2 - American Meat Science Association

384
A GROUP EXPERIENCE
IN
SENSORY EWAIUATION*
D . G . CORNISH and R. E . BALDWIN
Oscar Mayer & Co. and
University of Missouri
Yesterday, most of the RMC conference members participated i n the
wiener t a s t e t e s t conducted j u s t before t h e noon lunch. Analyses have
been conducted on the data from t h a t t e s t . This session is t o inform
you of the outcome of some of those analyses.
Before showing you some of the a n a l y t i c a l r e s u l t s , I would l i k e t o
mention a few reasons f o r performing t h i s exercise. F i r s t , the
organizers of t h i s meeting believed it would be i n t e r e s t i n g f o r those
i n attendance t o p a r t i c i p a t e d i r e c t l y i n t h e generation of information
f o r t h i s p a r t of the program. Secondly, it was considered t h a t it may
be of i n t e r e s t t o demonstrate the powers of time-share computers and
terminals.
The products you evaluated i n yesterday's t e s t were production
wieners. They were designated as pork wieners and beef wieners. The
composition and n u t r i t i o n a l information of pork and of beef wieners
a r e presented i n t a b l e 1. However, f o r the t a s t e t e s t , random code
numbers were assigned t o t h e samples and placement on t h e t r a y a l s o
was randomly assigned. The design of the t e s t w a s balanced s o t h a t
h a l f of t h e participants t a s t e d pork f i r s t and half t a s t e d beef f i r s t .
The meat formulation of the pork wieners w a s predominantly pork trim
w i t h some beef trim, while the meat formulation of t h e beef wieners w a s
lo@ beef trim. The wiener made from a combination of pork and beef
will be referred t o as pork wiener throughout t h i s presentation.
You were asked t o record your evaluation on a b a l l o t shown i n
figure 1. You were a l s o asked t o indicate some information concerning
your personal background. This b a l l o t has been coded t o enable entry
of t h e information i n t o the computer system.
Yesterday's sensory t e s t would be considered a preference t e s t w i t h
hedonic r a t i n g s . The objectives of a preference t e s t a r e t o predict
d i r e c t i o n of choice end sometimes t h e extent t o which a product appeals
t o some population. To obtain a measure of consumer reaction or
preference f o r one sample over another, a large number of panelists i s
desirable. These panelists not only need not, but should not, be trained.
The t a s t e t e s t data from yesterday's session was analyzed by using
a portable terminal. This p a r t i c u l a r terminal has t h e a b i l i t y t o access
350 c i t i e s i n North America w i t h data processing service. The methods
used t o input the t a s t e t e s t data were as follows:
* Presented
a t the 28th Annual Reciprocal Meat Conference of t h e American
Meat Science Association, 1975.
k IGU1,L 1 0
W IENEK EVALUATION
T a s t e t h e samples i n the o r d e r t h e y a r e p r e s e n t e d , from l e f t t o r i g h t .
I n d i c a t e how well you l i k e
y o u r iiiouth with a s i p o f water b e f o r e t a s t i n g e a c h .
o r d i s l i k e t h e p r o d u c t s b y p l a c i n g a clieck mark o n t h e s c a l e s b e l o w :
SmiPLE
PORK W I E ~ER
J s
__ L
____5
4
3
2
1
SAMPLE
RFFF WMERS
A_5
L I K E VERY MUCH
L I K E MODERATELY
4 -
LIKE S L I G H T L Y
3
D I S L I K E SLIGHTLY
7
D I S L I K E MODERATELY
1
D I S L I K E VERY MUCH
P L E A S E PLACE A CHECK MARK I N THE A P P R O P R I A T E CATEGORIES BELOW:
1. EMPLOYMENT :
1
7
3
_LJ-2.
1
7
3
4
3.
1
Education
2
Industry
6.
~esearcti
Lnstitute ( e g . , A . M . l . F . , WARF)
EDUCATlON:
High School
B.S.
