Academic literature on the topic 'Food – Sensory evaluation – Statistical methods'

In this paper, we construct a rating credibility model of red wine by the Analytic Hierarchy Process, achieve the classification of red grapes through the evaluation results of red wine and cluster analysis method and analyze the correlation of the physical and chemical indicators between red grapes and red wine. Thus, the paper demonstrates that aromatic substances play an important role in the quality of red wine, so we cannot evaluate the quality of wine only by the physical and chemical indicators of wine grapes and wine.

One of the main directions of statistics in sensory evaluation is an assessment of the dependence between experimental variables and measured characteristics. Statistical criteria are used to assess a degree of interaction between variables, a level of experimental effects, and allow accepting or rejecting hypothesis proposed. In sensory evaluation, people act as measurement instruments, and a variation associated with the human factor arises. This proves that the use of statistical methods is necessary. This article represents a network computer system for collection and evaluation of food sensory indicators based on the methods of rank correlation and multifactorial analysis of variance in real time. The article describes information technology of expert sensory evaluation of food quality by individual panelists and sensory panels regarding the indicators that are not measured by technical means of control, based on client-server network architecture. The software implementation of system for collecting and statistical processing of sensory data based on the principles of multifactorial analysis of variance in real-time mode makes it possible to evaluate the influence of the human factor on objectiveness and reliability of sensory evaluation results, as well as to visualize the data of expert scores by various expert panels.

Sensory analysis is unusual in sustainability research, although it can offer a neoteric aspect of nature and wild animals’ perception. The study’s objective was to identify consumers’ attitudes towards plant and animal products from wild and conventional foods and put these findings into a broader social context. A blind sensory evaluation with 80 semi-trained assessors was used, segmented by gender, age, education, income, place of origin, family status, number of children, and willingness to pay. Wild boar (Sus scrofa) was chosen as an example of an overpopulated animal species occurring in the wild, which could be considered a partial substitute for pork. Statistical testing in these blind evaluations proved that wild boar meat is not considered less tasty. Therefore, wild boar meat could represent a partial substitute, complementing pork, on which consumers are willing to spend the same amount of money. Despite the mostly indifferent sensory evaluation, focus group responses showed considerable barriers to wild food. This paper concludes that possible educational and popularizing procedures are presented, including forest pedagogy, eliminating consumers’ prejudices. A mixed-methods approach within quantitative and qualitative methodology was chosen.

Purpose – The aim of this paper is to determine the sensory quality of food in restaurants by professional food evaluators and to research the impact of education, age and number of employees on the quality of food. Design/methodology/approach – In the first phase five trained food tasters evaluated the sensory quality of food. In the second phase, the analysis of the structure of employees was done by establishing their level of education, age and number of employees. In the third phase the regression and correlation analysis was done with the aim to establish the impact of the level of education, age and number of employees on the sensory quality of food. Findings – The sensory evaluation has shown that the evaluated food is of moderate quality. Correlation matrix has shown that the education level of employees has a high impact on the sensory quality of food. There is a correlation between the number of employees, their age and their education. Practical implications – Obtained results are the indicators of the quality of food in restaurants in the region and they can serve for the improvement of quality. They have shown that education and staff training can contribute to a better quality of food. Established methodology can also contribute to the practical evaluation of quality. Originality/value – This paper is reflected on the specific application of methodology of the sensory analysis of food in restaurants. The paper pointed to the impact of employees on the sensory quality of food by statistical methods. Statistical results which point to the great impact of the level of education of employees on the sensory quality of food in restaurants are particularly valuable.

Abstract Objectives To assess the acceptability of two newly developed plant-based protein entrees to be served in the National School Lunch Program (NSLP) among middle school students in the state of Georgia. Methods Two newly developed plant-based entrees (sweet potato chili fries, lentil-based sloppy joes) were introduced at lunch and sensory evaluation was conducted using a nine-point hedonic scale were used to evaluate overall liking (OL) and specific sensory attributes (appearance, flavor, texture) of lunch entrees immediately following lunch. Recipe formulations were designed to meet NSLP standards, to address the recent popularity of plant-based meat alternatives, and to incorporate the flavor preferences of student populations. Sensory evaluation of both plant-based entrees and all other entrees sold at lunch or brought from home were assessed. Results A total of 964 sensory evaluations were collected from middle school students in grades 6–8 in the Jackson County School District in Jefferson, Georgia. The plant-based entrees had a mean OL = 2.43, appearance = 3.00, texture = 3.58, flavor = 2.63. The regular hotline entrees had a mean OL = 5.66, appearance = 5.21, texture = 5.16, flavor = 5.75. A la carte entrees had a mean OL = 6.07, appearance = 5.65, texture = 5.64, flavor = 5.95. Entrees brought from home had a mean OL = 8.14, appearance = 7.82, texture = 7.84, flavor = 8.19. Regressions and t-tests were used to determine significant differences in waste using the statistical software Stata. Conclusions Little research has been conducted utilizing sensory evaluation to determine student liking of plant-based entrees. Plant-based entrees were liked least out of all entrees offered at school or brought from home. Sensory evaluation may be utilized to develop healthy school meals, ensure recipes are responsive to the taste preferences of children and profitable on the school lunch menu. Funding Sources Jackson County School District, Georgia Department of Education.

