Some standard content:
Sensory analysis "A"-non "A" test
GB12316
This standard refers to the international standard ISO85881987 "Sensory analysis-methodology-\A-\non-A\ test". Subject content and scope of application
This standard specifies a sensory analysis method for differential testing of two types of samples-"A" and "non-A\ test. This standard is applicable to determining the differences in the sensory characteristics of products caused by differences in raw materials, processing, handling, packaging and storage. It is particularly suitable for evaluating samples with different appearances or aftertastes. The method specified in this standard is also applicable to sensitivity testing, used to determine whether the evaluator can distinguish a new stimulus related to a known stimulus or to determine the evaluator's sensitivity to a specific stimulus. 2
Cited standards|| tt||GB10220
General Introduction to Sensory Analysis Methods
GB10221.1~10221.4 Terminology of Sensory Analysis GB3358 Statistical Terms and Symbols
3 Summary of Methods
A series of samples are distributed to the assessors in a random order, some of which are samples "A" and some are "non-A". All "non-A\ samples should be the same in the main characteristic indicators being compared, but may have slight differences in non-main characteristic indicators such as appearance. "Non-A\ samples can also include \(non-A)\ and \(non-A)2\, etc. The assessors are required to identify whether each sample is \A\ or \non-A\ and make statistical analysis of the test results.
General Conditions for Tests
4.1 Assessors
4.1.1 Conditions
The conditions that assessors should have are shown in GB10220. All assessors participating in the test should have the same qualification level and test capabilities. For example, all are preferred evaluators or all are primary evaluators. 4.1.2 Number of evaluators
7 or more experts or 20 or more preferred evaluators or 30 or more primary evaluators are required 4.2 External conditions
4.2.1 Inspection room
The design and conditions of the inspection room can refer to the relevant provisions of GB10220. The details will be specified in the special standards. 4.2.2 Instruments
The instruments shall be selected by the person in charge of the inspection according to the nature and quantity of the samples. The instruments used shall not affect the results of the inspection in any way. Standardized instruments that meet the inspection needs shall be given priority. 4.3 Samples to be inspected
4.3.1 Sampling
Sampling shall be carried out according to the sampling standards for the inspected products. If there is no such standard or the sampling standard is not fully applicable, the sampling method shall be agreed upon by the parties concerned.
4.3.2 Sample preparation
The following should be determined according to the purpose of the inspection: The method of sample preparation and distribution: b.
Sample quantity. The amount of each sample sent to each evaluator for inspection should be equal and sufficient to complete the required number of inspections; Sample temperature. The temperature of all samples in the same inspection should be the same: Masking of certain characteristics. For example, using colored lights to remove color effects, etc.: Coding of sample containers. The coding should not be the same for each inspection. It is recommended to use a 3-digit random number coding: Container selection. The same container should be used. Inspection steps
Experience before inspection
Before the inspection evaluation, the evaluator should have a clear experience with sample \A\ and be able to recognize it. If necessary, the evaluator may also experience the "non-A" sample. After the test begins, the evaluator should not approach the clearly marked sample "A". If necessary, the evaluator may experience the sample A or "non-A" again during the test.
5.2 Distribution of samples
must be the same).
Distribute samples to the evaluators in a random order. The evaluators should not be able to draw conclusions about the nature of the samples from the way the samples are provided: the same samples are provided to each evaluator with different codes. The number of samples "A" or samples "non-A" distributed to each evaluator should be the same (the number of samples "A" and the number of samples "non-A" are not 5.3 Inspection technology
Require the evaluator to identify the series of samples as "A" or "non-A" in sequence: within a limited time Complete the inspection.
5.4 Evaluation record
After the inspection is completed, the evaluator records the results he or she has identified in the answer form. For the format of the answer form, see Appendix B (reference). The content of the record can be specified in detail according to the needs of the inspection. 6
Expression and interpretation of results
Collection of results
After the inspection is completed, the person in charge of the inspection shall collect the obtained data and fill in Table 1 Table 1 Inspection discrimination statistics table
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or "non-
A\
"Non-A"
Number of samples of "A" and "non-A\
"Non-A"
Huai: n-
Sample The total number of responses that the sample itself is "A" and the evaluator also thinks it is "A". The total number of responses that the sample itself is "non-A" and the evaluator also thinks it is "non-A". h
The total number of responses that the sample itself is "non-A" and the evaluator also thinks it is "non-A". The total number of responses that the sample itself is "non-A" and the evaluator also thinks it is "A". The sum of the responses in the first row.
