical values on NIR veracity].

The influence of sample annum and the distribution of sample component on NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that sample annum had an obvious influence on the total sugar and nicotine models, but had an unconspicuous influence on the total-nitrogen model. Models set up by samples, whose component content distribution was normal school, was better than those set up by even distribution. The conclusion in this study has a significant referenced value for the method and principle to select representative samples to modeling from a large amount of specimens.

[Influence of LPLS algorithm parameters on NIR veracity].

The theory of local partial least square (LPLS) algorithm was described based on locally weighted regression algorithm (LWR). The influence of data processing parameters, such as principal component numbers and local set-up sample number in LPLS mode, on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that for nicotine model, the principal component number decided by cross validation was not the best choice, and better results could be achieved by reducing the principal component number; using 30-50 samples to set up NIR model, the veracity of total sugar, total nitrogen, and nicotine could be improved by 7%, 14% and 10%, respectively. So, LPLS algorithm can effectively improve NIR model's veracity, and is a good method to set up robust NIR models.

[Influence of spectrometer scanning requirements in homemade grating diffuse NIR instrument on NIR veracity].

The influence of instrument parameters, such as scan internal, length of instrument run, frequency of scan background etc, on NIR veracity was studied with a homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that scan interval, such as 8 nm or 16 nm, had no evident influence on NIR quantitative analysis. To improve scan speed, the scan interval the authors decided to use was 16 nm. NIR model was set up which could revise the influence of the length of instrument run. This instrument can clue on baseline shift to decide the frequency of background scanning, which can deduce NIR analysis error and improve NIR veracity.