Transcript Document 7362672

ELANCO SYMPOSIUM
Medellin, Columbia
23 July 2009
Todd Frank Director of Manufacturing
Micro-Tracers, Inc. San Francisco, Ca. USA
ELANCO SYMPOSIUM

Microtracer FS-Red/Natural Yellow
Used by ELANCO to Code
RUMENSIN
Micro-Tracers,Inc. a Qualified
Supplier

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
Founded 1961, operated under same
management.
Financially stable, committed to
research.
Associated with Anresco,Inc. (1943)
commercial analytical laboratory.
What Are Microtracers ™ ?


Many Microtracer variations. First came
Microtracers S – colored salt then G
colored graphite.
Microtracers F, FS and RF are colored
iron grits, stainless steel grits and
reduced elemental iron powder.
History of Micro-Tracers Inc

Founder (1961)–Dr.
Sylvan Eisenberg
President, Mr. David
Eisenberg, MBA
MICROTRACERS
What Is FS-Red/Natural Yellow?
Stainless steel particles

Coated with food grade dye.

Same size.

Guaranteed particle number per gram.
Quality of Microtracers
Sieve Analysis.
 Particle Counts.
 Color Analysis.
 Periodic testing for dioxins
(none found) and for arsenic.

The Use of Microtracers in
Rumensin
Coding Rumensin and Feeds
Containing it as Proprietary
Providing a Value Added “Quick Test”
for Rumensin In Feeds to be used by Feed
Manufacturers and Elanco Technical
Support Personnel.
Coding Rumensin as Proprietary
Qualitative Test: Mash feed =one minute
Pelleted feed= two minutes
Quantitative Test: Counting colored spots
:Some skill required = 5 minutes
Test
Rumensin and Third party pre-mixes first.
Coding Rumensin as Proprietary As Value
Added Benefit to Feed Manufacturers
Allow immediate confirmation Rumensin
has been added to feed.
Permit validation of mixer performance by
taking/analyzing a series of samples from one batchor one sample from each on many batches
Permit validation of cross
contamination control procedures
Coding Rumensin as Proprietary
Microtracer FS-Red Natural Yellow is
Exclusive to Elanco
Stable in Rumensin premix
Not with Confused by other Microtracers
Coding Rumensin as
Proprietary Quantitative Use
Preciseness of Test Requires Counting More
Particles
Poisson statistics: Count has inherent standard
Deviation equal to it’s square root
100 particles =± 10 Standard Deviation
± 10% Coefficient of Variation
25 particles= ±5 Standard Deviation
±20% Coefficient Variation
Analytical Procedure
1.
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2.
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Mason Jar Technique.
Qualitative.
Rotary Detector Technique.
Qualitative and Quantitative.
C-1A/ Mason Jar Technique
Mason Jar Technique.
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Materials
500 ml Mason Jar
Scale
Developing solution
Filter paper (70 mm)
Grinder for pelleted
feed.
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Test Method
Weigh 100 g sample
Insert filter paper
into the magnetic
cap and close jar.
Shake jar so sample
contacts filter paper
Spray developing
Solution and identify
the color of the
Microtracer™ Spots.
Mason Jar Technique
Mason Jar Technique
Mason Jar Technique
Mason Jar Technique
Mason Jar Technique
Rotary Detector Technique.
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Materials
Rotary Detector.
Scale.
Demagnetizer.
Heating plate.
Developing Solution.
Filter paper 7.5 mm
Grinder for pelleted
feed
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Test Method
Weigh 100 g sample
Place filter paper on the
spindle of the rotary
magnet.
Transfer the sample of feed
to the top hopper of the
Rotary
Transfer the Microtracer™
to a scoop, demagnetize,
then disperse over a large
wetted filter paper on an
aluminium plate. Then dry
on hot plate to develop
spots. Count the spots.
Rotary Detector Technique
Rotary Detector Technique
Rotary Detector Technique
Rotary Detector Technique
Rotary Detector Technique
FS-Red/ Natural Yellow
Spots Developed with 50% Water and Alcohol
Coding Rumensin as
Proprietary Quantitative Use
Errors
Tracer count not precise per lot ±10% CV
Tracer recovery from mash feed in mixer 100%
Mash feed at truck 85%
Pelleted feeds 70%
Coding Rumensin as Proprietary:
Quantitative Use
Losses in Feed Manufacturing
5% to each feedmill magnets
5% to abrasion in mixing
5% to dissolution during steam pelleting
5% abrasion in grinding pellets to
mash for analysis
ELANCO SYMPOSIUM
Use of Microtracers in
Validating Feed Mixing
 Control of Cross
Contamination

