RELATIVE IMPORTANCE OF COHESION AND ADHESION FOR SENSORY STICKINESS OF SEMISOLID FOODS

Journal of Texture Studies

35

(2004) 603–620.

All Rights Reserved.

©

Copyright 2004, Blackwell Publishing

603

RELATIVE IMPORTANCE OF COHESION AND ADHESION FOR SENSORY STICKINESS OF SEMISOLID FOODS

B. DUNNEWIND

1,5

, A.M. JANSSEN

2

, T. VAN VLIET

3

and H. WEENEN

4

1

TNO Nutrition and Food ResearchPO Box 360, 3700 AJ Zeist

The Netherlands

2

Agricultural and Food InnovationPO Box 17, 6700 AA Wageningen

The Netherlands

3

Wageningen Centre for Food Sciencesc/o Department of Agrotechnology and Food Sciences

Wageningen University PO Box 8129, 6700 EV Wageningen

The Netherlands

4

Numico R & DBeech Ave 52–80, 1119 PW Schiphol-Rijk

The Netherlands

Received for Publication January 13, 2004 Accepted for Publication November 8, 2004

ABSTRACT

Sensory stickiness (sticky mouthfeel) was hypothesized to result from theviscoelastic and adhesive properties of a foodstuff. The objective of the presentstudy was to investigate the relative importance of these two properties.Measurements consisted of compression – decompression cycles on a textureanalyzer, with product, type of surface, the presence or absence of saliva andcompression regime as variables. Products included commercial mayon-naises, custard desserts and warm sauces, varying in apparent viscosity (atshear rate of 10 s

-

1

) between 0.3 and 18.3 Pa.s. Fairly good models wereobtained, predicting sensory stickiness with

R

2

=

0.85–0.92. The predictivevalue of the mathematical models did not increase when the surface charac-teristics approached those of the human tongue (use of porcine lingualmucosa). Different surfaces or the use of saliva resulted in differences in theabsolute values of the parameters, but their relative values when comparingdifferent products did not change. The parameters appearing in the predictive

Blackwell Science, LtdOxford, UKJTSJournal of Texture Studies0022-4901Copyright 2004 by Food & Nutrition Press, Inc., Trumbull, Connecticut.356603620Original Article

RELATIVE IMPORTANCE OF COHESION AND ADHESION B.

DUNNEWIND

ET AL.

5

Corresponding author. TEL:

+

31 30 6944041; FAX:

+

31 30 6944295; EMAIL:[email protected]

604 B. DUNNEWIND

ET AL.

models represented product characteristics only. The type of surface was notan important factor in determining differences in sensory stickiness betweenthese samples. For the products used in this study, adhesion was large enoughto prevent detachment of the sample from the surfaces, i.e., adhesion was notlimiting. Variations in perceived stickiness could be explained with

R

2

=

0.86,based on only two product characteristics: consistency and ‘long behavior’(the extent to which necking occurs during decompression). This was betterthan the correlation between sensory stickiness and apparent viscosity(

R

2

=

0.77), confirming the relevance of ‘long behavior’ for sensorystickiness.

INTRODUCTION

Stickiness is an important sensory attribute of semisolid food materials(Szczesniak 1971; Szczesniak and Kahn 1971; Kokini

et al.

1984; De Cockand Vanhemelrijck 1995; Kampp 1995; Kilcast and Roberts 1998; Fiszmanand Damásio 2000; Adhikari

et al.

2001; Weenen

et al.

2003). Sticky mouth-feel has been described by panelists as (Weenen

et al.

2003): ‘Sticky feelingthat can be perceived by tongue and palate. A really very sticky product is forinstance the caramel of a candy bar, it is perceived between the teeth duringmastication. The degree to which the product comes loose from the differentparts of the mouth determines the intensity of stickiness.’ De Wijk

et al.

(2003)found positive correlations between sensory stickiness and the starch, fat andcarrageenan levels in custard desserts. Sensory stickiness was found to beaffected most by the starch level, followed by the carrageenan and fat levels.

Several methods for the measurement of stickiness are available andmechanisms have been proposed, which relate to both adhesion and cohesion(Kilcast and Roberts 1998; Fiszman and Damásio 2000; Adhikari

et al.

2001).Consumer ratings of stickiness were found not to correlate with objectivemeasurements of the retention of foods by the teeth (Kashket

et al.

