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Discovery OMICS and Progenesis QI for Food Authenticity Testing

RECORD | Already taken place Mo, 15.12.2014
In this on-demand webinar, we describe a proof of principle method to assess the authenticity of basmati rice using the latest advancements in high resolution GC-MS and informatics technologies.
Go to the webinar
Pixabay/Trung Hieu Dang: Discovery OMICS and Progenesis QI for Food Authenticity Testing

Pixabay/Trung Hieu Dang: Discovery OMICS and Progenesis QI for Food Authenticity Testing

There is increased concern regarding the authenticity of basmati rice throughout the world. For years, traders have been passing off a lesser quality rice as the world's finest long-grained, aromatic rice, basmati, in key markets like the US, Canada and the EU.

In this on-demand webinar, we describe a proof of principle method to assess the authenticity of basmati rice using the latest advancements in high resolution GC-MS and informatics technologies. Volatile compounds of interest were extracted from heated dry rice via SPME and headspace. Following a generic GC separation, detection was performed using a SYNAPT G2-Si MS run in HDMSE mode. Collection of a HDMSE dataset offers a high level of specificity owing to the orthogonal nature of the ion mobility separation to the GC separation.

Progenesis QI, the latest OMICS informatics package from Waters, is designed to utilize the 4-dimensional data produced during a SYNAPT G2-Si HDMSE acquisition. Initially, alignment of all injections was performed followed by the unique peak co-detection process resulting in the same number of analyte measurements in every sample and no missing values. Data from all isotopes and adducts of a parent compound were then deconvoluted giving a single robust and accurate quantitative measurement for that parent compound. The peak picking and deconvolution algorithms ensure a high quality compound table where adducts and isotopes are grouped with the parent m/z. Compounds of interest from the rice samples were highlighted using various multivariate statistical techniques such as PCA and identified using elucidation tools and relevant database searches within the software platform.

This workflow has general applicability to many areas of discovery OMICS and food research where biomarkers differentiating between two or multiple groups are required.

What will I learn?

  • An experimental workflow to evaluate the authenticity of foodstuffs
  • A basic workflow for the discovery of volatile biomarkers between multiple groups of samples
  • The basics of HDMSE data independent acquisition
  • How Progenesis QI is used to analyze metabolomics data

Who should attend?

  • Food research scientists
  • Metabolomics research scientists
  • Biomarker research scientists

Presenter: Robert Tonge, Ph.D. (Senior Product Manager, OMICS Informatics, Waters Corporation)

Dr Robert Tonge is Senior Product Manager for OMICS Informatics at Waters Corporation, Manchester UK. Robert has been at Waters for 4 years in both Product Development and Field Marketing and has approaching 20 years experience in OMICS science. He trained initially in Biochemistry and Toxicology before moving to 'Big Pharma' where he worked in Discovery and Translational Research across a wide variety of disease areas from cancer, cardiovascular disease and infection research.

Presenter: Gareth Cleland, Ph.D. (Principal Scientist, Food & Environmental Business, Waters Corporation)

Dr Gareth Cleland is a Principal Scientist within the Food and Environment Business Operations at Waters Headquarters, USA. Following his Chemistry studies, he started his professional career working as a Development Chemist for a small coatings company in Oxfordshire, UK. He joined Waters Corporation in 2002 and has held various roles within the organization, both UK and US based, over the last 12 years.

Spectroscopy & Separation Science
 

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