Estimating the Level of Rumensin in Finished Feeds
from Microtracer® Particle Count

100 grams
500 grams
Expected Tracer Count
Feed from Mixer- 100% Tracer recovery
12± 3.5 or ± 30%*
Feed from truck-mash- 85% recovery
10±3.2 or ±32%
53 ±7 or ±14%
8±2.7 or ±34%
43 ±6 or ±15 %
Feed from truck- pellets- 70% recovery
62 ±8 or ±13%
*Coefficient of Variation (CV) based on one standard deviation range
(67% likelihood of actual count falling in range) For two SD range
(95% likelihood) double CV.
** Qualitatively, the likelihood of obtaining no tracer if the actual
expected count is 8 particles is less than 1 in 400 test.
Critical Issues to Consider in
Relying Upon Microtracer Test
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*The test must be run properly. You must use the
correct developer.(50% ethanol is the correct
solvent to develop Rumensin tracer spots.
* Run a “control positive” each day, a feed known
to contain Rumensin-to confirm you find
Microtracer from the feed you know contains it.
*The test is only as good as the sample analyzed.
The Use of Microtracers as a “Value
Added” Benefit to Feed Manufacturers
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The ability to confirm Rumensin is in a feed at a formulated
level.
The ability to test every truckload of “sensitive” feed (horse)
before it leaves the feedmill to be as certain as possible
Rumensin is not present.
If the feed manufacturers keeps a retained sample of each
truckload of feed, these can be tested if a feed
manufacturing error is suspected of having occurred.
The ability to validate the complete mixing of Rumensin into
final feed and to validate cross-contamination control
procedures.
Basic Premises of Formula
Feed Manufacturing-
Complete mixing of feed is
good.
 Dangerous crosscontamination of feeds is
bad.
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Official Status for validating mixer performance
and cross-contamination validation
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1. Colored iron particles are included in
GPM+ test method (Holland, 2006)
Colored iron powder is included in
Standard of American Society of
Agricultural Engineers (USA, 2007)
Basic Issues with Mixer Evaluation

1. How often to test?

How many samples to take?
How does one know if mixing is complete
and equipment cleanout adequate?
1. Initial feedmill design .
 2. Testing at startup.
 3. Developing manufacturing
procedures.
 4. Periodic testing.

Optimizing Mixing.
1. Mixing time.
 2. Batch size.
 3. Mixer speed.
 4. Particle size of
ingredients.

Validating Mixing.
1. Selection of tracer.
 2. Addition of tracer to the
batch.
 3. Sampling.
 4. Analyzing the samples.
 5. Interpreting the test results.
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Selection of tracer.
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1. Tracer from one source.
2. Tracer should be
microingredient.
3. Analytical procedure should be
accurate and reliable.
4. Results quickly available.
5. Results must be interpretable.
Commonly used tracers.
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1. Salt.
2. Minerals.
3. Vitamins, drugs and amino acids.
4. Methyl violet.
5. Colored iron particulates and
colored iron powder.
Tracer Addition to Feed
1. Tracer Should be
Premixed.
 2. Location of Tracer
Addition Will Depend Upon
Purpose of Test and
Practicalities.

Sampling.
1. Best- from the mixer.
 2. Often from screw
conveyer exiting surge bin.
 3. Samples must be “grab”.
 4. How many samples?
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Analyzing the samples.
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1. Depends upon tracer.
2. Vitamins, minerals, drugs, amino
acids or salt require laboratory
analysis.
3. Salt analysis by Quantab ™ test
strips and colored iron particles analysis at the feedmill.
Interpreting Test Data.

