Article ID Journal Published Year Pages File Type
1242553 Talanta 2016 7 Pages PDF
Abstract

•Hydrophobic-surface substrates for drop-and-dry spectroscopic measurement were investigated.•Amine- and FTS-coated substrate was optimal for analysis of milk and tobacco extract.•These substrates produced reproducible sample droplets and consistent dried shapes.•Also, spectra were collected by fully covering each spot for correct representation of a sample.

We investigated several spectroscopic substrates with hydrophobic surfaces that were able to form reproducible droplets of aqueous samples for reliable high throughput drop-and-dry measurements. An amine-coated substrate, a polytetrafluoroethylene (PTFE) disk, and a perfluorooctyltrichlorosilane (FTS) coated substrate were prepared and initially evaluated for use in the determination of fat concentrations in milks using near-infrared (NIR) spectroscopy. Since the dried milk spots were not compositionally uniform due to the localization of components during sample drying, NIR spectra were collected by fully covering each spot to ensure a correct compositional representation of the sample. The amine-coated substrate yielded more reproducible dried milk patterns because its hydrophobicity was optimal for loading an appropriate amount of milk with decreased component localization after drying. The relative standard deviation (RSD) of the absorbance at 4330 cm−1 was 1.0%, thereby resulting in the more accurate determination of fat concentration. In addition, infrared (IR) spectroscopic discrimination between wild and transgenic tobaccos using their extracts was attempted. The extracted metabolites had a low concentration, so an FTS-coated CaF2 substrate that maximized sample loading was used to improve measurement sensitivity and produce reproducible droplets. The RSD of the absorbance at 1070 cm−1 was only 0.8%. Our strategy produced droplets that had consistent sizes and provided reproducible IR spectral features, which enabled the differentiation between wild and transgenic tobacco groups in the principal component (PC) score domain.

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Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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