Abstract Factors that influence the acceptability and preferences of consumers have been perceived as sensory attributes, such as color, appearance, flavor, and texture. Understanding which attributes are most important for overall liking would be helpful to establish meaningful criteria for product grading. Thus, in addition to the overall chemical and sensory qualities, it is important to appreciate which sensory attributes make a product pleasant or unpleasant to a consumer. In this context, the aim of this study was to evaluate the sensory attribute that contributes most to the overall liking by a gamma regression model using different formulations of mixed fruit jams made with Brazilian Cerrado fruits. Based on the proposed model, we concluded that appearance was the most important predictor of the overall liking of the assessors.

RESUMO A análise sensorial do Café supõe que um painel sensorial é formado por provadores treinados, de acordo com as recomendações da American Specialty Coffee Association. No entanto, a escolha determina que a preferência de um café é rotineiramente feita através da experimentação com os consumidores, que em grande parte não tem habilidades especiais em termos de características sensoriais. Por este fato, este estudo objetivou aplicar o método computacional intensivo no estudo de notas sensoriais a partir de um painel sensorial não treinado considerando as distribuições de probabilidade pertencentes à classe dos valores extremos. Assim, foram considerados quatro tipos de cafés especiais produzidos em diferentes processos e alturas na região serrana da Mantiqueira, em Minas Gerais. Concluiu-se que a distribuição generalizada de Pareto pode ser aplicada à análise sensorial para discriminar os diferentes tipos de cafés especiais e que o método de amostragem por importância por simulação de Monte Carlo, considerando o modelo probabilístico ajustado para identificar o café especial, com notas apresentaram a maior variabilidade.

ABSTRACT 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.

Abstract Pereskia grandifolia Haworth (PGH) and Pereskia aculeata Miller (PAM) are recognized sources of proteins; dietary fiber; vitamins and minerals make this plant leaves, raw, cooked, and braised, an important ally against protein and micronutrient deficiencies. One of the main problems is the presence of antinutritional factors that may interfere in the digestibility and bioavailability of some nutrients. The objective was to evaluate the amino acid profile and the chemical score of the raw leaves and the effects of heating media and time on the total dietary fiber, minerals, trypsin inhibition, oxalic acid and tannins of leaves of PGH and PAM. The samples had similar amino acid profiles and total dietary fiber. With regard to antinutritional compounds, heating the leaves of PGH led to a decrease in trypsin inhibition, primarily after the first minutes of wet cooking. Oxalic acid and tannins predominated in both species. Considering the interaction with time, the variables related to iron and zinc minimized the tannin responses in PGH and PAM, respectively. Heating media and times interfered with the chemical components present in the leaves of Pereskia species and led to high antinutrient retention after heat treatment.

RESUMO O presente estudo tem por objetivo propor um modelo misto em uma análise sensorial de quatro experimentos de blendscom diferentes padrões de qualidade envolvendo as espécies Coffea Arabica L. e Coffea Canephora. Cada experimento foi diferenciado em função das proporções utilizadas na formulação dos blendse das concentrações utilizadas no preparo dabebida, sendo elas 7% e 10% de pó de café para cada 100 ml de água.As variáveis respostas analisadas foram características sensoriais encontradas na bebida do café a partir de avaliação feita por grupo de provadores treinados. As características consideradas foram o sabor, o amargor e a nota final. Cada descrição respeitou uma escala numérica de avaliação da intensidade que variou de 0 até 10. A implementação do modelo foi através do método de mínimos quadrados, possibilitando concluir que a inclusão dos parâmetros aleatórios no modelo, representados pelos experimentos permitiu comparar o efeito de cada componente, simultaneamente a todos os experimentos.

ABSTRACT 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.