The sum of the responses in the second row.
The sum of the responses in the first column.
n2—The sum of the responses in the second column.
—All responses.
Statistical interpretation
Use the x-test to express the test results.
Test the null hypothesis: the difference between the evaluator's judgment (thinking the sample is "A" or "non-A") and the characteristics of the sample itself The alternative hypothesis of the
test is that the judgement of the evaluator is related to the characteristics of the sample itself. That is, when the sample is "A" and the evaluator thinks it is "A", the possibility is greater than the possibility that the sample itself is "A" and the evaluator thinks it is "A". When the total number of samples n is less than 40 or n is less than or equal to 5, the x statistic is formula (1): 0.5
Where: E—the number of different types of discrimination n (/=1,2;J=1,2). E=nxn/n
When the total number of samples n is greater than 40 and n is greater than 5, the statistic is formula (2): --
When =1,2;j=1,2, then formulas (1) and (2) have the following equivalent formulas, see formulas (3) and (4): [1xnm- ngxnal- (n. / 2) xn.
RXRgXA,XB
x_ h1xna-xnl xn.
NXR X n XR
Compare the effect (or significance) statistic with the corresponding critical value of 1[ (2-1)×(2-1)) in Table 2, see formula (5) (6):
When the effect (or significance) statistic ≥.84 (in the case of α=0.05) When the effect (or significance) ≥.84 (in the case of α=0.05) When the effect (or significance) ≥.63 (in the case of a=0.0) (5)
Then at the selected significance level, the null hypothesis is rejected and the alternative hypothesis is accepted, that is, the evaluator's judgment is related to the characteristics of the sample itself, that is, it is believed that the samples "A\ and "A\ have significant differences. When
(or) <3.84 (in the case of α=0.05) (or) <6.63 (in the case of α=0.01) When
then the null hypothesis is accepted at the selected significance level, that is, it is believed that the judgment of the evaluator has nothing to do with the characteristics of the sample itself, that is, it is believed that there is no significant difference between the sample "A\" and "non-A". For the expression and interpretation of the results, see Appendix A (reference). Table 2 × distribution critical value table (extract)
Significance level
Degrees of freedom
Test report
After the test, a test report should be written, which should include the following contents: a.
Number of assessors and their qualification level;
Whether both "A" and "non-A" samples were tested before testing; Testing environment;
Description of the relevant samples;
Test results obtained and their statistical interpretation; Indicate that the test was conducted in accordance with this standard;
If there are practices that are inconsistent with this standard, they should be clearly stated; Name of the person responsible for the test;
Date and time of the test.
Appendix A
Application Examples
(Supplement)
Distinguishing the sweetness of sugar droplets (A" stimulation) from grass sweeteners (non-A" stimulation) Sweetness. Provide two aqueous solutions of substances, one is a saccharide aqueous solution with a concentration of 409/L, and the other is an aqueous solution of a sweetener with a sweetness equivalent to that of the saccharide.
Number of evaluators: 20 preferred evaluators.
Number of samples for each evaluator: 4 "A\ and 6 "non-A"° The evaluators' judgments are shown in Table A1.
Number of samples →
Number of judgments
Number of answers judged as \A\ or \non
A\
"Non-A"
For n greater than 40 and n greater than 5, use formula (2): "Number of A\ and \non-A\ samples
(hu Xna- nua xhp' xn.
R,1xAg X网xP.
(50 × 65 - 55 × 30p × 20080 ×120 ×105 × 95
“Non-A”
Because the statistical value 5.34 is greater than 3.84, from formula (5), it is concluded that the null hypothesis is rejected and the alternative hypothesis is accepted, that is, the sweetness of sugar and a certain sweetener are significantly different at the 5% significance level. A2 Example 2
It is known that the sweetness of sugar (A\) is significantly different from that of a certain sweetener (non-A”). Now it is necessary to determine whether an evaluator can distinguish the sweetness of the sweetener from the sweetness of sugar. The number of products evaluated by the evaluator: 13 “A” and 19 “non-A”. The evaluator’s judgment is shown in Table A2.
