2. AOACRIChemContMethods-2018Awards

1446 Pang et al.: J ournal of AOAC I nternational V ol. 98, N o. 5, 2015

Table 10. Distribution range of RSD r

, RSD R

, and HorRat values for aged samples

Parameters of method efficacy

RSD r

, %

RSD R

, %

HorRat

Range

<8

8–15

>15

<16

16–25

>25

<0.50 0.50–1.00 1.01–2.00 >2.00

GC/MS (16 laboratories)

20(100) a

Oolong tea

0

0

18(90)

2(10)

0

1(5)

19(95)

0

0

GC/MS/MS (14 laboratories)

Oolong tea

19(95)

1(5)

0

0

6(30)

14(70)

0

0

20(100)

0

LC/MS/MS (24 laboratories)

Oolong tea

15(75) 54(90)

5(25) 6(10)

0 0

0

8(40)

12(60) 26(43)

0

8(40)

12(60) 32(53)

0 0

Total

17(28)

17(28)

1(2)

27(45)

a Data in parentheses are the percentages.

are 20–50% higher than those from other laboratories. Review of the experimental raw data record found that this laboratory established the matrix calibration curves on June 8, 2013 and then the fortified sample of green tea (No. 1 and No. 2) and oolong tea (No. 6 and No. 7) were analyzed, while No. 4 and No. 5 green tea incurred samples and No. 9 and No. 10 aged samples were tested on June 12, 2013 with an interval of 4 days. Exact reasons that caused such deviations failed to be found in the raw data record, and it is assumed that during this 4 day interval instrument conditions had possibly changed, which may be the cause of such systematic deviations. The collaborator considered that his instrument was stable since comparison of a QC sample had been conducted, but no reasonable explanation has been yet offered for the cause of such errors. Laboratory 19 did not carry out continuous inspection of samples after establishing calibration curves, with a time interval of 4 days before continuing inspection, which led to the results from this laboratories 20–50% higher than those from other laboratories. Such practice is not recommended by the Study Director, who points out that the matrix-matched calibration standards should be prepared and used ONLY for the quantitative analysis of the samples prepared at the same time under the same conditions. As far as this point is concerned, Laboratory 19 deviated from the collaborative study operational procedures unconsciously, which inevitably led to relatively large deviations in test results compared to those from other laboratories. (b)  By GC/MS/MS.— Supplemental Tables 20, 22, and 23 show that 1704 effective data were obtained from determination of 20 pesticides in eight samples (excluding two blank samples) by 14 laboratories; Grubbs and Dixon test inspection was adopted, and 65 outliers were found (making up 3.8%). Sixty-five outliers came from 11 laboratories, of which 25 were from Laboratory 21, accounting for 38.5% of the total outliers; 19 from Laboratory 18, making up 29.2% of the total outliers; and seven from Laboratory 27, making up 10.8% of the total outliers. Outliers from these three laboratories total 51, accounting for 78.5% of the total outliers; outliers from eight other laboratories total 14, only making up 21.5%, and outliers from each laboratory are less than three due to accidental errors. Regarding Laboratory 21, there are 23 of 25 outliers from No. 6 and No. 7 oolong tea fortification samples, and the analytical results from these two samples are 40% lower than those from other laboratories. In addition, there are very big

( 2 )  GC/MS/MS.— Regarding GC/MS/MS: 14 laboratories established 556 matrix-matching ISTD calibration curves, respectively, for 20 pesticides in green tea and oolong tea, among which those with R 2 ≥0.995 reached 549, making up 98.7%; seven had R 2 between 0.990 and 0.995, accounting for 1.3%, and none R 2 less than 0.990. ( 3 )  LC/MS/MS.— Concerning LC/MS/MS, 24 laboratories established 958 matrix-matching ISTD calibration curves, respectively, for 20pesticides ingreen tea andoolong tea samples, among which those with R 2 ≥0.995 reached 893, accounting for 93.2%; 34 had R 2 between 0.990 and 0.995, making up 3.7%, and 11 R 2 <0.990, making up 1.2%. The above-mentioned data show that there are 2079 with R 2 ≥0.995 out of the 2153 matrix-matching ISTD curves established by 29 laboratories, accounting for 96.6%. It demonstrates that the matrix-matching ISTD calibration curves adopted for the method are capable of realizing accurate quantification for the majority of pesticides by different laboratories using three different types of instruments. The 6638 effective data derived in this study were inspected with Grubbs and Dixon tests for outliers, with 187 outliers obtained, accounting for 2.8%. The distribution of outliers derived from these three methods, GC/MS, GC/MS/MS, and LC/MS/MS, for different teas, different pesticide varieties, and different samples are tabulated in Supplemental Tables 19–21. The outliers from 10 samples of three categories determined by the three different methods for two teas in Supplemental Table 19–21 are summarized and tabulated in Supplemental Table 22. Distribution of outliers for different laboratories and different samples is listed in Supplemental Table 23. (a)  By GC/MS.— Supplemental Tables 19, 22, and 23 show that each of 16 laboratories analyzed 20 pesticide residues in eight samples (excluding two blank samples) and obtained 1977 effective data; the application of Grubbs and Dixon tests revealed 65 outliers making up 3.3%. They came from 11 laboratories, with 32 from Laboratory 19, accounting for 49.2% of the total outliers; outliers from other 10 laboratories are 33, making up 50.8%, and outliers from each of these laboratories are less than eight, due to accidental deviations. Thirty-two outliers from Laboratory 19 all came from No. 4 and No. 5 green tea incurred samples and No. 9 and No. 10 oolong tea aged samples. Test results from these four samples Error Analysis and Traceability