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ournal of
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nternational
V
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o.
5, 2015
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the measured concentration of these pesticides in the sample
was lower than the minimum concentration point calculated
(Calc. Conc.) of matrix standard curve and did not report the
result, thus causing the quantification results at the low end
of the calibration curves to show large and variable within-
laboratory SDs. Some laboratories (e.g., Laboratory 21) did not
report the test results when they found pesticide concentrations
in the samples to be lower than the minimum concentration
point of the calibration curves. In hindsight, the Study Director
thinks the laboratories that did not report the test results should
have designed the experiments better to include a much lower
minimum concentration point on the calibration curves (e.g.,
being 50% of fortification concentrations) than were designed
in this collaborative study, and they should have tried to ensure
that the concentrations of pesticide residues in the samples after
extraction were still above the minimum concentration points of
calibration curves.
While these issues became apparent during the collaborative
study, theywere not seen as an issue during the SLVof themethod
in which very good recoveries and precision were obtained for
samples fortified at concentrations where the minimum point on
the calibration curves used for quantification was 80% of the
fortification concentrations of samples (
see
Table 8). Therefore,
the Study Director hopes to pay more attention in any future
organization of or participation in a collaborative study to
this oversight and take appropriate measures to minimize its
occurrence again in a future study design.
(c)
Method extraction efficiency and reproducibility for aged
samples
.—The method efficiency parameters such as recovery,
RSD
R
, RSD
r
, and HorRat values in Table 9 are summarized in
Table 10 per sectors.
(
1
)
By GC/MS.—
The results of the statistical analysis of data
obtained from the analysis of the 20 pesticides in aged oolong
tea samples in Table 10 show that for the 16 collaborating
laboratories using GC/MS, all the pesticides demonstrated
within-laboratory repeatability RSD
r
<8%, between-laboratory
reproducibility RSD
R
<25%, and HorRat values less than 1.0.
(
2
)
ByGC/MS/MS.—
For the 14 collaborating laboratories using
GC/MS/MS, all the pesticides demonstrated within-laboratory
repeatability RSD
r
<15%, while only six of the 20 (30%)
pesticides demonstrated between-laboratory reproducibility RSD
R
<25%. Seventy percent (70%) of the 20 pesticides had between-
laboratory reproducibility RSD
R
>25%. The HorRat values for all
the pesticides were less than 2.0.
(
3
)
By LC/MS/MS.—
The within-laboratory repeatability
RSD
r
for the 24 laboratories using LC/MS/MS was <15% for
all the pesticides, and the between-laboratory reproducibility
RSD
R
was <25% for only eight of the 20 pesticides. The other
12 (60%) pesticides showed between-laboratory reproducibility
RSD
R
>25%. The HorRat values were <2.0 for all 20 pesticides.
The probable explanation for the large variability in
RSD
R
>25% for some of the pesticides in aged oolong tea in
the GC/MS/MS and LC/MS/MS analyses may be traced to just
how aged samples are prepared. They are prepared by spraying
pesticides onto dry tea powders in advance, which are then
mixed uniformly. In a certain period after sample preparation,
pesticides in tea slowly degrade during storage and transit, so
in our SLV at an earlier stage a two-phase study was conducted
to measure the rate of decrease in concentration of pesticides
Table 3. Comparision of the deviation rate of calculated concentration and expected concentration at the minimum
concentration point for LC/MS/MS matrix matched calibration curve for Laboratory 20
Oolong tea calibration curve
No.
Pesticide
Expected concn, μg/kg Calculated concn, μg/kg
Difference
Deviation ratio, %
1
Imidacloprid
18.0
14.2
3.8
21.1
2
Propoxur
20.0
29.3
−9.3
−46.3
3
Monolinuron
8.0
8.9
−0.9
−10.9
4
Clomazon
8.0
5.5
2.5
31.7
5
Ethoprophos
8.0
3.6
4.4
55.0
6
Triadimefon
8.0
4.8
3.2
39.8
7
Acetolachlor
16.0
7.2
8.8
55.0
8
Flutolanil
8.0
5.9
2.1
25.9
9
Benalaxyl
8.0
5.7
2.3
28.6
10
Kresoxim-methyl
80.0
69.5
10.5
13.1
11
Picoxystrobin
8.0
3.3
4.7
58.8
12
Pirimiphos-methyl
8.0
6.4
1.6
19.8
13
Diazinon
8.0
5.9
2.1
25.9
14
Bensulide
24.0
16.3
7.7
32.1
15
Quinoxyfen
40.0
49.0
−9.0
−22.4
16
Tebufenpyrad
8.0
6.9
1.1
13.7
17
Indoxacarb
8.0
9.0
−1.0
−13.0
18
Trifloxystrobin
8.0
7.3
0.7
8.3
19
Chlorpyrifos
80.0
110.0
−30.0
−37.5
20
Butralin
8.0
10.2
−2.2
−26.9