How to calculate LOD and LOQ from a nonlinear regression curve equation (quadratic y=ax^2 + bx + c) obtained from UV-Vis measurements.
Dear Ali Serol Ertürk,
LOD (and LOQ) are also calculated based on the standard deviation as the analyte concentration giving a signal equal to the blank signal, yB, plus three standard deviations of the blank, sB.
The standard deviation from a nonlinear regression curve equation (quadratic y=ax^2 + bx + c) can be calculated by Equation (8) of the attached manuscript.
Best regards,
Elcio Oliveira
Dear Elcio Oliveir,
Thank you for your answer.
We have tried to solve this problem by using the following procedure.
1) Take ten blank UV measurements (n=10).
2) Calculate “sB” from the blank measurements.
3) From the known values of the x (concentrations) and y (responses) we can drive the quadratic equation y=ax^2 + bx + c, and late on, calculate the roots from the equation you suggested by hand. However, for the simplicity of the dissolution of the equation you suggest, we preferred to use software, origin. For this solution, we used the x values as the ordinate values and y values as abscissa values, therefore, we have driven a quadratic equation in the form of x=ay^2 + by +c from the software
4) Calculate a signal equal to the blank signal, yB (average), plus three standard deviations of the blank measurements (n=10)
5) Then, from the defined equation in origin (x=ay^2 + by +c), calculate directly the LOD value by using the signal y value we calculated.
6) for the calculation of the LOQ, use 10 fold of sB, and drive LOQ.
Considering our solution procedure (resulting the same result with the your suggested equation), what do you think…?
Dear Ali Serol Ertürk,
I understand that are two accetable different approaches. The results must be close but not the same.
I suppose that the approach I have sent to you, be more laborious but more realistic than the other that certainly is simpler.
Your sincerely,
Elcio Oliveira
Dear E. C. de Oliveira,
Thank you again for your valuable suggestion and discussion.
Best regards,
Ali Serol Ertürk
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