For example, sensory panels are expensive but there is an alternative that can allow companies to lean away from this particular cost.
Sensory perception can be correlated with parameters measured using a Texture Analyser to simplify product development, investigating the mechanisms by which physical food properties act to produce specific sensations during consumption. Once appropriate equipment has been purchased, the measurement of physical parameters is often seen as an efficient alternative to costly sensory panels. Consequently, many studies in vastly different areas of the food industry have been performed with the aim of establishing methods that reflect in-mouth sensory properties using physical parameters.
Sensory studies can be expensive, time-consuming and susceptible to large variation in results. It is usually preferable to carry out instrumental studies wherever possible, as they are more repeatable and reproducible and do not become tired after a period of time.
Many companies and research bodies aim to achieve the best of both worlds by predicting the results of a sensory study using a model based on instrumental data. This is achieved by using a large body of both instrumental and sensory data, and forming relationships between the two. For example, considering a yoghurt consistency test performed on a spreadability rig, a female cone full of the sample is completely displaced using a male cone of the same dimensions. The positive force and area under the curve on penetration are measured (firmness and work of shear), as well as the negative peak force and area under the curve on withdrawal (stickiness and work of adhesion).
When a sensory panel investigates the yoghurt, they are asked to quantify less fundamental parameters such as ‘creaminess’. The work of shear measured on a Texture Analyser is related to this parameter, but it is not necessarily a directly proportional relationship between the two variables. Other factors have to be considered, and this is where the model comes into play.
The sensory and instrumental measurements are combined and analysed using principal component analysis, a statistical procedure that determines the most important relationships in a dataset. Following this process, regression analysis is used to model sensory attributes from instrumental parameters. This shows how the instrumental measurements reflect the sensory scores. The variable nature of a sensory panel means the model will be more successful with a larger number of participants.
To perform this procedure, definitions of the sensory parameters under question must be set out, and these definitions are then used to identify optimum instrumental procedures for the assessment of the sensory parameters.
Using apples as an example (Barreiro et al. 1998), the ‘mealiness’ of the fruit is of interest. A sensory panel might profile mealiness as a loss of crispness, hardness and juiciness and an increase in the floury sensation in the mouth. The instrumental compression test was found to correlate highly with these four attributes (as was a separate acoustic impulse test), so these tests were found to be useful as instrumental reference tests for the assessment of mealiness.
Although putting rheological techniques to use, the results of a 2016 study (He et al.) highlighted that there is no single rheological parameter that will ultimately correlate to a range of mouthfeel perceptions, and the same is applicable to texture analysis. A mouthfeel such as creaminess cannot be described by one instrumental result alone, so a predictive model will use several instrumental parameters in combination. Another such study (Jellema et al. 2005) relating sensory attributes of custards to rheological measurements showed that instrumental measurements are complementary to sensory analysis and can greatly facilitate the task for the practitioner at an early stage of product development. Even in cases such as this where the model shows lower correlation, this type of assessment is extremely useful.
The final product of this analytical process is a statistical model of the sensory attributes in question using a combination of parameters measured during the instrumental tests. This helps to calculate the confidence with which these instrumental tests can be used as a predictor. The sensory parameter in question is a sum-product of each instrumental result and its correlation coefficient. In practice, this simply requires the results spreadsheet to also contain the set of correlation coefficients. This is an easy task to perform using the Exponent spreadsheet package, and the initial statistical analysis can be performed automatically using a dedicated software package.
Not all instrumental results will be useful for all sensory parameters. For instance, in the yoghurt example above, the stickiness might have very little influence on a creamy mouthfeel. Stickiness will, therefore, be neglected from the creaminess model.
If successful, this technique can help to increase the throughput of screening new food products without the necessity of sensory panels at early development stages by gaining knowledge about the correlation between instrumental measurements and the multidimensional sensations felt when a consumer (or participant from a sensory panel) eats a product. The analysis is not limited to the food industry. Many other industries make use of sensory panel testing (such as cosmetics, pharmaceutical and packaging) and this analysis method is applicable to each case, presenting cost cutting potential.
There is a Texture Analysis test for virtually any physical property. Contact Stable Micro Systems today to learn more about our full range of solutions.
For more information on how to measure texture, please visit the Texture Analysis Properties section on our website.
The TA.XTplus texture analyser is part of a family of texture analysis instruments and equipment from Stable Micro Systems. An extensive portfolio of specialist attachments is available to measure and analyse the textural properties of a huge range of food products. Our technical experts can also custom design instrument fixtures according to individual specifications.
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