Biblioteca do Café
URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/1
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Resultados da Pesquisa
Item Evaluation of human postures during work in coffee crops in the southern region of Minas Gerais(Revista Engenharia na Agricultura, 2017-11-01) Fernandes, Allan Alves; Lima, Renato Ribeiro de; Cirillo, Marcelo Ângelo; Barbosa, Marco Antônio Gomes; Veiga, Elayne PenhaBrazil is the largest coffee producer in the world and Minas Gerais is the state responsible for 51.14% of this production, corresponding to 1.55 million tons of beans. In this context, contribution from family farming is signifcant. The aim of this work was to use a multivariate statistical methodology to provide plausible and interpretable results to diagnose the most in?uential body postures for each worker in coffee crops. Twelve workers were observed during a period of one hour in different tasks. Greater variability of body posture was shown during herbicide application on sloping ground. Despite body postural variability among workers during the tasks, some body postures, like 131 and 231, stood out. The proposed methodology allowed to identify the most in?uential body postures for each worker in an ergonomic point of view, and to aware the workers about the importance of adequate body postures during the tasks of coffee harvesting and post harvesting to avoid health damage.Item 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, RyosukeIn 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.Item 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 ÂngeloAnalysis 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.Item 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 MiguelCoffee 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.Item Association between the artificial aging test and the natural storage of coffee seeds(Associação Brasileira de Tecnologia de Sementes - ABRATES, 2018) Fantazzini, Tatiana Botelho; Rosa, Sttela Dellyzete Veiga Franco da; Pereira, Cristiane Carvalho; Pereira, Diego de Sousa; Cirillo, Marcelo Ângelo; Ossani, Paulo CésarThe accelerated aging test is recognized as an efficient method for evaluating the vigor of seed lots and for estimating their storage potential. Thus, this work aimed to evaluate the association between artificial aging and natural storage of coffee seeds, through the correlation factor analysis. Seeds of four cultivars of Coffea arabica L. (Catuaí Amarelo, Arara, Catiguá, and Mundo Novo) and one of Coffea canephora Pierre (Apoatã) were used. Part of the newly-harvested seeds were aged in a growth chamber under controlled temperature and relative humidity conditions (42 ºC and 100% RH) for periods of 0, 4, 6, 8, and 10 days. The other part of the seeds was stored in tri-wall paper packaging for a period of 2, 4, and 6 months in a non-climate-controlled environment. Artificial aging allows predictions on the storage potential of coffee seeds, although the artificial aging periods depend on the cultivars.Item Leaf count overdispersion in coffee seedlings(Universidade Federal de Santa Maria, 2019) Silva, Edilson Marcelino; Furtado, Thais Destefani Ribeiro; Fernandes, Jaqueline Gonçalves; Cirillo, Marcelo Ângelo; Muniz, Joel AugustoCoffee crops play an important role in Brazilian agriculture, with a high level of social and economic participation resulting from the jobs created in the supply chain and from the income obtained by producers and the revenue generated for the country from coffee bean export. In coffee plant growth, leaves have a determinant role in higher production; therefore, the leaf count per plant provides relevant information to producers for adequate crop management, such as foliar fertilizer applications. To describe count data, the Poisson model is the most commonly employed model; when count data show overdispersion, the negative binomial model has been determined to be more adequate. The objective of this study was to compare the fitness of the Poisson and negative binomial models to data on the leaf count per plant in coffee seedlings. Data were collected from an experiment with a randomized block design with 30 treatments and three replicates and four plants per plot. Data from only one treatment, in which the number of leaves was counted over time, were employed. The first count was conducted on 8 April 2016, and the other counts were performed 18, 32, 47, 62, 76, 95, 116, 133, and 153 days after the first evaluation, for a total of ten measurements. The fitness of the models was assessed based on deviance values and simulated envelopes for residuals. Results of fitness assessment indicated that the Poisson model was inadequate for describing the data due to overdispersion. The negative binomial model adequately fitted the observations and was indicated to describe the number of leaves of coffee plants. Based on the negative binomial model, the expected relative increase in the number of leaves was 0.9768% per day.Item 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 deThe 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.Item 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 MeiraBrazil 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.Item Quality of specialty natural coffee stored in different packages in Brazil and abroad(Editora UFLA, 2019-10) Borém, Flavio Meira; Andrade, Fabrício Teixeira; Santos, Cláudia Mendes dos; Alves, Ana Paula de Carvalho; Matias, Gabriel Carvalho; Teixeira, Daniela Edel; Ossani, Paulo César; Cirillo, Marcelo ÂngeloA challenge in the packaging and export of specialty coffees is to avoid green coffee bean storage and transport conditions that negatively affect the sensory quality of the roasted beans. The present study evaluated green beans of specialty coffees in eight types of packaging stored in a warehouse in the municipality of Poços de Caldas, Minas Gerais State, Brazil, for 18 months (Brazilian phase). This coffees were also subjected to sea transport and subsequent storage at a specialty coffee import company (export phase) in the United States, where it remained stored for 14 months. Physical, chemical, and sensory analyses of the beans were performed in the Brazilian phase and export phase. Green coffee beans stored in high-barrier packages had the best conserved quality. Packages with little or no barrier were not adequate for packaging or exporting specialty coffees. Beans in high-barrier packaging maintained their quality for long periods, which are therefore recommended for specialty coffee storage and export.Item Otimização simultânea das variáveis da qualidade do café durante o armazenamento(Embrapa Café, 2019-10) Abreu, Giselle Figueiredo de; Rosa, Sttela Dellyzete Veiga Franco da; Cirillo, Marcelo Ângelo; Malta, Marcelo Ribeiro; Pereira, Cristiane Carvalho; Borém, Flávio Meira; Sousa, Pedro Henrique AssisObjetivou-se neste trabalho aplicar a metodologia de delineamento de experimentos de otimização de variáveis relacionadas aos efeitos do ar refrigerado na conservação da qualidade de grãos de café. Frutos de Coffea arabica L. foram colhidos no estádio de maturação cereja, processados por via úmida ou por via seca e secados até atingirem 11% de teor de água. Parte dos grãos foi beneficiada e parte não foi beneficiada antes de serem armazenados em duas condições de ambiente: em ar refrigerado a 10ºC e umidade relativa de 50% e em 25ºC sem controle da umidade relativa do ar. Nos períodos de 3, 6 e 12 meses, foram retiradas amostras para avaliação da qualidade. Conclui-se que a temperatura de 10 °C é favorável à conservação de grãos de café, independentemente do método de processamento e do beneficiamento. Temperatura de 10°C e período de armazenamento de sete meses é a combinação ideal obtida pela otimização simultânea para a conservação do café natural.