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Quality Assurance How do you know your results are correct? How confident are you?

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Presentation on theme: "Quality Assurance How do you know your results are correct? How confident are you?"— Presentation transcript:

1 Quality Assurance How do you know your results are correct? How confident are you?

2 Quality Assurance Questions How do you sample the unknown in the field (this may be developed by a field analyst) and store them until lab prep and analysis? What levels of analyte do you need to measure? pg, ng,  g Based on above and the properties of the analyte, how will you measure it? RIA, NIR, UV, RI, etc What are desired selectivity and sensitivity? How do you conduct sample preparation? What are acceptable accuracy and precision values?

3 Quality Assurance Process What is an acceptable number of false negatives and false positives? What results are acceptable for a blank? If you have a complex sample prep with extractions, how do you verify %-recoveries? If your unknown samples have a complex matrix, how do you verify that the matrix is not interfering with the analysis? Do you run an instrument check to verify the instrument is working with its specifications? What calibration checks will you run? Will you run some reference standards or quality control samples to verify accuracy?

4 Definitions Selectivity: this is the ability of your instrumental method to see your analyte without interference from other substances. Sensitivity: mathematically, this is the slope of the calibration curve, so is the change in the instrument signal or response as the analyte concentration changes.

5 Definitions Signal to Noise Ratio, S/N: this is defined as: S/N = H/h H is the height of the analyte peak h is the absolute value of the largest noise fluctuation measured from the baseline of a blank solution.

6 Definitions Limit of Detection or Detection Limit: the lowest analyte level that the method can measure as being different than a blank. It is the amount injected that will give a signal which is twice the noise level. S/N = 2 A mathematical description: x – x b = 3s b where x is the analyte signal at the minimum detectable concentration, x b is the signal of the blank, and s b is the standard deviation of the blanks.

7 Definitions Lower Limit of Quantitation: the lowest concentration of analyte that can be accurately and precisely measured. It is the signal which is 10 (to 20) times the noise level. Calibration blank: the solution used for creating the zero concentration point of the calibration graph; this solution contains only the diluents used for making the standard solution.

8 Definitions Reagent blank: a blank solution that contains all the reagents used to dissolve the samples; the reading for this solution may be subtracted from sample readings or it may be plotted as a point on the calibration curve. Method blank: a blank solution that has gone through all the steps of the sample preparation. It is used to monitor any type of contamination taking place during the sample preparation.

9 Definitions Matrix: Everything in the unknown sample, except for the analyte. Spike: a known amount of the analyte that is added to a sample. The amount of analyte measured in the sample without the spike and with the spike should differ by the spiked amount. This can test for matrix effects.

10 Definitions Calibration Checks: samples of known concentration that are injected throughout the run to check the instrument response and to check the calibration curve. Blind Samples or QC Samples: these are samples that have a known concentration but the analyst does not know what the concentration is. This can eliminate analyst bias. Robust Method: this is a method which is not affected by small environmental and instrumental fluctuations. So slight temperature, pH changes would not affect the instrument signal.

11 Calibration Methods Most analysts prefer to use calibration standards to generate a linear (or nonlinear) curve. This curve shows the relationship between signal and analyte concentration. This is the external standard method. However, there are cases where an external standard calibration curve can not accurately and precisely measure the concentration of an analyte.

12 Calibration Methods Complex matrices are a common example of when external standard methods may fail. Complex matrices like soil or plasma contain many substances that can’t be entirely removed during the sample prep process, and they may interfere with the analyte analysis in several ways.

13 Calibration Methods Another problem is variations in the sample preparation that can’t be entirely eliminated. So slight differences in sample handling may lead to inaccurate analysis. If the method is not as robust as could be desired, there may also be differences in signal due to fluctuations in variables like the flow rate.

14 Calibration Methods When conditions like the above are present, there are 2 other methods that may be used: –Method of Standard Addition –Internal Standard Method

15 Internal Standard Method This calibration method is useful for very long run times, when different analysts run the samples, and when the sample preparation procedure leads to variablility. It involves the addition of a separate compound (the internal standard) in constant amounts to all of the unknowns and analyte standard solutions. This may be done prior to sample prep. The samples are then prepared and injected.


17 Internal Standard Method For the standards, the ratio of the analyte response over the internal standard response is then calculated: this is called the response ratio. The response ratio is plotted versus the concentration of the analyte in the standards. This graph then gives the calibration factor, F.

18 Internal Standard Method The actual concentration of the analyte in the unknowns is then calculated: There are disadvantages to this method. It can actually lower the precision as there is a second component present.

19 Method of Standard Additions This calibration method is generally used when the unknowns have complex matrices. The response of the unknown is measured normally. A known quantity of the analyte is then added to the unknown sample. The added amount is small yet concentrated to avoid changing the matrix.

20 Method of Standard Additions The response of the unknown should increase proportionally to the amount of analyte added. Usually, we add different amounts of the analyte to the unknown so we have more than 1 point.


22 Method of Standard Additions This gives a mathematical equation and graph for Standard Addition Method. The x-intercept of the graph is the initial concentration in the unknown.


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