M.S.
Ph.D.
AGE:
d. 20
20-29
4
40-49
6
> 59
5
--
1
SMOKE:
Government
2
3
5.
30-39
50-59
1
7
3
4
5
Clear
Yes
No
GEOGRAPHICAL LOCATlON
West ( A )
North C e n t r a l (B)
N o r t h East (C)
South (D)
Foreign
38 6
U ~ E I L L . .I
AND OF
CORPOS IT I O J A i W IIIUTR I T I Oi4AL I i4FORI"IATI Oil OF PORK
BEEF \!I ENERS
I p i ~ l < \ - [ ~
P0R lLk/~ F J I HS.
~ POICI;,
~ ~ ~ - \ I~A I~E R; ,
EEEF,
SALT,
CORN SYRUP,
DEXTROSE, FLAVORING,
S O D IUM ASCORBATE,
SO11 1 U M
CALOR I ES :
PROTE I N :
C A 13130HYD R A T E :
FAT:
PRO-I-E IN :
V I T , A,:
VIT, C I :
-rH I AM I N E :
R I B O F L A VNI :
IJ I A C I rd :
CALC I UM:
IRON:
R
--EEF\JI61\LER-S.
B E E F , H A T ~ ~CORN
, SYRUP,
SALT, FLAVORING, DEx-mosE,
PAPRIKA,
S O D I U M ASCORBATE,
SODIUIINITRITE
N I T :I I TE
I'J UT R I T I 014 A 1 V A LUES/ L I I1K
140
5
GM
13
GM
GM
2
10
0
15
4
2
4
0
2
2
6
2
X OF
1'10
5
2
13
U I S , RDA
10
0
15
0
2
4
0
2
2
8
2
GM
GM
GM
387
1. Dial t h e telephone access number i n S t . Louis.
2.
Type i n t h e coded information from each b a l l o t using t h e
portable terminal.
3.
Store data, and request a "canned program" run.
4.
I n s t r u c t t h e computer t o run the desired program and l i s t
the results.
The s t a t i s t i c a l systems o r "canned programs" t h a t a r e a v a i l a b l e
with t h i s p a r t i c u l a r u n i t a r e l i s t e d i n t a b l e 2 . The systems t h a t were
used i n analyzing t h e data f r o m t h e t a s t e t e s t a r e t h e l a s t 8 programs.
Figures 2 and 3 i l l u s t r a t e t h e computer's a b i l i t y t o generate a
bargraph. Figure 2 shows t h e number of people from four employment
areas who p a r t i c i p a t e d i n yesterday's t e s t . The next bargraph ( f i g u r e
3 ) shows t h e number of people a t each educational l e v e l who p a r t i c i p a t e d
i n t h e t a s t e t e s t . The information provided i n these bargraphs indicate
t h a t t h e majority of t h e panel p a r t i c i p a n t s were from education f i e l d
and had F'h.D. degrees.
The computer system i s a l s o capable of producing data i n histogram
form. The upper h a l f of f i g u r e 4 i l l u s t r a t e s t h e number of people who
f e l l i n t o d i f f e r e n t age groups. The histogram on t h e lower portion of
t h e f l g u r e 4 d e a l s with the number of paxticipants from d i f f e r e n t
geographical l o c a t i o n s .
The computer w a s requested t o display frequency t a b l e s on male/
female and smoker/non-smoker r a t i o s . The r e s u l t s a r e shown i n t a b l e 3 .
The information which I have described thus f a r has d e a l t with
t h e personal p r o f i l e s of t h e p a r t i c i p a n t s i n yesterday's t a s t e t e s t .
The next 2 f i g u r e s show how t h e p a r t i c i p a n t s r a t e d pork wieners and
beef wieners. This information i s given i n t h e form of simple s t a t i s t i c s
and histograms. Figure 5 i l l u s t r a t e s t h e d i s t r i b u t i o n of r a t i n g s given
exclusively t o pork wieners. The d i s t r i b u t i o n of r a t i n g s given t o beef
wieners i s contained i n f i g u r e 6.
