Features of importance in Data aquisition software

Chromatography Forum: LC Archives: Features of importance in Data aquisition software
Top of pagePrevious messageNext messageBottom of pageLink to this message  By Nitin Nimkar on Monday, September 27, 1999 - 12:52 am:

What are selected few features important for good data acquisition and representation of results?
how much does the resolution matters?


Top of pagePrevious messageNext messageBottom of pageLink to this message  By bjenko on Tuesday, October 5, 1999 - 10:12 pm:

The sampling frequency seems to me to be the most important technical feature. If you are trying to do acquire a very fast chromatographic signal (and who isn't?) then you need to sample the signal a lot. As a chromatographer, you work hard to achieve good resolution of peaks based on their chemistry/physics. You don't want to give up anything because your data system is slow, underpowered or insensitive. The resolution of your data system should exceed the resolution of your chromatography, so to speak.

Ease of use is also extremely important. A very powerfull, flexible system is useless if it is so complex you cannot take advantage of the features built-in. The man-machine-interface must be easy to understand, intuitive, and have really good tutorials for the novice. This is a subjective thing. I suggest you try before you buy. The quality suppliers will give you demo software, or demonstrate their instrument in your lab, and you can be the judge.

Bill Jenko
Siemens Applied Automation, Inc.


Top of pagePrevious messageNext messageBottom of pageLink to this message  By Jon Welsh on Monday, October 11, 1999 - 12:52 pm:

Bill's advice is right on the money. I would add one other factor to consider: full-range data acquisition in a single run. Data from a high-performance GC may span ten orders of magnitude and 35 bits. Some data systems limit the data collection range to only six orders of magnitude, which means you may have to perform more than one run to get all the data. This is especially true when you must quantitate both major and trace components.

Plus, if you are not aware of this limitation in the data system, you may get inaccurate results. If the data collection limits are set incorrectly, you might truncate large peaks or miss small peaks. This is particularly problematic when performing area percent calculations.


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