As you said, there are different approaches to doing this. In analytical labs, often we use %RSD from accuracy and/or precision tests to show uncertainty results. This is not necessary (only) what a mathematician would call an uncertainty test, however, that's a common practice in labs.

Simplest way to do accuracy is by preparing solutions with known amounts of your anayte (pesticide) added to your matrix. For precision, you just run your sample analysis 6 times and calculate your 1) relative standard deviation (standard deviation * 100 / average), 2) individual results, and 3) average result.

Normally, accuracy solutions are prepared in at least 3 ranges such as 50%, 100% (target/expected) and 150% range of your target concentration. Ranges may be adjusted as needed. You also prepare triplicates of each range (9 total) and one unpiked/control to subtract any analytes (pesticides) in your matrix. The data you need is 1) Analyte recovered (experimental amount from your raw data, 2) % Recovery (experimental amount * 100/theoretical or spiked amount), 3) Average recovery of the triplicates, and 3) %Relative Standard Deviation (standard deviation * 100 / average recovery).

Hi, I think you can read this guidance of European Commission on p 31.

https://ec.europa.eu/food/sites/food/files/plant/docs/pesticides_mrl_guidelines_wrkdoc_2017-11813.pdf

Dear M. D.H. Prodhan,

Unfortunately the question is not so easy. First of all you should understand which uncertainty you want to estimate because you can estimate uncertainty of instruments (GC LC) or methods (including sample preparation) or routine analysis.

As described above to estimate uncertainty of instrument you should prepare one solution (100 % target concentration) and perform 6 injection (it can be more, everything depends on time and resource which you have) and calculate RSD of analytical signal.

If you want to estimate the uncertainty of methods you should prepare 9 model solutions which include your analyte with matrix (placebo) and perform the determination of analyte and calculate RSD of find concentration.

However, I would like to pay your attention that several kind of uncertainty source influence on uncertainty of procedure. In general, all of them can divide into 3 groups: Controlled, Experimental and Noise. Unfortunately, predict the all noise sources impossible therefore uncertainty of procedure which you estimated by the 2nd way it is only approximate value. Routine uncertainty of procedure will be more, sometimes in several times.

So if you want to estimate for example uncertainty of procedure in routine analysis you should design experiment of evaluation uncertainty during routine analysis during a long period (to give possibility to face with noise uncertainty sources).

Kind regards,

Vasyl Petrus

Dear vasyl Petrus,

Thanks for your answer. But, I want to estimate combined uncertainty. I know how to calculate Accuracy and precision. And after that by using which easiest formula I will estimate combined uncertainty.

If I correctly understand your question then the easiest way to calculate the uncertainty is:

U = RSD x t (P; n - 1)

where U - is uncertainty,

RSD - relative standard deviation of 9 results of Recovery (for example, from accuracy).

t - Student coefficient

P - probability, ussualy 95 %.

n - number of Recovery results, in this case 9.

I hope I give you correct answer.

If I did not correct understand you would excuse me in advance and please do not hesitate me to ask.

Dear Vasyl Petrus,

Thanks for your answer. I am grateful to you. Could you please give me the ref. Of the used formula.

1 JCGM 100:2008. Evaluation of measurement data – Guide to the expression of uncertainty in measurement. The Joint Committee for Guides in Metrology, 2008. 120 p.

2 EURACHEM/CITAC Guide CG 4 QUAM:2012.P1. Quantifying Uncertainty in Analytical Measurement, 2012. 133 p.

3 EURACHEM/CITAC Guide STMU 2015. Setting and Using Target Uncertainty in Chemical Measurement, 2015. 24 p.

I hope it should be enough

Dear Vasyl Petrus,

Thanks a lot. Indeed it will be very much helpful for me.

Vasyl Petrus , thank you for these resources. I didn't know about them for nowadays, but they`ll been useful in my work and further research.

Dear Olena Bevz,

Thank you so much for your active participation in this fruitful discussion and also providing your valuable comments.