The information provided i n t a b l e 4 summarizes t h e data acquired i n
t h e t a s t e t e s t broken down according t o employment, education, age, sex,
smokers and geographical l o c a t i o n . The r e s u l t s shown i n t h i s t a b l e make
it possible t o r a p i d l y scan t h e data and provide a b a s i s f o r deciding i f
f u r t h e r s t a t i s t i c a l analyses a r e desirable o r necessary. For example,
it i s impossible t o Judge from t h e information provided i n t h i s t a b l e
whether o r not a s i g n i f i c a n t difference e x i s t s between t h e o v e r a l l mean
of t h e r a t i n g given t o pork wieners versus t h e o v e r a l l r a t i n g given t o
beef wieners.
The computer w a s asked t o provide a t - s t a t i s t i c which can be used
t o determine i f t h e o v e r a l l mean of t h e r a t i n g s given t o pork wieners
and the o v e r a l l mean of t h e r a t i n g s given t o beef wieners a r e s i g n i f i c a n t l y d i f f e r e n t . The " t " - s t a t i s t i c f o r the o v e r a l l means i s shown i n
FH EQ
0
e
e
0
EDUCAT I ON
GOVEHNNENT
INDUSTRY
1 36
15
32
RESEARCH INSTITUTE 1 1
0
0
-_e
e
a
e
Fti Ell
0
0
2
27
52
115
0
0
NOTE:
F H EG]
0
0
54
53
38
28
1H
0
0
HEHL E A C h
'&'
AGE
h€.,FHESENTS
2 OBSERVATIONS.
EhEO
0
CI
1
0
11
u
u
0
0
0
0
0
7
0
0
0
0
0
0
0
0
0
31
0
0
0
0
0
0
0
0
0
91
0
0
ti
0
0
0
0
0
0
66
S M P L E STATISTICS b O h P O R K
NO.
OF' ODSEHVATlONS
146
Se091b4
0 e82363
2*G(JOUU
6.00000
392
196
E HEO
0
0
5
0
0
0
0
16
u
0
0
0
44
0
0
0
0
72
0
0
0
0
59
0
0
AVEUGE:
STANDARD DEVIATION 8
SbiLLEST OBSEHVA T I O N :
LAhGEST OBSEHVATION 8
393
IkIjLk, ‘1.
STATISTICAL ANALYSIS MODULES
REGRESSION ANALYSI s
ONE-\/AY ANALYSIS OF VARIANCE
2 AND 5 FACTORANALYSIS OF VARIANCE
WEIBULL
RELIABILITY
ANALYS I s
CHI -SQUARE TEST
EXPONENTIAL SMOOTHI NG
POLYNOMIAL CURVE FITTING
LEASTSQUARES POLYNOMIAL FIT
CONFIDENCE
LIMITS
AUTOCORRELATION
LEASTSQUARES REGRESSION
CORRELATION VATR IX
FREQUENCY COUNT OF TWO CROSS V A R I A B L E S
REGRESSION ANALYSIS ON BIVARIATE DATA
GROWTH RATE CALCULATION
I ~ V I N GAVERAGES
FITS FOR NEIGHTED DATA POLYNOMIAL
BARGRAPH
11I STOGRAM
FREQUENCY TABLE
SIMPLE STATI ST Ics
T-TEST
CORR E L A T I ON
MULTIPLE
REGRESSION
X-Y PLOT
394
FIiEDUENCY TABLE FOR SEXCODE
MALE
FEbiALE
FFi EQ
PCT.
CUM*
E HEGi
184
12
93.88
6.12
164
196
CUM.
PCl.
93.88
100.00
F h E Q U U C Y TAELE FOR SWOHCODE
FR EQ
YES
NO
70
126
PCT*
35.71
64.29
CUM.