The support and development of the primary agri-food sector is receiving increasing attention. The complexity of modern farming issues has lead to the widespread penetration of Integrated Pest Management (IPM) Decision Support Systems (DSS). IPM DSSs are heavily dependent on numerous conditions of the agro-ecological environment used for cultivation. To test and validate IPM DSSs, permanent crops, such as olive cultivation, are very important, thus this work focuses on the pest that is most potentially harmful to the olive tree and fruit: the olive fruit fly. Existing research has indicated a strong dependency on both temperature and relative humidity of the olive fruit fly’s population dynamics but has not focused on the localised environmental/climate conditions (microclimates) related to the pest’s life-cycle. Accordingly, herein we utilise a collection of a wide-range of integrated sensory and manually tagged datasets of environmental, climate and pest information. We then propose an effective and efficient two-stage assignment of sensory records into clusters representing microclimates related to the pest’s life-cycle, based on statistical data analysis and neural networks. Extensive experimentation using the two methods was applied and the results were very promising for both parts of the proposed methodology. The identified microclimates in the experimentation were shown to be consistent with intuitive and real data collected in the field, while their qualitative evaluation also indicates the applicability of the proposed method to real-life uses.

The good use of food is one of the fundamental points of the food security of the populations especially in the developing countries. Therefore, for convincing results, the methods of strengthening nutritional knowledge by improving the culinary practices of vulnerable populations must take into account the dietary habits of the targets. The objective of the present study was to contribute to the consumption of the project crops to develop food formulations. In practice, eight (8) cornmeal formulas using soybeans and orange-fleshed sweet potatoes have been proposed and submitted to the grantees. The different proportions of ingredient to be mixed were obtained by the Pearson's Square method. Analysis of the sensory evaluation data was possible to the Statistical Package for Social Sciences (SPSS) software version 21 and the different results were presented in the form of radar graphs. The results showed that simultaneously flours and “kabato” accepted by the populations of the study area were formulations of: - E: 72.26 percent of maize flour and 27.74 percent of sweet potato flour - F: 53.76 percent of corn flour and 46.24 percent of sweet potato flour - G: 89.3 percent of composite flour (maize and sweet potato) and 10.7 percent of soya flour - H: 78.09 percent of composite flour (maize and sweet potato) and 21.91 percent of soya flour So, it can be envisaged to implement a strategy for a better vulgarization of these methods.

Background: Shea butter is the under-consumed vegetable fat and oil. Making shea butter a part of food components in confectionaries would increase its utilization. Objective: In this study, the cake was produced by incorporating shea butter as shortening. Methods: Shea butter to margarine ratio was 100: 0, 50:50, 40:60, 30:70, and 0:100%, and additional cake samples were produced using flashed shea butter. Standard methods determined the physical and proximate properties of the cake samples, while 25-member panelists did the sensory evaluation. Statistical significance was done at p<0.05. The height, weight, and volume of the cake samples ranged from 3.2 to 3.9 cm, 39 to 50 g, and 625 cm3 to 1026 cm3, respectively. The ranges of moisture, fat, protein, carbohydrate, crude fiber, and the ash content of cakes were 13.7-17.3, 24.3- 30.7, 4.4-8.6, 43-50, 0.10-1.10, and 2.9-3.9%, respectively. The energy value of cake samples in kcal ranged from 440 to 471. Results: There was no significant difference (p>0.05) in the height and volume of the cakes produced from 100% shea butter and 100% margarine. The fat, crude fiber, and ash content increase with the increase in Shea butter substitution. There was no significant difference in the taste and appearance of cake samples from 100%, 70%, 60%, and 50% margarine. Conclusion: Cake samples produced with 60% margarine and 40% shea butter were the most liked by the consumers. Acceptable cakes can be produced by the inclusion of up to 50% shea butter as part of the shortening.

This study set out to establish artificial neural networks (ANN) as an alternate to regression methods (multiple linear, principal components and partial least squares regression) to predict consumer liking from trained sensory panel data. The study has two parts viz., I) Flavour study - evaluation of ANNs to predict consumer flavour preferences from trained sensory panel data and 2) Fragrance study ??? evaluation of different ANN architectures to predict consumer fragrance liking from trained sensory panel data. In this study, a multi-layer feedforward neural network architecture with input, hidden and output layer(s) was designed. The back-propagation algorithm was utilised in training of neural networks. The network learning parameters such as learning rate and momentum rate were optimised by the grid experiments for a fixed number of learning cycles. In flavour study, ANNs were trained using the trained sensory panel raw data as well as transformed data. The networks trained with sensory panel raw data achieved 98% correct learning, whereas the testing was within the range of 28 -35%. A suitable transformation methods were applied to reduce the variations in trained sensory panel raw data. The networks trained with transformed sensory panel data achieved between 80-90% correct learning and 80-95% correct testing. In fragrance study, ANNs were trained using the trained sensory panel raw data as well as principal component data. The networks trained with sensory panel raw data achieved 100% correct learning, and testing was in a range of 70-94%. Principal component analysis was applied to reduce redundancy in the trained sensory panel data. The networks trained with principal component data achieved about 100% correct learning and 90% correct testing. It was shown that due to its excellent noise tolerance property and ability to predict more than one type of consumer liking using a single model, the ANN approach promises to be an effective modelling tool.