ABSTRACT: Tetrazolium tests use conventional sampling techniques in which a sample has a fixed size. These tests may be improved by sequential sampling, which does not work with fixed-size samples. When data obtained from an experiment are analyzed sequentially the analysis can be terminated when a particular decision has been made, and thus, there is no need to pre-establish the number of seeds to assess. Bayesian statistics can also help, if we have sufficient knowledge about coffee production in the area to construct a prior distribution. Therefore, we used the Bayesian sequential approach to estimate the percentage of viable coffee seeds submitted to tetrazolium testing, and we incorporated priors with information from other analyses of crops from previous years. We used the Beta prior distribution and, using data obtained from sample lots of Coffea arabica, determined its hyperparameters with a histogram and O’Hagan's methods. To estimate the lowest risk, we computed the Bayes risks, which provided us with a basis for deciding whether or not we should continue the sampling process. The results confirm that the Bayesian sequential estimation can indeed be used for the tetrazolium test: the average percentage of viability obtained with the conventional frequentist method was 88 %, whereas that obtained with the Bayesian method with both priors was 89 %. However, the Bayesian method required, on average, only 89 samples to reach this value while the traditional estimation method needed as many as 200 samples.

ABSTRACT. 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.

RESUMO: A cultura do café desempenha papel relevante na agricultura do Brasil, com expressiva participação social e econômica tanto pelos empregos gerados na cadeia produtiva, bem como pela renda obtida pelos produtores e pelas divisas geradas para o país na exportação do grão. No crescimento das plantas de café, as folhas desempenham papel decisivo para que tenha maior produção, portanto a contagem do número de folhas por planta fornece informações importantes aos produtores para o manejo adequado da cultura como, por exemplo, a aplicação de adubações foliares. Em geral, na descrição de dados obtidos por contagem, o modelo mais utilizado é o Poisson, sendo que quando os dados apresentam superdispersão, o modelo Binomial Negativo tem se mostrado mais adequado. O objetivo deste trabalho foi comparar o ajuste dos modelos de Poisson e Binomial Negativo em dados de contagens do número de folhas por planta em mudas do cafeeiro. Os dados foram obtidos de um experimento usando o delineamento em blocos casualizados com trinta tratamentos e três repetições com quatro plantas por parcela. Foram utilizados os dados de apenas um tratamento no qual foi feita a contagem do número de folhas ao longo do tempo. A primeira avaliação foi feita em 8 de abril de 2016 e as demais aos 18, 32, 47, 62, 76, 95, 116, 133 e 153 dias após a primeira avaliação, totalizando dez medidas. A adequação dos mesmos foi verificada com base nos valores da Deviance e no envelope simulado para os resíduos. Os resultados do ajuste indicaram que o modelo Poisson foi inadequado para descrição dos dados devido a superdispersão. O modelo Binomial Negativo se ajustou adequadamente e foi indicado para descrever o número de folhas das plantas do cafeeiro. Com base no modelo Binomial Negativo o aumento relativo esperado para o número de folhas foi de 0,9768% para cada dia.

ABSTRACT: Coffee 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.

Resumo: O teste de envelhecimento artificial tem se destacado como um método eficiente para avaliar o vigor de lotes de sementes e para estimar o potencial de armazenamento dos mesmos. Assim, este trabalho teve o objetivo de avaliar a associação entre o envelhecimento artificial e o armazenamento natural de sementes de café, por meio da correlação via análise de fatores. Foram utilizadas sementes de quatro cultivares de Coffea arabica L. e uma de Coffea canephora Pierre. Parte das sementes recém-colhidas foi envelhecida em câmara de crescimento do tipo BOD sob condições controladas de temperatura e umidade relativa (42 ºC e 100% UR) por períodos de 0, 4, 6, 8 e 10 dias. A outra parte das sementes foi armazenada em embalagens de papel trifoliado por um período de 2, 4 e 6 meses em armazém, em ambiente não controlado. O envelhecimento artificial prediz a armazenabilidade de sementes de café, sendo os tempos de envelhecimento artificial dependentes das cultivares.

Abstract: The 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.