Fh EQ
70
A96
CUM.
PCT*
35.71
100*00
'lAt3LE 4 .
SAMPLE STATISTICS
UlP LO Y Pi EN 1'
EIJUCATION
G o v EWN EN 'r
OF
NO.
OBSEWV.
136
is
I NDU s 'rLY
I;E:s EAli CH I Eu s 1 I 'AUlE
32
11
H I G b SCHOOL
B.S.
M.S.
El1.D.
27
52
2
FOhK
MEAN
SOD.
5.2
U.b
4.9
4.b
0.8
4.9
5.5
BEEF
MEAN
S.D.
0.8
4.9
5.1
0.9
5.2
0.7
0.9
0.8
0 08
4.3
5.0
1.0
1.1
0.9
0.8
1.4
4.5
0.9
0.
4.&
0.
0.9
5.2
0.
0.9
0.9
u.7
0.4
0.6
4.6
1.1
1.1
1.0
1.1
184
12
5.1
0.8
0.5
4.8
5.4
1.0
1.0
70
126
5.1
5.1
0.7
0.5
4.7
4.9
1.1
1.0
19
5.1
0.8
4.5
21
52
6
4.9
1.0
1.0
1.0
0.9
115
4.8
5.1
5.1
4.8
4.9
1.0
1.1
AGE
0
59
53
38
28
18
0.
5.1
5.1
5.1
5.2
4.b
5.0
4.9
SLX
5.5
SMOKE
YES
NO
GEOGHAPHIC LOCAI'ION
WEST
NOh 1'H C EN 1'FiAL
NOFr'I'h EAST
SOCIl'H
F ON E I GN
58
5.1
5.2
5.0
0.8
1.0
0.8
0.
4.9
4.5
5.1
4.3
1.4
396
t a b l e 5. A s i g n i f i c a n t l y (P < 0.05) higher r a t i n g was given t o the
pork wieners when compared t o beef w i e n e r s . The t - s t a t i s t i c can be
used t o determine more s u b t l e e f f e c t s on ratings. For example, the
comparison of preference t o pork wieners between males and females
( t a b l e 6 ) , and t h e difference i n preference t o pork wieners between
smokers and non-smokers (table 7). The r e s u l t s indicate t h e r e was
no s i g n i f i c a n t difference i n preference t o pork wieners between males
and females o r between smokers and non-smokers.
The r e l a t i o n s h i p of t h e r a t i n g s given t o pork wieners as influenced
by age of p a r t i c i p a n t s m i g h t be u s e f u l l y subjected t o f u r t h e r evaluation.
Therefore, t h e computer was instructed t o produce a s e r i e s of equations
t o describe t h e r e l a t i o n s h i p between these two variables. This i n f o r mation i s s h m i n t a b l e 8. The curve w i t h t h e l a r g e s t index i s t h e
b e s t - f i t . Curve 5 , y=l/(a+B%) r e s u l t s i n an index of determination
of 0.005C8. The index of determination i s r2. Thus, t h e r e s u l t s
i n d i c a t e l i t t l e o r no r e l a t i o n s h i p between t h e r a t i n g s given t o pork
wieners and age of t h e judge.
Another c a p a b i l i t y of t h e computer and terminal system i s t o
produce multiple regression and multiple c o r r e l a t i o n c o e f f i c i e n t s as
shown i n t a b l e 9. The r e s u l t s i n d i c a t e t h a t there i s l i t t l e o r no
r e l a t i o n s h i p of the r a t i n g given t o pork wieners t o age and education
of t h e p a n e l i s t .
A simple but i n t e r e s t i n g system c a p a b i l i t y i s the production of
x-y p l o t s . Figure 7 shows the means of t h e r a t i n g s given t o pork and
beef wieners on t h e basis of age c l a s s i f i c a t i o n .
