ANALYTICAL CORE FACILITY

The Analytical Core Facility within the Faculty of Land and Food Systems at the University of British Columbia is a shared resource facility with specialized equipment for the analysis of small molecules. The facility provides training and access to analytical equipment for academic and non-academic research projects on a fee-for-service basis. The facility offers high analytical data quality, relevant and effective instrument and analysis training, and expertise on analytical research projects.

If you’re interested in analytical method development, quantitative and qualitative small molecule analysis, or equipment training please reach out! We have experience in a range of small molecules using our GC or LC system. We have the capacity for LC-MS, GC-MS, HPLC-UV, HPLC-RID, or HPLC-FLD chromatography. See our equipment page for more specifics.

Contact
Harley Gordon
Facility Manager
Email: harley.gordon@ubc.ca
Phone: 604-827-2157
Address: 327-2205 East Mall | Vancouver BC | V6T 1Z4 Canada

LC-MS analysis using our Agilent 6530B LC-qTOF system. This instrument can provide high resolution MS1 and MS2 scans of target analytes. It is routinely used for the detection and quantification of low-abundance natural products in crude extracts.

GC-MS analysis with our Agilent GC-MS instruments can reliably detect and quantify trace levels of volatile compounds in crude mixtures. These instruments are regularly used for the quantification of terpenes.

GC-MS (Headspace or SPME) analysis, with these autosamplers we can assess static headspace or SPME concentrated volatiles using GC-MS systems. This is a technique regularly used for the analysis of important flavor compounds in wine and grapes.

GC-MS-ODP analysis is a technique that couples highly sensitive mass spectrometry with sensory data using an olfactometry detection port. This technique is often used in flavor and perfume analysis, product development, and sensory studies.

GC-MSMS analysis on our Agilent GC-triple quad can be used for trace level analysis of target analytes using multiple reaction monitoring (MRM). This is a widely used technique for trace analysis of environmental contaminants such as pesticides in plant tissue.

HPLC (DAD, UV, RID, FLD) analysis is a robust technique used for reliable quantification and detection of compounds. We regularly use HPLC methods for the quantification of sugars, amino acids, small organic acids, and carotenoids. This is often an excellent instrument method for the initial screening of enzyme assays.

Equipment:

Instrument	Model
LC-qTOF	Agilent 6530B with Agilent 1290 LC stack
GC-MS	Agilent 6890 GC with a 5975 MS
GC-MSMS	Agilent 7890 GC with a 7000A triple quad
GC-MS-HS	Agilent 6890 GC with a 5975 MS and an autosampler for HS or SPME
GC-MS-ODP	Agilent 6890 GC, a Gerstel ODP4, and 5973 MS, and a HS autosampler
HPLC-DAD-RID	Agilent 1260 binary pump stack with RID and DAD detectors
HPLC-DAD-FLD	Agilent 1260 quaternary pump stack with FLD and DAD detectors

All fees are charged per sample:

Services	UBC	External Academic	External Non-Academic
GC-MS (MS or MSMS) / per run	$20.00	$26.00	$40.00
HPLC (DAD, RID, FLD) / per run	$17.00	$22.10	$34.00
LCMS (qTOF)	$25.00	$32.50	$50.00
User Training	$120.00	$156.00	Inquire
Staff Services** / per hour	$100.00	$130.00	$200.00

**Discounts on more than 50 runs per billing period

** ie. method development, data-processing, formal consultation (does not include general advice or assistance)

Note: If you assist the facility in acquiring new equipment, you may qualify for special ACF member rates. Please contact the facility manager for more information about membership.

2022

Yan Y, Castellarin SD. 2022. Blueberry water loss is related to both cuticular wax composition and stem scare size. Postharvest Biology and Technology. 188: 111907. https://doi.org/10.1016/j.postharvbio.2022.111907

Pico J. Yan Y, Gerbrandt EM, Castellarin SD. 2022. Determination of free and bound phenolics in northern highbush blueberries by a validated HPLC/QTOF methodology. Journal of Food Composition and Analysis. 108: 104412. https://doi.org/10.1016/j.jfca.2022.104412