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Restraints
The Burning Question
Fixed or Random?
Facilities
Types of data.
Collection.
Measure or visual assess.
Time availability
Graduate students.
Short term grant.
Funding.
Never enough!
Factors and Factor Levels
Number of Factors
How many factors to include?
Often it is the more simple experiments that yield “best” results.
Two-way interactions can be difficult to interpret.
Generally include no more than 3 factors.
Number of Factor Levels
Explain the effect of increasing or decreasing levels.
• Usually only a few.
Predict values not included in actual study.
• Regression.
• Usually many factor levels.
Test different treatments to find “best”.
• Different insecticides, herbicides, etc.
• Determined by how many are available.
Fixed or Random?
Number of Factor Levels
Number of Replicates
The variation that is likely between factors and factor levels.
Degree of variability or heterogeneity over the experimental area.
Degree of precision required.
Precision
Number of
Replicates
Standard error of the
treatment mean
1 1.00
2 0.71
3 0.58
4 0.50
5 0.45
se[x] = /n
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1 3 5 7 9 11
13
15
17
19
21
23
se[m
ean
]
Number of Replicates
Precision
What is the magnitude of
difference that needs detecting?
Variance of plot = 2
sed[x] = 22/n
Differences 3 x sed[x] will be
significant at 5% level 5 times out of 6
Precision
What is the magnitude of
difference that needs detecting?
Variance of plot = 252 , n = 4
sed[x] = 2[5/2]=2.236
Differences 3 x 2.236 = 6.7 will be
significant at 5% level 5 times out of 6
Precision
In an experiment is 10% of the mean
(i.e. =m/10)
sed[x] = 2(m/10)2/4 = 0.07m
3 x 0.07 = 0.21
A true difference of 21% of the mean value will
be significant at the 5% level 5 times out of 6.
sed[x] = (m2/200)/ = 0.07m
Precision
To detect a true difference of 15% how
many reps would be needed?
sed[x] = 2(m/10)2/n
3 x 2(m/10)2/n < 0.15m
18 x (m2/102) /n < 0.152m2
n > [18 x (1/10)2/0.152 = 8
Precision
Plot Size
Bigger plots and more
replicates are always best.
Usually a compromise has to
be reached to fit restraints.
Machinery availability.
Physical yields.
Plot Size
Layout se[x] se[x] se[plot]
1 x 100 r/1 r1.00 p0.10
2 x 50 r/2 r0.71 p0.14
4 x 25 r/4 r0.50 p0.20
5 x 20 r/5 r0.45 p0.22
10 x 10 r/10 r0.32 p0.32
Machinery Available
On-farm Testing
Guard Rows and
Discard Rows
Mechanical damage usually occurs around the edges.
Avoid “edge effect”.
Guard rows can be used to “buffer” treatment effects.
Guard rows do not have to be the same species as is in trial.
Discard Rows
?
Examples
Jeannie’s Oriental Mustard
Oriental mustard (Brassica juncea
L.) is a new crop to the PNW
Growers have little experience
growing the crop.
Design an experiment to determine
the optimum growing conditions to
maximize productivity.
Four cultivars.
◦ 2 oilseed and 2 condiment.
2 planting dates.
3 seeding rates.
5 nitrogen levels.
3 Replicates.
Jeannie’s Oriental Mustard
Jeannie’s Oriental Mustard
9&10
7&8
5&6
3&4
1-2
Late Planting Early Planting
Jeannie’s Oriental Mustard
9&10
7&8
5&6
3&4
1-2
Late Planting Early Planting
I II III I II III
Jeannie’s Oriental Mustard
9&10 75lb 25lb 75lb 50lb 0lb 25lb
7&8 0lb 0lb 25lb 70lb 50lb 100lb
5&6 25lb 50lb 100lb 25lb 75lb 75lb
3&4 50lb 75lb 50lb 0lb 100lb 0lb
1-2 100lb 100lb 0lb 100lb 25lb 50lb
Late Planting Early Planting
I II III I II III
Jeannie’s Oriental Mustard
9&10 75lb 25lb 75lb 50lb 0lb 25lb
7&8 0lb 0lb 25lb 70lb 50lb 100lb
5&6 25lb 50lb 100lb 25lb 75lb 75lb
3&4 50lb 75lb 50lb 0lb 100lb 0lb
1-2 100lb 100lb 0lb 100lb 25lb 50lb
Late Planting Early Planting
I II III I II III
Jeannie’s Oriental Mustard
1
2
Ari
d 3
g
Ari
d 4
g
Ari
d 5
g
Jeannie’s Oriental Mustard
1
2
Ari
d 3
g
Ari
d 4
g
Ari
d 5
g
Am
ula
t 4 g
Am
ula
t 5
g
Am
ula
t 3 g
P. G
old
5 g
P. G
old
3 g
P. G
old
4 g
Ko
dia
k 5
g
Ko
dia
k 3
gK
od
iak 4
g
Jeannie’s Oriental Mustard
1
2
Ari
d 3
g
Ari
d 5
g
Ari
d 4
g
Jeannie’s Oriental Mustard
1
2
Ari
d 3
g
Am
ula
t 4 g
P. G
old
5 g
Ko
dia
k 5
g
Ko
dia
k 3
g
Ko
dia
k 4
g
P. G
old
4 g
P. G
old
3 g
Am
ula
t 5 g
Am
ula
t 3 g
Ari
d 5
g
Ari
d 4
g
Jeannie’s Oriental Mustard
Revision of
Experimental Design
and More Examples