1991).Stickiness is hypothesized here to result from the viscoelastic and adhe-

sive properties of a foodstuff: subjective stickiness is the result of the forcerequired to separate the tongue from the palate, when a semisolid product ismanipulated between the tongue and the palate, but is also assumed to bedependent on the work required to do so. This means that failure occurringwhen separating tongue and palate is expected to play a role. Two types offailure can occur. Adhesive failure occurs when the sample undergoes little orno necking before clean separation from one surface. Cohesive failure occurswhen the sample undergoes necking followed by failure within the material,leaving residues on both surfaces (Kilcast and Roberts 1998). The distinctionbetween adhesive and cohesive failure and, as a consequence, the influence

RELATIVE IMPORTANCE OF COHESION AND ADHESION 605

of the type of surface, the viscoelasticity of the sample and the separationspeed, has been addressed for products such as caramels (Kilcast and Roberts1998), dough (Hoseney and Smewing 1999) and sugar-rich foods (Adhikari

et al.

2003).The objective of the present study was to investigate the relative impor-

tance of adhesion versus the viscoelastic properties for sensory stickiness fora group of semisolid foodstuffs (mayonnaises, custard desserts and warmsauces). Product, surface and test set-up were varied to gain an insight intothis matter. It was hypothesized that differences in adhesion characteristicsare reflected in the decompression part of the measurements and that thepredictive value of models should increase when the characteristics of thesurfaces used would approach those of the tongue and palate.

MATERIALS AND METHODS

Materials

Investigated products included five custard desserts, five mayonnaisesand five sauces bought at local stores (see Table 1). The sauces were preparedfrom instant powders according to the description on the package. The sensorystickiness of the products as experienced during mastication in the mouth wasassessed by a Quantitative Descriptive Analysis panel (see sensory methodsfor a short description and Weenen

et al.

(2003) for a detailed description).The experimental effects on stickiness were analyzed by using a repeatedmeasures

ANOVA

(SPSS, SPSS Inc.) with the Huynh-Feldt value as epsilon,carried out on the sensory data averaged across three replicates.

ANOVA

indicated that differences in stickiness were significant over products(

F

14,112

=

10.9,

P

=

0.0001). The average stickiness ratings are given in Table 1.The sandpaper used to cover the plates in some of the experiments was

from Norton, type NO-FIL A219, 100 grit. This sandpaper has about the sameroughness as a human tongue (light microscopy). Of the readily availablesources of fresh material, the mucosa from the dorsal surface of porcinelingual material provides a close approximation of the human tongue surface.Porcine tongues were taken from pigs after scalding (6.5 min at 61C) at alocal slaughterhouse. Upper surface was sliced from the tongue (3 mm thick-ness, 7 cm square) and stored in 0.9 N NaCl solution at 4C until use. Salivawas human saliva gathered fresh from the laboratory technician.

Sensory Methods

Quantitative descriptive sensory analysis was used to investigate sticki-ness of the products as perceived in the mouth. Assessors were selected for

606 B. DUNNEWIND

ET AL.

TAB

LE

1.

PRO

DU

CT

S A

ND

TH

E A

VE

RA

GE

SC

OR

E F

OR

SE

NSO

RY

ST

ICK

INE

SS A

SSE

SSE

D B

Y A

QU

AN

TIT

AT

IVE

DE

SCR

IPT

IVE

AN

ALY

SIS

PAN

EL

(W

EE

NE

N

ET

AL

.

200

3). T

HE

CH

AR

AC

TE

R C

OD

E G

IVE

N B

EH

IND

TH

E S

TIC

KIN

ESS

SC

OR

E I

ND

ICA

TE

SIG

NIF

ICA

NT

DIF

FER

EN

CE

S,

OB

TAIN

ED

BY

TH

E L

EA

ST S

IGN

IFIC

AN

T D

IFFE

RE

NC

E M

ET

HO

D W

ITH

SIG

NIF

ICA

NC

E L

EV

EL

0.0

5 (S

PSS,

SPS

S IN

C.)

. IF

TW

O P

RO

DU

CT

S D

O N

OT

HA

VE

TH

E S

AM

E C

HA

RA

CT

ER

IN

TH

IS C

OD

E T

HE

DIF

FER

EN

CE

IN

ST

ICK

INE

SS I

S SI

GN

IFIC

AN

T

Prod

uct

grou

pC

ode

Prod

uct

(Dut

ch)

Prod

uct

(Eng

lish

tran

slat

ion)

Bra

ndFa

t/oil

cont

ent

(%)

App

aren

t vi

scos

ity (

Pa.s

)‡St

icki

ness

scor

e

Cus

tard

des

sert

sFV

VV

anill

e vl

aV

anill

a cu

star

d de

sser

tFr

iesc

he V

lag

2.6

2.6–

2.7

22.2

a,b

CR

XV

anill

e vl

aV

anill

a cu

star

d de

sser

tC

ream

ex0.

14.

9–5.

023

.5

b,c

AH

VV

anill

e vl

aV

anill

a cu

star

d de

sser

tA

lber

t H

eijn

33.

8–3.

