SAMPLE PREPARATION AND PROCESSING For food commodities, the Codex MRLs refer to the specified portion of the

5.3 SAMPLE PREPARATION AND PROCESSING For food commodities, the Codex MRLs refer to the specified portion of the

commodity which is analyzed. 14 The preparation of the analytical sample* may require removal of foreign materials and certain parts of the sampled material (such as shell of nuts, stone of mango or peach, adhering soil, outer withered loose leaves in case of plant materials, and peddles and remains of plants from soil, etc.). These procedures may significantly affect the residue level. As they cannot be

* The material prepared for analysis from the laboratory sample, by separation of the portion of the product to be analyzed.

Quality Assurance 137 validated and their contribution to the uncertainty of the results cannot be estimated,

the sample preparation procedure should be clearly written and consistently followed without any deviation to obtain comparable results.

The residues in individual crop units are not uniformly distributed. Therefore the whole laboratory sample must be prepared and the entire analytical sample should be chopped, ground, or mixed to obtain a well-mixed material from which the repre- sentative test portions can be withdrawn for extraction. The large crops making up the laboratory sample (e.g., five watermelons) may not be processed together due to the limited capacity of the equipment. In these cases, representative portions should

be cut from the individual units in such a way that the ratio of the surface and inner part remains the same. The efficiency of the comminuting procedure depends on the equipment, matur- ity, and variety of the crops, but it is independent of the concentration and nature of the analyte, and the extraction method. The efficiency of processing is characterized with CV Sp (Equation 5.2). It is more difficult to obtain a well-mixed matrix from plant materials with hard peal and soft pulp (tomato) than from a soft fruit (orange). The homogeneity (well-mixed status) of the processed analytical sample cannot be verified with the usual recovery studies. It should either be tested with samples 29 treated with pesticides according to the normal practice, or a small part of the

surface of the crops should be treated with suitable test compounds. 30

A third alternative is to treat a small portion of the sample matrix with the test compound and then mix it with the rest of the sample. 16

The uncertainty of sample processing can be quantified as part of the method validation by applying fully nested or staggered nested 31 experimental design and evaluating the results with ANOVA. The scheme of the process is very similar to that shown in Figure 5.1. In this case, uncertainty information can be obtained only for the size of the test portion. If the expectable uncertainty should be determined for a given range of test portion size to optimize the analytical procedure, the concept of

sampling constant 29 can be used. The sampling constant, K

s , is defined as

( 5:5) where m is the mass of a single increment and CV is the relative standard deviation

¼ mCV 2 ,

of the concentration of the analyte in the test portions of size m. If the analytical sample is well-mixed, the sampling constant should be the same for small (Sm) and large (Lg) portions, and Equation 5.5 can be written as

( 5:6) If the ratio of S 2 Sm m Sm =S Lg 2 m Lg is smaller than the critical F value, the processed

m Sm S 2 Sm ¼m Lg S 2 Lg :

sample can be considered well-mixed, and the expected sample processing uncer-

Sm .

The acceptable variability of sample processing depends on the variability of the other steps of the determination. When the combined uncertainty of the meas- urement results should include the sampling uncertainty, then the CV Sp should be

8% –10% depending on the crop analyzed. Where only the CV L is taken into

138 Analysis of Pesticides in Food and Environmental Samples account, the CV Sp should be less than 0.25 –0.3 3 CV A . Under these conditions, the

sample processing will not significantly contribute to the combined uncertainty of the measurement.

The efficiency of sample processing depends on, among others, the type and variety of the sample and the implementation of the process. As it can be a significant contributor to the combined uncertainty, it should be tested regularly as part of the performance verification of the laboratory phase of the determination of pesticide residues. It can be most economically carried out with the reanalysis of the replicate test portions of samples containing the analyte in a different analytical batch. The within laboratory reproducibility of the procedure (CV L ) can be calculated with Equation 5.4. As it was shown in Section 5.2.3, a minimum of 20 measurement pairs are needed to obtain a reliable estimate.