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The standard additions method (often referred to as "spiking" the sample)
is commonly used to determine the concentration of an analyte that is
in a complex matrix such as biological fluids, soil samples, etc. The
reason for using the standard additions method is that the matrix may
contain other components that interfere with the analyte signal causing
inaccuracy in the determined concentration. The idea is to add analyte
to the sample ("spike" the sample) and monitor the change in instrument
response. The change in instrument response between the sample and the
spiked samples is assumed to be due only to change in analyte concentration.
The procedure for standard additions is to split the sample into several
even aliquots in separate volumetric flasks of the same volume. The first
flask is then diluted to volume with the selected diluent. A standard
containing the analyte is then added in increasing volumes to the subsequent
flasks and each flask is then diluted to volume with the selected diluent.
The instrument response is then measured for all of the diluted solutions
and the data is plotted with volume standard added in the x-axis and instrument
response in the y-axis. Linear regression is performed and the slope (m)
and y-intercept (b) of the calibration curve are used to calculate the
concentration of analyte in the sample.
From the linear regression: S = mVS + b [Equation
1]
Where: S
= instrument response (signal)
VS
= volume of standard
Conceptually, if the curve started where the instrument response is zero,
the volume of standard [(Vs)0]
from that point to the point of the first solution on the curve (x = 0)
contains the same amount of analyte as the sample. So:
Vxcx
= |(VS)0|cS
[Equation 2]
Where:
Vx = volume of the sample
aliquot
cx = concentration of the sample
cs
= concentration of the standard
Combining Equation 1 and Equation 2 and solving for cx
results in:

And one can then calculate the concentration of analyte in the sample
from the slope and intercept of the standard addition calibration curve.
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