CHAPTER 1
Introduction to Descriptive Analysis

Sarah E. Kemp, May Ng, Tracey Hollowood and Joanne Hort

1.1 Introduction

Descriptive analysis is a method used to objectively describe the nature and magnitude of sensory characteristics. It was a pioneering development for its day, and represented a major step forward that gave sensory evaluation a scientific footing through the ability to produce objective, statistically reliable and statistically analysable data. Today, it remains a cornerstone method in sensory analysis.

A wide range of descriptive analysis techniques have been developed since its inception. Traditional descriptive techniques, such as profiling-based methods and quantitative descriptive analysis, involve a panel of trained assessors objectively measuring the quality and strength of the sensory attributes of samples. More recently, faster descriptive techniques, such as sorting, projective mapping and polarized sensory positioning, involve untrained consumers grouping samples based on holistic similarities and differences in sensory characteristics. Over the years, descriptive analysis has proved itself to be flexible and customizable, which has contributed to its usefulness and hence its longevity.

As descriptive analysis enables objective, comprehensive and informative sensory data to be obtained, it acts as a versatile source of product information in industry, government and research settings. Descriptive analysis was first applied to foods and beverages, but is now applied to a broad range of products including home, personal care, cars, environmental odours, plants, etc. It is used throughout the product lifecycle, including market mapping, product development, value optimization, and quality control and assurance. Descriptive analysis is particularly useful in product design, when sensory data are linked to consumer hedonic data and physico-chemical data produced using instrumental measures. This allows product developers and marketing professionals to understand and identify sensory drivers of product liking in order to design products with optimal liking. Sensory descriptive information can also be linked to other types of consumer data to enhance brand elements, emotional benefits, functional benefits and marketing communication.

There are many general texts and reviews on descriptive analysis and the reader is directed to the following: ASTM (1992), Gacula (1997), Murray et al. (2001), Meilgaard et al. (2006), Kemp et al. (2009), Lawless and Heymann (2010a,b), Varela and Ares (2012, 2014), Stone et al. (2012) and Delarue et al. (2014).

1.2 Development of Descriptive Analysis

1.2.1 Evolution

Descriptive analysis grew from the need to assess products in a reliable fashion. Originally, product sensory quality relied on assessment by experts, such as brewers, wine tasters, tea tasters and cheese makers, who judged quality on key product attributes and made recommendations on how ingredients and process variables affected production and the finished product, which might often have a very fixed, invariable specification over a long period of time. The expert, sometimes called the 'golden tongue', was often a single person, who had product experience or had been trained by other experts. Businesses relied heavily on a few key individuals, which could be problematic if they left, particularly if they were the prime expert on the unique sensory characteristics of a company's product. Attributes were often important to the manufacturing process, rather than the consumer, and might comprise defects or complex terms that were difficult to understand. Attributes were often assessed using grading on quality scales that might be idiosyncratic to a company, an industry or a country. Indeed, experts could also be idiosyncratic and subjective in their judgements. Data often comprised a single value, which could not be interrogated statistically, making it difficult to compare scores in a meaningful way. In many cases, only the expert could interpret differences in scores between products.

As the market became more complex and fast-paced, with increasing numbers of ingredients, processing technologies, products, competition and consumer choice, the need arose for a more robust system for assessing product quality. The introduction of descriptive analysis moved away from a single expert to a trained panel of assessors, removing the reliance on a single person and making the data more reliable. Controls were introduced, such as experimentally verified scales, physical sensory references rather than descriptive words, consistent assessment methodology and thorough training. As sensory evaluation became recognized as a scientific discipline, good experimental design as used in other scientific areas was introduced, such as elimination of variability and bias, and use of experimental design and replication. This enabled the production of robust, objective data that could be analysed statistically. In a similar fashion, food production had moved from a craft to a science, and data produced from descriptive analysis now became available for food scientists and technologists to use in conjunction with physico-chemical instrumental measures to understand food quality in a science-based, rigorous manner.

The market continued to grow, and became increasingly international and global. Companies began to manufacture greater volumes, often at many national and international sites, and the rigorous nature of descriptive analysis now made it easier to compare data across studies and across panels, for example, to check that product quality was consistent across manufacturing sites. At this point, descriptive analysis was a key tool for quality assurance and control, and the sensory department was essentially providing a service based on routine testing. Traditional methodologies continued to be honed. In the US, several dominant descriptive analysis methods emerged driven by sensory agencies. In Europe, where the market for sensory agencies was more fragmented, the trend was towards customizing descriptive methodology to suit the needs of individual companies.

With globalization, the marketplace has evolved to be highly competitive. Consumers have become increasingly sophisticated and demanding, with a wide range of choices. To gain a competitive advantage, it is important to deliver consumers' needs, wants and desires. Product push has given way to consumer pull, and it is now consumers who are the ultimate judges of product nature and quality (Kemp 2013). The applications of descriptive analysis have evolved to become a key tool for use in product design and development, in order to interpret and deliver consumers' sensory requirements. New product development can be guided to create products based on consumer likes and dislikes. Descriptive data are now routinely combined with consumer data to determine sensory attributes that drive consumer liking, aided by the advances in technology outlined below that have enabled sophisticated, rapid statistical modelling and analysis. Physico-chemical and process data can also be combined in these models to enable manipulation of product characteristics to optimize consumer liking. Sensory attributes of key importance to the consumer can be comprehensively understood, and are now routinely used in quality control and assessment.

As the marketplace has become complex and sophisticated, so has the means of marketing products. There are many ways in which product sensory characteristics play a role in marketing, as described in section 1.4.3, including sensory pleasantness leading to repeat purchase, as an essential brand characteristic, as a functional benefit or indicator of a functional benefit, and as part of the brand/product experience, which is increasingly highlighting emotional aspects. Statistical modelling using descriptive data has been able to illuminate and design sensory characteristics linked to brand elements, functional benefits and emotional benefits. Hence, descriptive analysis is now an important tool for marketing and can be used across the product life cycle. As a result, the sensory department itself has now evolved to become a full partner to marketing and technical functions, rather than a service provider in the quality department.

As factors related to the commercial environment have influenced the evolution of descriptive analysis, and indeed sensory evaluation in general, so have advances in technology. Methods of data collection have changed considerably. In the early days, all data had to be collected using pen and paper, and then transcribed into raw data tables by hand. The chance of error was higher and data entry was usually double checked, further slowing progress. Preparing paper questionnaires was time-consuming, and could be complex given the experimental design. Transcribing data from a continuous line scale involved measuring the distance from the end of the scale to the assessment mark with a ruler, which was a daunting task made exponentially larger by the number of attributes, samples, assessors and replicates. The size and complexity of descriptive analysis studies were limited, as was the statistical analysis that was feasible.

The introduction of computers in the 1980s considerably speeded up operations. Initially, computers were expensive and one computer might be used in a conjunction with an optical reader to carry out data input and analysis. As computers became faster and cheaper, the process of descriptive analysis became increasingly more automated. Computers were introduced into sensory...