I n summary, t h e r e a r e no s e t formulas t h a t can be universally
applied t o analyze sensory problems. Each company o r i n s t i t u t i o n must
evaluate i t s own needs and d e s i r e s and develop sensory c a p a b i l i t i e s
i n accordance w i t h those needs. For example, this computer system
functions very w e l l f o r Market Research people who conduct tests on
new products. I n t h i s example, a prompt, r e l i a b l e feedback of consumer
opinion i s needed.
Today I have presented a portion of t h e t o t a l amount of data which
was generated. The terminal which was used i n analyzing data from t h i s
sensory t e s t was furnished by General E l e c t r i c Co. I have the terminal
i n t h e educational e x h i b i t room f o r those of you i n t e r e s t e d . The data
output yesterday c o s t $27 and took 1 5 minutes f o r r e t r i v a l .
I would l i k e t o thank our hosts here a t Missouri f o r the telephone
hook-up provided a t t h e conference. A s p e c i a l thanks f o r D r . Ruth
Baldwin and h e r staff f o r conducting t h e sensory t e s t , and a l s o f o r
h e l p in analyzing t h e r e s u l t s .
I h L hOLLOWING b O U H h k P O l h E 3 E S khL O P T I O N A L EOH CALCULAlION O F A
I - S I A T I S l l C Oh 1 H E IrEANS OF SAMFLE VAfiIABLES POL)<
&
BEEF
C O k P U 1 E ; D ?' VALUE
2 70820
I'AI3ULAR "T" VALUES
1.96 ( P . * . 0 5 )
2.137 ( P . < . O l )
DEGkE.ES OF FREEDOPI
390 .oo
2 - l A I LLD PliOBAE I L I TY
0 00 70 6
THE FOLLOWING FQUh hYFOlhIESES A R E OPTIONAL FOR C A L C U L A T I O N OF A
T - S T A T I S T I C ON 'i'hE MEANS OP SAMPLE VAKIARLES FkPiALE
&
PKF'EMALE
1
2
3
4
5
FIEAN O F PIWALE
P r U N O F PKE-ALE
M I A N OF PKPiiLE
~ v I J A NOF PXMALE
EXIT EhOh TTESTo
= G I V E N VALUE
= N U N OF PHFENALEJ ASSUMING 2 VARIANCES ARE EQUAL
= M E A N OF PHFEPALE, A S S U M I N G 2 VAHIANCES ARE UNEQUAL
= M E A N OF FKFEPALE, khEHt THE VllliIABLES A R E HELfi'I'LD
HYPOTHESIS TYPE --?2
CO.PiUTED T VALUE
-1.78119
TAbULAR "T" VALUES
1.96 < P . < o O 5 )
2.97
<P.<.Ol)