Assignment (MComm)--University of Stellenbosch, 2007.
ENGLISH ABSTRACT: This study is the result of part-time work done at a product development centre. The organisation extensively makes use of trained panels in sensory trials designed to asses the quality of its product. Although standard statistical procedures are used for analysing the results arising from these trials, circumstances necessitate deviations from the prescribed protocols. Therefore the validity of conclusions drawn as a result of these testing procedures might be questionable. This assignment deals with these questions. Sensory trials are vital in the development of new products, control of quality levels and the exploration of improvement in current products. Standard test procedures used to explore such questions exist but are in practice often implemented by investigators who have little or no statistical background. Thus test methods are implemented as black boxes and procedures are used blindly without checking all the appropriate assumptions and other statistical requirements. The specific product under consideration often warrants certain modifications to the standard methodology. These changes may have some unknown effect on the obtained results and therefore should be scrutinized to ensure that the results remain valid. The aim of this study is to investigate the distribution and other characteristics of sensory data, comparing the hypothesised, observed and bootstrap distributions. Furthermore, the standard testing methods used to analyse sensory data sets will be evaluated. After comparing these methods, alternative testing methods may be introduced and then tested using newly generated data sets. Graphical displays are also useful to get an overall impression of the data under consideration. Biplots are especially useful in the investigation of multivariate sensory data. The underlying relationships among attributes and their combined effect on the panellists’ decisions can be visually investigated by constructing a biplot. Results obtained by implementing biplot methods are compared to those of sensory tests, i.e. whether a significant difference between objects will correspond to large distances between the points representing objects in the display. In conclusion some recommendations are made as to how the organisation under consideration should implement sensory procedures in future trials. However, these proposals are preliminary and further research is necessary before final adoption. Some issues for further investigation are suggested.
AFRIKAANSE OPSOMMING: Hierdie studie spruit uit deeltydse werk by ’n produk-ontwikkeling-sentrum. Die organisasie maak in al hul sensoriese proewe rakende die kwaliteit van hul produkte op groot skaal gebruik van opgeleide panele. Alhoewel standaard prosedures ingespan word om die resultate te analiseer, noodsaak sekere omstandighede dat die voorgeskrewe protokol in ’n aangepaste vorm geïmplementeer word. Dié aanpassings mag meebring dat gevolgtrekkings gebaseer op resultate ongeldig is. Hierdie werkstuk ondersoek bogenoemde probleem. Sensoriese proewe is noodsaaklik in kwaliteitbeheer, die verbetering van bestaande produkte, asook die ontwikkeling van nuwe produkte. Daar bestaan standaard toets- prosedures om vraagstukke te verken, maar dié word dikwels toegepas deur navorsers met min of geen statistiese kennis. Dit lei daartoe dat toetsprosedures blindelings geïmplementeer en resultate geïnterpreteer word sonder om die nodige aannames en ander statistiese vereistes na te gaan. Alhoewel ’n spesifieke produk die wysiging van die standaard metode kan regverdig, kan hierdie veranderinge ’n groot invloed op die resultate hê. Dus moet die geldigheid van die resultate noukeurig ondersoek word. Die doel van hierdie studie is om die verdeling sowel as ander eienskappe van sensoriese data te bestudeer, deur die verdeling onder die nulhipotese sowel as die waargenome- en skoenlusverdelings te beskou. Verder geniet die standaard toetsprosedure, tans in gebruik om sensoriese data te analiseer, ook aandag. Na afloop hiervan word alternatiewe toetsprosedures voorgestel en dié geëvalueer op nuut gegenereerde datastelle. Grafiese voorstellings is ook nuttig om ’n geheelbeeld te kry van die data onder bespreking. Bistippings is veral handig om meerdimensionele sensoriese data te bestudeer. Die onderliggende verband tussen die kenmerke van ’n produk sowel as hul gekombineerde effek op ’n paneel se besluit, kan hierdeur visueel ondersoek word. Resultate verkry in die voorstellings word vergelyk met dié van sensoriese toetsprosedures om vas te stel of statisties betekenisvolle verskille in ’n produk korrespondeer met groot afstande tussen die relevante punte in die bistippingsvoorstelling. Ten slotte word sekere aanbevelings rakende die implementering van sensoriese proewe in die toekoms aan die betrokke organisasie gemaak. Hierdie aanbevelings word gemaak op grond van die voorafgaande ondersoeke, maar verdere navorsing is nodig voor die finale aanvaarding daarvan. Waar moontlik, word voorstelle vir verdere ondersoeke gedoen.