Number of samples -
Number of judgments
Number of answers judged as \A\ or \non-A"
"A"
“Non-A”
Since n is less than 40 and n is equal to 5, so using formula (A1) "A\ and "non-A\ sample number
"A"
"non-A"
[hux na- nua x nal-(a./2)P xnaixnaxmxn
[x×13 6 x5]- 3212/ x 32
13×19 ×14 ×18
Because the death statistic 1.73 is less than 3.84, from formula (7), it is concluded that: accept the null hypothesis and believe that there is no significant difference between the sweetness of sugar and the sweetness of sweeteners. Or the evaluator can distinguish the sweetness of sweeteners from the sweetness of sugar. A3
is similar to the situation in Example 1 in A1, the difference is that here "non-A\ includes two kinds of sweeteners (non-A)" and (non-A) 2° The evaluator's judgment is shown in Table A3.
Number of samples of “A\” and “non-A\
Number of samples→
Number of discriminations
The
test to discriminate as “A\” or “non-A\” can have the following objectives:
difference.
difference.
“Non-A”
“A\”
“(Non-A)”
Non-A”
Test whether the sweetness of sucrose “A” and the sweetness of the other two sweeteners ((Non-A)\+“(Non-A)2) are significant. Test whether the direction of sugar “A\, sweetener (A)” and sweetener “(Non-A)”\ are significant in terms of sweetness. Test the direction of sugar “A\ and sweetener “(Non-A)\; the direction of difference sugar “A\ and sweetener “(Non-A)2\; the direction of sweetener “(Non-A)” and sweetener (Non-A)2 \ is there a significant difference in sweetness. In order to achieve the goal of testing a. or c:, we must first test b. After testing b., if there is no significant difference between the samples (A" "non-A)\ (non-A)2), there is no need to test a. and C.
When testing b., you can use formula (1) or (2), but at this time = 1, 2; J = 1, 2, 3. In this example, because n is greater than 40 and n is greater than 5, formula (2) is used:
"(non-A)2"
-_ (60-145×100/280)
145x100/280
(40-135×100/280))
135×100/280
(55-135×100/280
135x100/280
(40-1 35×80/ 280)
135×80/280
(45-145×100/280))
145x100/280
(40-145×80/280)
145x80/280
Because the × total increase of 4.65 is less than the corresponding critical value of 5.99 corresponding to (2-1)×(3-1)=2; α=0.05, we can conclude that anhydrous sugar and sweetener (non-A) There is no significant difference in sweetness among the three "sweeteners (non-A)".
When testing a. and C., Table A1 can be transformed into Table A4 to Table A7, and the testing method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \non-A\"
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \(non
A)\
Number of samples→||tt ||Number of discriminations
“Non-A”
“Non-A”
Number of samples of “A\ and\Non-A\
“A\ and “(Non-A)\”Number of samples
“Non-A”
“(Non-A)”
“A\ and “(Non-A)2”
Number of samples
“(Non-A)2”
Cumulative
Number of answers to “A)2\
“(Non-A)2\
Number of samples→
Discriminations Number of identification
Number of answers identified as \A\ or \Non
“(Non-A)”
“(Non-A)2”
Only sample “A” is shown to the evaluators in advance
“(Non-A)\ and “(Non-A)2”
Number of samples
“(Non-A)\
Appendix B
Sample format of inspection answer sheet
(reference)
1. Identify sample “A\ and return it to the management personnel. Take out the coded sample. “(Non-A)2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \Non-A\ is random. All "non-A" samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample code
+++++++++++
............
++++++++++
............
The sample is
"non-A"
.........
Comments:
Preview the evaluators with samples "A" and "non-A" separately.