DEGHEES OF F'HEEDOM
194000
-
2 TA I LED PH OBAB I L I 1 Y
0 007645
399
THE FOLLOWING F O U H hYPOTHESES A R E OPTIONAL FOR CALCULATION OF A
T - S T A ' I I S T I C ON 1 h E PiFANS O F SAMPLE VARIABLES PKSMOKE
&
PKNOSMOIi
1 NEAN O F PKSMOKE
2 M E A N O F PKSMOKE
3 MEAN Ob PKSPiOIiG
4 M E A N O F PKSPiOKE
5 E X 1 1 F R O M ?'TEST.
= GIVEN VALUE
= hWiV O F PKNOSMOKI ASSUMING 2 VARIANCES ARE EQUAL
= PIEAN OF PKNOSIVIOKI ASSUMING 2 VAZiIANCES A R E UNEQUAL
= N U N OF PKNOSKOKI WHEFrE THE V A h I H b L E S AHE HLLATLD
HYPOTHESIS TYPE --?2
COtiPUTED T VALUE
0 046436
TABULAR "T" VALUES
1 * 9 8 (P.<.O5)
2 . 9 7 < P . < * 0 11
DEGREES OF FREEDOM
194*OO
2 - T A I LEIj PRODAD I L 1 TY
0 64291
400
Y UAIIIARLE:
X bAii I A D L E
POHH
AGECOLE
XbIEAN:
3*454062E+OO
N U P B E&
CURVE
1
2
3
4
5
6
Y =A +u "X
k = A U EN- (B*X 1
Y=A'(
x -B 1
k=A+(B/X)
k = 1 / < A + B Q X1
Y = X /<A *x +B >
YMEAN:
5.041837E+00
1NDEX
0.00140
0 000265
0.00234
0~ O 0 U 6 4
OOU0500
U.O(j400
A
5*01006E+00
4088889E+00
4.681 75E+OU
5.14854E+CJO
2.11142k-01
1 *95523E-01
B
2 *36747E*
7042731E.
2.3 1 €554E.
- 1 *70%69E*
-20 3641 3 E
2023827E
4 01
XFIEAN
3 *4540b2E+UO
3*4%8571E+00
YMEAN
5*091837E+00
RULTIPLE C O R F i E L A T I O N COEFFIC I ENT =
COEFFICIENTS
6 661 6443E-03
9 5558 14 S E - 0 2
F UAI'IO(
9 *242587E-02
E S T OF SD
4 7589427E-02
8 10 402 5 2 s - 0 8
2 ~ 1 4 3 DEGREES OF FREEDOM)=
80314581E-01
w
0
I
b
(D
+
f
n
n
u
0
.-
ii
r,
m
m
C
U
c
m
u
. O
Y
O
.e
. O
0
Y
+
0
* &
.a
-
0
m
O
W
* O I
W .
0
0
4 03
D . H. Kropf: I ' v e j u s t discovered i n t a l k i n g with Dwight Loveday
that our North C e n t r a l d a t a i s contaminated, he was r a i s e d below t h e
Mason-Dixon l i n e and he wrote down North C e n t r a l .
E . C . Allen: I ' v e always been curious i n formulations such as t h i s .
How m c h do you have t o change them t o g e t d i f f e r e n c e s between beef and
pork? Is t h i s t y p i c a l what you normally f i n d ?
D . G . Cornish: The formula which was used i n y e s t e r d a y ' s t a s t e
t e s t was 60$7 pork and 4C$ beef. Some of t h e f l a v o r d i f f e r e n c e is due
t o s p i c e d i f f e r e n c e . However, t h e wieners used yesterday are market
standard items.
R . L. Henrickson:
color?
D . G . Cornish:
D . H. Kropf:
g i v e us t h e code?
W h a t was t h e function of paprika?
Flavor or
Color.
I s t i l l remember t h e number of my sample.
Odd o r even? What was t h e code?
Could you
D . G . Cornish: The odd numbered sample was pork and t h e even
number sample was b e e f .
R . E. Baldwin: Normally I wouldn't have done that. It f a c i l i t a t e d
decoding t h e raw d a t a . Usually I would a s s i g n random numbers. It was
i n t e r e s t i n g that you were able t o d e t e c t t h a t d i f f e r e n c e on t h e b a l l o t .
M. C . Brockmann: How on e a r t h d i d you g e t a n a l y t i c a l moisture t o
equal p r e c i s e l y f o u r times p r o t e i n plus lo?
D . G . Cornish:
That's a s e c r e t .
J. H. Z i e g l e r : We promised t o give you t h e opportunity t o a s k
questions--we d i d n ' t guarantee any answers.
J . W . Carpenter:
f l a v o r w i t h cost?
How i s t h e a c c e p t a b i l i t y of t h e s e two wieners on
D . G . Cornish: Currently t h e c o s t of t h e s e two wieners a r e e q u a l l y
p r i c e d . The r e l a t i o n s h i p that t h e s e two v a r i a b l e s have on acceptance i s
probably based on personal preference, d i e t , e t c . The d i f f e r e n c e t h a t
each c o n t r i b u t e t o acceptance--1 couldn't t e l l you.