4.6 Article Proceedings Paper

Pyrolysis-gas chromatography-isotope ratio mass spectrometry for monitoring natural additives in polylactic acid active food packages

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1525, Issue -, Pages 145-151

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2017.10.023

Keywords

Bioplastics; Analytical pyrolysis; Compound-specific isotope analysis; Carbon isotopes; Py-CSIA

Funding

  1. 'Junta de Andalucia' grant [AGR-7252]
  2. FPI [BES-2013-062573]
  3. Project INTERCARBON [CGL2016-78937-R]
  4. FEDER
  5. [CSIC10-1E-448]

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Compound-specific isotope analysis (CSIA) usually requires preparative steps (pretreatments, extraction, derivatization) to get amenable chromatographic analytes from bulk geological, biological or synthetic materials. Analytical pyrolysis (Py-GC/MS) can help to overcome such sample manipulation. This communication describe the results obtained by hyphenating analytical pyrolysis (Py-GC) with carbon isotope-ratio mass spectrometry (IRMS) for the analysis of a polylactic acid (PLA) a based bio-plastic extruded with variable quantities of a natural plant extract or oregano essential oil. The chemical structural information of pyrolysates was first determined by conventional analytical pyrolysis and the measure of delta C-13 in specific compounds was done by coupling a pyrolysis unit to a gas chromatograph connected to a continuous flow IRMS unit (Py-GC-C-IRMS). Using this Py-CSIA device it was possible to trace natural additives with depleted delta C-13 values produced by C3 photosystem vegetation (cymene: -26.7 parts per thousand +/- 2.52; terpinene: 27.1 parts per thousand +/- 0.13 and carvacrol: 27.5 parts per thousand +/- 1.80 from oregano and two unknown structures: -23.3 parts per thousand +/- 3.32 and - 24.4 parts per thousand +/- 1.70 and butyl valerate: -24.1 parts per thousand +/- 3.55 from Allium spp.), within the naturally isotopically enriched bio-plastic backbone derived from corn.(C4 vegetation) starch (cyclopentanones: 14.2 parts per thousand +/- 2.11; lactide enantiomers: -9.2 parts per thousand +/- 1.56 and larger polymeric units: 17.2%, 1.71). This is the first application of Py-CSIA to characterize a bio-plastic and is shown as a promising tool to study such materials, providing not only a fingerprinting, but also valuable information about the origin of the materials, allowing the traceability of additives and minimizing sample preparation. (C) 2017 Elsevier B.V. All rights reserved.

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