825

.1

b,c

BR

VR

omig

e va

nille

vla

Cre

amy

vani

lla c

usta

rd d

esse

rtFr

iesc

he V

lag

3.6

4.1–

4.3

29.7

b,c,

d

AL

DV

anill

e de

sser

tV

anill

a cu

star

d de

sser

t (s

oy b

ased

)A

lpro

1.8

5.2–

5.4

32.8

b,c,

d,e

May

onna

ises

RFL

Frite

slijn

May

onna

ise

Rem

ia10

18.1

–18.

241

.3

d,e,

f

DL

MM

ayon

nais

eM

ayon

nais

eD

& L

7914

.3–1

4.3

47.1

e,f

CV

MM

ayon

nais

eM

ayon

nais

eC

alvé

7013

.3–1

3.6

47.9

e,f

BC

DD

ress

ing

Dre

ssin

gB

ecel

4012

.2–1

2.3

48.4

e,f

CM

HM

ayoh

alf

May

onna

ise

C10

0035

14.1

–14.

752

.2

f

Sauc

esK

WA

Witt

e sa

us*

Whi

te s

auce

*K

norr

20.

34–0

.36

7.5

a

KH

OH

olla

ndai

se s

aus

Hol

land

aise

sau

ceK

norr

8.5

5.14

–5.3

519

.0

a,b

KR

MR

oom

saus

Cre

am s

auce

Kno

rr7.

56.

7–7.

423

.1

b,c

KG

VW

itte

saus

†W

hite

sau

ce†

Kno

rr25

8.8–

9.1

29.9

b,c,

d

GIB

Bes

ciam

ella

sau

sB

esci

amel

la s

auce

Gra

nd d

’Ita

lia1.

89.

0–9.

638

.7

c,d,

e,f

*Pr

epar

ed w

ith w

ater

ins

tead

of

milk

.†

Ext

ra b

utte

r w

as a

dded

.‡

App

aren

t vi

scos

ity a

t sh

ear

rate

of

10 s

-

1

; ea

ch o

f du

plic

ate

mea

sure

men

ts a

re g

iven

.


their sensory capabilities, trained with samples that were later used for mea-surement and paid for their participation. Subject behavior during evaluationwas as during normal eating. The products were measured in triplicate, offeredsemi-monadically, and all three types of products were evaluated in the samesession, to standardize context effects as much as possible. Stickiness wasdescribed as ‘sticky feeling that can be perceived by tongue and palate. Areally very sticky product, for instance, is the caramel of a candy bar. It isperceived between the teeth during mastication. The degree to which theproduct comes loose from different parts of the mouth determines the intensityof sticky.’ With vanilla custard desserts, stickiness was also described as ‘Foodis pulled apart by downward movement of the tongue and the resulting threatsare sensed as sticky by tongue, palate, and throat, making swallowing difficult’(de Wijk

et al.

2003). The procedures regarding assessor selection and trainingand sensory procedure have been described in detail elsewhere (Weenen

et al.

2003).

Physical Methods

Physical tests were performed after the sensory study. The definition ofstickiness given by the sensory panel (see sensory methods) suggested theimportance of the movement (up and down) of the tongue in relation to thepalate. Therefore, a compression-decompression test was chosen as the phys-ical test as this resembles the movement of tongue and palate in duringmastication of a semisolid food. All sample–condition combinations weremeasured at least four times. Compression-decompression measurementswere performed with a Texture Analyzer, type XT-2

plus

, of Stable MicroSystems, with Texture Exponent 32 software. The apparatus was equippedwith a 25-kg load cell and a 6-cm diameter round stainless steel upper plate.The lower plate was large and was varied regarding type of surface. Tests werestarted at 15 mm distance between the plates. The compression and decom-pression speeds were 10 and 1.5 mm/s, respectively. The decompression speedwas chosen on the basis of literature, stating that at lower speeds stressrelaxation effects on experimental adhesiveness increased and that at higherspeeds rupture occurred after a small deformation because of cavitation(Schweingruber

et al.

1979). At the intermediate speed of 1.5 mm/s bothphenomena should be relatively small.

Two different types of compression were used. During the first method,a maximum compression was applied of 7.0

¥

10

3

N/m

2

, which is in thesame range as the stress humans apply to semisolid food materials in themouth during a short time (Takahashi 1990). In the other method, sampleswere compressed to a final thickness of 0.5 mm. The compression was main-tained for 0.3 s before starting decompression, which is the estimated time

608 B. DUNNEWIND

ET AL.

humans compress semisolid foods in the mouth (J.F. Prinz, personal com-munication). For the first method this means that the apparatus was set tomaintain the pressure of 7.0

¥

10

3

N/m

2

for 0.3 s, using the ‘track force’mode and for the second one, that compression was kept constant at a sepa-ration between the plates of 0.5 mm. Figure 1 shows typical curves for bothmethods. The temporary increase in force after reaching

-

7.0

¥

10

3

N/m

2

(Fig. 1A) was a result of fast stress relaxation in the sample in comparisonwith the reaction time of the instrument. The test setup that discriminatedbest between the products was used to investigate the effect of variations inplate roughness, the addition of saliva and the use of porcine tongue materialon the plates.

