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Assessing maize genetics’ response to corn gluten meal herbicide and
corn flour residue
by Anthony Cavender
Program of Study Committee:
Nick Christians, Major Professor
Kenneth J. Moore
Thomas E. Loynachan
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Todays presentation
• Agenda review
• Safety Moment
• Who am I?
• How did this project come about?
• What did I do?
• How did I analyze it?
• What do I think was learned?
• Acknowledgements
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Safety is a priority!
You are here.
Image from http://www.ehs.iastate.edu/sites/default/files/uploads/evacmaps/Agron-3rd.pdf
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Who I am • Came to ISU in 1989 in EE • Finished in 1997 as AnEcol, minor Agron/CrJu • Started with Garst 1998 in corn breeding • Moved to BASF 2005, in transgenic corn • Moved to managing transgenic seed production
of multiple crops in 2009 • Entered MS in Agronomy program Spring 2010 • Took on North American Stewardship (Regulatory,
Safety, and Quality) for BASF in 2011 • Supported by an understanding wife and two
teenage girls
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Basis for concern
• Experimentation on Un-approved Transgenic Materials requires in field crop destruct methods.
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Initial areas of interest
• Execution of plot harvest leaves piles of milled corn
• Concerns over nitrogen distribution
• Mostly a two year rotation
• Potential nitrogen studies in subsequent seasons
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An idea was born
• Research for an organic soil amendment paper
• A single sentence in a paper published by Dr. Christians in a 1992 paper on CGM use in turf
“He (Dr Jack Dekker) has also
shown that some corn hybrids are
susceptible to its effects
whereas others are tolerant.”
• This raised concerns over some of our experiments
1
Nick E. Christians, “The Use of a Natural Product for the Control of Annual Weeds in Turf”. Horticulture Department, Iowa State University. 1992. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/cornglut.pdf
1
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Testing is conducted on a wide array of maize germplasm
Aerial photo courtesy Brian Meese, 2010
• 200 to 600 inbreds tested at a single location • Spanning as many heterotic groups as possible • Any non-genetic source of variation jeopardizes
research
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What is the project?
The goals of the project
• Determine if there is any autotoxic effect, defined as the negative impact from the breakdown of corn residue (Elmore and Abendroth, 2007), on research plots grown where flour is distributed on land in previous years.
• Identify heterotic groups that may be more susceptible to any potential impacts.
2
Roger Elmore and Lori Abendroth, “ Allelopathy: A Cause for Yield Penalties in Corn Following Corn”. Integrated Crop Management. IC-498(1). February 12, 2007. http://www.ipm.iastate.edu/ipm/icm/2007/2-12/allelopathy.html
2
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Step 1: Select some inbreds to test
Photo courtesy Jeremy Kracht, 2010
Inbreds were selected for heterotic diversity
All seed was produced by hand in a BASF increase on Kauai, HI
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Step 2: Plan a greenhouse screen
Develop multiple treatments to test 1. Control = No additions to soil
2. CGMx1 = Label rate of corn gluten meal herbicide
3. CGMx2 = Twice the label rate of CGM
4. MCFx1 = The rate of milled corn flour applied during testing
5. MCFx2 = Twice the normally applied rate of MCF
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Still Step 2: The reason we’re here today not last November
• Misguided assumption
• Lead to some misplaced efforts
• No effect seen on initial screening
Treatment Control CGMx1 MCFx1 MCFx2 MCFx3
Soil Lot ID A B C D E
Acre Furrow Slice (6 inch depth) 2,000,000 2,000,000 2,000,000 2,000,000 2,000,000
1/2 AFS (3 inch depth) 1,000,000 1,000,000 1,000,000 1,000,000 1,000,000
Factor (1/2 AFS/25# bag soil) 0.000025 0.000025 0.000025 0.000025 0.000025
Pounds of Soil per bag 25 25 25 25 25
Pounds of Soil Ammendment per Acre 0 900 9000 18000 27000
Pounds of Soil Ammendment per 25# bag of soil 0 0.02 0.2 0.4 0.6
Grams of Soil Ammendment per 25# bag of soil 0 9.2 91.8 183.6 275.4
The only number to remember
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The assumption problem
• Field Acre Furrow Slice weight = Greenhouse Potting Soil AFS weight
• Ignored soil density as a factor
• When recalculated by area
o New GCMx1 rate = 95 g/25 lbs of soil
o All soil amendment rates were 10X short of intended rates
• Resulted in rescreening
Versus 9.2 from last slide
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Lessons learned
• Calculate rates more than one way
• Need more information than just ratings
• Small germination trays make even watering difficult and can lead to tray positional effects
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Incorporate the lessons learned
• Use larger pots (10 cm round x 10 cm deep) to minimize the edge effects seen on the tray cells
• Add measured amendments to pots individually, versus relying on mixing
• Incorporate amendments into planting zone, versus whole soil lot (Bingaman and Christians, 1995) 3
3 Barbara R. Bingaman and Nick E. Christians, “Greenhouse Screening of Corn Gluten Meal as a Natural Control Product for Broadleaf and Grass Weeds”. HORTSCIENCE 30(6):1256 – 1259, October 1995. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/grnhsechr.pdf
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The new Step 2: Plan a better greenhouse screen
• Use the proper area based rates!
