Periódicos

URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352

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Resultados da Pesquisa

Agora exibindo 1 - 10 de 47
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    Fermented natural coffee followed by pulping: Analysis of the initial sensory quality and after six months of storage
    (Universidade Federal de Lavras, 2023-09-01) Salvio, Luís Gustavo Amaral; Cirillo, Marcelo Ângelo; Borém, Flávio Meira; Alves, Ana Paula de Carvalho; Palumbo, Juliana Maria Campos; Santos, Cláudia Mendes dos; Haeberlin, Luana; Schwan, Rosane Freitas; Nakajima, Makoto; Sugino, Ryosuke
    In recent years, different methods of fermentation have emerged for coffee, with the intention of adding complexity to its flavor. To be able to clearly identify the information from sensory analysis, tools capable of detecting small differences are needed. One such tool is multiple factor analysis (MFA). Thus, the objective of this experiment was to evaluate the effects of fermentation time and storage on the quality of sensory attributes using MFA. The coffee (Coffea arabica L.) samples collected for the study were from the Serra da Mantiqueira region – Brazil. In the present study, two natural coffee fermentation methods were evaluated, one using natural coffee microbiota (NF) and the other using a starter culture (Y), along with different times of anaerobic fermentation (0, 24, 48, 72, and 96h), followed by the pulping of the samples without the use of water. Sensory analysis of fermented coffee samples was performed immediately after drying and after six months of storage in permeable packaging in a refrigerated environment. Thus, the experiment was conducted in an intirely randomized design with a 2 x 5 x 2 factorial scheme (2 fermentation treatments; 5 fermentation times; 2 storage times). The highest scores and the attributes described in higher quality coffees, such as sweetness, acidity, and aftertaste, were attributed to coffees fermented for 96 hours. Results indicated that inoculation of the yeast Saccharomyces cerevisiae CCMA 0543 was responsible for maintaining the sensory qualities of the coffee fermented for 96 hours after 6 months of storage.
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    Case study of modeling covariance between external factors and sensory perception of coffee
    (Universidade Federal de Lavras, 2023-08-18) Resende, Mariana; Borém, Flávio Meira; Cirillo, Marcelo Ângelo
    Analysis and inference of sensory perceptions in coffee beverages are complex due to numerous random causes intrinsic to productivity, preparation, and especially consumer and/or taster subjectivity. In this context, latent variables often composed of a combination of other observed variables are discarded from conventional analyses. Following this argument, this study aimed to propose a model of structural equations applied to a database, geographical indication of coffees in Serra da Mantiqueira, with a methodological contribution characterized by inclusion of a treatment effect, contemplated by different altitudes at which coffees were produced. From the methodology used, a covariance structure was estimated, and used in another statistical methodology to discriminate the effects. It is concluded that the proposed model proved to be advantageous for allowing the analysis of the relationship of latent variables, production and environmental variations, which are not considered in a sensorial analysis, and showed that, in fact, they influence the sensorial perception, for the coffees produced in the Serra da Mantiqueira region. The correlation structure generated from the covariance matrix adjusted by the model resulted in estimates that could be used in other statistical methodologies more appropriate to discriminate the effects, exemplifying the use of principal components.
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    Evaluation of the behavior of coffee stored in cooled and natural environments
    (Universidade Federal de Lavras, 2023-01-11) Andrade, Ednilton Tavares de; Rezende, Renan Pereira; Borém, Flávio Meira; Rosa, Sttela Dellyzete Veiga Franco da; Rios, Paula de Almeida; Oliveira, Filipe da Silva de
    The market value of coffee is strongly influenced by loss of quality, which makes storage one of the main steps in the entire production chain. The finite element method (FEM) and computational fluid dynamics (CFD) are numerical and computational techniques that facilitate the simulation of agricultural product storage systems. Computational modeling satisfactorily represents real experimentation, simplifies decision-making, and reduces costs. This study aimed to analyze mocha coffee storage for 6 months in a cooled environment with temperatures between 15 and 18 °C and in a natural environment. The water content, bulk density, specific heat, thermal conductivity, and thermal diffusivity were determined and colorimetry and sensory analysis were applied to compare initial and final samples of the product after storage. It was found that the water content and specific heat were the only properties that presented significant changes. Through sensory analysis, it was observed that the quality of the coffee was the same for both systems. A computational model was developed to simulate the heat transfer process during storage. The comparison of the simulation results with the experimental results for the temperature distribution in the grain mass showed overall mean relative errors of 2.34% for the natural environment and 5.74% for the cooled environment.