1. Identify samples "A" and "non-A" and return them to the management staff, and take out the coded samples.口
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample coding
Comments:
Additional sharp note:
“A”
Sample is
“Non-A”
This standard was proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard was drafted by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences and the China Institute of Standardization and Information Classification and Coding. The main drafters of this standard are Li Weige, Zhou Suyu and Bi Jian.
(50 × 65 - 55 × 30p × 20080 ×120 ×105 × 95
“Not A”
Because the total needle value 5.34 is greater than 3.84, according to formula (5), we can conclude that we reject the null hypothesis and accept the alternative hypothesis, that is, we believe that the sweetness of sugar The sweetness of sugar (A\ leftover) is significantly different from that of a certain sweetener at a 5% significance level. The goal is to determine whether an evaluator can distinguish the sweetness of a sweetener from that of an anorectic sweetener. The number of products evaluated by the evaluator: 13 "A" and 19 “Non-A° evaluator discrimination is shown in Table A2.
Number of samples 1
Number of discriminations
Number of answers discriminated as \A\ or \non-A”
|tt||“A”
“Not A”
Since n. is less than 40 and n is equal to 5, so use the formula (A1) "A\ and "non-A\ sample number
"A"
"non-A"
[hux na- nua x nal-(a./2)P xnaixnaxmxn
[x×13 6 x5]- 3212/ x 32
13×19 ×14 ×18
because the death statistic is 1.73 Less than 3.84, from formula (7), we can conclude that: accept the null hypothesis, that there is no significant difference between the sweetness of sugar and the sweetness of sweeteners. Or the evaluator is unable to distinguish the sweetness of sweeteners from differences. The sweetness difference of sugar is similar to the situation in Example 1 in A1, except that the difference here is that "non-A\including two-sweetener (non-A)" is different from (non-A) 2° Evaluator See Table A3 for discrimination.
Number of samples of “A\ and “non-A\”
Number of samples→
Number of discriminations
Discrimination as “A\ or “non-A\” The back
test can be the following targets:
sexual difference.
difference.
“not A”
“A\”||tt| |" (non-A) "
Non-A"
Test whether the sweetness of sucrose "A" and the sweetness of the other two sweeteners ((Non-A)\+"(Non-A)2) are significantly related to Sugar "A\Sweetener (A)" Sweetener "(Non-A)"\ Whether the three have significant sweetness in terms of sweetness, respectively test sugar "A\ and sweetener "(Non-A)\ the difference between sugar "A\" and sweetener "(non-A)2\"; the difference between sweetener "(non-A)" and sweetener (non-A)2\ in sweetness In order to achieve the goal of testing a. or c:, we must first conduct the test of standard b. After the test of standard b., if the samples (A) "non-A" \ (non-A) 2) If there is no significant difference, there is no need to conduct the test of a. and C.
When testing b., you can use formula (1) or (2), but in this case = 1, 2; J = 1, 2, 3. In this example, because n is greater than 40 and n is greater than 5, Use formula (2):
"(non-A)2"
-_ (60-145×100/280)
145x100/280
(40- 135×100/280))
135×100/280
(55-135×100/280
135x100/280
(40-135×80 / 280)
135×80/280
(45-145×100/280))
145x100/280
(40-145×80/280)| |tt||145x80/280
Because the × total increase of 4.65 is less than the corresponding critical value of 5.99 corresponding to (2-1)×(3-1)=2; α=0.05, Garden
The conclusion is that there is no significant difference in sweetness between anorthose, sweetener (non-A) and sweetener (non-A).
When testing a. and C. Table A1 can be transformed into Table A4 to Table A7, and the inspection method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non-A\"
Number of samples→| |tt||Discrimination number
Number of answers that are judged as \A\ or \(not
A)\
Number of samples→
Discrimination number||tt| |“Non-A”
“Non-A”
“A\ and\Non-A\ sample number
“A\ and“(Non-A)\ sample number||tt| |“non-A”
“(non-A)”
“A\ and “(non-A)2”
Number of samples
“(non- A) 2"
Cumulative
Number of answers to A) 2\
"(non-A) 2\
Number of samples→
Number of discriminations| |tt||Number of answers judged as \A\ or \non
"
"(non-A)"
"(non-A)2"
In advance Only show the evaluators samples "A"
"(non-A)\ and "(non-A)2"
Number of samples
"(non-A)\||tt| |Appendix B
Test answer sheet format
(reference)
1. Identify the sample "A\ and return it to the management staff. Take out the coded sample." ( Not A) 2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random. All "non-A\ samples are of the same type. The specific number of the two types of samples is not announced in advance. 3. Taste and record your judgement below. Sample Code
+++++++++++
............