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Step 3: Set up the screening
• Ten separate experiments were conducted, one for each inbred
• For each experiment, 5 treatments were added to 15 pots per treatment, color coded with pot stakes
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Step 4: Conduct the experiments
• Two seeds were planted in each pot for each experiment
• A total of 150 seeds were used for each experiment, 2 seeds x 15 pots x 5 treatments
• Seed was planted approximately 1 ½ “ deep
• Amendments were incorporated 1 ½ “ deep
• All pots were watered to capacity
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Water and wait
• Pot placement was randomized within an experiment to avoid positional effects
• For photos and data collection, pots were rearranged by treatment
• Emergence was uniform within an experiment
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Apply some stress
• Dr. Christians noted increased CGM efficacy following a stress period (Christians, 1993)
• After emergence water was withheld until stress was visible on control treatment plants
4
Nick E Christians, “Making Its Way to the Marketplace: A Natural Product for the Control of Annual Weeds”. Golf Course Management: 72-76. October 1993. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/cornglut2.pdf
4
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Re-water for recovery
• Pots were watered and plants were allowed to recover
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Vigor ratings
• Each plant was rated for vigor after a ten day recovery period
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Plant weights
• Each plant was also removed at the soil surface and weighed
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Step 5: Did the treatment impact the plants?
• Each plant was treated as a replication
• Each inbred was analyzed independently
• Each experimental soil treatment was compared only to the control treatment within that experiment
• No comparisons were made between experimental treatments
• Analysis was conducted on vigor ratings and weights
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Analysis tools
• Excel’s Data Analysis tool
– Two Sample t-Test Assuming Equal Variance
– Zero hypothesized mean difference
– Confidence level of 0.85 (alpha = 0.15)
• Individual tables generated for all 80 comparisons, 4 treatments compared to control x 2 factors (weight and rating) x each of 10 inbreds.
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The resulting Excel table
T-Stat is basis for comparison
T-Crit is based on 85% Confidence Level
One vs Two tails looks for differences in only one or either direction
t-Test: Two-Sample Assuming Equal Variances
Control
Plant
Weight
CGMx2 Plant
Weight
Mean 2.36 1.39
Variance 3.82 0.80
Observations 23 27
Pooled Variance 2.18
Hypothesized Mean Difference0
df 48
t Stat 2.33
P(T<=t) one-tail 0.01
t Critical one-tail 1.05
P(T<=t) two-tail 0.02
t Critical two-tail 1.46
An example of one Excel output
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The data reporting
• An example of how the data was summarized
Excel output was gathered per factor per inbred P values less than 0.15 were considered statistically significant
Significant increases were denoted with a “^” and highlighted in green Significant decreases were denoted with an “*” and highlighted in pink
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The overall summary
Plant
Weight (g)
Vigor
Rating
Plant
Weight (g)
Vigor
Rating
Plant
Weight (g)
Vigor
Rating
Plant
Weight (g)
Vigor
Rating
Plant
Weight (g)
Vigor
Rating
Inbred 1 2.36 2.7 2.10 2.4 1.39* 2.4 1.07* 2.1 1.40* 2.5
Inbred 2 2.16 2.4 1.96 2.2 2.03 2.5 2.39 2.6 3.29^ 2.9
Inbred 3 0.81 1.1 1.87^ 2.4^ 2.33^ 2.4^ 1.93^ 2.6^ 2.50^ 2.2^
Inbred 4 1.63 1.8 2.90^ 2.4 5.36^ 3.2^ 3.38^ 2.7^ 3.42^ 2.3
Inbred 5 2.13 2.3 2.41 2.0 1.84 1.9 2.02 2.5 3.28 2.7
Inbred 6 2.78 2.6 2.45 2.5 4.27^ 2.9 3.71^ 3.2^ 3.98^ 2.5
Inbred 7 1.91 2.5 1.52 1.7* 2.15 2.3 2.43 2.0 1.86 1.9
Inbred 8 2.04 2.5 3.4^ 2.9 2.80^ 2.6 2.56 2.6 3.31^ 2.9
Inbred 9 1.55 1.8 1.89 2.4 2.51^ 2.7^ 1.29 2.0 1.21 2.3
Inbred 10 2.52 3.0 1.98 2.1* 2.68 3.0 3.30 2.7 3.07 3.2
* = Statistically significant decrease in mean at 0.85 confidence level
^ = Statistically significant increase in mean at 0.85 confidence level
Summary results of mean comparisons against the controls for both plant weight and vigor
rating for all ten inbreds.