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    A mixed model applied to joint analysis in experiments with coffee blends using the least squares method
    (Universidade Federal do Ceará, 2019) Paulino, Allana Lívia Beserra; Cirillo, Marcelo Angelo; Ribeiro, Diego Egídio; Borém, Flávio Meira; Matias, Gabriel Carvalho
    The aim of the present study was to propose a mixed model for a sensory analysis of four experiments with blends of different standards of quality, including the species Coffea Arabica L. and Coffea Canephora. Each experiment differed in the proportions used to formulate the blends and the concentrations used in preparing the beverages, these being 7% and 10% coffee powder for each 100 ml of water. The response variables under analysis were the sensory characteristics of the beverage found in an assessment made by a group of trained tasters, considering taste, bitterness and a final score. Each description followed a numerical rating scale of intensity that ranged from 0 to 10. The model was implemented using the least squares method; this led to the conclusion that including random parameters in the model, represented by the experiments, made it possible to compare the effect of each component simultaneously for each of the experiments.
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    Monte Carlo simulation and importance sampling applied to sensory analysis validation of specialty coffees
    (Universidade Federal do Ceará, 2021) Ferreira, Haiany Aparecida; Liska, Gilberto Rodrigues; Cirillo, Marcelo Ângelo; Borém, Flávio Meira; Ribeiro, Diego Egídio; Cortez, Ricardo Miguel
    Coffee sensory analysis is usually made by a sensory panel, which is formed by trained tasters, following the recommendations of the Specialty Coffee Association of America. However, the preference for a coffee is commonly determined by experimentation with consumers, who typically have no special skills in terms of sensory characteristics. Therefore, this study aimed at applying an intensive computational method to study sensory notes given by an untrained sensory panel, considering the probability distributions of the class of extreme values. Four types of specialty coffees produced under different processes and in varied altitudes in the mountainous region of Mantiqueira, Minas Gerais, were considered. We concluded that the generalized Pareto distribution can be applied to sensory analysis to discriminate types of specialty coffees. Furthermore, the method of importance sampling by Monte Carlo simulation showed greater variability considering a probabilistic model adjusted to identify specialty coffees.
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    Statistical procedure for the composition of a sensory panel of blends of coffee with different qualities using the distribution of the extremes of the highest scores
    (Editora da Universidade Estadual de Maringá - EDUEM, 2019) Cirillo, Marcelo Ângelo; Ramos, Mariana Figueira; Borém, Flávio Meira; Miranda, Felipe Mesquita de; Ribeiro, Diego Egídio; Menezes, Fortunato Silva de
    The identification and interpretation of discrepant observations in sensory experiments are difficult to implement since the external effects are associated with the individual consumer. This fact becomes more relevant in experiments that involve blends, which scrutinize coffees with different qualities, varieties, origins, and forms of processing and preparation. This work proposes a statistical procedure that facilitates the identification of outliers while also evaluating the discriminatory powers of a sensory panel concerning the differentiation of pure blends and coffees. For this purpose, four experiments were performed that tested coffees with different qualities and varieties. The results suggest that the statistical procedure proposed in this work was effective for discriminating the blends relative to the pure coffees and that the effects of the concentrations and types of processing did not interfere with the statistical evaluations.
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    Unsupervised classification of specialty coffees in homogeneous sensory attributes through machine learning
    (Editora UFLA, 2020) Ossani, Paulo César; Rossoni, Diogo Francisco; Cirillo, Marcelo Ângelo; Borém, Flávio Meira
    Brazil is the largest exporter of coffee beans, 29% world exports, 15% this volume in specialty coffees. Thereby researches are done, so that identify different segments in the market, in order to direct the end consumer to a better quality product. New technologies are explored to meet an increasing demand for high quality coffees. Therefore, in this article has an objective to propose the use of machine learning techniques combined with projection pursuit in the construction of unsupervised classification models, in a sensory acceptance experiment, applied to four groups of trained and untrained consumers, in four classes of specialty coffees in which they were evaluated sensory characteristics: aroma, body coffee, sweetness and general note. For evaluating classifier performance, in the data with reduced dimension, all instances were used, and considering four groupings, the models were adjusted. The results obtained from the groupings formed were compared with pre-established classes to confirm the model. Success and error rates were obtained, considering the rate of false positives and false negatives, sensitivity and classification methods accuracy. It was concluded that, machine learning use in data with reduced dimensions is feasible, as it allows unsupervised classification of specialty coffees, produced at different altitudes and processes, considering the heterogeneity among consumers involved in sensory analysis, and the high homogeneity of sensory attributes among the analyzed classes, obtaining good hit rates in some classifiers.