Complete MixingWhen CV for series of
samples equals CV for
repeat analysis of one
sample.
Interpreting Test Data- contd.
1. Typical CV’s -drug assays
20%, salt- 3%, minerals- 7%,
methyl violet or colored iron
powder- 5%.
 2. CV for particle counts defined
by Poisson and Chi-Squared
statistics.
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Poisson Distribution
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1.
2.
3.
4.
The poisson Distribution describes the probability that
a specified count will occur as a function of the
average count and the number of such counts. The
distribution assumes that counts are integral and
independent of each other
At one time there is only one event.
Each event is independent of others (no influence
between each other).
The events are independent (not influenced by a
number of events happening in the past)
The distribution is stationary (the mean event rate do
not change with time)
E. Interpretation of Results.
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Mathematical sizes
Micro tracer count x1, x2,
x3
 Number of repeated
experiments n
 Mean X
 Difference between
single event and mean
d1, d2, d3
 Sum of differences
squared d1²+d2²+d3²=S
2 = S ÷ X
 Chi-Square 
(see 2 table)
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1.
2.
3.
Determination of
number of
independent elements:
x-2=n
Finding of probability
p for n and 2
Homogeneous
mixture: P > 0.05
Mixing is marginal
0.01< P < 0.05
Non-homogeneous
mixture: P < 0.01
Interpreting Particle Counts as
evidence of mixing.
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1.Poisson Complete Mix- series of analyses standard deviation (sd) = square root of
average count. Average of 100 then sd = 10
and CV = 10/100 or 10%.
2. Average = 25 then sd = 5 and CV = 5/25
or 20%.
3. Average = 1 then sd = 1 and CV = 1/1 or
100%.
Experimental Design for Mixer
Tests.
Guidline of Authorities: Mixing homogeneity
1: 100 000
Example:
10 g / t of Feed
25 000 particles / gram of tracer F
250 000 particles / ton of Feed
250 particles / kg of Feed
50 particles / 200 grams of Feed