Control CGMx1 CGMx2 MCFx1 MCFx2
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Summarization
• Positive Impact 31% (25 of 80 comparisons)
Greater frequency on higher rates
• No discernible impact 63% (50 of 80 comparisons)
Many inbreds showed few effects
• Negative impact 6% (5 of 80 comparisons)
3 of the 5 were Inbred 1 (B73) plant weights
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Conclusions
• Many inbreds responded well to the nitrogen addition of the treatments
• B73 showed consistent susceptibility to autotoxic effects on seedling weight
• Research implications of positive impacts of soil additions may be overcome through fertilization, if the study allows
• Negative impacts could have serious implications
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Potential improvements
• Apply greater stress
• Measure soil moisture to provide equal water
• Expose amendments to lighted period prior to incorporation (Minorsky, 2002)
• Measure whole plant dry matter instead of above ground plant weight (Bingaman and Christians, 1995)
Peter V. Minorsky, “Allelopathy and Grain Crop Production”. Plant Physiology, vol 130 no 4, 1745-1746, December 2002. http://www.plantphysiology.org/content/130/4/1745.full
5
5
Barbara R. Bingaman and Nick E. Christians, “Greenhouse Screening of Corn Gluten Meal as a Natural Control Product for Broadleaf and Grass Weeds”. HORTSCIENCE 30(6):1256 – 1259, October 1995. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/grnhsechr.pdf
3
3
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Next steps
• With B73 genetics involved with primary testing and many current commercial hybrids (Lu and Bernardo, 2001), more work to explore autotoxic susceptibility is warranted
• Additional field studies would also be warranted to determine what impact the uneven distribution of flour from crop destruct trials may be having on data quality
H. Lu and R. Bernardo, “Molecular marker diversity among current and historical maize inbreds”. Theoretical Applied Genetics. 103:613-617. January 2001. http://link.springer.com/article/10.1007%2FPL00002917?LI=true#page-1
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Acknowledgements • Deb, Kori, and Tia – Endless support at home
• BASF Management (Ken, Michael, Stuart, Perry, and beyond) – Financial and personal support through the whole process
• Program faculty and staff (Dawn, Jaci, Dr Christians, Dr Moore, Dr Loynachan, and all) – Support and dedication to make this possible for working students
• Other program students – Variety of real world experience keeps the classwork fresh
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References
Nick E. Christians, “The Use of a Natural Product for the Control of Annual Weeds in Turf”. Horticulture Department, Iowa State University. 1992. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/cornglut.pdf Roger Elmore and Lori Abendroth, “ Allelopathy: A Cause for Yield Penalties in Corn Following Corn”. Integrated Crop Management. IC-498(1). February 12, 2007. http://www.ipm.iastate.edu/ipm/icm/2007/2-12/allelopathy.html Barbara R. Bingaman and Nick E. Christians, “Greenhouse Screening of Corn Gluten Meal as a Natural Control Product for Broadleaf and Grass Weeds”. HORTSCIENCE 30(6):1256 – 1259, October 1995. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/grnhsechr.pdf Nick E Christians, “Making Its Way to the Marketplace: A Natural Product for the Control of Annual Weeds”. Golf Course Management: 72-76. October 1993. http://www.hort.iastate.edu/sites/default/files/imported/gluten/pdf/cornglut2.pdf Peter V. Minorsky, “Allelopathy and Grain Crop Production”. Plant Physiology, vol 130 no 4, 1745-1746, December 2002. http://www.plantphysiology.org/content/130/4/1745.full H. Lu and R. Bernardo, “Molecular marker diversity among current and historical maize inbreds”. Theoretical Applied Genetics. 103:613-617. January 2001. http://link.springer.com/article/10.1007%2FPL00002917?LI=true#page-1
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Are there any questions?