Orientadores: Maria Aparecida A. Pereira da Silva, Ademir Jose Petenate
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos
Made available in DSpace on 2018-08-03T16:42:14Z (GMT). No. of bitstreams: 1 MontesVillanueva_NildaDoris_D.pdf: 7571939 bytes, checksum: 5b97da35754c8719f94ee3b21e0cf955 (MD5) Previous issue date: 2003
Resumo: Em testes sensoriais, a análise dos dados geralmente é realizada através de algum modelo ANOVA. Estes modelos pressupõem que as respostas experimentais sejam: i) independentes, ii) normalmente distribuídas, m) homoscedásticas (variâncias iguais) e, iv) provenientes de uma mesma escala de medida (aditividade). Os principais problemas na análise de dados sensoriais através de modelos ANOV A referem-se aos dois últimos pressupostos. A homogeneidade das variâncias não pode ser assegurada devido à existência de pelo menos duas fontes potenciais de variabilidade dos dados, quais sejam: provadores e tratamentos. Por outro lado, a aditividade pode ser violada quando um provador utiliza faixas consistentemente mais (ou menos) amplas da escala para expressar a sua impressão sobre o produto. A maneira pessoal com que cada provador utiliza a escala para avaliar os produtos, chama-se de variação da expansibilidade entre provadores. Tanto a falta de homogeneidade das variâncias como a não aditividade do modelo, acarretam conseqüências sérias na obtenção do verdadeiro nível de significância para o efeito dos tratamentos, podendo afetar adversamente as comparações entre as médias dos tratamentos e comprometer seriamente tanto a interpretação dos resultados fornecidos pelo experimento como a validade do modelo ANOVA. Em testes com consumidores, escalas tradicionais como a escala hedônica de 9 pontos freqüentemente apresentam a seguinte problemática: i) geram dados que freqüentemente não satisfazem os pressupostos estatísticos de normalidade, aditividade e homoscedasticidade exigidos nos modelos ANOVA, ii) oferecem pouca liberdade aos consumidores para expressarem. suas percepções sensoriais, devido ao limitado número de categorias, m) induzem efeitos numéricos e contextuais no julgamento dos provadores e, iv) os valores numéricos associados às suas categorias, embora numericamente possuam intervalos iguais, não refletem iguais diferenças em percepção. Das metodologias utilizadas em testes sensoriais com consumidores, a escala hedônica de 9 pontos, é sem dúvida, a mais utilizada. Porém, em função da problemática anteriormente mencionada, surge a necessidade de serem pesquisadas escalas alternativas que possuam um melhor desempenho que a escala hedônica tradicional, tanto quando os dados são analisados através de modelos ANOVA como quando os mesmos são analisados através de métodos multivariados como Mapa Interno de Preferência - MDPREF. De um modo geral, o objetivo do presente trabalho foi pesquisar o desempenho de duas escalas alternativas em estudos com consumidores, quais sejam: escala autoajustável e escala hedônica híbrida, comparando-as com métodos afetivos tradicionais como a escala de ordenação e escala hedônica de 9 pontos. Para isso, três experimentos foram realizados conforme descrito a seguir: o primeiro experimento foi realizado com o objetivo de se avaliar em condições reais de teste de consumidor, o desempenho da escala autoajustável em relação à escala hedônica de 9 pontos e escala de ordenação, utilizando-se os seguintes critérios: i) diferenças em expansibilidade entre provadores, ii) poder discriminativo e, iii) adequação dos dados coletados por cada escala aos pressupostos do modelo ANOVA. Três marcas comerciais de confeitos foram avaliadas por 288 consumidores. Os resultados obtidos através das escalas hedônica de 9 pontos e autoajustável foram analisados através de ANOVA e os resultados da escala de ordenação, através do teste de Friedman. Os valores de pFamostra. pFprovador e QMresíduo fornecidos pela ANOVA de cada escala, foram respectivamente utilizados para avaliar o poder discriminativo, a expansibilidade dos provadores e a variabilidade residual dos dados. Teste de Tukey foi também aplicado para análise do poder discriminativo de cada escala. A normalidade dos dados foi verificada através do cálculo dos Coeficientes de assimetria e curtose, gráfico de probabilidade normal e teste de Kolmogorov-Smirnov. A homoscedasticidade, foi avaliada através de gráficos de dispersão e teste de Levene. Os resultados mostraram que a escala autoajustável foi efetiva para tratar o problema da expansibilidade entre provadores e da desigualdade das variâncias, porém, os resíduos mostraram moderados desvios da normalidade. A escala hedônica de 9 pontos apresentou problemas de heteroscedasticidade. As escalas autoajustável e de ordenação apresentaram o menor e o maior poder discriminativo respectivamente. Apesar dos problemas detectados, as três escalas apresentaram as mesmas tendências de preferência dos produtos avaliados. O segundo experimento foi realizado com o objetivo de se avaliar o desempenho da escala hedônica híbrida em estudos com consumidores, comparando-a à escala hedônica de 9 pontos, escala autoajustável, e escala de ordenação; através dos seguintes critérios: i) variabilidade das respostas sensoriais, ii) poder discriminativo, iii) adequação dos dados às suposições dos modelos ANOVA e, iv) facilidade de uso pelos consumidores. Cinco marcas de suco de laranja foram avaliadas por 80 consumidores, divididos em quatro grupos de 20 indivíduos cada. Todos os indivíduos avaliaram todas as amostras através de todas as escalas em 4 diferentes sessões de degustação. Um delineamento em quadrado latino 4x4, foi utilizado para controlar o efeito de ordem de apresentação das escalas e avaliar sem vícios a facilidade de uso das mesmas. Para cada escala, a ordem de apresentação das amostras e efeitos residuais ("carry-over") foram balanceados. Os resultados obtidos através das escalas hedônica tradicional, híbrida e autoajustável foram avaliados através de ANOVA. A normalidade dos dados foi verificada através do teste de Shapiro-Wilks, a homoscedasticidade através do teste de Brown-Forsythe e a aditividade, através do teste de Tukey para um grau de liberdade. Os valores de pFamostra, pFprovador e QMresíduo fornecidos pela ANOVA de cada escala, foram respectivamente utilizados para avaliar o poder discriminativo, a expansibilidade dos provadores e a variabilidade residual dos dados. O teste de REGWQ foi também aplicado para análise do poder discriminativo de cada escala. Os resultados obtidos através da escala de ordenação foram avaliados pelo teste de Friedman e, a facilidade de uso das escalas por testes de Cochran-Mantel-Haenszel. Os resultados sugeriram uma superioridade da escala hedônica híbrida sobre as escalas hedônica estruturada e a utoaj ustável , tanto em função do poder discriminativo como da adequação dos dados às suposições de normalidade e homoscedasticidade. A despeito dos dados da escala autoajustável terem apresentado maior variabilidade e sérios desvios da normalidade dos resíduos, o poder discriminativo desta escala foi ligeiramente superior ao da escala hedônica estruturada. A escala de ordenação apresentou o menor poder discriminativo em relação às demais. As escalas hedônicas estruturada e híbrida foram consideradas significativamente (p:S;0,01) mais fáceis de serem utilizadas que a autoajustável, não havendo diferença (p:s;O,OS) entre as duas primeiras. Finalmente, o objetivo do terceiro experimento foi avaliar o desempenho das escalas hedônica estruturada, hedônica híbrida e autoajustável na construção de Mapas Internos de Preferência - MDPREF. Nesta pesquisa, a aceitação global de 8 marcas comerciais de vinho tinto, a maioria deles varietal Cabernet Sauvignon, foi avaliada por 112 consumidores. Foram utilizados delineamentos experimentais balanceados para ordem de apresentação das escalas, ordem de apresentação das amostras e efeitos residuais. Os dados foram analisados através de ANOV A e MDPREF. O critério de avaliação do desempenho da cada escala baseou-se no número de consumidores significativamente ajustados (ps O,OS) e no grau de segmentação dos produtos e dos consumidores produzidos pelo MDPREF. Os resultados sugeriram uma superioridade da escala híbrida sobre a escala hedônica tradicional e autoajustável. O MDPREF gerado pelos dados da escala híbrida produziu um maior número de dimensões significativas de preferência (pS O,OS), trazendo como decorrência, uma porcentagem de 79,S% consumidores significativamente ajustados (pS O,OS), enquanto a escala autoajustável ajustou S4,S% dos consumidores e a escala hedônica S1,8%. Em geral a escala hedônica de 9 pontos apresentou um desempenho inferior ao das demais escalas. Os resultados do presente estudo sugerem fortemente que a escala hedônica híbrida é uma ferramenta válida e eficiente que pode ser utilizada na coleta de dados associados a estudos com consumidores, tanto quando eles forem analisados através de modelos normais para análise da variância como através da metodologia de Mapa Interno de Preferência
Abstract: In sensory tests, the basie statistieal toei for analyzing data is almost invariably some sort of analysis of variance models. These models presuppose that the experimental responses are: i) independent, ii) normally distributed, iii) homoscedastie (have equal varianees) and, iv) seores are on the same scale of measurement (additivity). The main problems arising from the analysis of sensory data using ANOVA models are related to the last two assumptions. Homogeneity of error variance is not assured, espeeially as there are at least two potential sources of heterogeneity: treatments and assessors. On the other hand, the additivity could be violated if one assessor used a eonsistently larger (or smaller) portion of the scale range, scoring more (or less) expansively than other assessors to express his opinion of the produet. The individual way in whieh eaeh panelist uses the scale to evaluate the produets is known as the differential expansiveness of seoring between assessors. 80th the laek of homogeneity of the variances and the non-additivity of the model, result in serious consequenees in obtaining a true levei of significance for the effect of the treatments and may adversely affeet the eomparison of treatment means. The non-additivity can seriously affeet and possible invalidate the analysis of variance and the interpretation of the results that it provides. In consumer tests, traditional scales sueh as the nine-point hedonie scale frequently present the following problems: i) they do not satisfy the statistical assumptions of independenee, normalityand homoscedastieity required by ANOVA models; ii) they give little freedom to the individuais to express their perceptions, due to the limited number of categories; iii) they induce numerical and contextual effects in the judgments by the panelists and, iv) the difference between numerical values associated with the categories do not reflect equivalent differenees in perception. Of the methodologies used in sensory tests with consumers, the 9-point hedonie scale is undoubtedly the most widely used. However, considering the previously mentioned problem, there is a need to investigate alternative scales providing better performanee than the traditional hedonie scale, both when the data are analyzed by ANOVA models and multivariate methods such as the Internal Preference Map - MDPREF. In general the objective of this research was to investigate the performance of two alternative scales in consumer studies, these being the self-adjusting scale and the hybrid hedonic scale, comparing them with traditional affective methods such as the ranking scale and the 9-point hedonic scale. With this objective three experiments were carried out as follows: The first experiment was carried out with the objective of evaluating the performance of the self-adjusting scale as compared to the 9-point hedonic scale and ranking scale under real consumer test conditions, using the following criteria: i) differential expansiveness between assessors, ii) discriminating power and, iii) compliance of the data collected by each scale with the ANOVA assumptions. Three commercial brands of candy were evaluated by 288 consumers. The results obtained from the 9-point hedonic and self-adjusting scales were analyzed by ANOVA and those of the ranking test by Friedman's test. The values for pFsample, pFassessor and QMerror provided by ANOV A for each scale, were used respectively to evaluate the discriminating power, the expansiveness of scoring between assessors and the data variability. Tukey's test was also applied to analyze the discriminating power of each scale. Normal probability plots, Kolmogorov-Smirnov test and coefficients of skewness and kurtosis checked data normality. Homoscedasticity was evaluated by scatter plots and the Levene test. The results showed that the self-adjusting scale was effective to deal with differential assessor expansiveness and produced homogeneous variances, however the residuais showed moderate deviations from normality. The 9-point hedonic scale showed problems with heteroscedasticity. Rank and the self-adjusting scales showed the highest and the lowest discriminating powers, respectively. Despite the problems detected, the three scales presented the same tendencies for preference amongst the products tested. The second experiment was carried out with the objective of evaluating the performance of the hybrid hedonic scale in consumer studies, comparing it with the 9point hedonic, the self-adjusting and the ranking scales, using the following criteria: i) variability of sensory response, ii) discriminative power, iii) data adequacy to the assumptions of ANOVA models and, iv) ease of use. Eighty consumers, divided into four groups of 20 individuais each, evaluated tive brands of orange juice. Ali the individuais evaluated ali the samples using ali the scales, in 4 distinct tasting sessions. A 4 x 4 Latin square design was used to control the effect of the order of presentation of the scales and evaluate their ease of use without biases. For each scale the presentation order and carry-over were balanced. The results obtained using the traditional hedonic, hybrid hedonic and self-adjusting scales were evaluated using ANOVA. Data normality was evaluated using the Shapiro-Wilks test, homoscedasticity by the Brown-Forsythe's test and the Tukey's one degree of freedom test for non-additivity. The values for pFsample, pFassessor and QMerror, provided by ANOVA for each scale, were used respectively to evaluate discriminating power, expansiveness between assessors and data variability. The REGWF test was also applied to analyze the discriminative power of each scale. The results obtained from the ranking test were evaluated by Friedman's test and the ease of use of the scales by the Cochran-Mantel-Haenszel tests. The results indicated the superiority of the hybrid hedonic scale as compared to the structured hedonic and self-adjusting scales, both with respect to discriminative power and to data adequacy to the assumptions of normality and homoscedasticity. The self-adjusting scale presented a slightly greater discriminative power than the structured hedonic scale, despite the former having presented data with a greater variability and lack of normality of the residuais. Of ali the methods, the ranking test presented the least discriminative power. The structured and hybrid hedonic scales were considered to be signiticantly (psO.01) easier to use than the self-adjusting scale, there being no difference (pSO.O5) between these first two scales. Finally, the objective of the third experiment was to evaluate the performance of the nine-point hedonic, hybrid hedonic and self-adjusting scales in the segmentation of samples and consumers using Internal Preference Mapping methodology. One hundred and twelve consumers evaluated the overall acceptability of 8 commercial brands of red wine, the majority being Cabernet Sauvignon. The effects of presentation order -scales and samples- and carry over effects were balanced. The data were analyzed by ANOVA and MDPREF. Scale performance was evaluated using as criteria: number of significant dimensions in the MDREF (psO.O5), number of consumers significantly adjusted (psO.O5) and the degree of segmentation of the products and consumers. The results suggested a superiority of the hybrid scale over the traditional hedonic and self-adjusting scales. The MDPREF generated by the hybrid scale data produced the greatest number of significant dimensions (p=5%), yielding 79.5% of the consumers significantly adjusted (p=5%), while the MDPREF generated by the self-adjusting scale adjusted 54.5% of the consumers and that of the hedonic scale, 51.8%. Overall, the 9-point hedonic scale showed the worst performance in relation to the other scales examined. The results of this study strongly suggest that the hybrid hedonic scale is a valid and efficient tool for use in data collection associated with consumer studies, both when analyzed by normal models for the analysis of variance and by Internal Preference Mapping methodology
Doutorado
Doutor em Alimentos e Nutrição