Examples of Mixer Study
Homogeneous Mixture
Samples
Value
#1
#2
#3
#4
#5
47
57
45
55
50
Mean
50
50
50
50
50
x n- d n
3
7
5
5
0
( x n- d n) ²
9
49
25
25
0
50
Sum
d n² = S
108
Number of repeated experiments: n=5
S : X = 2 (108 : 50 = 2)
Chi-Square 2 :
Table:
Horizontal:
n –2=3
Mean
x
Vertical 2 :
Probability
P:
2
0.572
51
Table for determination of probability,
horizontal: number of degrees of freedom,
vertical: chi squared values
2
1
2
3
4
5
6
7
8
9
1
.317
.607
.801
.910
.963
.986
.995
.998
.999
2
.157
.368
.572
.736
.849
.920
.960
.981
.991
3
.083
.223
.392
.558
.700
.809
.885
.934
.964
.
.
.
.
.
.
.
.
.
.
13
**
.002
.005
.011
.023
.043
.072
.112
.163
14
**
.001
.003
.007
.016
.030
.051
.082
.122
15
**
.001
.002
.005
.010
.020
0.036
.059
.091
Interpreting Particle Counts as Evidence
of Mixing- contd.
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1. When study CV exceeds PoissonChi-Squared Statistics employed.
2. If CV = 13% when 10%
predicted and 50 samples
analyzed- Chi-Squared Likelihood
less than 1%. Mixing is Incomplete.
Non-homogeneous Mixture
Samples Value
#1
#2
#3
#4
#5
Mean
x
Mean
43
57
70
35
61
53
53
53
53
53
53
Sum
Number of repeated experiments:
Chi-Square 2 :
Table:
Horizontal:
P:
( x n- d n) ²
10
4
17
18
8
d n²=S
n=5
100
16
289
324
64
793
S : X = 15 (793 : 53 = 15)
Vertical 2 :
Probability
x n- d n
n– 2=3
15
0.002
54
Study Where 15 Tracers Employed- two mills expected
to have complete mixing and one mill expected to have
incomplete mixing.
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1. 12 of 14 tracers correctly identified
problem at mill #3.
2. 3 “external” tracers all correct.
3. Fat and magnesium results in error.
4. Analytical variances greater than
expected.
Mixing Data from Study Where Many
Tracers Employed- 3 feedmills
Protein
% CV
Moisture Fat
% CV
% CV
Calcium Sodium
% CV
% CV
Mill #1
5.23
0.58
8.5
13.2
11.2
Mill #2
5.53
1.23
13.4
8.8
13.4
Mill #3
12.6
1.66
12.1
13.7
18.6
Mixing Data from Study Where Many
Tracers Employed- 3 feedmills (cont.)
Phos.
% CV
Copper
% CV
Potass.
% CV
Iron
% CV
Zinc
% CV
Magn.
% CV
Mill #1
8.90
17.50
7.00
16.70
14.50
7.70
Mill #2
5.70
18.00
6.50
12.70
12.40
15.90
Mill #3
10.20
27.30
10.00
18.20
77.70
8.30
Mixing Data from Study Where Many
Tracers Employed- 3 feedmills (cont.)
Brilliant Blue Red Colored Iron Blue Very Fine Iron
FCF
Particles
Powder
% CV
% CV
% CV
Mill #1
Chance
12.70
11.50
9.50
10.20
Mill #2
Chance
9.50
13.50
61.40
6.30
Mill #3
Chance
22.00
28.50
0.00
29.30
Problems in Determining
Cross-Contamination of Feeds.
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1. Analytical methods for ruminant
by-products in feeds not adequate.
2. Analytical methods for drugs in
feeds at 1% formulated levels not
adequate.
3. Analytical methods for drugs in
meat, poultry and fish are more
“sensitive”.
Study of Cross-Contamination of Amprolium
Using Colored Iron Particles and Powder.
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1. Colored Iron Particles and Colored Iron
Powder Formulated at 1-kilo per tonne of
Amprolium 2.5% Premix.
2. Samples Taken from Premix, 3 Succeeding
Batches and Pellets from Combined Batches.
3. Amprolium Determined Chemically and
Colored Iron Particles and Colored Iron
Powder Determined by tracer tests.
Premix Plant CrossContamination Study
Red Iron Particulates Blue Iron Powder
Weight (g) Count Color Absorbance Color Absorbance
Amprolium 2.5%
4
121
0.28
0.415
Batch #1-Following-Mixer
Conveyer
Elevator
200
200
200
21
395
144
0.062
0.59
0.381
0.091
0.675
0.38
Batch #2-Following-Mixer
Conveyer
Elevator
200
200
200
0.04
47.4
37
Nil
0.105
0.083
Nil
0.143
0.081
Premix Plant CrossContamination Study (cont.)
Amprolium
Amprolium Red Tracer Amprolium Blue Tracer
Chemical Assay Count
Color
Color
Amprolium 2.5%-Mixer
2.02%
2.75%
2.25%
2.73%
Packer Pellets
1.79%
2.09%
2.25%
1.70%
370 ppm
4170 ppm
730 ppm
150 ppm
660 ppm
170 ppm
90 ppm
4470 ppm
790 ppm
Nil
470 ppm
130 ppm
120 ppm
4380 ppm
760 ppm
Nil
340 ppm
Nil
140 ppm
2360 ppm
590 ppm
Nil
340 ppm
Nil
Batch #1-Following-Mixer
Batch #1-Following-Conveyer
Elevator
Batch #2-Following-Mixer
Conveyer I
Conveyer II
Premix Plant Cross-Contamination StudyConclusions
1. The level of detection (LOD)
for the amprolium assay was 50
ppm or 0.2% the formulated
level.
 2. The LOD for the colored iron
particles and colored iron
powder was 0.02%.

Premix Plant Cross-Contamination
Study- Conclusions- continued.
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3. Below 500ppm Amprolium – chemical
assays yielded higher results than tracer
results.
4. The amprolium was powdered and
the iron particles granulated.
5. Cross-contamination higher for
powders.
QUESTIONS?
Please e-mail at
[email protected]
or
[email protected]
THANK YOU