Addendum
No.
1
to
MRID
#
421698­
44
DER
Study
Title:
Hardies,
D,
1991.
An
aerobic
soil
metabolism
study
with
S­
23031,
an
experimental
herbicide.
Guideline
Number:
162­
1
Reasons
for
changes:


Upgrade
of
status
from
(
Upgradable,
Unacceptable)
to
Acceptable.
Specify
why

Recalculation
of
t
1/
2
values.
Specify
why

Recalculation
of
Koc
values.
Specify
why

Identification
of
degradates

Others
Half­
life
was
recalculated
to
include
the
degradate
IMCA,
or
flumiclorac­
acid,
along
with
the
parent,
flumiclorac­
pentyl,
for
use
in
the
Drinking
Water
Assessment.
Calculation
was
on
the
basis
of
applied
radiation
(%
AR),
and
was
done
with
SigmaPlot,
using
2­
parameter,
single
first­
order
(
SFO/
2)
procedure.
This
study
was
for
test
compound
labeled
in
the
phenyl
ring.

Results
Procedure
Half­
life
or
DT50
3*
half­
life
or
DT90
Intercept
p­
value,
R2
Empirical
4
to
7
days
>
85
days
100.1
%
AR
­­

SFO/
2
8.04
days
24.1
days
94.7
%
AR
0.0005,
0.906
Revised
by
:
____________________________
Date:
____________

Secondary
reviewed
by:
___________________
Date:
___________

­­
August
2000
 
MRID
42169844
aerobic
soil
metabolism
of
flumiclorac
pentyl
(
S­
23031)

day
parent
IMCA
sum
0
100.1
0
100.1
0.0833
74.8
24.2
99
0.25
66.2
31.3
97.5
0.5
45.5
49
94.5
1
33.4
53
86.4
2
20.1
51.4
71.5
4
18.8
37.4
56.2
7
17.8
20.6
38.4
14
17.2
16
33.2
28
12.1
9.1
21.2
30
14.1
7.8
21.9
56
13.7
3.7
17.4
85
13.2
1.8
15
parent
+
IMCA
by
SFO/
2
days
0
20
40
60
80
100
%
AR
0
20
40
60
80
100
120
x
column
2
vs
y
column
2
MRID
42169844
aerobic
soil
metabolism
of
flumiclorac
pentyl
(
S­
23031)
vs
Col
4
Nonlinear
Regression
[
Variables]
x
=
col(
1)
y
=
col(
4)
reciprocal_
y=
1/
abs(
y)
reciprocal_
ysquare=
1/
y^
2
'
Automatic
Initial
Parameter
Estimate
Functions
xnear0(
q)=
max(
abs(
q))­
abs(
q)
yatxnear0(
q,
r)=
xatymax(
q,
xnear0(
r))
[
Parameters]
a
=
yatxnear0(
y,
x)
''
Auto
{{
previous:
94.7265}}
b
=
­
ln(.
5)/(
x50(
x,
y)­
min(
x))
''
Auto
{{
previous:
0.0862027}}
[
Equation]
f=
a*
exp(­
b*
x)
fit
f
to
y
''
fit
f
to
y
with
weight
reciprocal_
y
''
fit
f
to
y
with
weight
reciprocal_
ysquare
[
Constraints]
b>
0
[
Options]
tolerance=
0.0001
stepsize=
100
iterations=
100
R
=
0.95189399
Rsqr
=
0.90610217
Adj
Rsqr
=
0.89756601
Standard
Error
of
Estimate
=
11.1222
Coefficient
Std.
Error
t
P
a
94.7265
5.0126
18.8976
<
0.0001
b
0.0862
0.0179
4.8239
0.0005
Analysis
of
Variance:
DF
SS
MS
F
P
Regression
1
13131.0041
13131.0041
106.1486
<
0.0001
Residual
11
1360.7436
123.7040
Total
12
14491.7477
1207.6456
PRESS
=
1769.2214
Durbin­
Watson
Statistic
=
0.3666
Normality
Test:
Passed
(
P
=
0.2200)

Constant
Variance
Test:
Failed
(
P
=
0.0018)

Power
of
performed
test
with
alpha
=
0.0500:
1.0000
Regression
Diagnostics:
Row
Predicted
Residual
Std.
Res.
Stud.
Res.
Stud.
Del.
Res.
3
94.7265
5.3735
0.4831
0.5412
0.5230
4
94.0487
4.9513
0.4452
0.4962
0.4785
5
92.7069
4.7931
0.4309
0.4760
0.4586
6
90.7304
3.7696
0.3389
0.3703
0.3552
7
86.9029
­
0.5029
­
0.0452
­
0.0486
­
0.0464
8
79.7254
­
8.2254
­
0.7395
­
0.7876
­
0.7731
9
67.0999
­
10.8999
­
0.9800
­
1.0683
­
1.0760
10
51.8096
­
13.4096
­
1.2057
­
1.4059
­
1.4801
11
28.3366
4.8634
0.4373
0.5386
0.5204
12
8.4767
12.7233
1.1440
1.2265
1.2587
13
7.1343
14.7657
1.3276
1.4043
1.4780
14
0.7585
16.6415
1.4962
1.4994
1.6028
15
0.0623
14.9377
1.3431
1.3431
1.4006
Influence
Diagnostics:
Row
Cook'sDist
Leverage
DFFITS
3
0.0373
0.2031
0.2641
4
0.0298
0.1951
0.2356
5
0.0250
0.1805
0.2152
6
0.0133
0.1621
0.1563
7
0.0002
0.1362
­
0.0184
8
0.0416
0.1183
­
0.2831
9
0.1075
0.1585
­
0.4670
10
0.3556
0.2646
­
0.8878
11
0.0750
0.3408
0.3742
12
0.1125
0.1301
0.4868
13
0.1172
0.1063
0.5096
14
0.0048
0.0043
0.1050
15
0.0001
0.0001
0.0114
95%
Confidence:
Row
Predicted
Regr.
5%
Regr.
95%
Pop.
5%
Pop.
95%
3
94.7265
83.6938
105.7592
67.8754
121.5777
4
94.0487
83.2363
104.8612
67.2874
120.8101
5
92.7069
82.3065
103.1073
66.1093
119.3045
6
90.7304
80.8745
100.5863
64.3410
117.1198
7
86.9029
77.8674
95.9383
60.8088
112.9970
8
79.7254
71.3063
88.1445
53.8383
105.6126
9
67.0999
57.3537
76.8462
40.7512
93.4486
10
51.8096
39.2172
64.4020
24.2808
79.3383
11
28.3366
14.0452
42.6281
­
0.0096
56.6829
12
8.4767
­
0.3542
17.3075
­
17.5473
34.5007
13
7.1343
­
0.8458
15.1144
­
18.6134
32.8820
14
0.7585
­
0.8411
2.3582
­
23.7735
25.2906
15
0.0623
­
0.1366
0.2611
­
24.4184
24.5429