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Thank You for Your Attention
It has been a pleasure to be part of the program.
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Inbred 1
Inbred 1 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.36 2.10 1.39 1.07 1.40 2.7 2.4 2.4 2.1 2.5
P(T<=t) two-tail 0.62 0.02 0.01 0.04 0.47 0.57 0.16 0.65
Variance 3.82 2.65 0.80 1.21 1.35 2.49 2.24 2.26 2.08 1.34
Observations 23 22 27 25 27 23 22 27 25 27
Pooled Variance 3.25 2.18 2.46 2.48 2.37 2.37 2.28 1.87
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 43 48 46 48 43 48 46 48
t Stat 0.50 2.33 2.86 2.17 0.72 0.58 1.41 0.46
t Critical two-tail (at 85% Confidence Level) 1.47 1.46 1.46 1.46 1.47 1.46 1.46 1.46
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Inbred 2 Inbred 2 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.16 1.96 2.03 2.39 3.29 2.4 2.2 2.5 2.6 2.9
P(T<=t) two-tail 0.63 0.77 0.55 0.01 0.60 0.90 0.54 0.19
Variance 2.24 2.26 2.21 1.65 2.65 1.85 1.95 2.46 1.03 1.09
Observations 26 27 21 29 28 26 27 21 29 28
Pooled Variance 2.25 2.23 1.92 2.45 1.90 2.12 1.42 1.46
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 51 45 53 52 51 45 53 52
t Stat 0.48 0.30 -0.60 -2.64 0.53 -0.12 -0.61 -1.32
t Critical two-tail (at 85% Confidence Level) 1.46 1.46 1.46 1.46 1.46 1.46 1.46 1.46
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Inbred 3 Inbred 3 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 0.81 1.87 2.33 1.93 2.50 1.1 2.4 2.4 2.6 2.2
P(T<=t) two-tail 0.03 0.00 0.06 0.01 0.03 0.01 0.01 0.08
Variance 1.70 2.26 2.88 4.08 5.56 2.78 2.91 2.17 2.34 3.33
Observations 16 25 24 24 23 16 25 24 24 23
Pooled Variance 2.04 2.42 3.14 3.99 2.86 2.41 2.52 3.11
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 39 38 38 37 39 38 38 37
t Stat -2.32 -3.04 -1.96 -2.61 -2.28 -2.58 -2.85 -1.83
t Critical two-tail (at 85% Confidence Level) 1.47 1.47 1.47 1.47 1.47 1.47 1.47 1.47
Ratings
Weights
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Inbred 4
Inbred 4 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 1.63 2.90 5.36 3.38 3.42 1.8 2.4 3.2 2.7 2.3
P(T<=t) two-tail 0.05 0.00 0.00 0.01 0.16 0.00 0.03 0.19
Variance 4.92 5.95 13.98 4.21 6.84 2.98 2.94 1.88 1.91 1.88
Observations 29 27 23 27 24 29 27 23 27 24
Pooled Variance 5.42 8.90 4.58 5.78 2.96 2.49 2.46 2.48
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 54 50 54 51 54 50 54 51
t Stat -2.03 -4.47 -3.06 -2.69 -1.41 -3.21 -2.25 -1.32
t Critical two-tail (at 85% Confidence Level) 1.46 1.46 1.46 1.46 1.46 1.46 1.46 1.46
Ratings
Weights
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Inbred 5 Inbred 5 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.13 2.41 1.84 2.02 3.28 2.3 2.0 1.9 2.5 2.7
P(T<=t) two-tail 0.62 0.51 0.79 0.10 0.60 0.42 0.66 0.42
Variance 2.33 3.99 1.76 1.66 6.78 2.21 3.06 2.19 1.91 3.78
Observations 22 18 21 24 15 22 18 21 24 15
Pooled Variance 3.07 2.05 1.98 4.11 2.59 2.20 2.05 2.84
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 38 41 44 35 38 41 44 35
t Stat -0.51 0.66 0.27 -1.70 0.53 0.81 -0.44 -0.82