碩士
國立中興大學
動物科學系所
106
Emphasis of the importance in meat qualities has been increased continuously recently. Evaluation the qualities of beef and pork has been conducted for years. Some characteristics, such as juiciness, texture and flavor of pork and beef are often determined using physicochemical analysis and sensory evaluation. In contrast, there is less an objectively assessed standard for chicken meat. In Taiwan, some pork is sold at the ambient temperature. Consumers choose and purchase meat according to the sensory characteristics of products. A multivariate statistical method namely principal component analysis (PCA) has been used to identify the most critical variables in a multivariate data matrix, thus analyze data more effectively and efficiently. Additionally, some methods including the triangle test have been applied in the sensory evaluation. Therefore, this study was intended to utilize of physicochemical analysis, sensory evaluation and statistical methods to evaluate pork and chicken meet quality. In the 1st experiment, Taiwan native chicken (TNC) breast was cooked in a 95°C water bath until the internal temperature of the meat reached 85°C for 0, 20 and 40 minutes. Cooking loss, moisture content, water holding capacity (WHC) and some descriptive sensory parameters were determined, followed by a PCA analysis, thus to determine the juiciness of meat samples. In the 2nd experiment, shear force, total collagen content, and soluble collagen content as well as some descriptive sensory parameters of breast from TNC which fed for 12 and 16 weeks were determined, followed by a PCA analysis to analyze the texture of samples. In the 3rd experiment, sensory panelists attempted to apply the triangle test to differentiate the pork loins stored at 23±2°C for 4, 6, and 8 h (M4h, M6h, and M8h) as well as at 33±2°C for 2, 4, and 6 h (H2h, H4h, and H6h) to the one stored at 7°C (COM). The results of the 1st experiment showed that the four major principal components explained about 80.0% of the total variation. The PCA score plot showed a clear separation into the three clusters. According to the loadings, cooking loss, moisture content and WHC, as well as some sensory characteristics including moisture release, cohesiveness and oily mouthcoat were considered as the most effective variables for PC1, while WHC was most effectively to PC2. Sensory attributes including fiber texture, meat particle size, and chicken flavor intensity were effectively to PC3, while initial hardness, residual loose particles, and total acceptance were effectively to PC4. The results of the 2nd experiment showed that the four major principal components explained about 84.6% of the total variation. The PCA score plot showed a clear separation in two clusters. Base on the loadings, the soluble collagen content was effectively to PC1, while the total collagen content as well as some sensory characteristics including chew down hardness, chicken flavor intensity and total acceptance were the most effective variables to determine PC2. Three sensory attributes including moisture release, oily mouthcoat and chicken flavor intensity were effectively to PC3, while the total collagen content was effectively to PC4. The results of the 3rd experiment showed that the sensory characteristics of M8h and H6h samples significantly differed than those of COM (P < 0.05) base on the result of triangle test. According to the Fisher’s exact test, the chooses of 5 sensory characteristics including color, exudative, odor, mucus, and texture did not significantly relate to the correct answering and differentiation the samples (P > 0.05), thus more than one sensory characteristics was applied by the panelist to differentiate the samples. For M8h samples, texture was chosen by the 42.1% of the panelists who successfully differentiate samples, while texture was also chosen by the 80% of the panelist who differentiate samples fail. The results implied texture might be an appropriate judge criterion for those experienced panelists to functionally successfully while texture might be the possible cause leading to the failure for those inexperienced panelists. In summary, PCA can be applied to select a number of physicochemical and sensory parameters to determine the juiciness and texture characteristics of Taiwan native chicken breast effectively. Triangle test can be applied to evaluate the qualities of pork stored at ambient temperatures for 6 to 8 hours. In addition to the sensory characteristics that evaluated in the current study, the safety of product (i.e., the microbiological) should be also addressed. In conclusion, it is promising to apply physicochemical analysis, sensory evaluation and statistical methods appropriately to evaluate meat quality more effectively and efficiently.

