Modelling and analysis of dynamic sensory data

• Time intensity (TI) data from earlier reported studies on cream cheese and salad dressing were used to develop models based on both polynomials and ordinary differential equations (ODE) that can be used to describe and interpret TI-data. Polynomials were thus fitted to experimental data. By taking the first and second derivatives of the polynomials one gets new polynomials that express how the perceived intensity changes with time. By integrating the original polynomial one gets a new polynomial that expresses how the classical TI-parameter "Area Under the Curve" is accumulated with time. Graphical display of all these types of polynomials gives an immediate and easily interpretable impression of the influence of different experimental factors on the time dependent perception. In the ODE models experimental factors, both formula and process conditions, were taken into account. Thus it was possible to develop equations that can be used for prediction of TI-curves for intermediate experimental settings.

Ämnesord

MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Nutrition and Dietetics (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskaper -- Näringslära (hsv//swe)

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskaper (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Health Sciences (hsv//eng)

AGRICULTURAL SCIENCES  -- Agricultural Science, Forestry and Fisheries -- Food Science (hsv//eng)

LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Livsmedelsvetenskap (hsv//swe)

LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske (hsv//swe)

AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries (hsv//eng)

Nyckelord

salad dressing

cream cheese

time intensity

sensory

ordinary differential equations

fattiness

polynomials

least square method

Food Engineering

Livsmedelsteknik

Publikations- och innehållstyp

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