**1. Introduction**

Basically the methodology involved in the analysis of sensory data is summarized in a set of experimental and statistical techniques applied with the purpose of verifying the quality or the degree of acceptance of a given product, without, however, disregarding the characteristics of the individuals, with respect to your sensory skills. In this context, two distinct groups of consumers can be inserted, that is, consumers who have some enhanced sensory ability (s), resulting from product training or knowledge and totally lay consumers.

Faced with this situation, it becomes plausible to admit that a sensory analysis, applied to a group of trained consumers, being able to discriminate small differences between the samples, the results provided by the evaluations will show little variation [1]. Therefore, a sensory experiment carried out with this group shows a greater agreement with the procedures standardized by [2], since the objective assessments would be more homogeneous for the perception of uniformity, sweetness, defects, among others, mentioned by [3, 4].

analogous characteristics of the sample should give us information about the characteristics of the population. Bootstrap helps to learn about these sample characteristics by taking resamples (samples with replacement of the original sample) and we

*Intensive Computational Method Applied for Assessing Specialty Coffees by Trained…*

In this sense, to detect a difference in the judgment of special coffees by trained and untrained tasters, a test built via non-parametric Bootstrap will be proposed for

In accordance with the opinion of the Ethics and Research Council, registered with the CAAE: 14959413.1.0000.5148, the preparation of the Samples of 100% Arabica coffee was done by removing all defective beans and toast, respecting the

The roasting point was determined visually, using the color classification system by means of standardized discs (SCAA/Agtron Roast Color Classification System).

maintained using filtered water ready for consumption, free of any contaminants and without added sugar. With these specifications, four types of specialty coffees,

For each type of coffee, the following sensory characteristics were assessed in the acceptance test: aroma, body, hardness, and final score, in four sessions, with the participation of a volunteer group of consumers with basic knowledge in regard to sensory analysis of coffees and another group without basic knowledge. **Table 2** provides a list of the tasters, as well as the sensory characteristics assessed by each taster, in which *aij* represents the score given by taster *i* (*i = 1, 2, … , n1, n1 + 1, n1 + 2, … , n2*), such that *n1 + n2 = n*, for the sensory characteristic coffee *j* (*j = 1, 2,*

In the test, four different types of coffee were evaluated in terms of their sensory characteristics, flavor, acidity, body and note. In different sessions, voluntary consumers were grouped into two classes: (a) people with the habit of consuming coffee, but who do not have basic knowledge about specialty coffees and (b) people with the habit of consuming coffee and trained with information basic information

The fit of the probability distributions was carried out, considering the random variable *X* representing the maximum consumers'sensory scores for the each type

Bearing in mind that the highest score provided by a tester will be considered, this being considered as a block, the distribution of the maximums, according to the Fisher-Tippet theorem, is the generalized extreme values distribution (GEV). Its

**Type Genotype Altitude Processing** A Bourbon Above 1200 m Natural B Acaia Below 1100 m Pulped natural C Acaia Below 1100 m Natural D Bourbon Above 1200 m Pulped natural

*Description of specialty coffees evaluated in the sensory analysis with untrained consumers.*

of coffee (**Table 1**), totaling in a sample of 696 observations.

probability density function is defined by:

use this information to infer about the population [16].

maximum period of 24 hours for tasting.

*DOI: http://dx.doi.org/10.5772/intechopen.95234*

*… , 16*) combination.

about specialty coffees.

**Table 1.**

**179**

the mode of distribution of extreme values that best fits the data set.

**2. Modeling maximum sensory scores and numerical procedure**

Regarding the preparation of the drink, the concentration of 7% w/v was

coded in the samples by A, B, C and D given the description in **Table 1**.

In an opposite situation, considering a group of untrained consumers, it is more likely that the evaluations will present heterogeneous results, in such a way that the statistical treatment to be given in the analysis of these results may include the atypical observations, classified as outliers arising from the evaluation. Individual to each consumer [5, 6].

It is worth mentioning that the heterogeneity between the observations may be the result of uncontrollable factors, such as, for example, genetics, fatigue, unwillingness to carry out all tests and differences between the abilities of consumers, as well as external causes such as, for example, the geographical origin of a particular product whose qualities or characteristics are due exclusively or essentially to the geographical environment, including natural and chemical factors, which, among others, mention variations in chemical composition due to the genetic variability between cultivars that influence the sensory quality of coffees [7–12].

Given countless causes that are supposed to be the sources that cause outliers in a sensory analysis and reporting the analysis of the quality of coffees, special coffees can be highlighted. Following the definition given by [2], in summary, a coffee is said to be special, as it presents superior quality to its competitors in relation to its origin, absence of defects, processing and/or sensory expressions such as aroma, flavor.

The results of the sensory evaluation are established on a scale ranging from 0 to 10 in which these values represent the increasing levels of coffee quality. According to the analysis protocol [2] the results of the sensory evaluation vary according to a scale where the grades 6, 7, 8, 9 correspond respectively to: good, very good, excellent and exceptional. When the grades are less than 6, the coffees are declared to be of a quality below the Specialty Grade.

Respecting these characteristics, Coffee arabica cultivars are potential coffees worthy of being classified as special [13, 14]. However, studies related to the interference of the environment and geographic origin can influence the quality of the drink. [14], in a study interacting quality with environmental factors, concluded that the coffees with the highest scores in a contest held in the state of Minas Gerais, were produced in colder regions with milder temperatures and annual precipitation index around 1600 mm [15]. In this context, in humid regions it is recommend that processing be performed prioritizing peeled and desmucilated coffees. Thus, the quality of the coffee would be inferred without the interference of defects.

In the case of statistical methodology, it is highlighted that the usual methods of analysis, in general, are sensitive to outlier observations, these being plausible to have arisen in a sensory analysis carried out by untrained consumers [5, 15].

Due to this fact and assuming that the assignment of maximum sensory scores can be understood as random phenomena, in the sense that there are variations in the judgment of different consumers, this work aims to propose the use of some distributions belonging to the generalized extreme value distribution class in sensory analysis. For this purpose, this work analyzes a sensory experiment to evaluate four special coffees produced in the Serra da Mantiqueira Region of Minas Gerais, differentiated in preparation and geographical identification classified by different altitudes.

Bootstrap, developed by Efron in the 70s, can be used in many situations. It is based on a simple, yet powerful idea that the sample represents the population, so *Intensive Computational Method Applied for Assessing Specialty Coffees by Trained… DOI: http://dx.doi.org/10.5772/intechopen.95234*

analogous characteristics of the sample should give us information about the characteristics of the population. Bootstrap helps to learn about these sample characteristics by taking resamples (samples with replacement of the original sample) and we use this information to infer about the population [16].

In this sense, to detect a difference in the judgment of special coffees by trained and untrained tasters, a test built via non-parametric Bootstrap will be proposed for the mode of distribution of extreme values that best fits the data set.
