6/11-06-2011

Statistical Methodologies in Confectionery

W. Peñaloza and A. Bousbaine

Nestlé Research Center, P.O. Box 44, 1000 Lausanne 26, Switzerland

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Project objectives

• Evaluate the microbiological safety and stability of confectionery products

• Provide guidance for microbiological challenge testing for the development of similar products

Business trend for low fat and reduced calorie to bring guilt free indulgence to consumers

Background & Objectives

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Aw 0.8Aw 0.3

What do we know

• Praline concept & technology developed at NRC (P. Rousset) with industrial potential

• Industrial feasibility (Darryl Barwick)

Background & Objectives

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Production

Thorough understanding of product stability against fungal growth (mycotoxins/spoilage)

Challenge testing

(at conditions as close as possible to industrial

production)

End of shelf life

Shelf life of product & conditions

Background & Objectives

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What needs to be defined for the challenge testing

• Recipe (“canada”) – polishing & approval

• Product format/presentation praline, moulded or enrobed

• Storage e.g. refrigerated, ambient, warm?

( likely industrial production)

Major impact for planning:

Water migration kinetics

Challenge testing (Experimental design)

Background & Objectives

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Experimental Design

Generic Design

Other Parameters

• Format: Bâton and Perforated

• Cocktail: None, Safety and Spoilage

• Storage Temperature: Refrigerated (10 °C), Ambient (22°C) and Warm (32 °C)

Run No Sorbate (%) aW1 0 0.762 0 0.843 0.2 0.764 0.2 0.845 0.1 0.8

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Cocktails

• None: no inoculation, but natural contamination (air, raw materials, clean equipment surfaces, …)

• Safety: micotoxigenic moulds (aflatoxines, ochratoxins, …)

• Spoilage: moulds found in production line, storage tests,contaminated raw materials, inadequate hygenein the production line, …

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Measurements

Response

Visual Mould Growth

Codification

• 0: No growth seen even under the stereomicroscope

• 1: Incipient Mycelium growth normally detected after careful inspection and frequently under the stereomicroscope, detected by specialist

• 2: Mycelium growth clearly noticeable as white hairy areas by any consumer (not specialist)

• 3: Abundant mycelium growth and sporulation with or without change of colour

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Format: Bâton, Cocktail: NoneResults After 24 Weeks of Storage

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Format: Bâton, Cocktail: SafetyResults After 24 Weeks of Storage

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Format: Bâton, Cocktail: SpoilageResults After 24 Weeks of Storage

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Format: Perforated, Cocktail: NoneResults After 24 Weeks of Storage

13

Format: Perforated, Cocktail: Safety Results After 24 Weeks of Storage

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Format: Perforated, Cocktail: SpoilageResults After 24 Weeks of Storage

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Format: Bâton & Perforated, Cocktail: Spoilage

Results After 24 Weeks of Storage

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I Index

Response

Let be the categories defined to characterize the degreeof visual moulds, where

Let k be the number of replicates for each combinationFormula-Format-Cocktail-Storage Temperature.

For each combination Formula-Format-Cocktail-Storage, let be the number of samples with a degree of visual moulds

It follows that

niwi ...,,1

nwww ...0 21

ix

iw

kxn

ii

1

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I Index

An index I can be defined as follows:

Properties of the I index

Situation 1 then

Situation 2 then

n

n

iii

wk

xwI

1

0..., 321 nxxxkx 011 nwk

xwI

kxandxxx nn 0... 121 1n

n

n

nn

wk

wk

wk

xwI

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I Index

Statement

Proof

1. By definition, it is clear that

2. We have to show that

We have

Since

It follows that because

10 I

0I

1I

n

n

iii

n

n

iii

kwxwkw

xwI

1

1 11

nni

n

iinnni

n

iin

n

iii wxkxwkwxwxwkwxw )(

1

1

1

11

1

121 ...

n

iinn xkxkxxx

0)(1

11

in

n

iini

n

ii xkwwkwxw 0)( ni kww

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Weights

Visible mould growth (spoilage)

1

3

noticed by expert

Storage time

stationary phase

lag phase

exponential phase

2noticed by consumer

Completely mouldy

high aw

low aw

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Weights

Time

Growth

0

10

Germination

Specialist

Consumer

Abundant

7.5

2.5

Initial Inoculation

Growing

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Modelling

Response

I index

Modelling

A model relating the I index to the 2 parameters Sorbate and aW isestablished for each combination Format-Cocktail-Storage Temperature.

The contour plots of the established models are given in the next slides.

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Results After 24 Weeks of Storage

0 0.004 0.008 0.012 0.016 0.02 0.024 0.028 0.032 0.036 above

Index: Contour Plots

Format: Bâton, Cocktail: None, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.012 0.024 0.036 0.048 0.06 0.072 0.084 0.096 0.108 above

Index: Contour Plots

Format: Bâton, Cocktail: Safety, Storage Temperature: 22°C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.09 0.18 0.27 0.36 0.45 0.54 0.63 0.72 0.81 0.9 above

Index: Contour Plots

Foramt: Bâton, Cocktail: Spoilage, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.034 0.068 0.102 0.136 0.17 0.204 0.238 0.272 0.306 above

Index: Contour Plots

Format: Perforated, Cocktail: None, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.04 0.08 0.12 0.16 0.2 0.24 0.28 0.32 0.36 above

Index: Contour Plots

Format: Perforated, Cocktail: Safety, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.09 0.18 0.27 0.36 0.45 0.54 0.63 0.72 0.81 0.9 above

Index: Contour Plots

Format: Perforated, Cocktail: Spoilage, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 above

Index: Contour Plots

Format: Bâton & Perforated, Cocktail: None, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.03 0.06 0.09 0.12 0.15 0.18 0.21 0.24 0.27 above

Index: Contour Plots

Format: Bâton & Perforated, Cocktail: Safety, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Results After 24 Weeks of Storage

0 0.09 0.18 0.27 0.36 0.45 0.54 0.63 0.72 0.81 0.9 above

Index: Contout Plots

Format: Bâton & Perforated, Cocktail: Spoilage, Storage Temperature: 22 °C

Sorbate (%)

aW

0.76

0.78

0.80

0.82

0.84

0.00 0.04 0.08 0.12 0.16 0.20

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Conclusions

After 24 weeks of storage, visual mould growth appears mainly when thecocktail is spoilage and when the storage temperature is ambient.Visual mould growth is seen on the combinations No 2 and 4.Visual mould growth is more pronounced when the samples are perforated.Combination No 2 does not contain Sorbate and has an aW of 0.84.Combination No 4 contains 0.2% Sorbate and has an aW of 0.84.

The results show that:

• aW plays an essential role• Sorbate plays also a role, but less pronounced• Storage temperature plays also a role. Ambient temperature increases the degree of visual mould growth.• Format plays as well a role. Perforation increases the degree of visual mould growth.

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The established I index characterizes very well the degree of visual moulds,and allows a very easy and understandable way of communicating theresults.

From the modelling using the I index, it appears that:

1. Cocktails: None and Safety

• aW is the key parameter, and this parameter should be as low as possible.• Sorbate plays a slight role. It helps a little bit.

2. Cocktail: Spoilage

• aW is the key parameter, and it should be kept at its lowest value.• Sorbate plays a negligible role. It brings more or less nothing!

The effect of Format is also highlighted in the modelling results.

Conclusions

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The authors wish to thank all the people involved in the whole project, inparticular:

- V. Meunier- P. Rousset- A. Rytz

Acknowlegements

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