Instrumental measurements of beer taste attributes using an electronic tongue

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Instrumental measurements of beer taste
attributes using an electronic tongue
Sixth Winter Symposium on Chemometrics Kazan 18
22 February 2008
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• Alisa Rudnitskaya Evgeny Polshin Dmitry
  Kirsanov Katrien Beullens Jeroen Lammertyn
  Bart Nicolai Freddy Delvaux Andrey Legin

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Purpose of the study

• Brewing and aging of beer are complex processes
• Several parameters have to be controlled to
  ensure reproducible quality of the finished
  product
• One of the most important taste and flavour are
  evaluated by the sensory panel
• Similarly to all sensory analyses of any
  foodstuffs assessment of beer taste and flavour
  is slow, expensive and suffering from
  irreproducibility of the assessors.
• The aim of the present study is evaluation of the
  electronic tongue sensor system as a screening
  tool for the beer taste and flavour attributes

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ExperimentalSamples

• Samples
• 50 Belgian and Dutch beers of different types
• Sensory evaluation
• trained sensory panel has estimated 72 attributes
  in total
• beer aroma
• taste
• mouthfeel
• appearance
• global quality

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ExperimentalET measurements

• Sensor array
• 29 potentiometric chemical sensors of different
  types
• multichannel custom-made voltmeter
• Sample preparation
• filtering
• dilution
• thermostatting at 270C
• 7-9 replicated measurements

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Data processing

• Data exploration
• Principal Component Analysis (PCA)
• Canonical Correlation Analysis (CCA)
• Prediction of sensory attributes
• Partial Least Square Regression (PLS)

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Data setFlavour and taste attributes

• 72 attributes were evaluated
• 27 aroma attributes intensity,
  sour, fruity, alcoholic,
• 29 taste and flavour attributes sour,
  sweet, bitter, hoppy,
• 9 aftertaste attributes intensity,
  duration, body,
• 4 mouth feel attributes astringency, CO2,
  warming,
• 2 foam attributes colour,
  texture
• global quality
• Sets of attributes are overlapping
• Aroma and taste attributes sets include the same
  parameters
• Taste and aftertaste attributes include the same
  parameters

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Data setFlavour and taste parameters

• Correlation between beer taste and aroma
  attributes
• The same attributes related to the taste and
  aroma or aftertaste were highly correlated
  (correlation coef. 0.8-0.9) with exception of
  attributes fusty and metallic
• Considering high correlation of the same aroma
  and taste attributes and the fact that ET is
  measuring liquid only attributes pertaining to
  the beer taste were chosen for the further data
  processing, i.e. 45 in total
• Correlation was also observed between following
  groups of attributes (correlation coef. 0.9-0.7)
• aroma, taste and after taste intensity and
  mouthfeel, duration and body
• mouthfeel, CO2, warming and aftertaste intensity,
  duration and body
• taste, aftertaste and aroma sour, artificial and
  fruity
• taste and aroma alcoholic and mouthfeel and
  warming
• taste and aroma ester and solvent
• taste and aroma sulphury, DMS and rubber

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Data setSensory panel

• Problem of the sensory panel data set
• Sensory panel consisted of 18 people
• Not all of them were present at each tasting
  session
• Each sample was tasted by a sub-panel of 7-11
  assessors
• None of them tasted all samples
• Data sets used
• 7 tasters that tasted more than half of the
  samples
• Average values of each attribute were calculated
  using scores of those of the 7 tasters that
  assessed this particular sample, which resulted
  in 50x45 data matrix.
• Sensory attributes data set was centered and
  standardized

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Beer samples discriminationSensory panel data
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Beer samples discriminationSensory panel data
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Beer samples discriminationET data comparison
with sensory panel
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Beer samples discriminationET data comparison
with sensory panel
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Beer samples discriminationET data
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Beer samples discriminationET data
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Comparison of ET and sensory panel data sets
using CCA

• Four significant canonical roots were extracted
• Correlations between first four pairs of
  canonical variables were 0,96, 0,91, 0,79 and
  0,77

Similarity maps
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Prediction of the attributes using ET
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Conclusions

• Electronic Tongue multisensor system seems to be
  very promising tool for instrumental beer taste
  screening
• Determination of taste attributes with ET in some
  cases allows to achieve lower error values than
  sensory panel
• Sensory panel data set handling and methods of ET
  data processing are still to be improved

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Acknowledgments

• RFBR project 05-03-34824-??_?
• Centre for Malting and Brewing Sciences, Leuven,
  Belgium
• InBev Brewery Company, Belgium
• Sensor Systems LLC, St Petersburg, Russia

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THANK YOU FOR YOUR ATTENTION !
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Data setFlavour and taste attributes

• 72 attributes pertaining to the beer aroma and
  taste were evaluated
• 27 aroma attributes (intensity, sour, fruity,
  alcoholic, hoppy, floral, spicy, caramel,
  liquorice, worty, artificial, ester, solvent,
  burned, yeast, autolysis, sulphury, H2S, DMS,
  diacetyle, fusty, oxidation, metallic,
  chlorophenol, vinylguaiacol, rubber,
  acetaldehyde)
• 29 taste and flavour attributes (intensity, sour,
  sweet, bitter, fruity, alcoholic, hoppy, floral,
  spicy, caramel, liquorice, worty, artificial,
  ester, solvent, burned, yeast, autolysis,
  sulphury, H2S, DMS, diacetyle, fusty, oxidation,
  metallic, chlorophenol, vinylguaiacol, rubber,
  acetaldehyde)
• 9 aftertaste attributes (intensity, duration,
  bitter, sour, sweet, fruity, liquorice,
  artificial, body)
• 4 mouth feel attributes (mouthfeel, astringency,
  CO2, warming)
• 2 foam attributes (colour, texture)
• global quality
• Sets of attributes are overlapping
• Aroma and taste attributes sets include the same
  parameters with exception of sweet and bitter
  that are only taste characteristics
• Taste and aftertaste attributes include the same
  parameters (e.g. intensity, bitter, sour, sweet,
  fruity, liquorice, artificial)