RESUMO A demanda por café de alta qualidade tornou-se um critério consolidado para atingir os melhores preços. Atualmente, as cooperativas avaliam os grãos de café através, principalmente, da granulometria e da quantidade de defeitos na amostra. Este tipo de avaliação gera dados de contagem que originam tabelas de contingência oriundas de épocas ou grupos distintos envolvendo as mesmas variáveis em linha e coluna e pode haver interesse em saber se duas tabelas estão relacionadas, e o quanto estão relacionadas. Estas são as denominadas tabelas combinadas. As técnicas de análise estatística, normalmente empregadas, não contemplam dados categóricos em tabelas combinadas. Assim, este trabalho tem por objetivo avaliar a incidência de diferentes tipos de defeitos em amostras de grãos de café chatos graúdos em duas safras diferentes, através da construção de biplots. Foi utilizada a teoria da decomposição em valores singulares simultânea de tabelas de contingência de dupla entrada. Avaliou-se os resultados da contagem de defeitos em grãos de 24 amostras de cafés provenientes do Sul de Minas Gerais, nas safras de 2014 e 2015. Além disso, verificou-se a associação entre os tipos de defeitos, considerados dentro de diferentes proporções totais de defeitos na amostra, tendo como base o percentual em peneiras 17/18. Avaliou-se ainda, as somas de quadrados relativas, a partir da similaridade e dissimilaridade entre as safras. Conclui-se que a técnica de análise simultânea permite visualizar melhor o comportamento comum e alterações entre diferentes safras, distinguindo os tipos de defeito associados a cada safra e entre diferentes proporções de grãos chatos graúdos.

ABSTRACT The demand for high quality coffee has become a consolidated criterion to achieve the best prices. Currently, cooperatives evaluate the coffee beans mainly through the particle size and the number of defects in the sample. This evaluation type generates counting data that originates contingency tables from different periods or groups involving the same variables in the row and column and there may be interest in knowing if two tables are related and how much are related. These are the so-called combined tables. Statistical analysis techniques normally employed do not include categorical data in the combined tables. The aim of this study was to evaluate the incidence of different types of defects in samples of large flat coffee beans in two different harvests through the construction of biplots. The decomposition theory in single simultaneous values of double entry contingency tables was used. The results of defect counting in beans of 24 coffee samples from southern Minas Gerais, Brazil, were evaluated in the 2014 and 2015 harvests. Moreover, the association among defect types, considered within different total defect proportions in the sample, was verified based on the percentage in 17/18 sieves. It was also evaluated the relative sums of squares from the similarity and dissimilarity among the harvests. It is concluded that the simultaneous analysis technique allows better visualizing the common behavior and alterations among different harvests, distinguishing the defect types associated with each harvest and among different proportions of large flat beans.

ABSTRACT The objective of the present study was to quantify the biomass and carbon stock in a Seasonal Semideciduous Forest remnant in southern Minas Gerais. Forest inventory data taken between 2010 and 2013 in permanent plots, was used to estimate biomass with an allometric equation. Basic wood density (Db) and carbon content were determined in the laboratory and the carbon stock was obtained by multiplying biomass by carbon content. The species with the lowest and highest Db were Nectandra lanceolata (0.38 g cm-3) and Machaerium villosum (0.77 g cm-3). The species that showed the lowest and highest carbon content values were Casearia decandra (41.85%) and Nectandra oppositifolia (46.57%). The biomass stock for the area was 126.92 ± 0.09 t ha-1, which corresponded to 55.91 ± 0.05 t ha -1 of carbon stock and a periodic annual increment of 3.07 t ha-1 year -1.

RESUMO. Este trabalho foi realizado com o objetivo de avaliar a correlação entre um grupo de variáveis fisiológicas (condutividade elétrica, lixiviação de potássio e porcentagem de germinação) e um grupo de variáveis de cinética de secagem (tempo e taxa de secagem), bem como verificar a relação entre as variáveis de cinética de secagem e a qualidade sensorial do café, em função do tipo de processamento, da temperatura e do fluxo de ar de secagem. A secagem do café foi realizada em secador de leito fixo com duas temperaturas e dois fluxos de ar. Após a secagem, foi avaliada a qualidade fisiológica e sensorial. A partir dos resultados obtidos, conclui-se que: o café processado via seca é mais sensível à secagem mecânica com ar aquecido do que o processado via úmida, apresentando pior desempenho fisiológico; o fluxo de ar não interfere na qualidade fisiológica do café despolpado e natural; a elevação da temperatura de 40 para 45°C resultou em queda da qualidade fisiológica apenas para o café despolpado e a elevação da taxa de secagem, por meio da elevação do fluxo de ar de secagem, para a temperatura de 40°C teve efeito negativo na qualidade sensorial do café despolpado.