Time, distance and force were recorded at 500 points per second, usinga filter frequency of 400 Hz. To obtain maximum information from the record-ings, several parameters were calculated from the curves representing forceversus displacement. The abbreviations used and a short description of theparameters are given in Table 2.

When stainless steel surfaces were used, the surfaces were cleaned withethanol between the measurements. Sandpaper was glued (Pritt ‘glue-it’) tothe lower plate and replaced every 4–8 tests and between products. Each timethe sandpaper was replaced, the texture analyzer was recalibrated for height.A new piece of sandpaper was slightly wetted with tap water prior to the firsttest to prevent it from taking up moisture from the sample. Between tests thesandpaper was cleaned with tissue. Saliva was applied on the sandpaper andspread out using a spatula. The amount of saliva applied ranged from 0.1 to0.2 g per measurement. The product was then placed on the saliva layer. Thetime between applying the sample and the start of the compression was about25 s.

Porcine tongue preparations were glued to the lower plate with Super-glue. Each time a porcine tongue piece was replaced, the texture analyzerwas recalibrated for height using a calibration force of 2 N. Using this cali-bration force the tongue material was just very slightly compressed. Betweentests the tongue surface was rinsed with running tap water, then washed with0.9 N NaCl solution and finally patted dry with tissue to remove excesssolution.

As the sauces were served warm during sensory assessment (Weenen

et al.

2003), they were heated in the same way in the experiments describedhere (to 65C using a water bath). To prevent the sauces from cooling duringthe test, the lower plate was preheated with warm tap water.

In all experiments the amount of compressed product was suchthat the outside of the product reached the rim of the upper plate at maxi-mum compression. Hence the amount of product varied when compressingto 7.0

¥

10

3

N/m

2

, whereas in the case of compression to 0.5 mm the


FIG. 1. TYPICAL CURVES FOR THE TWO DIFFERENT TEST METHODS. COMPRESSION TO 7.0

¥

10

3

N/M

2

AND ‘TRACK FORCE’ DURING 0.3 S (A) AND COMPRESSION TO 0.5 MM AND FORCE RELAXATION DURING 0.3 S (B)

Note that compression is plotted as a negative force and decompression as a positive force.

–40

0

40

80

12.5 13.0 13.5 14.0 14.5 15.0

Distance (mm)

Force (N)

track force at –7.0*103 N/m2

Compression

Decompression

A

0.3 s

–5

–4

–3

–2

–1

0

1

2

3

0 1 2 3 4 5 6

Time (s)

Force (N)

0.5 mm

Compression Decompression

Forc

e re

laxa

tion

B

610 B. DUNNEWIND

ET AL.

TAB

LE

2.

AB

BR

EV

IAT

ION

AN

D S

HO

RT

DE

SCR

IPT

ION

OF

TH

E P

AR

AM

ET

ER

S U

SED

IN

TH

E T

WO

DIF

FER

EN

T T

EST

ME

TH

OD

S. G

=

GR

AD

IEN

T;

D

=

DIS

PLA

CE

ME

NT

OF

UPP

ER

PL

AT

E; E

=

EN

ER

GY

IN

PUT

; F

=

FO

RC

E. I

T I

S IN

DIC

AT

ED

WH

ET

HE

R T

HE

PA

RA

ME

TE

R I

S M

EA

SUR

ED

IN

T

HE

CO

MPR

ESS

ION

PA

RT

OR

TH

E D

EC

OM

PRE

SSIO

N P

AR

T O

F T

HE

ME

ASU

RE

ME

NT.

NO

TE

TH

AT

NE

GA

TIV

E F

OR

CE

S A

RE

FR

OM

C

OM

PRE

SSIO

N A

ND

PO

SIT

IVE

FO

RC

ES

FRO

M D

EC

OM

PRE

SSIO

N

Test

met

hod

Para

met

erU

nits

Shor

t de

scri

ptio

n

1C

ompr

essi

onG

com

pN

/mm

Gra

dien

t in

0.1

mm

ran

ge p

rior

to

reac

hing

the

tar

get

forc

e1

Dtr

ack

mm

Dis

plac

emen

t du

ring

tra

ckin

g of

for

ce1

Etr

ack

Nm

mE

nerg

y in

put

duri

ng t

rack

ing

of f

orce

1L

ayer

thm

mFi

nal

laye

r th

ickn

ess

afte

r 0.

