Fragmentation Trees for Automated de novo Interpretation of Impure Electron Ionization Spectra from Gas Chromatographic Complex Mixture Analysis—Chemical Deconvolution
Poster Jun 12, 2015
Kevin Siek, Vasily Makarov, Viatcheslav Artaev, Dmitry Mazur, Albert T. Lebedev
-Impure spectra contain signals from multiple analytes or signals unrelated to the main analyte, due to propinquitous coelution that confounds purely mathematical de-coelution. Some such spectra are expected in complex sample analysis.
-Impure spectra may impede manual or automated interpretation and beget false assignments or other failures.
-Chemical information within high-resolution spectra can assist mathematical de-coelution and facilitate analyte identification.
Fundamentals and Comparisons for Organic Sample Extract EvaporationPoster
Sample preparation is a key step in the analysis process
Parameters for evaporation and their impact on analysis have been discussed
Improvements in matching the sample to the evaporation device characteristics can help reduce variability and improve recovery
Examples for choosing a system based on sample volume, types of analytes, sample load, and initial investment considerations
Using Elemental Analysis For Discrimination Of Pinot Noir Wines From Six Different Districts In An AvaPoster
The determination of geographical origin of wine is gaining increased interest by researchers and federal agencies around the world, partially due to increased fraud with regards to place of origin labelling. For wine, multi-elemental profiling of macro, micro, and trace elements has been proposed for determination of authenticity. Commercial wines from different wineries in 5 different neighborhoods within one AVA show characteristic elemental fingerprints. Macro, micro and trace elements as well as elemental ratios contribute to the observed separation, indicating the involvement of multiple factors and underlying mechanisms, including location and soil composition, elemental uptake by vine and rootstock, viticulture and nutrient management, water sources, and small differences in the different wineries.READ MORE
Fast arsenic speciation analysis of wines and rice with LC-ICP-QQQPoster
This method was designed in response to recent and proposed food standards, both international and national, that limit inorganic arsenic rather than total, organic, or individual arsenic species such as arsenite (AsIII) and arsenate (AsV). Analysis time is 10x faster than the current FDA regulatory method, increasing sample throughput, avoided spectral interferences and dramatically increased sensitivity. Validation data from two laboratories demonstrate the method’s accuracy and reproducibility of both wine and rice matrices in a single analytical batch.READ MORE