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SUMMARY:High-Throughput Characterization Of Hops Using DART-MS
LOCATION:Chemistry A101
TZID:America/Denver
DTSTART:20211018T160000
UID:2026-05-19-02-35-03@natsci.colostate.edu
DTSTAMP:20260519T023503
Description:About the Seminar:\n\nHops are one of the four primary raw ingr
 edients used to make beer and they are employed by brewers to impart speci
 fic flavor and aroma profiles\, particularly in craft beer styles.   The
 se unique sensory attributes are a result of chemical compounds in hops su
 ch as alpha acids and terpenes which can vary significantly between hop cu
 ltivars and can also be influenced by the growing environment in which the
  hops were produced.  Thus\, while it is clear that understanding the che
 mical profile of hops is critical for beer quality (and the development of
  new\, unique beers)\, the optimal analytical tools are often out of reach
  for the craft brewer due to cost\, time\, and required expertise.  Inste
 ad\, hop producers and brewers primarily rely on sensory evaluation for ho
 p characterization which requires a large group of trained panelists\, is 
 often subjective\, and is time consuming and fatiguing – limiting throug
 hout.  Here\, we evaluate direct analysis by mass spectrometry (DART-MS) 
 coupled with predictive computational tools as an alternative “fit for p
 urpose” approach for hop characterization.   The approach was characte
 rized using unique hop samples sourced from three different suppliers acro
 ss four different farms located in Washington and Oregon over two growing 
 seasons.  Chemical profiles generated by DART-MS were used to train multi
 variate predictive models for classification of both cultivar and growing 
 location and were validated against traditional sensory evaluation.  Over
 all\, our results provide strong proof-of-concept data that support the us
 e of DART-MS for classification of hop cultivar based on the detection of 
 flavor and aroma (volatile and non-volatile) relevant compounds.\n\n&nbsp\
 ;\n\nAbout the Speaker:\n\nDr. Prenni received her Ph.D. in Analytical Che
 mistry from the University of Colorado\, Boulder followed by post-doctoral
  training at the Scripps Research Institute in La Jolla\, CA.  She has ov
 er 18 years of experience in biological mass spectrometry and served for o
 ver ten years at the Director of the Proteomics and Metabolomics Core Faci
 lity at Colorado State University (CSU).  During this time\, her group de
 veloped novel approaches in metabolomics for analytical methods and data a
 nalysis including the RAMClustR algorithm for metabolite clustering and an
 notation.  Presently\, Dr. Prenni is an Associate Professor in the Depart
 ment of Horticulture at CSU where the overall theme of her research is the
  application of mass spectrometry to address important issues in food/crop
  safety and quality.  Current projects are focused on the use of mass spe
 ctrometry to (1) dissect complex genotype by environment (GxE) interaction
 s\, including the microbiome\, in plant and animal systems (2) develop nov
 el approaches using ambient ionization for characterization of food qualit
 y and authenticity (3) perform sensitive and rapid quantification of drug 
 and chemical residues in food products (4) develop novel methods for metab
 olomics sample preparation\, data acquisition\, and informatics. 4:00 pm
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