++ ++++++++
............
The sample is
“non-A”
.... .....
Comment:
Preview the evaluators with samples "A" and "non-A" respectively.
1. Recognize samples "A" and "non-A" Non-A\ and return it to the management staff, take out the coded sample. 口
Evaluator
2. The order of the coded series samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two types of samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample Code
Comments:
Additional Notes:
"A"
The sample is
“Non-A”
This standard is proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard is issued by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences , the China Institute of Standardization and Information Classification and Coding drafted this standard. The main drafters are Li Weiguo, Zhou Suyu and Bi Jian.
(50 × 65 - 55 × 30p × 20080 ×120 ×105 × 95
“Not A”
Because the total needle value 5.34 is greater than 3.84, according to formula (5), we can conclude that we reject the null hypothesis and accept the alternative hypothesis, that is, we believe that the sweetness of sugar The sweetness of sugar (A\ leftover) is significantly different from that of a certain sweetener at a 5% significance level. The goal is to determine whether an evaluator can distinguish the sweetness of a sweetener from that of an anorectic sweetener. The number of products evaluated by the evaluator: 13 "A" and 19 “Non-A° evaluator discrimination is shown in Table A2.
Number of samples 1
Number of discriminations
Number of answers discriminated as \A\ or \non-A”
|tt||“A”
“Not A”
Since n. is less than 40 and n is equal to 5, so use the formula (A1) "A\ and "non-A\ sample number
"A"
"non-A"
[hux na- nua x nal-(a./2)P xnaixnaxmxn
[x×13 6 x5]- 3212/ x 32
13×19 ×14 ×18
because the death statistic is 1.73 Less than 3.84, from formula (7), we can conclude that: accept the null hypothesis, that there is no significant difference between the sweetness of sugar and the sweetness of sweeteners. Or the evaluator is unable to distinguish the sweetness of sweeteners from differences. The sweetness difference of sugar is similar to the situation in Example 1 in A1, except that the difference here is that "non-A\including two-sweetener (non-A)" is different from (non-A) 2° Evaluator See Table A3 for discrimination.
Number of samples of “A\ and “non-A\”
Number of samples→
Number of discriminations
Discrimination as “A\ or “non-A\” The back
test can be the following targets:
sexual difference.
difference.
“not A”
“A\”||tt| |" (non-A) "
Non-A"
Test whether the sweetness of sucrose "A" and the sweetness of the other two sweeteners ((Non-A)\+"(Non-A)2) are significantly related to Sugar "A\Sweetener (A)" Sweetener "(Non-A)"\ Whether the three have significant sweetness in terms of sweetness, respectively test sugar "A\ and sweetener "(Non-A)\ the difference between sugar "A\" and sweetener "(non-A)2\"; the difference between sweetener "(non-A)" and sweetener (non-A)2\ in sweetness In order to achieve the goal of testing a. or c:, we must first conduct the test of standard b. After the test of standard b., if the samples (A) "non-A" \ (non-A) 2) If there is no significant difference, there is no need to conduct the test of a. and C.
When testing b., you can use formula (1) or (2), but in this case = 1, 2; J = 1, 2, 3. In this example, because n is greater than 40 and n is greater than 5, Use formula (2):
"(non-A)2"
-_ (60-145×100/280)
145x100/280
(40- 135×100/280))
135×100/280
(55-135×100/280
135x100/280
(40-135×80 / 280)
135×80/280
(45-145×100/280))
145x100/280
(40-145×80/280)| |tt||145x80/280
Because the × total increase of 4.65 is less than the corresponding critical value of 5.99 corresponding to (2-1)×(3-1)=2; α=0.05, Garden
The conclusion is that there is no significant difference in sweetness between anorthose, sweetener (non-A) and sweetener (non-A).
