Heng Hui, Gan

12 Nov 2014

Content

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Introduction

Why?

Aims How?

Methods

Conclusion

What?

Results &

Discussion

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Cheddar Facts

Country of origin: Somerset, England

Made from cow’s milk (whole milk)

Orange Cheddars are coloured with annatto

(natural dye)

As Cheddar aged moisture is lost

becomes dry &

crumbly

As Cheddar aged, taste and flavours develop

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Analytical Tools Used

Method Pros Cons

GC-MS i. Able to identify

compounds with library

software

i. Expensive

E-nose i. Non-destructive to

samples

ii. Real-time Analysis

iii. Efficient, informative

i. Expensive

ii. No identification of

compounds

Sensory Panel i. Interactive

ii. Can be trained

i. Expensive

ii. Time-consuming

iii. Not done at real time

pH, Texture

analysis

i. Low cost

ii. Simple to execute

i. Lack information

Flavour Generation Pathways

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Casein

Lactose

Triglycerides

Amino Acids

Lactic Acids

Fatty Acids

Citrate

Acetate Diacetyl

Proteolysis by

Chymosin, Plasmin

Lipolysis by Lipases

Metabolism

Fermentation by

LAB

Aims

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1. Evaluate GC-MS and direct injection APCI-MS for the ability to identify & characterise

aroma volatiles of Cheddar Cheese

2. Predict the age of Cheddar Cheese using proposed PLS models

Analysis of Aroma by HS-SPME GC-MS

Samples preparation: Five commercial Cheddar cheese

brands (V, W, X, Y, Z) - Mild (MI), Medium (ME), Mature (M),

Extra Mature (EM) & Vintage (V) were grated

(i) GC-MS: SPME StableFlex fibre (50/30 μm

DVB/CAR/PDMS)

ZB-Wax capillary column

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(ii) APCI-MS: Scanning at FULL SCAN mode (m/z: 40-200) for

Cheddar Cheese volatiles

Static headspace

Analysis of Aroma by APCI-MS

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Statistical Analysis

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i. Principal Component Analysis (PCA)

ii. Partial Least Square Regression (PLS-1) with full cross

validation

Cheddar Cheese Aroma Profile

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Table1. Volatile compounds in Cheddar identified in the

headspace using SPME-GC-MS

Aroma Volatiles

(MW)

Description Aroma Volatiles (MW) Description

Acetonitrile (41) Solvent-like Heptanal (114) Fatty, oily

Acetic acid (60) Vinegar Hexanoic acid (116) Cheese, fatty

Diacetyl (86) Buttery Octanal (128) Fatty, citrus

2-methyl-2-buten-1-

ol (86)

Green, fruity Octanoic acid (144) Cheese, oily

Butyric acid (88) Rancid cheese 2-decenal (154) Fatty, green

Acetoin (88) Butter, creamy δ-nonalactone (156) Butter, meaty

Methional (104) Meaty, creamy 2-undecanone (170) Citrus, fruity

2-heptanone (114) Banana, spicy n-decanoic acid (172) Fatty, citrus

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Figure 1. PCA on the data obtained by GC-MS and APCI-MS headspace

analysis of the 42 grated Cheddar cheeses.

Correlation of Maturity with Headspace

Maturity

V

EM

M

ME

MI

(28%)

(7%)

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Maturity

Changes in Aroma with Maturity

V

EM / V MI / ME

M

Figure 2. PCA biplot on the obtained by headspace analysis of the

grated Cheddar cheeses .

Acids

Ketones

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Figure 3. PLS-DA loadings for the first two factors of the classification

models based on headspace data

Key Aromas Driving Maturity in Cheddar

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Figure 4. Age of Cheddar cheeses indicated by the manufacturer

(labeled as ‘Actual’) vs predictive values from model (labeled as

‘Predicted’)

Predicted vs Actual Cheddar Age

R² = 0.85

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Pre

dic

ted

Ag

e (

mo

nth

s)

Actual Age (months)

Conclusion

• GC-MS and APCI-MS headspace analysis were efficient

techniques for determining aroma compounds relevant to

Cheddar Cheese

• Cheddar cheese maturity could be predicted using APCI-

MS and GC-MS headspace analysis combined with

chemometric data pre-treatment

• PLS models were able to predict Cheddar cheeses

maturity (R2 = 0.85)

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References

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• Fox, P.F., ed Cheese: Chemistry, Physics and Microbiology. 2004. 3rd Ed.

Elsevier Academic Press, Amsterdam.

• Law, B.A. ed. Microbiology and Biochemistry of Cheese and Fermented Milks.

1997. 2nd Ed. Blackie Academic and Professional, London.

• McSweeney, P.L.H., Sousa, M.J. (2000). Biochemical pathways for the

production of flavour compounds in cheeses during ripening: A review. Lait 80,

293-324

• Biasioli, F., Gasperi, F., Aprea, E., Endrizzi, I., Framondino, V., Marini, F.,

Mott, D., & Mark, T. D. (2006). Correlation of PTR-MS spectral fingerprints

with sensory characterisation of flavour and odour profile of 'Trentingrana'

cheese. Food Quality and Preference, 17, 63-75

• Curionia, P. M. G., & Bosset, J. O. (2002). Key odorants in various cheese

types as determined by GCO.pdf. International Dairy Journal, 12, 959-

984.Fatma A. M. Hassan, Mona A M*. Abd El- Gawad, A. K. Enab. 2003. Flavour

Compounds in Cheese. Research on Precision Instrument and Machinery, 2

(2),15-29

• Whetstine, M. E. C., Drake, M. A., Nelson, B. K., & Barbano, D. M. (2006).

Flavour Profiles of Full-Fat and Reduced-Fat Cheese and Cheese Fat Made

from Aged Cheddar with the Fat Removed Using a Novel Process. Journal of

Dairy Science, 89, 505-517.

Acknowledgements

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• Bingnan Yan (Msc student, Division of Food Sciences,

The University of Nottingham)

• Fisk Ian, (Associate Prof, Division of Food Sciences,

The University of Nottingham)

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HEADSPACE TECHNIQUES HAVE BEEN EXTENSIVELY EMPLOYED IN FOOD ANALYSIS TO MEASURE VOLATILE COMPOUNDS, WHICH PLAY A CENTRAL ROLE IN THE PERCEIVED QUALITY OF FOOD. IN THIS RESEARCH ATMOSPHERIC PRESSURE CHEMICAL IONISATION-MASS SPECTROMETRY (APCI-MS), COUPLED WITH GC-MS, WAS USED TO INVESTIGATE THE COMPLEX MIX OF VOLATILE COMPOUNDS PRESENT IN CHEDDAR CHEESE OF DIFFERENT YEAST STRAINS, PROCESSING AND RECIPES TO ENABLE CHARACTERIZATION OF THE CHEESES. PARTIAL LEAST SQUARE-LINEAR DISCRIMINANT ANALYSIS (PLS-LDA) PROVIDED A 70% SUCCESS RATE IN CORRECT CLASSIFICATION OF THE CHEESE VARIETIES BASED ON HEADSPACE VOLATILE PROFILES. THE ANALYTICAL RESULTS COUPLED WITH SENSORY EVALUATION OFFERED A MORE RAPID AND DETAILED PROFILING OF THE CHEESES, WHICH COULD ADD VALUE TO FURTHER PRODUCT DEVELOPMENT RESEARCH WORK.

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