In cross-cultural studies, respondents from specific cultures may have different product preferences and scale usage. Combining data from different cultures will result in departures from the basic assumptions of analysis of variance (ANOVA) and loss of power in testing capability of finding product and culture differences. However, the result of violations on power of ANOVA is unknown by sensory researchers. The objectives of this research were by simulating consumer product evaluation data, to evaluate the robustness and testing power of ANOVA under different cross-cultural situations. The study was conducted in two parts. First, an Empirical Logit simulation model was employed for generating sensory data. This model included respondent, product, consumer segment and product by segment interaction effects. Four underlying distributions: Binomial, Beta-Binomial, Hypergeometric, and Beta-Hypergeometric were used to increase or decrease the dispersion of the responses. Alternatively, instead of using these four distributions, the same applications were achieved by a binning step. The entire simulation procedure including the Empirical Logit model and the binning step was called Discrete Empirical Logit model. In the second part of the study, the Discrete Empirical Logit model was chosen to generate specified data sets under six different cross-cultural cases. After analyzing these data sets by ANOVA reduced and full models, the empirical power of ANOVA under different cases was calculated and compared. The results showed that both Beta-Hypergeometric and Discrete Empirical Logit were flexible on simulating sensory responses, but the Discrete Empirical Logit was relatively simple to use. Comparing with the ANOVA reduced model, the full model gave better information on evaluating the case that segments differ in product preferences. This suggested segmentation was very important in cross-cultural data analysis. Under the situations that sample sizes were equal and respondents performed consistently within segment (MSE ≈ 1), ANOVA was very robust to different scale usage, losing at worst 18% in power. From the scope of this study, we recommend using the ANOVA full model in the cross-cultural research. Results from different cultures could be combined when consistency within segments was high.
Graduation date: 2003