3 s

trac

king

of

forc

e1

Dec

ompr

essi

onFm

axN

Max

imum

for

ce i

n de

com

pres

sion

1D

toFm

axm

mD

ista

nce

trav

eled

fro

m f

orce

zer

o to

Fm

ax1

Eto

Fmax

Nm

mE

nerg

y in

put

from

for

ce z

ero

to F

max

1D

afte

rFm

axm

mD

ista

nce

trav

eled

fro

m F

max

to

end

of t

est

1E

afte

rFm

axN

mm

Ene

rgy

inpu

t fr

om F

max

to

the

end

of t

he t

est

1Sw

eigh

tN

Wei

ght

of s

ampl

e st

uck

to u

pper

pla

te a

fter

com

plet

e de

tach

men

t2

Com

pres

sion

F5co

mp

NFo

rce

at 5

mm

dis

tanc

e be

twee

n pl

ates

2Fm

inN

Min

imum

for

ce r

each

ed i

n co

mpr

essi

on2

G50

com

pN

/mm

Gra

dien

t at

50%

of

min

imum

for

ce2

G90

com

pN

/mm

Gra

dien

t at

90%

of

min

imum

for

ce2

Eco

mp

Nm

mE

nerg

y in

put

up t

o m

axim

um c

ompr

essi

on2

Frel

axN

Forc

e af

ter

rela

xatio

n du

ring

0.3

s2

Frel

axre

l%

Forc

e ch

ange

bec

ause

of

rela

xatio

n as

a p

erce

ntag

e of

Fm

in2

Dec

ompr

essi

onFm

axN

Max

imum

for

ce r

each

ed i

n de

com

pres

sion

2G

90to

Fmax

N/m

mG

radi

ent

at 9

0% o

f m

axim

um f

orce

pri

or t

o th

e m

axim

um2

Eto

Fmax

Nm

mE

nerg

y in

put

from

for

ce z

ero

to F

max

2G

90af

terF

max

N/m

mG

radi

ent

at 9

0% o

f m

axim

um f

orce

aft

er t

he m

axim

um2

G50

afte

rFm

axN

/mm

Gra

dien

t at

50%

of

max

imum

for

ce a

fter

the

max

imum

2E

afte

rFm

axN

mm

Ene

rgy

inpu

t fr

om F

max

to

end

of t

est

2E

deco

mp

Nm

mTo

tal

ener

gy i

nput

in

deco

mpr

essi

on2

Wid

th50

mm

Wid

th o

f th

e fo

rce-

dist

ance

cur

ve a

t 50

% o

f Fm

ax2

F5de

com

pN

Forc

e at

5 m

m d

ista

nce

betw

een

plat

es

Test

met

hod

1: c

ompr

essi

on t

o 70

.9 g

/cm

2

; se

e M

ater

ials

and

met

hods

.Te

st m

etho

d 2:

com

pres

sion

to

0.5

mm

; se

e M

ater

ials

and

met

hods

.


amount was about 1.7, 2.1 and 2.5 g when using, respectively, a smoothsurface, sandpaper and porcine tongue on the lower plate. When usingsaliva on sandpaper the total amount of saliva and product was about2.1 g.

Apparent viscosities were determined with a Paar Physica MCR 300rheometer using 40 mm flat rough plates at a gap of 1 mm at 20C, in duplicate.Flow curves were obtained at logarithmic increasing shear rates from 0.01 to1000 s-1 (15 s per measuring point, total number of measuring points was 36).All samples were allowed to relax and acclimatize for 10 min before startingthe measurements. A cover was placed over the measuring system to preventdehydration of the sample.

Data Analysis

The parameters obtained from the physical tests were used as inputvariables for modeling sensory stickiness. A forward selection linear regres-sion modeling procedure was used to generate predictive models for stickymouthfeel. The influence of experimental procedure and surface characteris-tics on the predictive value of the models was analyzed. All models were basedon linear correlations. In selected cases quadratic correlations were tested, butthis did not result in better correlation coefficients. In the present report onlyparameters with 95% significance are included in the predictive mathematicalmodels.

Principal Components Analysis (PCA) was performed with XLSTAT 4.2.Raw data were used as input and PCA was based on correlations.

RESULTS AND DISCUSSION

Compression Type

Both types of compression resulted in significant differences between theproducts (Fig. 2). The discriminating power between the custard desserts(Fig. 2) was smaller for the compression to 7.0 ¥ 103 N/m2 than when com-pressing to 0.5 mm thickness.

For each method separately the mathematical model best predictingsensory stickiness was determined (Fig. 3). In both cases this involved param-eters from the compression and decompression part of the test. In spite of aslightly lower R2, but because of its slightly better discriminative power forcustard desserts (compare Fig. 2A and B with 2C and D) and the simpler testsetup, the method in which compression was applied to 0.5 mm was usedfor the study of the effects of different surfaces.

