Análise sensorial: um estudo sobre procedimentos estatísticos e número mínimo de julgadores

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Teste de aceitação em amostras de cachaça: avaliação de métodos estatísticos e de número mínimo de julgadores

Based on data of global impression acceptance tests of 4 cachaças samples, sensory evaluated by 120 judges, statistical parametric and non-parametric proceedings were compared. In this way, based on the sensory acceptance obtained data, 5400 systematic samples were created with different judges numbers and submitted to the established statistical proceedings. The obtained results showed that ANOVA, with two factors and Friedman tests, were equivalent to determine signifi cant differences among the cachaça samples, and in relation to the number of judges, the results pointed out 45 as the minimum necessary to detect signifi cative differences.

Bioactive and toxic compounds in different foodstuffs: analytical techniques and sensory analysis

Foods that provide medical and health benefits or have a role in disease risk prevention are termed functional foods. The functionality of functional foods is derived from bioactive compounds that are extranutritional constituents present in small quantities in food. Bioactive components include a range of chemical compounds with varying structures such as carotenoids, flavonoids, plant sterols, omega-3 fatty acids (n-3), allyl and diallyl sulfides, indoles (benzopyrroles), and phenolic acids. The increasing consumer interest in natural bioactive compounds has brought about a rise in demand for these kinds of compounds and, in parallel, an increasing number of scientific studies have this type of substance as main topic. The principal aim of this PhD research project was the study of different bioactive and toxic compounds in several natural matrices. To achieve this goal, chromatographic, spectroscopic and sensorial analysis were performed. This manuscript reports the main results obtained in the six activities briefly summarized as follows: • SECTION I: the influence of conventional packaging on lipid oxidation of pasta was evaluated in egg spaghetti. • SECTION II: the effect of the storage at different temperatures of virgin olive oil was monitored by peroxide value, fatty acid activity, OSI test and sensory analysis. • SECTION III: the glucosinolate and phenolic content of 37 rocket salad accessions were evaluated, comparing Eruca sativa and Diplotaxis tenuifolia species. Sensory analysis and the influence of the phenolic and glucosinolate composition on sensory attributes of rocket salads has been also studied. • SECTION IV: ten buckwheat honeys were characterised on the basis of their pollen, physicochemical, phenolic and volatile composition. • SECTION V: the polyphenolic fraction, anthocyanins and other polar compounds, the antioxidant capacity and the anty-hyperlipemic action of the aqueous extract of Hibiscus sabdariffa were achieved. • SECTION VI: the optimization of a normal phase high pressure liquid chromatography–fluorescence detection method for the quantitation of flavanols and procyanidins in cocoa powder and chocolate samples was performed.

Sensory analysis of specialty coffee from different environmental conditions in the region of Matas de Minas, Minas Gerais, Brazil.

Specialty coffees can be differentiated in various ways, including the environmental conditions in which they are produced and the sensory composition of the drink. This study aimed to evaluate the effect of altitude, slope exposure and fruit color on the sensory attributes of cafes of the region of Matas de Minas. Sampling points were georeferenced in four altitude ranges (< 700 m; 700 < x> 825 m, 825 < x < 950 m and > 950 m) of the coffee crop; two fruit colors of var. Catuaí (yellowand red); and two slope exposures (North-facing and South-facing). Coffee fruit at the cherry stage were processed andsubmitted to sensory analysis. The sensory attributes evaluated were overall perception, clean cup, balance, aftertaste, sweetness, acidity , body and flavor, which made up the final score. The scores were examined by ANOVA and means werecompared by the Tukey test (p < 0.05). From the sensory standpoint, coffee fruits of both colors are similar, as well as the cof fees from both slope exposures when these factors were analyzed separately . However , at higher altitudes, Y ellow Catuaí produces coffees with better sensory quality . Similarly , coffees from North-facing slopes, at higher altitudes produce better quality cup. The altitude is the main factor that interferes with coffee quality in the area. All factors together contribute tothe final quality of the beverage produced in the region of Matas de Minas.

Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Pre-processing for approximate Bayesian computation in image analysis

Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computational cost of these simulations can be prohibitive for high dimensional data. An important example is the Potts model, which is commonly used in image analysis. Images encountered in real world applications can have millions of pixels, therefore scalability is a major concern. We apply ABC with a synthetic likelihood to the hidden Potts model with additive Gaussian noise. Using a pre-processing step, we fit a binding function to model the relationship between the model parameters and the synthetic likelihood parameters. Our numerical experiments demonstrate that the precomputed binding function dramatically improves the scalability of ABC, reducing the average runtime required for model fitting from 71 hours to only 7 minutes. We also illustrate the method by estimating the smoothing parameter for remotely sensed satellite imagery. Without precomputation, Bayesian inference is impractical for datasets of that scale.

Scalable Bayesian Computation for intractable likelihoods in image analysis

The inverse temperature hyperparameter of the hidden Potts model governs the strength of spatial cohesion and therefore has a substantial influence over the resulting model fit. The difficulty arises from the dependence of an intractable normalising constant on the value of the inverse temperature, thus there is no closed form solution for sampling from the distribution directly. We review three computational approaches for addressing this issue, namely pseudolikelihood, path sampling, and the approximate exchange algorithm. We compare the accuracy and scalability of these methods using a simulation study.

Shepard avocado sensory analysis

Avocados Australia has commissioned a study to evaluate whether the current dry matter maturity standards for Shepard avocado are reasonable, or whether they need to be refined. A sensory analysis program will be conducted from within the 2010 Shepard avocado season.

Volatility Smile Dynamics in Scenario Analysis

The objective of this paper is to suggest a method that accounts for the impact of the volatility smile dynamics when performing scenario analysis for a portfolio consisting of vanilla options. As the volatility smile is documented to change at least with the level of implied at-the-money volatility, a suitable model is here included in the calculation process of the simulated market scenarios. By constructing simple portfolios of index options and comparing the ex ante risk exposure measured using different pricing methods to realized market values, ex post, the improvements of the incorporation of the model are monitored. The analyzed examples in the study generate results that statistically support that the most accurate scenarios are those calculated using the model accounting for the dynamics of the smile. Thus, we show that the differences emanating from the volatility smile are apparent and should be accounted for and that the methodology presented herein is one suitable alternative for doing so.

Effects Of Subgrid-Scale Modeling On Lagrangian Statistics In Large-Eddy Simulation

The application of large-eddy simulation (LES) to turbulent transport processes requires accurate prediction of the Lagrangian statistics of flow fields. However, in most existing SGS models, no explicit consideration is given to Lagrangian statistics. In this paper, we focus on the effects of SGS modeling on Lagrangian statistics in LES ranging from statistics determining single-particle dispersion to those of pair dispersion and multiparticle dispersion. Lagrangian statistics in homogeneous isotropic turbulence are extracted from direct numerical simulation (DNS) and the LES with a spectral eddy-viscosity model. For the case of longtime single-particle dispersion, it is shown that, compared to DNS, LES overpredicts the time scale of the Lagrangian velocity correlation but underpredicts the Lagrangian velocity fluctuation. These two effects tend to cancel one another leading to an accurate prediction of the longtime turbulent dispersion coefficient. Unlike the single-particle dispersion, LES tends to underestimate significantly the rate of relative dispersion of particle pairs and multiple-particles, when initial separation distances are less than the minimum resolved scale due to the lack of subgrid fluctuations. The overprediction of LES on the time scale of the Lagrangian velocity correlation is further confirmed by a theoretical analysis using a turbulence closure theory.

Mathematical prerequisites for learning statistics in Psychology: Assessing core skills of numeracy and mathematical reasoning among undergraduates.

This study sought to extend earlier work by Mulhern and Wylie (2004) to investigate a UK-wide sample of psychology undergraduates. A total of 890 participants from eight universities across the UK were tested on six broadly defined components of mathematical thinking relevant to the teaching of statistics in psychology - calculation, algebraic reasoning, graphical interpretation, proportionality and ratio, probability and sampling, and estimation. Results were consistent with Mulhern and Wylie's (2004) previously reported findings. Overall, participants across institutions exhibited marked deficiencies in many aspects of mathematical thinking. Results also revealed significant gender differences on calculation, proportionality and ratio, and estimation. Level of qualification in mathematics was found to predict overall performance. Analysis of the nature and content of errors revealed consistent patterns of misconceptions in core mathematical knowledge , likely to hamper the learning of statistics.