The taste qualities of acidulants have not been studied in detail despite the fact that they are widely used by the food industry. Studies on characterizing the sensory properties of organic and inorganic acids are very limited. Reported studies are commonly on threshold, equi-sour and the time intensity values of sourness. A series of experiments were conducted to determine the sensory properties of selected acidulants by different sensory and multivariate methods. First, the technique of Free-Choice Profiling was applied in order to characterize the sensory profile of some selected acids (adipic, citric, fumaric, glucono-delta-lactone, hydrochloric, lactic, malic, phosphoric, quinic, succinic, tartaric, citric:fumaric, citric:malic and fumaric:malic) on a weight (0.08% w/v or v/v) basis. Results analyzed through Generalized Procrustes Analysis indicate that on a weight basis (w/v or v/v), acids differed in their flavor and taste dynamics. Likewise, acids were described differently by individual panelists. Second, the sourness power functions of the selected acidulants were generated from five molar concentrations by magnitude estimation involving 16 trained panelists. Equi-sour concentrations were determined by regressing the log of the rescaled response (sensory) on the log of the stimuli (physical). The calculated equi-sour levels ranged from 0.48 ml/L for HCl to 2.34 g/L for glucono-delta-lactone when citric add was set at 1.0 g/L. These theoretical equi-sourness were then tested by using an alternative sensory method, the directional difference from control test. Third, the sensory profile of the acidulants at their equi-sour levels was characterized using two sensory methods, free-choice profiling and the conventional descriptive analysis. The former was analyzed by Generalized Procrustes Analysis while the latter was analyzed by Principal Component Analysis. The two sensory methods gave similar patterns of information regarding the add samples. The similarities of several organic acids and their mixtures were very evident. Hydrochloric and phosphoric acids were astringent while succinic add was bitter and had a monosodium glutamate taste. It was concluded that adds had other sensory properties aside from sourness that must be considered in a given food application.
Graduation date: 1993

Abstract 'Quality' of greenhouse and hydroponic produce implies suitability for a particular purpose or the degree to which certain set standards are met. Aspects of produce quality may encompass sensory properties (appearance, texture, taste and aroma), nutritive values, chemical constituents, mechanical properties, functional properties and defects. Quality standards and testing methods have been developed for most commercial crops to help ensure consumers receive produce of a suitable standard. These quality standards can range from basic grading for removal of damaged produce and for size, shape, weight and overall appearance, to analytical testing for compositional factors such as acidity, volatiles, dry matter, starch and sugars, toxins, vitamins and minerals, and others. This chapter discusses the components of crop quality, quality improvement, cultural practices to improve greenhouse produce quality (nutrient solution electrical conductivity levels, salinity and deficit irrigation), environmental conditions (including light and temperature) affecting quality of greenhouse crops, role of genetics in the quality of greenhouse-grown produce, microbial quality and food safety. Different quality testing and grading methods are described such as colour analysis, total soluble solids (Brix) testing, sensory evaluation of compositional quality, volatiles testing (aroma), texture and firmness quality assessment.

Abstract 'Quality' of greenhouse and hydroponic produce implies suitability for a particular purpose or the degree to which certain set standards are met. Aspects of produce quality may encompass sensory properties (appearance, texture, taste and aroma), nutritive values, chemical constituents, mechanical properties, functional properties and defects. Quality standards and testing methods have been developed for most commercial crops to help ensure consumers receive produce of a suitable standard. These quality standards can range from basic grading for removal of damaged produce and for size, shape, weight and overall appearance, to analytical testing for compositional factors such as acidity, volatiles, dry matter, starch and sugars, toxins, vitamins and minerals, and others. This chapter discusses the components of crop quality, quality improvement, cultural practices to improve greenhouse produce quality (nutrient solution electrical conductivity levels, salinity and deficit irrigation), environmental conditions (including light and temperature) affecting quality of greenhouse crops, role of genetics in the quality of greenhouse-grown produce, microbial quality and food safety. Different quality testing and grading methods are described such as colour analysis, total soluble solids (Brix) testing, sensory evaluation of compositional quality, volatiles testing (aroma), texture and firmness quality assessment.

