Understanding Adiption Curves in Analysis

Analogies (curves of adiption) are like rulers. If the ruler is broken, you can still use it as long as you measure from the 10cm mark, right? Just measure from 10cm, counting as 0.

The analitical curve is a linear scale. So, if an object measures 12cm, you would know that it has 2cm and wouldn't need to recalibrate the ruler, subtracting 10 from all the measurements. This is because the linear scale is unchanging throughout the measurement.

The adiption curve has a different characteristic: the signal from the sample is superimposed on the signal from the standard, with the exception of the first balloon. Both signals are affected nonlinearly (multiplyively) because of the matrix, which means that the inclination of the curve is affected.

When you don't have matrix interference, the signal is simply moved linearly upwards in 10 units for each balloon. The reason for the matrix affecting the signal is dependent on the technique being used for analysis.

Thus, the adiption curve has an equation y = mx + k where m is the constant amount of analog data in each balloon, x is the point on the curve where y equals mx, and k is the negative of mx. You want to determine x, which is the concentration of the analog data in the sample that's present in all the balloons.

This way, your curve's equation becomes y = mx + k - sb, where sb is the signal from the white balloon. If you don't subtract the white balloon's signal, your curve's equation becomes y = mx + k.