Instrumental Sensometry. Machines instead of panellists?

Friday, 25 March, 2011

In the highly competitive FMCG business the sensory attributes of products can determine success or failure. Indeed, consumers evaluate product’s ‘quality’ by means of their senses.  They do not use instrumental measurements such as Gas Chromatography, Mass Spectrometry or Infrared Spectroscopy.  Instead, they observe, smell and taste the new smoothie they bought. If they judge it as ‘nice and refreshing’, they will perhaps re-purchase it, but if they judge it as ‘sickly sweet and tasteless’, not only they will not purchase it again, but they will ‘get angry’ with the whole brand and they might move to competition. It is an extremely serious matter.

However, producers have laboratories well-equipped with all kinds of analytical instruments in order to ensure product ‘quality’. They can quickly have a lot of chemical and physical data about all their samples. Now the question is whether and how these instrumental data correlate with the sensory perception.

Sensory evaluation has a strategic value for producers since sensory results are used to take key business decisions,  such as accepting or rejecting a formula batch, launching or not a new product, or choosing the flavour, texture and colour among hundreds of different formulas. So far, it has not been possible to replace sensory evaluation by instrumental data because the sensory attributes such as ‘I like it’, ‘good mouth feel’, or simply ‘too bitter’ are not produced by machines. Therefore we have to stick to human beings when we need to know about this type of parameters. We get this information by means of sensory panels and we use sensory sciences, experimental design and statistic analysis.  

On the other hand, human beings, as measurement instruments, have a lot of inconveniences.  They are expensive, they need to be trained, selected and monitored to seek reliability. They need to be managed and motivated. They are not always reliable because they can be sad, bored, tired or stressed, and sometimes over-enthusiastic or pessimistic about some particular products. Some of them do not like certain flavours. They can have or get allergies and they can be sick. And, even worse, they need time to eat, to sleep, to socialise and to balance work-personal life. Humans are far more difficult to handle than machines!  If only we could get sensory data by means of a reliable, cheap, constant and tireless tool!!!  ... But, is this possible? Well, this is not just a dream: it is actually the question that the research on Instrumental Sensometry tries to answer. 

In fact,Instrumental Sensometry explores the connection between chemical and sensory data by means of special statistical methods.  It is a complex and multidisciplinary field that requires the collaboration of experts in analytical chemistry, statistics, sensory sciences and food technology.  The ultimate objective is to define a purely Instrumental ‘Sensory’ Profile (ISP) of the samples that might be used to characterise them.

Scientific literature about Instrumental Sensometry is scarce. So far, most efforts have focussed on the correlation of a single instrument with sensory evaluation, or combining few different data types. There is no deep knowledge about how to merge instrumental data in order to define ISPs of products.  

Open-Senses takes part in a project about Instrumental Sensometry led by the Group of Analytical Chemistry of Food and Wine, related to the Department of Analytical and Organic Chemistry of the Rovira i Virgili University (URV) of Tarragona (around 100 Km south of Barcelona), www.quimica.urv.es/w3qaea/ang/intro.html. The project's main objective is to establish a methodology to objectively define sensory characteristics of foods by means of multivariate statistical analysis of instrumental data and their relationship with results of descriptive panels.

The main analytical techniques used in the project are: An electronic nose system based on Mass Spectrometry (HS-MS), an electronic tongue system based on mid-Infrared spectroscopy with Fourier Transform (FT-IR), and Near Infrared (NIR) spectroscopy together with a spectrophotometer for colour measurement. These techniques are complemented with excitation-emission fluorescence spectroscopy and Nuclear Magnetic Resonance (NMR) spectroscopy. Additionally, Gas Chromatography with Olfactometric detection (GCO) is used to further characterise the smell pattern of some samples, specially the atypical ones.

We are researching how the application of chemometric techniques to the instrumental data allows the comparison and discrimination of the samples’ chemical composition. And how these patterns correlate with the sensory properties (smell, colour, flavour, texture) defined by the taste panel.  Shall Instrumental Sensometry succeed to provide suitable instrumental ‘sensory’ profiles, they could be used to:

- Define product types based on their ISP, for example regarding origin or product quality specifications.

- Predict failure on sensory quality control (before actually tasting it), by checking if a sample belongs or not to a particular ISP.

- Further document samples rejected by a panel, by means of an objective ISP for rejection, in addition to the sensory panel report.

- Examine the ‘sensory evolution’ of a product,  by checking its ISP for instance throughout a couple of years, without need to rely on a sensory panel.

- Monitor product variation over batches, suppliers, formulations, etc by comparing their ISPs.  