612 B. DUNNEWIND ET AL.

Effect of Rough Surface and Saliva

In general the standard deviation of the parameter values increased whenusing sandpaper and further increased when using saliva on sandpaper. Thedifferences between custard desserts remained small. Good predictive modelscould be derived from (or obtained for) the experiments with sandpaper andfor those with sandpaper and saliva (Fig. 4). Figure 4B indicates that theprediction of stickiness of mayonnaises was better when using saliva.

The predictive models for the experiments in which samples were com-pressed to 0.5 mm (Figs. 3B and 4) all contained parameters that relate to two‘groups’ of parameters. The first group of parameters reflects the consistencyof the product. In the models this is represented by the maximum force duringdecompression (Fmax), the force at 5 mm distance between the plates incompression (F5comp) and the gradient at 90% of the force at maximumcompression (G90comp). The second ‘group’ of parameters is the force thatstill remains after a certain extent of decompression, i.e., at 5 mm distance

FIG. 2. THE VALUE OF SOME PARAMETERS OBTAINED FOR THE PRODUCTS IN THE TWO DIFFERENT TEST METHODS

The maximum force in decompression Fmax (A) and final layer thickness Layerth after 0.3 s tracking of force (B) measured after compression to 7.0 ¥ 103 N/m2 and ‘track force’ during 0.3 s. The

maximum force in decompression Fmax (C) and the force at 5 mm distance between the plates in decompression F5decomp (D) measured after compression to 0.5 mm and force relaxation during

0.3 s. Product codes are explained in Table 1. Error bars are the 95% confidence intervals of the mean.


between the plates in decompression (F5decomp). This ‘group’ may be ameasure of the extent to which necking of the product occurs during decom-pression (‘shortness’ or ‘long behavior’ of the product) and the extent to whichthe product is flowing back to the lower plate because of gravity.

FIG. 3. THE VALUE OF SENSORY STICKINESS PREDICTED BY THE BEST MATHEMATICAL MODEL OBTAINED PLOTTED AGAINST SENSORY STICKINESS.

EXPERIMENTS PERFORMED WITH SMOOTH PLATES. PARAMETERS ARE EXPLAINED IN TABLE 1

A: Compression to 7.0 ¥ 103 N/m2 and ‘track force’ during 0.3 s. Stickiness = 36*Layerth + 95*Dtrack - 162*DtoFmax. B: Compression to 0.5 mm and force

relaxation during 0.3 s. Stickiness = 1.1*Fmax + 548*F5decomp + 83*F5comp.

0

20

40

60

0 20 40 60Measured stickiness

Pred

icte

d st

icki

ness

custard dessertsmayonnaisessauces

A R2=0.92

0

20

40

60


Pre

dict

ed s

tick

ines

s

custard dessertsmayonnaisessauces

B R2=0.85

FIG. 4. THE VALUE OF SENSORY STICKINESS PREDICTED BY THE BEST MATHEMATICAL MODEL OBTAINED PLOTTED AGAINST SENSORY STICKINESS.

COMPRESSION WAS TO 0.5 MM WITH FORCE RELAXATION DURING 0.3 S. PARAMETERS ARE EXPLAINED IN TABLE 1

A: Sandpaper on lower surface. Stickiness = 382*F5decomp + 87*F5comp - 1.0*G90comp.B: Sandpaper on lower surface; measured in presence of saliva.

Stickiness = 2.5*Fmax + 382*F5decomp.

0

20

40

60


Pred

icte

d st

icki

ness

custard desserts

sauces

A R2=0.90

0

20

40

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Pred

icte

d st

icki

ness

custard desserts

sauces

B R2=0.88

mayonnaisesmayonnaises


The second ‘group’ seems to resemble the degree to which the productcomes loose from different parts of the mouth as described in Materials andMethods. In the mouth differences in necking result in differences in the timeor the distance during which a force has to be applied by the tongue (or teeth).When consuming a product with ‘long’ necking behavior, the tongue has tobe moved over a long distance away from the palate before the product fails.Vice versa, a product with ‘short’ necking behavior requires only a shortamount of time or distance for the tongue to separate from the palate, althoughthe force may be relatively high.

As the parameters in each group are strongly mutually correlated andrepresent similar physical properties, they are exchangeable in the modelswithout greatly reducing their predictive value. The strong mutual correlationis apparent from Principal Components Analysis (PCA). Figure 5 shows thecorrelations between the parameters and the first two principal componentsfor the experiments with sandpaper. PCA plots of the other experiments weresimilar. For all three experiments with compression to 0.5 mm the results fittedalmost in a two-dimensional space only. Seventy-seven to eighty-seven per-cent of the total variance was included in the first dimension and 90–93% inthe first and second dimension combined. The parameters related to the firstprincipal component all account for the consistency of the products and thoserelated to the second principal component to the extent in which neckingoccurs (shortness). The PCA indicates that both types of parameters representindependent product properties.

