Latest News and Application Notes

Gas chromatography-mass spectrometry (GC-MS) has long been an invaluable tool in a chemist's belt. With its ability to tease apart the compounds in a sample, identifying even trace analytes, it is able to perform specific tests and pinpoint what, exactly, is in the material being analyzed. But what can you do when GC-MS isn't enough?

LECO recently concluded a webinar series on agricultural applications of our instruments with a presentation by Dr Frank Dorman of Dartmouth College, Department of Chemistry, formerly of Penn State University, Department of Biochemistry and Molecular Biology. While at Penn State, Frank worked on an environmental forensic investigation of wastewater applied to agricultural fields.

Petroleum products are used the world over, and they all start with crude oil refinement. In distilling, cracking, and reforming the crude oil into petroleum products, many analytical instruments and tests are needed to monitor the process and maintain the quality demanded by consumers and regulations.

Environmental crises are now a daily concern in labs all around the world, and scientists are racing to get ahead of the problems. In their latest e-book partnership, LCGC and LECO teamed up to turn a spotlight on some of the latest GC-MS and GCxGC-MS techniques that can help labs pull ahead of the curve.

Pesto can trace its roots back to ancient times, though it really only started taking off in North America in the 1980s and 90s. Though the primary base is consistent, with pine nuts, basil, and olive oil, individual recipes vary. As canned and bottled pesto became more accessible, individual manufacturers developed their own unique flavor profiles. While these recipes are usually trade secrets, the power of GCxGC TOFMS can tease apart some of the differences.

It seems like every December, the world becomes just a little more interested in frankincense and myrrh. Just what are these gifts mentioned in the Christmas story? And what sets them apart?

The pressure to save money is everywhere these days. The changes due to COVID-19 have only exacerbated the age-old question your own lab has probably asked: how can we cut costs? One hidden expense in a GC-MS lab setting is the cost of cleaning your instrument's ion source.

Charred oak barrels that were once used to age bourbon have found new life as they get repurposed for a variety of foods and beverages to add a new flavor profile to familiar delicacies. But how much can an old bourbon-soaked barrel change the chemical makeup? LECO used ChromaTOF® Tile to differentiate regular and barrel-aged maple syrups and quantify the difference.

Food contamination by mineral oil hydrocarbons (MOH), which is usually separated into the subclasses of MOSH (Mineral Oil Saturated Hydrocarbons) and MOAH (Mineral Oil Aromatic Hydrocarbons), is a growing concern across the EU and the world. In 2012, the European Food Safety Authority flagged them as a potential health concern, and the increasing research since then has only been expanding our understanding of these hydrocarbons. However, the two main analytical methods suggested to quantify these substances, either an off-line method consisting of a solid phase extraction (SPE) followed by a GC-FID analysis or an on-line, LC-GC-FID method, both can result in inaccuracies and leads to challenges in the end results. Some of these inaccuracies are due to the lack of a strong and robust confirmatory method. However, a GCxGC-TOFMS system, like LECO's Pegasus® BT 4D can help unveil the complexity of contaminated food samples. It has also been suggested by the EFSA to be used as a confirmatory tool in case of uncertain results from other standard methods.

LECO has released a revolutionary new data analysis software for GCxGC data: ChromaTOF Tile. This software provides an industry-first data comparison tool that identifies statistically significant differences between classes of samples, reducing days-to- weeks of work down to hours, or even minutes. Based on Dr. Robert Synovec’s tile-based Fisher ratio analysis, ChromaTOF Tile partitions the data into a set of regions (tiles) and compares regionalized data. This allows it to disregard normal variances of alignment shifts to focus on where the actual differences are, so users can stop looking at their data and start actually using it.