To improve the capacity of the two-phase fluid movement through the horizontal pipes, in the turbulent regime, it is necessary to determine as correctly as possible the turbulent drag coefficient and to be estimated the associated energetic balance. For a hydrodynamic flow, the gas-liquid interfacial distribution may have different possible forms, with effect in various flow patterns, due to the different flow rates of the fluid and gas. Usually, we may express the dimensionless pressure gradients as drag coefficients. During the time, some analytical available methods, described the two-phase flows in the horizontal tubes. In previous researches, the author has tested four models: the homogeneous model, the separated-flow model, the mechanistic models, and the drift-flux model. In the present paper, there were selected to accomplish the research, the results obtained from the first three mentioned models. The theoretical and experimental results proved that there are more accurate and more suitable for the actual dedicated applications. The two-phase flow is important in a large variety of applications from engineering, such as natural gas production, oil transportation, the drilling, the food processing, polymer processing industry, pharmaceutical domains, etc. In the case of flow for a single phase, the shear forces on the wall create friction, losses, followed by a pressure decreasing, known as linear hydraulic losses. In the case of the two-phase flows, an additional interaction appears between the two phases, having as consequence a supplementary difficulty in the evaluation of the pressure drop. For the mentioned models, there were considered different flow rates for oil and gas. We vary in laboratory the gas flow rate. For each model the variables were made dimensionless, to enable generalization at different types of horizontal tubes, pipelines, with different diameters. The accuracy of the developed correlations from this paper is evaluated by comparing the predictions of previous calculations and correlations with the measured and obtained results, and with the data from technique literature. The relation between the pressure gradient and mass flow is expressed also in dimensionless form, as a relation between the drag factor and the Reynolds number, considered for the two-phase flow. This one was correlated with the generalized Reynolds number, with values from 6000 to 140000. For this Reynolds range were tested in the laboratory more than 200 measurements points, for each of the three selected models. The analyzed cases allowed the estimation in a proper manner of the accuracy of the drag turbulent factor, by calculating all 10 statistical parameters, for pipes up to 80 cm.

Background. Automated-entry consumer devices that collect and transmit patient-generated health data (PGHD) are being evaluated as potential tools to aid in the management of chronic diseases. The need exists to evaluate the evidence regarding consumer PGHD technologies, particularly for devices that have not gone through Food and Drug Administration evaluation. Purpose. To summarize the research related to automated-entry consumer health technologies that provide PGHD for the prevention or management of 11 chronic diseases. Methods. The project scope was determined through discussions with Key Informants. We searched MEDLINE and EMBASE (via EMBASE.com), In-Process MEDLINE and PubMed unique content (via PubMed.gov), and the Cochrane Database of Systematic Reviews for systematic reviews or controlled trials. We also searched ClinicalTrials.gov for ongoing studies. We assessed risk of bias and extracted data on health outcomes, surrogate outcomes, usability, sustainability, cost-effectiveness outcomes (quantifying the tradeoffs between health effects and cost), process outcomes, and other characteristics related to PGHD technologies. For isolated effects on health outcomes, we classified the results in one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. When we categorized the data as “unclear” based solely on health outcomes, we then examined and classified surrogate outcomes for that particular clinical condition. Findings. We identified 114 unique studies that met inclusion criteria. The largest number of studies addressed patients with hypertension (51 studies) and obesity (43 studies). Eighty-four trials used a single PGHD device, 23 used 2 PGHD devices, and the other 7 used 3 or more PGHD devices. Pedometers, blood pressure (BP) monitors, and scales were commonly used in the same studies. Overall, we found a “possible positive effect” of PGHD interventions on health outcomes for coronary artery disease, heart failure, and asthma. For obesity, we rated the health outcomes as unclear, and the surrogate outcomes (body mass index/weight) as likely no effect. For hypertension, we rated the health outcomes as unclear, and the surrogate outcomes (systolic BP/diastolic BP) as possible positive effect. For cardiac arrhythmias or conduction abnormalities we rated the health outcomes as unclear and the surrogate outcome (time to arrhythmia detection) as likely positive effect. The findings were “unclear” regarding PGHD interventions for diabetes prevention, sleep apnea, stroke, Parkinson’s disease, and chronic obstructive pulmonary disease. Most studies did not report harms related to PGHD interventions; the relatively few harms reported were minor and transient, with event rates usually comparable to harms in the control groups. Few studies reported cost-effectiveness analyses, and only for PGHD interventions for hypertension, coronary artery disease, and chronic obstructive pulmonary disease; the findings were variable across different chronic conditions and devices. Patient adherence to PGHD interventions was highly variable across studies, but patient acceptance/satisfaction and usability was generally fair to good. However, device engineers independently evaluated consumer wearable and handheld BP monitors and considered the user experience to be poor, while their assessment of smartphone-based electrocardiogram monitors found the user experience to be good. Student volunteers involved in device usability testing of the Weight Watchers Online app found it well-designed and relatively easy to use. Implications. Multiple randomized controlled trials (RCTs) have evaluated some PGHD technologies (e.g., pedometers, scales, BP monitors), particularly for obesity and hypertension, but health outcomes were generally underreported. We found evidence suggesting a possible positive effect of PGHD interventions on health outcomes for four chronic conditions. Lack of reporting of health outcomes and insufficient statistical power to assess these outcomes were the main reasons for “unclear” ratings. The majority of studies on PGHD technologies still focus on non-health-related outcomes. Future RCTs should focus on measurement of health outcomes. Furthermore, future RCTs should be designed to isolate the effect of the PGHD intervention from other components in a multicomponent intervention.