t Critical two-tail (at 85% Confidence Level) 1.47 1.47 1.47 1.47 1.47 1.47 1.47 1.47
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Inbred 6
Inbred 6 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.78 2.45 4.27 3.71 3.98 2.6 2.5 2.9 3.2 2.5
P(T<=t) two-tail 0.45 0.01 0.03 0.02 0.72 0.43 0.07 0.81
Variance 2.39 2.52 4.53 1.94 3.80 1.92 1.81 1.31 0.82 1.98
Observations 25 28 26 28 22 25 28 26 28 22
Pooled Variance 2.46 3.48 2.15 3.05 1.86 1.61 1.34 1.94
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 51 49 51 45 51 49 51 45
t Stat 0.77 -2.85 -2.28 -2.34 0.36 -0.80 -1.82 0.25
t Critical two-tail (at 85% Confidence Level) 1.46 1.46 1.46 1.46 1.46 1.46 1.46 1.46
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Inbred 7
Inbred 7 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 1.91 1.52 2.15 2.43 1.86 2.5 1.7 2.3 2.0 1.9
P(T<=t) two-tail 0.37 0.59 0.34 0.90 0.08 0.65 0.36 0.21
Variance 1.86 2.11 2.33 3.99 1.76 2.06 2.33 2.21 3.06 2.19
Observations 21 21 22 18 21 21 21 22 18 21
Pooled Variance 1.99 2.10 2.84 1.81 2.20 2.14 2.52 2.13
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 40 41 37 40 40 41 37 40
t Stat 0.91 -0.54 -0.96 0.12 1.77 0.46 0.93 1.27
t Critical two-tail (at 85% Confidence Level) 1.47 1.47 1.47 1.47 1.47 1.47 1.47 1.47
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Inbred 8
Inbred 8 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.04 3.40 2.80 2.56 3.31 2.5 2.9 2.6 2.6 2.9
P(T<=t) two-tail 0.02 0.07 0.19 0.00 0.35 0.72 0.68 0.24
Variance 1.66 5.10 2.39 2.27 2.65 1.91 2.94 1.92 1.36 1.09
Observations 24 20 25 28 28 24 20 25 28 28
Pooled Variance 3.22 2.04 1.99 2.20 2.38 1.91 1.61 1.47
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 42 47 50 50 42 47 50 50
t Stat -2.51 -1.87 -1.33 -3.08 -0.95 -0.36 -0.42 -1.18
t Critical two-tail (at 85% Confidence Level) 1.47 1.46 1.46 1.46 1.47 1.46 1.46 1.46
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Inbred 9
Inbred 9 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 1.55 1.89 2.51 1.29 1.21 1.8 2.4 2.7 2.0 2.3
P(T<=t) two-tail 0.36 0.01 0.44 0.22 0.19 0.03 0.62 0.24
Variance 1.04 2.26 2.51 1.69 0.99 1.58 2.91 2.22 2.19 2.20
Observations 25 25 26 22 27 25 25 26 22 27
Pooled Variance 1.65 1.79 1.34 1.01 2.25 1.91 1.87 1.90
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 48 49 45 50 48 49 45 50
t Stat -0.92 -2.55 0.78 1.24 -1.32 -2.31 -0.50 -1.20
t Critical two-tail (at 85% Confidence Level) 1.46 1.46 1.46 1.46 1.46 1.46 1.46 1.46
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Inbred 10
Inbred 10 Results
Control CGMx1 CGMx2 MCFx1 MCFx2 Control CGMx1 CGMx2 MCFx1 MCFx2
Mean 2.52 1.98 2.68 3.30 3.07 3.0 2.1 3.0 2.7 3.2
P(T<=t) two-tail 0.21 0.75 0.26 0.21 0.04 1.00 0.63 0.68
Variance 1.70 1.36 2.27 6.78 1.77 1.67 1.53 3.00 3.78 1.14
Observations 19 16 13 15 19 19 16 13 15 19
Pooled Variance 1.55 1.93 3.92 1.73 1.60 2.20 2.59 1.40
Hypothesized Mean Difference 0 0 0 0 0 0 0 0
df 33 30 32 36 33 30 32 36
t Stat 1.29 -0.32 -1.14 -1.27 2.18 0.00 0.48 -0.41
t Critical two-tail (at 85% Confidence Level) 1.47 1.48 1.47 1.47 1.47 1.48 1.47 1.47
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