When testing a. and C. Table A1 can be transformed into Table A4 to Table A7, and the inspection method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non-A\"
Number of samples→| |tt||Discrimination number
Number of answers that are judged as \A\ or \(not
A)\
Number of samples→
Discrimination number||tt| |“Non-A”
“Non-A”
“A\ and\Non-A\ sample number
“A\ and“(Non-A)\ sample number||tt| |“non-A”
“(non-A)”
“A\ and “(non-A)2”
Number of samples
“(non- A) 2"
Cumulative
Number of answers to A) 2\
"(non-A) 2\
Number of samples→
Number of discriminations| |tt||Number of answers judged as \A\ or \non
"
"(non-A)"
"(non-A)2"
In advance Only show the evaluators samples "A"
"(non-A)\ and "(non-A)2"
Number of samples
"(non-A)\||tt| |Appendix B
Test answer form format
(reference)
1. Identify the sample "A\ and return it to the management personnel. Take out the coded sample." ( Not A) 2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random. All "non-A\ samples are of the same type. The specific number of the two types of samples is not announced in advance. 3. Taste and record your judgement below. Sample Code
+++++++++++
............
++ ++++++++
............
The sample is
“non-A”
.... .....
Comment:
Preview the evaluators with samples "A" and "non-A" respectively.
1. Recognize samples "A" and "non-A" Non-A\ and return it to the management staff, take out the coded sample. 口
Evaluator
2. The order of the coded series samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two types of samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample Code
Comments:
Additional Notes:
"A"
The sample is
“Non-A”
This standard is proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard is issued by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences , the China Institute of Standardization and Information Classification and Coding drafted this standard. The main drafters are Li Weiguo, Zhou Suyu and Bi Jian.Conclusion: Accept the null hypothesis and think that there is no significant difference between the sweetness of sugar and sweetener. Or the evaluator can distinguish the sweetness of sweetener from the sweetness of sugar. A3
is similar to the situation in Example 1 in A1, except that the difference between "non-A\ including two kinds of sweeteners (non-A)" and (non-A)2° evaluator discrimination is shown in Table A3.
"A\ and "non-A\" sample number
sample number →
discrimination number
discrimination as "A\ or "non-A\"
test can be the following target:
difference.
difference.
“Non-A”
“A\”
“(Non-A)”
Non-A”
Test whether the sweetness of sucrose “A” and the sweetness of the other two sweeteners ((Non-A)\+“(Non-A)2) are significant. Test whether the direction of sugar “A\, sweetener (A)” and sweetener “(Non-A)”\ are significant in terms of sweetness. Test the direction of sugar “A\ and sweetener “(Non-A)\; the direction of difference sugar “A\ and sweetener “(Non-A)2\; the direction of sweetener “(Non-A)” and sweetener (Non-A)2 \ is there a significant difference in sweetness. In order to achieve the goal of testing a. or c:, we must first test b. After testing b., if there is no significant difference between the samples (A" "non-A)\ (non-A)2), there is no need to test a. and C.
When testing b., you can use formula (1) or (2), but at this time = 1, 2; J = 1, 2, 3. In this example, because n is greater than 40 and n is greater than 5, formula (2) is used:
"(non-A)2"
-_ (60-145×100/280)
145x100/280
(40-135×100/280))
135×100/280
(55-135×100/280
135x100/280
(40-1 35×80/ 280)
135×80/280
(45-145×100/280))
145x100/280
(40-145×80/280)
145x80/280
Because the × total increase of 4.65 is less than the corresponding critical value of 5.99 corresponding to (2-1)×(3-1)=2; α=0.05, we can conclude that anhydrous sugar and sweetener (non-A) There is no significant difference in sweetness among the three "sweeteners (non-A)".