ABSTRACT. The objective of this study was to evaluate the correlation between a group of physiological variables (electrical conductivity, potassium leaching, and germination percentage) and a group of drying kinetics variables (drying time and drying rate) in addition to verifying the relation between drying kinetics variables and coffee quality as a function of processing type, temperature, and drying airflow. Coffee drying was conducted in a fixed-layer dryer at two temperatures and two airflows. After drying, an evaluation of the physiological and sensorial quality was conducted. Based on the results obtained, the following conclusions were drawn: coffee that is processed via a dry method is more sensitive to mechanical drying with heated air than coffee processed via a wet method, resulting in poor physiological performance; airflow does not interfere with the physiological quality of pulped and natural coffees; a temperature increase from 40 to 45°C resulted in a decrease in the physiological quality only for pulped coffee; and an increase in the drying rate as a result of an increase in the drying temperature to 40°C had a negative effect on the sensorial quality of pulped coffee.

RESUMO Este trabalho teve como objetivo propor uma modelagem matemática para determinar qual a melhor combinação formada por subprodutos do processamento do café para a produção de silagem. Para atingir este objetivo foram avaliados 13 tratamentos, resultantes da combinação da casca de café úmida (CCU), casca de café seca (CCS), com ou sem a utilização de melaço (M) e com ou sem a utilização do inoculante Lactobacillus plantarum (I). Em função desses componentes, diversas misturas foram propostas, as quais foram avaliadas por meio da técnica de otimização de respostas simultâneas. As silagens com as melhores características foram obtidas com a utilização de 76,40% de CCU, 18,77% de CCS, 4,83% de M e 0,0001% de I.

ABSTRACT The aim of this work was to propose a mathematical model to determine the best combination of the by-products of coffee processing in the production of silage. To this end, 13 treatments were evaluated, resulting from the combination of wet coffee husks (WCH) and dried coffee husks (DCH), both with and without the use of molasses (M) and with or without the use of the inoculant Lactobacillus plantarum (I). From these components, various mixtures were proposed and evaluated, using the technique of simultaneous optimisation of multiple response variables. Silages with the best characteristics were obtained from the use of 76.40% WCH, 18.77% DCH, 4.83% of M and 0.0001% I.

RESUMO A qualidade sensorial de cafés especiais, cujas características se relacionam com o meio geográfico é apreciada pelo setor produtivo e o mercado, no qual, uma relação comercial é pautada na livre escolha, por parte do consumidor e na agregação de valores e diferenciação de preços em função da qualidade do produto. Neste cenário, focar as tendências dos consumidores é primordial para que um café seja diferenciado em relação aos demais; para isso, novas metodologias de análise devem ser exploradas para que os resultados sejam dignos de contemplaram inúmeros fatores inerentes às particularidades de cada consumidor e/ou produto. Com esse propósito, o objetivo desse artigo é propor o uso da técnica de múltiplos fatores aplicada a tabelas de contingência (MFACT), em dados categorizados obtidos em um experimento sensorial realizado com diferentes grupos de consumidores com a finalidade de identificar similaridades entre quatro cafés especiais. Concluiu-se que o uso dessa técnica é viável, por permitir discriminar os cafés especiais produzidos em diferentes ambientes (altitudes) e processamentos, considerando a heterogeneidade entre os consumidores envolvidos na análise sensorial.

