340 likes | 434 Views
Statistical Methodologies in Confectionery W. Peñaloza and A. Bousbaine Nestlé Research Center, P.O. Box 44, 1000 Lausanne 26, Switzerland. Background & Objectives. Business trend for low fat and reduced calorie to bring guilt free indulgence to consumers. Project objectives.
E N D
Statistical Methodologies in Confectionery W. Peñaloza and A. Bousbaine Nestlé Research Center, P.O. Box 44, 1000 Lausanne 26, Switzerland
Background & Objectives Business trend for low fat and reduced calorie to bring guilt free indulgence to consumers Project objectives • Evaluate the microbiological safety and stability of confectionery products • Provide guidance for microbiological challenge testing for the development of similar products
Aw 0.8 Aw 0.3 Background & Objectives What do we know • Praline concept & technology developed at NRC (P. Rousset) with industrial potential • Industrial feasibility (Darryl Barwick)
Background & Objectives Production End of shelf life • Thorough understanding of product stability against fungal growth (mycotoxins/spoilage) • Challenge testing • (at conditions as close as possible to industrial production) X Shelf life of product & conditions
Background & Objectives What needs to be defined for the challenge testing ( likely industrial production) • Recipe (“canada”) – polishing & approval • Product format/presentation praline, moulded or enrobed • Storage e.g. refrigerated, ambient, warm? • Major impact for planning: • Water migration kinetics • Challenge testing (Experimental design)
Generic Design Run No Sorbate (%) aW 1 0 0.76 2 0 0.84 3 0.2 0.76 4 0.2 0.84 5 0.1 0.8 Experimental Design • Other Parameters • Format: Bâton and Perforated • Cocktail: None, Safety and Spoilage • Storage Temperature: Refrigerated (10 °C), Ambient (22°C) • and Warm (32 °C)
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 hygene • in the production line, …
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
Format: Bâton, Cocktail: NoneResults After 24 Weeks of Storage
Format: Bâton, Cocktail: SafetyResults After 24 Weeks of Storage
Format: Bâton, Cocktail: SpoilageResults After 24 Weeks of Storage
Format: Perforated, Cocktail: NoneResults After 24 Weeks of Storage
Format: Perforated, Cocktail: Safety Results After 24 Weeks of Storage
Format: Perforated, Cocktail: SpoilageResults After 24 Weeks of Storage
Format: Bâton & Perforated, Cocktail: SpoilageResults After 24 Weeks of Storage
I Index Response Let be the categories defined to characterize the degree of visual moulds, where Let k be the number of replicates for each combination Formula-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
I Index An index I can be defined as follows: Properties of the I index Situation 1 then Situation 2 then
I Index • Statement • Proof • By definition, it is clear that • We have to show that • We have • Since • It follows that because
Weights Visible mould growth (spoilage) stationary phase Completely mouldy 3 high aw noticed by consumer 2 exponential phase noticed by expert 1 low aw lag phase Storage time
Weights Growth 10 Abundant 7.5 Consumer 2.5 Specialist Initial Inoculation 0 Time Germination Growing
Modelling • Response • I index • Modelling • A model relating the I index to the 2 parameters Sorbate and aW is • established for each combination Format-Cocktail-Storage Temperature. • The contour plots of the established models are given in the next slides.
Conclusions • After 24 weeks of storage, visual mould growth appears mainly when the • cocktail 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.
Conclusions • The established I index characterizes very well the degree of visual moulds, • and allows a very easy and understandable way of communicating the • results. • From the modelling using the I index, it appears that: • 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.
Acknowlegements • The authors wish to thank all the people involved in the whole project, in • particular: • V. Meunier • P. Rousset • A. Rytz