When testing a. and C., Table A1 can be transformed into Table A4 to Table A7, and the testing method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \non-A\"
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \(non
A)\
Number of samples→||tt ||Number of discriminations
“Non-A”
“Non-A”
Number of samples of “A\ and\Non-A\
“A\ and “(Non-A)\”Number of samples
“Non-A”
“(Non-A)”
“A\ and “(Non-A)2”
Number of samples
“(Non-A)2”
Cumulative
Number of answers to “A)2\
“(Non-A)2\
Number of samples→
Discriminations Number of identification
Number of answers identified as \A\ or \Non
“(Non-A)”
“(Non-A)2”
Only sample “A” is shown to the evaluators in advance
“(Non-A)\ and “(Non-A)2”
Number of samples
“(Non-A)\
Appendix B
Sample format of inspection answer sheet
(reference)
1. Identify sample “A\ and return it to the management personnel. Take out the coded sample. “(Non-A)2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \Non-A\ is random. All "non-A" samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample code
+++++++++++
............
++++++++++
............
The sample is
"non-A"
.........
Comments:
Preview the evaluators with samples "A" and "non-A" separately.
1. Identify samples "A" and "non-A" and return them to the management staff, and take out the coded samples.口
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample coding
Comments:
Additional sharp note:
“A”
Sample is
“Non-A”
This standard was proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard was drafted by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences and the China Institute of Standardization and Information Classification and Coding. The main drafters of this standard are Li Weige, Zhou Suyu and Bi Jian.Conclusion: Accept the null hypothesis and think that there is no significant difference between the sweetness of sugar and sweetener. Or the evaluator can distinguish the sweetness of sweetener from the sweetness of sugar. A3
is similar to the situation in Example 1 in A1, except that the difference between "non-A\ including two kinds of sweeteners (non-A)" and (non-A)2° evaluator discrimination is shown in Table A3.
"A\ and "non-A\" sample number
sample number →
discrimination number
discrimination as "A\ or "non-A\"
test can be the following target:
difference.
difference.
“Non-A”
“A\”
“(Non-A)”
Non-A”
Test whether the sweetness of sucrose “A” and the sweetness of the other two sweeteners ((Non-A)\+“(Non-A)2) are significant. Test whether the direction of sugar “A\, sweetener (A)” and sweetener “(Non-A)”\ are significant in terms of sweetness. Test the direction of sugar “A\ and sweetener “(Non-A)\; the direction of difference sugar “A\ and sweetener “(Non-A)2\; the direction of sweetener “(Non-A)” and sweetener (Non-A)2 \ is there a significant difference in sweetness. In order to achieve the goal of testing a. or c:, we must first test b. After testing b., if there is no significant difference between the samples (A" "non-A)\ (non-A)2), there is no need to test a. and C.
When testing b., you can use formula (1) or (2), but at this time = 1, 2; J = 1, 2, 3. In this example, because n is greater than 40 and n is greater than 5, formula (2) is used:
"(non-A)2"
-_ (60-145×100/280)
145x100/280
(40-135×100/280))
135×100/280
(55-135×100/280
135x100/280
(40-1 35×80/ 280)
135×80/280
(45-145×100/280))
145x100/280
(40-145×80/280)
145x80/280
Because the × total increase of 4.65 is less than the corresponding critical value of 5.99 corresponding to (2-1)×(3-1)=2; α=0.05, we can conclude that anhydrous sugar and sweetener (non-A) There is no significant difference in sweetness among the three "sweeteners (non-A)".
When testing a. and C., Table A1 can be transformed into Table A4 to Table A7, and the testing method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \non-A\"
Number of samples→
Number of discriminations
Number of answers that are judged as \A\ or \(non
A)\bzxZ.net
Number of samples→||tt ||Number of discriminations
“Non-A”
“Non-A”
Number of samples of “A\ and\Non-A\
“A\ and “(Non-A)\”Number of samples
“Non-A”
“(Non-A)”
“A\ and “(Non-A)2”
Number of samples
“(Non-A)2”
Cumulative
Number of answers to “A)2\
“(Non-A)2\
Number of samples→
Discriminations Number of identification
Number of answers identified as \A\ or \Non
“(Non-A)”
“(Non-A)2”
Only sample “A” is shown to the evaluators in advance
“(Non-A)\ and “(Non-A)2”
Number of samples
“(Non-A)\
Appendix B
Sample format of inspection answer sheet
(reference)
1. Identify sample “A\ and return it to the management personnel. Take out the coded sample. “(Non-A)2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \Non-A\ is random. All "non-A" samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample code
+++++++++++
............
