2. There has been done a study on the addition of ascorbic acid in the manufactu
ID: 3318391 • Letter: 2
Question
2. There has been done a study on the addition of ascorbic acid in the manufacture of dangke to identify the effect on the storage capacity based on the value of TBA. The research was conducted by using Completely Randomized Design (RAL) Factorial pattern: Factor A is level of addition of ascorbic acid (1%, 1.5%, and 296); and Factor B is the length of storage time (4 days, 5 days and 6 days). The result (TBA value) research obtained is presented in the following table. Faktor B 5hr 6.30 6.10 6.80 5.30 6.30 30.80 5.20 6.20 5.60 6.50 5.30 28.80 5.10 4.80 4.87 5.16 5.00 24.93 84.53 Faktor A TOTAL 4hr 5.20 5.10 5.30 5.00 5.20 25.80 5.00 5.10 4.90 6hr 6.68 6.71 6.73 6.76 6.78 33.66 5.90 6.00 6.30 5.77 5.52 29.48 5.10 18.18 17.91 18.83 17.06 18.28 90.26 16.10 17.30 16.80 17.13 15.92 S3.25 14.92 14.68 14.84 15.03 14.50 73.97 247.47 1% Sub Total 1.5% 5.10 24.96 4.72 4.78 4.77 4.67 4.70 23.64 74.40 Sub Total 5.20 5.20 4.80 25.40 88.54 2% Sub Total Use Minitab software to answer the questions below. a. Does the ascorbic acid addition rate affect the value of TBA? b. Does storage time affect the value of TBA? c. Is there an interaction between ascorbic acid level (Factor A) and storage time (Factor B) to the value of TBA obtained?Explanation / Answer
Result:
General Linear Model: TBA versus A, B
Method
Factor coding
(-1, 0, +1)
Factor Information
Factor
Type
Levels
Values
A
Fixed
3
1.00%, 1.50%, 2.00%
B
Fixed
3
4hr, 5hr, 6hr
Analysis of Variance
Source
DF
Adj SS
Adj MS
F-Value
P-Value
A
2
8.903
4.45136
51.18
0.000
B
2
7.089
3.54444
40.75
0.000
A*B
4
1.957
0.48919
5.62
0.001
Error
36
3.131
0.08697
Total
44
21.079
To test effect of ascorbic acid, calculated F=51.18, P=0.000 which is significant at 5% level.
To test effect of storage time, calculated F=40.75, P=0.000 which is significant at 5% level.
To test effect of interaction, calculated F=5.62, P=0.001 which is significant at 5% level.
Model Summary
S
R-sq
R-sq(adj)
R-sq(pred)
0.294912
85.15%
81.85%
76.79%
Coefficients
Term
Coef
SE Coef
T-Value
P-Value
VIF
Constant
5.4996
0.0440
125.10
0.000
A
1.00%
0.5178
0.0622
8.33
0.000
1.33
1.50%
0.0504
0.0622
0.81
0.422
1.33
B
4hr
-0.5396
0.0622
-8.68
0.000
1.33
5hr
0.1358
0.0622
2.18
0.036
1.33
A*B
1.00% 4hr
-0.3178
0.0879
-3.61
0.001
1.78
1.00% 5hr
0.0069
0.0879
0.08
0.938
1.78
1.50% 4hr
-0.0184
0.0879
-0.21
0.835
1.78
1.50% 5hr
0.0742
0.0879
0.84
0.404
1.78
Regression Equation
TBA
=
5.4996 + 0.5178 A_1.00% + 0.0504 A_1.50% - 0.5682 A_2.00% - 0.5396 B_4hr + 0.1358 B_5hr
+ 0.4038 B_6hr - 0.3178 A*B_1.00% 4hr + 0.0069 A*B_1.00% 5hr + 0.3109 A*B_1.00% 6hr
- 0.0184 A*B_1.50% 4hr + 0.0742 A*B_1.50% 5hr - 0.0558 A*B_1.50% 6hr + 0.3362 A*B_2.00%
4hr - 0.0811 A*B_2.00% 5hr - 0.2551 A*B_2.00% 6hr
Fits and Diagnostics for Unusual Observations
Obs
TBA
Fit
Resid
Std Resid
8
6.800
6.160
0.640
2.43
R
9
5.300
6.160
-0.860
-3.26
R
21
5.200
5.760
-0.560
-2.12
R
24
6.500
5.760
0.740
2.81
R
R Large residual
MINITAB data
A
B
TBA
1%
4hr
5.2
1%
4hr
5.1
1%
4hr
5.3
1%
4hr
5
1%
4hr
5.2
1%
5hr
6.3
1%
5hr
6.1
1%
5hr
6.8
1%
5hr
5.3
1%
5hr
6.3
1%
6hr
6.68
1%
6hr
6.71
1%
6hr
6.73
1%
6hr
6.76
1%
6hr
6.78
1.50%
4hr
5
1.50%
4hr
5.1
1.50%
4hr
4.9
1.50%
4hr
4.86
1.50%
4hr
5.1
1.50%
5hr
5.2
1.50%
5hr
6.2
1.50%
5hr
5.6
1.50%
5hr
6.5
1.50%
5hr
5.3
1.50%
6hr
5.9
1.50%
6hr
6
1.50%
6hr
6.3
1.50%
6hr
5.77
1.50%
6hr
5.52
2%
4hr
4.72
2%
4hr
4.78
2%
4hr
4.77
2%
4hr
4.67
2%
4hr
4.7
2%
5hr
5.1
2%
5hr
4.8
2%
5hr
4.87
2%
5hr
5.16
2%
5hr
5
2%
6hr
5.1
2%
6hr
5.1
2%
6hr
5.2
2%
6hr
5.2
2%
6hr
4.8
Factor coding
(-1, 0, +1)
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