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Abstract: Methods for the determination of manganese and nickel in lake and marine sediment slurries by graphite furnace atomic absorption spectrometry using permanent modifiers are proposed. The slurries were maintained [...]

A methodology was developed to monitor the adulteration of the B10 blend of diesel and crambe biodiesel using proton nuclear magnetic resonance (1H NMR) spectroscopy combined with data driven soft independent modeling of class analogy (DD-SIMCA) model. The training was performed only with samples of the target class (B10) while the validation was performed with a test set consisting of new samples of the target class (B10) and samples of B10 adulterated with crambe oil, used frying oil, and residual automotive lubricating oil. The efficiency of this methodology was characterized based on the sensitivity parameters for the training set and specificity for the test set, in which a value of 1 was obtained for both parameters. This sensitivity value for the training set indicates that no target class samples were classified as extreme or outliers. The specificity for the test set shows that all samples in the test set were correctly classified into their respective classes, demonstrating the high efficiency of the DD-SIMCA model in monitoring adulterants in B10 mixture of diesel and crambe biodiesel. The DD-SIMCA model is simpler to construct than the multivariate control chart and the partial least squares discriminant analysis (PLS-DA) because its development does not require prior information about the adulterants. The excellent obtained results in the application of this model suggest that this analytical methodology is efficient, feasible and suitable for use by inspection agencies to characterize the quality of this fuel. [ABSTRACT FROM AUTHOR]

Abstract: Attenuated total reflectance-Fourier transform infrared spectrometry, in conjunction with multivariate calibration, was used for determination of reducing sugars, humidity and acidity in honey bee samples. Multivariate calibration models were built using partial least squares (PLS) and were refined through variable selection per interval (iPLS) and genetic algorithms. The calibration models show satisfactory results for all parameters with average relative errors of 6% for acidity, 1% for reducing sugars and 2% for humidity. For the acidity and reducing sugars parameters, variable selection was irrelevant, but for humidity it was essential. For the humidity parameter, it was necessary to use two variable selection techniques (by intervals and genetic algorithm) concomitantly in order to obtain a satisfactory calibration model. [Copyright &y& Elsevier]

The article proposes a method for direct determination of manganese (Mn) in human serum by graphite furnace atomic absorption spectrometry (GFAAS). The optimization of the instrumental conditions was designed with the use of multivariate approach. It mentions the availability of the pyrolysis and atomization temperatures and the use of modifier.

A method for direct determination of manganese (Mn) in human serum by graphite furnace atomic absorption spectrometry (GFAAS) was proposed in this work. The samples were only diluted 1:4 with nitric acid 1% (v/v) and Triton(®) X-100 0.1% (v/v). The optimization of the instrumental conditions was made using multivariate approach. A factorial design (2(3)) was employed to investigate the tendency of the most intense absorbance signal. The pyrolysis and atomization temperatures and the use of modifier were available and only the parameter modifier use did not have a significant effect on the response. A Center Composed Design (CCD) presented best temperatures of 430 °C and 2568 °C for pyrolysis and atomization, respectively. The method allowed the determination of manganese with a curve varying from 0.7 to 3.3 μg/L. Recovery studies in three concentration levels (n=7 for each level) presented results from 98 ± 5 to 102 ± 7 %. The detection limit was 0.2 μg/L, the quantifying limit was 0.7 μg/L, and the characteristic mass, 1.3 ± 0.2 pg. Intra- and interassay studies showed coefficients of variation of 4.7-7.0% (n=21) and 6-8%(n=63), respectively. The method was applied for the determination of manganese in 53 samples obtaining concentrations from 3.9 to 13.7 μg/L.