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    Mathematical modeling of dehydration resistance of pericarp tissues and endosperm in fruits of arabic coffee
    (Editora UFLA, 2020) Dias, Camila de Almeida; Andrade, Ednilton Tavares de; Lemos, Isabella Àvila; Borém, Flávio Meira; Westerich, Diogo Nogueira; Silva, Ana Claudia Almeida da
    Coffee represents an important source of income for producers and for the Brazilian economy, being the second product in the country’s agricultural exports. Unlike other agricultural products, freshly harvested coffee has a high fruit water content, approximately 60% (dry base). It is fundamental to optimize the drying process for cost reduction and quality maintenance, making it necessary to understand the interdependence relation of the tissues of the pericarp and the coffee endosperm during the dehydration of the fruit. The objective of this work was to elaborate a drying model for the constituent parts of coffee fruits evaluating the resistance of each of the pericarp tissues and endosperm. The experiment was set up in a 4x6 factorial scheme (4 relative humidity of the drying air and natural, pulped natural coffee, pericarp tissues and endosperm: 1 - natural coffee and 2 – pulped natural coffee, 3 - exocarp + a portion of mesocarp, 4 - mesocarp, 5 - endocarp, 6 - endosperm]) in a completely randomized design with four replicates. The results were analyzed through analysis of variance and regression, using the statistical software STATISTICA 5.0®. The resistance to water outflow, regardless of the processing or the fruit part of the coffee, is greater when the coffee is dried with the lowest relative humidity. The natural coffee was the treatment that presented greater resistance, while the lower resistance was presented by the exocarp + a portion of mesocarp.
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    Avaliação sensorial do café cereja descascado, armazenado sob atmosfera artificial e convencional
    (Editora UFLA, 2008-11) Borém, Flávio Meira; Nobre, Gilberto Westin; Fernandes, Simone Miranda; Pereira, Rosemary Gualberto F. A.; Oliveira, Pedro Damasceno de
    Objetivou-se, com o presente trabalho, avaliar sensorialmente as bebidas e classificar quanto ao tipo o café cereja descascado submetido a diferentes acondicionamentos, ao longo do armazenamento. O experimento foi instalado em delineamento inteiramente casualizado (DIC), em esquema fatorial 2x5x5, com três repetições. Foram testados cinco acondicionamentos, com e sem modificação de atmosfera, em cinco épocas de avaliação, em dois lotes de café cereja descascado, sendo um em pergaminho e o outro beneficiado. Os acondicionamentos em embalagens impermeáveis (sacos de náilon, sacos de náilon com 40% de CO 2 e sacos aluminizados a vácuo) apresentaram capacidade de preservar a qualidade de bebida do café cereja descascado, na duração e nas condições do experimento. Os cafés acondicionados em embalagens permeáveis (sacos de juta e sacos de juta com casca de café picada) apresentaram alterações sensoriais que depreciaram a qualidade do café. Na classificação física, o tipo do café não sofreu alteração nos diversos acondicionamentos usados durante o experimento.
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    Avaliação de máquinas e equipamentos que oferecem riscos à segurança do trabalhador nas etapas de pós-colheita do café
    (Editora UFLA, 2008-11) Carvalho, Cinara da Cunha Siqueira; Borém, Flávio Meira; Rabello, Giovanni Francisco
    A Lei Brasileira no 6.514, de 22 de dezembro de 1977 (BRASIL, 2004) e as leis aprovadas pela portaria n°3.067, de 12 de abril de 1988 que cuida das questões de saúde e segurança do trabalhador, prometem o direito subjetivo do trabalhador urbano e rural, a redução dos riscos do trabalho mediante normas de saúde, higiene e segurança. Considerando que essas leis atualmente estão sendo aplicadas em fazendas e unidades de processamento de café, no intuito de preservar o bem-estar do trabalhador, conduziu-se este trabalho, com o objetivo de avaliar o estado de conservação de máquinas e equipamentos que podem oferecer riscos à saúde e comprometer a segurança do funcionário, e verificar sua conformidade com as normas regulamentadoras durante a fase de pós-colheita de café. Foram observados e registrados os riscos oferecidos pelas máquinas e equipamentos, existentes em trinta unidades de beneficiamento de café do município de São Sebastião do Paraíso – MG, e avaliados de forma qualitativa. Foi observado que o estado de conservação desses equipamentos é irregular, pois apresentam ruído, temperaturas extremas, poeira e oferecem riscos de choques e acidentes mecânicos que comprometem a saúde do trabalhador.