++++++++++
............
The sample is
"non-A"
.........
Comments:
Preview the evaluators with samples "A" and "non-A" separately.
1. Identify samples "A" and "non-A" and return them to the management staff, and take out the coded samples.口
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample coding
Comments:
Additional sharp note:
“A”
Sample is
“Non-A”
This standard was proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard was drafted by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences and the China Institute of Standardization and Information Classification and Coding. The main drafters of this standard are Li Weige, Zhou Suyu and Bi Jian.Table A1 can be transformed into Table A4 to Table A7, and the inspection method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non-A\"
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \(non
A)\
Number of samples→
Number of discriminations
"non-A"
"non-A"
"Number of samples of A\ and \non-A\
"A\ and "(non-A)\"Number of samples
"non-A"
"(non-A)"
"A\ and "(non-A)2"
Number of samples
"(non-A) tt||Cumulative
Number of answers for A) 2\|tt||“(Non-A) 2\
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non
“(Non-A)”
“(Non-A) 2”
Only samples “A” and “(Non-A)\ and “(Non-A) 2” are shown to the evaluators in advance
“(Non-A)\ and “(Non-A) 2”
Number of samples
“(Non-A)\
Appendix B
Sample format of inspection answer sheet
(reference)
1. Identify sample “A\ and return it to the management staff. Take out the coded sample. “(Non-A) 2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random. All "non-A\ samples are of the same type. The specific number of the two samples is not announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample code
+++++++++++
............
++++++++++
............
The sample is
"non-A"
.........
Comments:
Preview the evaluators with samples "A\" and "non-A" separately.
1. Identify samples "A\ and \non-A\ and return them to the management staff, and take out the coded samples.口
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample coding
Comments:
Additional sharp note:
“A”
Sample is
“Non-A”
This standard was proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard was drafted by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences and the China Institute of Standardization and Information Classification and Coding. The main drafters of this standard are Li Weige, Zhou Suyu and Bi Jian.Table A1 can be transformed into Table A4 to Table A7, and the inspection method is similar to A1. Table A4
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non-A\"
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \(non
A)\
Number of samples→
Number of discriminations
"non-A"
"non-A"
"Number of samples of A\ and \non-A\
"A\ and "(non-A)\"Number of samples
"non-A"
"(non-A)"
"A\ and "(non-A)2"
Number of samples
"(non-A) tt||Cumulative
Number of answers for A) 2\|tt||“(Non-A) 2\
Number of samples→
Number of discriminations
Number of answers discriminated as \A\ or \non
“(Non-A)”
“(Non-A) 2”
Only samples “A” and “(Non-A)\ and “(Non-A) 2” are shown to the evaluators in advance
“(Non-A)\ and “(Non-A) 2”
Number of samples
“(Non-A)\
Appendix B
Sample format of inspection answer sheet
(reference)
1. Identify sample “A\ and return it to the management staff. Take out the coded sample. “(Non-A) 2”
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random. All "non-A\ samples are of the same type. The specific number of the two samples is not announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample code
+++++++++++
............
++++++++++
............
The sample is
"non-A"
.........
Comments:
Preview the evaluators with samples "A\" and "non-A" separately.
1. Identify samples "A\ and \non-A\ and return them to the management staff, and take out the coded samples.口
Evaluator
2. The order of the coded series of samples consisting of \A\ and \non-A\ is random, and all \non-A\ samples are of the same type. The specific number of the two samples will not be announced in advance. 3. Taste the samples one by one in order and record your judgment below. Sample coding
Comments:
Additional sharp note:
“A”
Sample is
“Non-A”
This standard was proposed by the State Administration of Technical Supervision and the Ministry of Agriculture of the People’s Republic of China. This standard is under the jurisdiction of the National Agricultural Analysis Standardization Technical Committee. This standard was drafted by the Analysis and Testing Center of the Chinese Academy of Agricultural Sciences and the China Institute of Standardization and Information Classification and Coding. The main drafters of this standard are Li Weige, Zhou Suyu and Bi Jian.
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