ABSTRACT The sensory quality of specialty coffees, whose characteristics are related to the geographical environment, is appreciated by both the productive sector and the market, where the commercial relationship is guided by free choice on the part of the consumer, and the added value and price differentiation which depend on the quality of each product. In such a scenario, focusing on consumer trends is fundamental if one coffee is to be seen as different to the others. For that reason, new methods of analysis should be investigated so that the results are able to take into account the many factors which are inherent to the peculiarities of each customer and/or product. To that end, the aim of this paper is to propose the use of a technique of Multiple Factor Analysis for Contingency Tables (MFACT) on categorised data from a sensory experiment conducted with different groups of consumers, for the purpose of identifying similarities between four speciality coffees. It was concluded that the use of this technique is feasible, as it allows discrimination of specialty coffees produced in different environments (altitudes) and processing methods, considering the heterogeneity between consumers involved in the sensory analysis.

RESUMO O presente trabalho teve como objetivo propor uma metodologia de agrupamento com reamostragem bootstrap por meio do modelo AMMI (Additive Main Effects and Multiplicative Interaction Analysis), contribuindo para melhor predição da estabilidade fenotípica de genótipos e de ambientes. Ao mesmo tempo, analisar a divergência genética na avaliação de linhagens experimentais de soja, identificando genótipos que reúnam características de alta produtividade, com controle de insetos mastigadores e sugadores, reunindo grupos de genótipos similares para os caracteres avaliados. Foram conduzidos 24 experimentos aleatorizados em blocos com duas repetições subdivididas em conjuntos experimentais com testemunhas comuns. A análise AMMI por componentes principais indicou os dois primeiros eixos como significativos, os quais explicaram 83,9% da porção da soma de quadrados da interação. O primeiro eixo singular da análise AMMI capturou a maior porcentagem de "padrão" e, com acumulação subsequente das dimensões dos eixos, houve uma diminuição na porcentagem de "padrão" e um incremento de "ruídos". Utilizou-se a distância euclidiana entre escores de genótipos como medida de dissimilaridade e posteriormente obtidos os agrupamentos por meio do método hierárquico de Ward. Os genótipos 97-8011, 97-8029, 97-8050 e a testemunha IAS-5 se comportaram como os mais promissores para fins de recomendação, pois os resultados indicaram maior estabilidade e melhor performance quanto à produtividade de grãos.

ABSTRACT This study aimed to propose a clustering methodology with bootstrap resampling using the Additive Main Effects and Multiplicative Interaction Analysis (AMMI) to contribute to better prediction of phenotypic stability of genotypes and environments. It also aims to analyze the genetic divergence in the assessment of soybean lines, identify genotypes with high-yielding characteristics, with control of chewing and sucking insect pests, and cluster similar genotypes for the traits evaluated. A total of 24 experiments were conducted in randomized blocks, with two replications subdivided in experimental groups with common controls. AMMI with principal component analysis indicated that PC1 and PC2 were significant, explaining 83.9% of the sum of squares of the interaction. The first singular axis of AMMI analysis captured the highest percentage of "pattern" and, with subsequent accumulation of the dimensions of the axes, there was a decrease in the percentage of "pattern" and an increase in "noise". The Euclidean distance between genotype scores was used as the dissimilarity measure and clusters were obtained by the hierarchical method of Ward. Genotypes 97-8011, 97-8029, 97-8050 and IAS-5 had the best performance and are promising for recommendation purposes, with the greatest stability and best performance on grain yield.

El presente trabajo tiene como objetivo proponer un estimador para estimar la probabilidad de éxito de un modelo binomial que incorpora la variación extra-binomial generada por muestras cero-inflados. La construcción de este estimador se llevó a cabo con una base teórica dada por la función Holder y su desempeño fue evaluado a través de la simulación de Monte Carlo considerando diferentes tamaños de muestra, valores paramétricos (π), y el exceso de proporciones cero (γ). Se concluyó que para las situaciones en (γ = 0,20) y (γ = 0,50) que el estimador propuesto presenta resultados prometedores basados en el margen de error especificado..

This present work aims to propose an estimator in order to estimate the probability of success of a binomial model that incorporates the extra-binomial variation generated by zero-inflated samples. The construction of this estimator was carried out with a theoretical basis given by the Holder function and its performance was evaluated through Monte Carlo simulation considering different sample sizes, parametric values (π), and excess of zero proportions (γ). It was concluded that for the situations in (γ = 0.20) and (γ = 0.50) that the proposed estimator presents promising results based on the specified margin of error.