Consistency and shortness of the products could both be included in apredictive model for sensory stickiness. For example, good models can beobtained based on only the gradient at 90% of the force at maximum com-pression (G90comp, a measure of consistency) and the force at 5 mm distancebetween the plates in decompression (F5decomp, a measure of ‘necking,’ i.e.,shortness or ‘long’ behavior):

Surface Model R2

Smooth Stickiness = - 0.49*G90comp + 530*F5decomp R2 = 0.80Sandpaper Stickiness = - 0.70*G90comp + 386*F5decomp R2 = 0.83Sandpaper Stickiness = - 1.42*G90comp + 342*F5decomp R2 = 0.86+ saliva

Both parameters are roughly equally important regarding their contribu-tion to the predicted value, despite the large difference between the regressioncoefficients. Note that the absolute values for G90comp were 100–1000 timeslarger than for F5decomp (Fig. 6). The difference in coefficients betweendifferent models reflect the changes in absolute values of the parameters. Thesechanges may be explained, to some extent, by differences in average (oreffective) layer thickness. For sandpaper the texture analyzer was calibrated


on the top of the grains, whereas the space in between the grains also influencesthe flow of the product. The average (or effective) layer thickness is larger fora sandpaper covered surface than for a smooth surface, resulting in lowerforces. The larger amount of sample used for sandpaper may have also led tothe higher values for the force at 5 mm distance between the plates in decom-pression (F5decomp, represents degree of necking) compared with the smoothsurface, as a larger amount of sample allows necking over a longer distance.

Differences in adhesion properties should have an effect on the decom-pression part of the experiment. The absolute values of the decompression

FIG. 5. THE FIRST TWO PRINCIPAL COMPONENTS, OBTAINED WITH PRINCIPAL COMPONENT ANALYSIS (PCA) OF THE MEASURED PARAMETERS, WHEN APPLYING COMPRESSION TO 0.5 MM WITH FORCE RELAXATION DURING 0.3 S AND A LOWER

PLATE COVERED WITH SANDPAPER

Correlations circle on axes 1 and 2 (93%)

F5comp

FminG50comp

G90compEcomp

Frelax

FrelaxrelFmax

G90toFmax

EtoFmax

G90afterFmaxG50afterFmax

EafterFmaxEdecomp

Width50 F5decomp

–1

–0.5

0

0.5

1

–1 –0.5 0 0.5 1

–– axis 1 (81%) ––>

–– a

xis

2 (1

2%)

––>


parameters indeed changed with the change of surface (Fig. 6). In all experi-ments they were strongly correlated with the compression parameters, sug-gesting that their relative values are not affected by the surface applied.Correlations between the values of the same parameters in the different exper-iments were very high (Table 3; the low correlation for some parameters waslargely caused by the very low-viscosity sauce KWA; KWA spread out acrossthe lower surface considerably even before the test was started). For most ofthe semisolid products studied here, the parameters needed to explainvariations in sensory stickiness include only product properties, i.e., theyrepresent cohesive properties only.

Because of the lack of clear, product-specific effects of the type of surfaceon the decompression parameters and the predictive value of the models, itwas concluded that the products in this study did not cause differences in theadhesion component of stickiness. The cohesive properties of these productsseem to play a predominant role and explain the observed variations in sensorystickiness scores to a large extent in all experiments. The validity of thisobservation is limited to products in a certain viscosity range. Products withextremely high viscosities (solid products) will be perceived as hard, and willnot be sticky. Within the viscosity range studied here (apparent viscositiesbetween 0.3 and 18.3 Pa.s), the conclusions and models apply. We do notknow at which viscosities the models start to deviate from linearity. From thework of Kilcast and Roberts (1998) it is clear that for products with very highviscosities such as caramels, adhesive properties are very important. But theydid not report the viscosities of the products studied.

FIG. 6. COMPARISON OF THE RESULTS OBTAINED FOR TWO PARAMETERS USING DIFFERENT SURFACES FOR THE PRODUCTS WITH CODES FVV, ALD, RFL AND CMH

Product codes are explained in Table 1. The value of the porcines tongue is the average value for four porcine tongues.A: Gradient of the force-distance curve at 90% of the peak force in compression

(G90comp). B: the force at 5 mm distance between the plates in decompression (F5decomp). Error bars are the 95% confidence intervals of the mean.


Effect of the Use of Porcine Tongue Material as an Adhesive Surface

Porcine tongue material was used as a model for the human tongue.Porcine tongues strongly varied in surface structure (as is the case in humans).The values obtained for the various parameters when using porcine tonguematerial significantly depended on the tongue used. Several tongues were usedto obtain a representative average. In the present study measurements on fourproducts were carried out using four different porcine tongues.

