42. Computer-aided product development in the food industry

Abstracts of Oral Presentations instead

of MRA

followed

the PLS loadings. procedure,

by the subsequent

Accordingly,

to map

the strategy

the preference

space, can be briefly

collapse

outlined

data

nent model)

on the sample

as follows: a) the coordi-

ings

and cross-product

transformed

are

compo-

of sample space are coded and expanded

squared

into

terms;

b) PLS

polynomial

to

load-

coefficients

either

method

information

of CARS0

nate (sample scores of first and second principal include

of

for

nificance

about

similarities

information

a new software

aided

development,

maximum

the

software

the

experimental

are

necessary

experimental

value

domain;

preference

value

determined. to analyze

than

within

within

which

a certain

value,

to demonstrate

the results

new experiments.

of 20 families.

to

tem, specially

extra vir-

food industry,

In order

by a consumer

The flavor profile of the by a laboratory

trained

panel. The results obtained

by using the traditional

and

CARS0

very

and

procedures

demonstrates

show

CARS0

good

can facilitate

agreement

the understanding

of the results.

42.COMPUTEbAIDED DEVELOPMENTINTHE

Camo AS, Olav Tryuggvasonsgt Trondheim,

-

research

forsk (The

Norwegian

tematize

knowledge

methodology development

about

results through

techniques

concept

use of experimental

was applied

matter

of processed

variables

were maturity

design for ana-

has been an to processed

and processing

effects on its sensory quality.

processing

for efficient

PCA and ANOVA

tool. The approach

nificant

development

data. Sensory evaluation

cheese to identify ingredients the greatest

to sys-

values with

The most sigof cheese, dry

cheese and pH. Samples

that both

the

forward

proideas

analysts in the part of

for Food Research,

influence

the sensation

the acceptance

is correlated

to the characterized

a model. The preparation

Examples

conditions

parameters

design. The balanced

different

The

gel used as

of whey protein

gels were

experimental

design made it possible to

in pH, salt concentration

microstructure

microscopic

will be given

known to have an

in a factorial

factorial

identify effects of changes rate.

of tex-

and quantified

whey protein

on the microstructure

heating

with instruments

has been tested, where the sensory

of the product.

used as design

of a food into struc-

on the perception

from results with a particulate impact

of texture

that can be measured

vital information

microstructure

P.O.

Sweden

and texture

tural properties

work has given very promising

the extensive

lysis of multivariate

Institute)

product

and form a strategy work. Their

and the statistics important

Food Research

and

The

and challenging

Translating

can provide

has been done by Mat-

statistics

the user through bring

is

will be a

to (inexperienced)

29 Goteborg,

ture. A new concept

applied

knowledge

of a help sys-

The Swedish Institute

quality Interesting

for computer-

Maud Langton, Annika AstrOm and Anne-Marie Hermansson,

Flavor

Norway

A.S.,

43.lNFLUENCEOF MICROSTRUCTUREON THESENSORYQUALITY

product.

24, N-701 1

Nor-

Camo

Implementation

is an important

Box 5401, S-402

Suzanne Schbnkopf, Tormod Naes, Pernille Baardseth, Marit Risberg-Ellekjaer and Arne Midjo,

sensoric

(The

result

on multivariate

sig-

the project.

SIK

PRODUCT FOOD INDUSTRY

this

use. The

to continuously

tailored

and

the right conclusions.

is designed

produced

same oil samples were obtained

steps toward

about

way.

program

that guides

gram

we investigated

data

based

design,

that the latter permit

in an easier

gin olive oil preference

package

detailed important

Tine

company

where

for industrial

these

aim of this study is to compare

these methodologies,

group consisting

data)

d) the ranges,

is higher

The

two methodologies compare

(preference

of samples

are developing

each of the terms; c) the surface is studied to find out the

gives

Matforsk,

and the software

product

more

PCA/PLS

due to changes.

Dairies)

gives

effects and statistical

while

implemented

response

ANOVA

significant

of results,

differences wegian

alone.

about

319

was characterized

techniques

and

quantified

and by by

image analysis and by using a group of experienced microscopists evaluating micrographs from scanning electron done

microscopy

(SEM).

with a trained

panel

The sensory evaluation which

developed

was

a partial

have improved properties compared to today’s product and low intensity of undesirable properties were identi-

sensory profile using Quantitative Descriptive Analysis. The sensory characterization of the whey protein gels

fied. The same strategy

was focused

of dairy ingredients

was also used to study the effects

on sausage sensory properties,

the aim to assess the potential

of dairy ingredients.

addition to sensory analysis, textural was performed. They all indicated

with In

and color analysis the same results;

ingredient concentration was more important than the type of ingredient and starch. Both applications show that the strategy to combine PCA and ANOVA complementary information that is not available

gives from

though

on the

the perception

also included

properties

related

to consistency,

of an acid and salty

in the assessment

of the products.

taste was The pH

had a pronounced effect on all measured parameters, both as a main effect and as an interaction effect in combination with heating rate or salt addition. All sensory descriptors of the texture showed main effects of heating rate and interaction effects between pH and salt addition. A logarithmic correlation was found between