This study focuses on the determination of the chemical profile of 24 non-aged Brazilian artisanal sugarcane spirits (cachaça) samples through chromatographic quantification and chemometric treatment via principal component analysis (PCA) and Kohonen’s neural network. In total, forty-seven (47) chemical compounds were identified in the samples of non-aged artisanal cachaça, in addition to determining alcohol content, volatile acidity, and copper. For the PCA of the chemical compounds’ profile, it could be observed that the samples were grouped into seven groups. On the other hand, the variables’ bearings were grouped together, making it difficult to separate the components in relation to the sample groups and reducing the chances of obtaining all the necessary information. However, by using a Kohonen’s neural network, samples were grouped into eight groups. This tool proved to be more accurate in the groups’ formation. Among the chemical classes of the compounds observed, esters stood out, followed by alcohols, acids, aldehydes, ketones, phenol, and copper. The abundance of esters in these samples may suggest that these compounds would be part of the regional standard for cachaças produced in the region of Salinas, Minas Gerais.

This study aimed to evaluate the physicochemical parameters of polifloral honey marketed in Rio de Janeiro. In the period of 2007 and 2008 were analyzed, through official methods, 24 samples. The analysis of main component was performed to improve results obtained in the physicochemical characterization. The results revealed that 12 samples (50 %) were in agreement with Brazilian legislation, 10 samples (42 %) were reproved in one parameter; and 2 samples (8 %) were reproved in two or more quality parameters. The component analysis revealed that three principal components described 84,8 % of total variance of data. Also, 75 % of physicochemical parameters were adequately represented by the three principal components. However, no efficient grouping of samples was observed, by using parameters as origin and shelflife time, due to heterogeneous behavior of physicochemical parameters of polifloral honeys. Therefore, the principal component analysis did not allow a correct grouping of samples. Furthermore, physicochemical evaluation shows that the quality control procedures must be improved in order to guarantee the safety of honeys produced and acquired in the Rio de Janeiro markets Keywords: honey; physicochemical parameters; quality control; discriminant analysis RESUMO O objetivo do trabalho foi avaliar os parâmetros físico-químicos de méis silvestres comercializados no Rio de Janeiro. Foram analisadas 24 amostras, no período entre 2007 e 2008. A análise por componentes principais foi executada para aprimorar os resultados obtidos na caracterização físico-química dos méis silvestres. Os resultados da avaliação físico-química mostraram que 12 amostras (50 %) estavam em conformidade com a legislação vigente, 10 amostras (42 %) foram reprovadas em um parâmetro físico-químico e 2 amostras (8 %) foram reprovadas em 2 ou mais parâmetros de qualidade. A análise por componentes principais revelou que três componentes principais apresentaram 84,8 % da variância total dos dados. Além disso, 75 % dos parâmetros físico-químicos foram adequadamente apresentados pelos três componentes principais. Contudo, não foi possível observar o agrupamento eficiente das amostras, por regionalização ou prazo de validade, devido ao comportamento heterogêneo dos parâmetros físico-químicos dos méis silvestres. Portanto, a análise de componentes principais não permitiu a classificação dos méis silvestres. Além disso, a análise físico-química mostrou que as medidas de controle da qualidade devem ser aprimoradas com o objetivo de garantir a qualidade dos méis silvestres produzidos e comercializados no Rio de Janeiro.Palavras chave: mel; parâmetros físico-químicos; controle de qualidade; análise discriminante Recebido em: 12/03

Cachaça is a distilled spirit made from sugarcane, exclusively produced in Brazil, and appreciated worldwide. This paper seeks to evaluate the sensory characteristics of 24 nonaged artisanal cachaça samples from Salinas (Minas Gerais, Brazil) through descriptive analysis, as well as chemometrically treat the obtained data based on principal components analysis (PCA) and Kohonen's neural network. The attributes (23) were divided between aroma (11) and flavor (12). PCA does not show good differentiation of nonaged cachaça samples. On the other hand, by using Kohonen's neural network it was possible to group samples according to their aroma and flavor characteristics in 9 and 10 distinct groups, respectively. A reduced number of descriptors could be used to describe the flavor of cachaça samples (alcohol, acidic, sweet, bitter, citric, tar, and burning), as significant correlations (R > 0.70, p < .05) exist among them with fruity, bagasse, fermented sugarcane juice, and astringent descriptors. This diminution on descriptors numbers could be able to reduce the workload of the judging panel with no losses to the sample' sensory characterization. The use of Kohonen's network chemometric treatment for treat sensory data showed to be a better alternative that PCA approach in this study. Practical applications The growth in production and the appreciation of cachaça in the domestic and foreign markets have directed the production of the drink in Brazil with a focus on its quality and added value, seeking to obtain international recognition and increase exports. In this sense, the lexicon development and sensory characterization of samples from Salinas‐MG is very important to compare with commercial and artisanal samples from other regions in future studies. This work created a sensory profile for samples from this region, which despite its national and international popularity, does not exist yet. Finally, this is the first study that describes a lexicon development and sensory characterization of cachaças from Salinas‐MG and describes data with artificial neural networks, a potential approach for further studies.

Resumo: O objetivo desta pesquisa foi traçar o perfil pedagógico dos egressos-docentes dos Institutos Federais de Educação, Ciência e Tecnologia do Brasil (IFECT)-da área de Ensino dos Saberes Técnicos, do Programa de Pós-Graduação em Educação Agrícola (PPGEA), da Universidade Federal Rural do Rio de Janeiro (UFRRJ), por meio de suas pesquisas propostas ao Programa: temas e conteúdos temáticos, e caracterizar a área pelas escolhas desses professores. Para tais feitos, foi incrementada uma investigação em suas dissertações, em que, por intermédio das sínteses e das ideias centrais dos títulos, objetivos, sujeitos da pesquisa e resultados, se procurou estabelecer tais conjunturas. Como resultado, foi constatado que o egresso do PPGEA é um professor que emprega a metodologia de projetos como proposta pedagógica, de forma interdisciplinar, promovendo a contextualização e buscando renovação pedagógica por meio de práticas que favoreçam a construção do conhecimento. Quanto à caracterização da área, descreve-se pela intenção/implementação de metodologias de projetos, com o uso de instrumentos que possibilitem a abordagem dos eixos e dos temas de maneira interdisciplinar, no intuito de construir-se um conhecimento de forma contextualizada. Palavras-chave: Egressos. Mestrado em Educação Agrícola. Perfil pedagógico.