Figure 6 compares the values of the gradient at 90% of the force atmaximum compression (G90comp) and the force at 5 mm distance betweenthe plates in decompression (F5decomp), obtained in the experiments withdifferent surfaces, including porcine tongue surfaces. The main conclusionthat can be drawn from this figure is that the use of porcine tongue surfacesstrongly influenced the values of both parameters, but hardly their relativevalues when comparing different products. The average values obtained withporcine tongue material was virtually the same as those obtained when usingthe rough surface with saliva. Only in case of Mayohalf C1000 (CMH,mayonnaise containing 35% oil) the porcine tongues showed different resultsfor F5decomp (degree of necking).

The use of porcine tongue material did not lead to an improvement inthe prediction of sensory stickiness. A complication when using porcinetongue material was that porcine tongue surface material is rough and

TABLE 3.THE PEARSONS CORRELATION COEFFICIENTS BETWEEN THE VALUES OF THE SAME

PARAMETER IN THE DIFFERENT EXPERIMENTS

Smooth vs. sandpaper Smooth vs. sandpaperwith saliva

Sandpaper vs. sandpaperwith saliva

F5comp 0.99 0.92 0.95Fmin 0.98 0.98 0.99G50comp 0.96 0.94 0.98G90comp 0.93 0.90 0.98Ecomp 0.98 0.97 0.98Frelax 0.97 0.96 0.99Frelaxrel 0.96 0.94 0.98Fmax 0.99 0.99 0.99G90toFmax 0.95 0.53 0.65EtoFmax 0.98 0.99 0.98G90afterFmax 0.77 0.91 0.86G50afterFmax 0.84 0.76 0.92EafterFmax 0.97 0.92 0.98Edecomp 0.98 0.94 0.98Width50 0.42 0.06 0.86F5decomp 0.89 0.88 0.91


compressible, giving rise to similar, or even larger problems than when usingsandpaper.

Apparent Viscosity

Because the results suggested that product characteristics independent ofproduct–surface interactions are sufficient to predict sensory stickiness at leastfor the product types tested, the relation sensory stickiness–apparent viscositywas determined. The linear correlation for this relationship was R2 = 0.76,which is lower than for the model based on consistency and ‘long behavior.’The main difference between the two is the ‘long behavior’ component of thedecompression term.

Effect of Saliva

Figure 6 addresses the question to what extent saliva affects the compres-sion and decompression movements, which we assume are characteristics forsticky mouthfeel perception. Figure 6A indicates that addition of saliva con-siderably decreases the gradient in the force distance curve upon compression,which could be a result of the lubricative effect of the addition of saliva, orthe decreased viscosity resulting from amylase breakdown of starch in theproducts. The addition of saliva increases the decompression force measuredat 5 mm distance (Fig. 6B). As the apparent viscosity is expected to decreaseupon starch breakdown by salivary amylase, we speculate that the increase inthis decompression force is a result of an increase in the ‘long behavior’ ofthe product + saliva combination. This increase in long behavior could beattributed to either the properties of saliva itself, or the salivary amylase-induced changes in starch structure, i.e., the change from a particle networkto a polymer strand network.

CONCLUSIONS

Significant differences between products could be measured with bothtypes of compression/decompression tests for all surfaces. Differencesbetween custard desserts were relatively small, because of relatively smalldifferences in their consistencies. Fairly good models were obtained, predict-ing sensory stickiness with R2 = 0.85–0.92. The predictive value did notimprove when the characteristics of the surfaces used approached those of thetongue and palate (rough surface of sandpaper, porcine tongue material).

Although different surfaces resulted in differences in the absolute valuesof the parameters, their relative values (when comparing different products)did not change. The correlations between the same parameters for the different


surfaces were very high. Moreover, the parameters appearing in the resultingpredictive models have similar meanings and all seem to represent productcharacteristics only. This leads to the conclusion that for these products thetype of surface was not an important factor in determining differences instickiness between samples. It seems that in all experiments adhesion waslarge enough to prevent detachment of the sample from the surfaces, i.e.,adhesion was not limiting. The consistency and ‘long behavior’ (the extent towhich necking occurs during decompression) of the products seem to be themost important factors explaining variations in perceived stickiness.

ACKNOWLEDGMENTS

We thank J.M. van Doorn and R.A. de Wijk for preparation of thesamples and sensory evaluation of the products, M.E.J. Terpstra for measuringthe apparent viscosities and J.F. Prinz, R.W. Visschers, R.A. de Wijk and H.Logtenberg for valuable suggestions.

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DE COCK, P. and VANHEMELRIJCK, J. 1995. Predictive rheology fortexture design of starch-based emulsified sauces. Food IngredientsEurope, Conference Proceedings, pp. 215–222.

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RELATIVE IMPORTANCE OF COHESION AND ADHESION FOR SENSORY STICKINESS OF SEMISOLID FOODS