- Screen products prior to sensory testing  them, thus saving time and efforts on sensory evaluation because only some ISP will be tested by the panel.

- Benchmark over time.  Develop and keep reliable ISPs over time that can be used, for instance, as a benchmarking system for quality control. This could complement the current system of storing reference samples at low temperature and gradually rotating them.

- Cost reduction and reliability improvement  on the routine tasks of sensory evaluation: replacing them by an automatic check of the ISP (colour, texture, flavour) of samples.

- Develop a new system to record ‘sensory data’  by means of a distinctive ISP for each sample type. For example a unique pattern to register a fragrance ‘sensation’.

Therefore, Instrumental Sensometry could greatly contribute to take further advantage of sensory research: keeping, improving and monitoring product quality. Regarding product innovation, the technique could be useful to define objective ‘sensory specifications’ to check and ensure ‘sensory’ stability and consistency over time. Therefore, if successful, Instrumental Sensometry could be a complement rather than a replacement of sensory evaluation.

Yet poor analysts in charge of Instrumental Sensometry will have to suffer all the disadvantages of working with machines. Because obtaining complex analytical data from instruments can also become a nightmare.  Indeed, these tools need a lot of time to be set, programmed and fine-tuned. Calibration of an ISP for a simple mayonnaise can take more than a year of research, and the new mayonnaise flavoured with ginger will require another eight months of calibrating. Machines are not ‘reasonable’, they never ‘do us a favour’, they cannot be motivated, flattered or threatened, they do not ‘make an effort’, they do not resolve problems and they are not flexible at all. A sophisticated instrumental system tends to have complex breakdown that can take a month to solve. And it can break just before the analyst’s holidays or, worse, when the new R&D Vice-president drops by to have a look at the brand new ‘sensory robot’...  Definitely, Instrumental Sensometry can be risky!

Thus, even if Instrumental Sensometry succeeds in providing useful new ‘sensory’ tools, it will always be a complement to sensory evaluation with panels and experts. We will keep working with people, with all their inconveniences and... Advantages!!! Because human beings do bring major added value to sensory evaluation, such as insights related to language and culture. They can easily switch from apple pie to strawberry yoghurt. They can alert about off-flavours so that flavourists can take action. Panels can quickly evaluate ‘intensity’ with complex matrixes. Panellists can provide useful suggestions for product innovation regarding texture, acidity or ‘body’. In short, human beings are the closest system to our beloved human consumers.

At Open-Senses we are passionate about sensory innovation.If you share this passion, you can contact us at www.open-senses.com.

 

Related scientific literature

-  R. Consonni, L.R. Cagliani. Adv. Food Nutr. Res.59 (2010)87-165

-  L. Jaitz, K. Siegl, R. Eder, G. Rak, L. Abranko, G. Koellensperger, S. Hann. Food Chem. 122(2010)366-372

-  Dion M.A.M. Luykx and S. M. VanRuth.Food Chem107 (2008) 897-911clear

-  S. Roussel, V. Bellon-Maurel, J.M. Roger, P. Grenier. Chemom. Intell. Lab. Syst. 65 (2003) 209–219

-  C. Apetrei, J.M. Apetrei, S. Villanueva, J.A. de Saja, F. Gutiérrez-Rosales, M.L. Domínguez-Méndez. Anal. Chim. Acta663 (2010) 91-97

-  M. Casale, C. Casolino, P. Oliveri, M. Forina. Food Chem,118 (1) (2010) 163-170

-  P Mielle. Trends Food Sci & Technol, 7 (1996) 432-438

-  C Pérès. F Begnaud, L Eveleigh, JL Berdagué. Trends Anal. Chem. 22 (2005) 858-866

-  MP Martí, R Boqué, O Busto, J Guasch. Trends Anal. Chem. 24 (2005) 57-66

-  JL Pérez, M del Nogal, C García, ME Fernández, B Moreno, A Guerrero. Trends Anal. Chem.  25 (2006) 257-266

-  Y Vlasov, A Legin, A Rudnitskaya. Anal. Bional. Chem. 373 (2002) 136-146

-  AK Deisingh, DC Stone, M Thompson. Internat. J. Food Sci. Technol. 39 (2004) 587-604

-  A Z. Berna, S. Trowell, D. Clifford, W. Cynkar, D. Cozzolino. Anal. Chim. Acta 648, 2 (2009) 146-152

-  S Roussel, V Bellon-Maurel, JM Roger, P Grenier Chemometrics Intell. Lab. Syst. 65 (2003) 209–219

-  M.Casale, C. Casolino, P  Oliveri, M. Forina Food Chemistry, 118 (2010) 163–170

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