9 resultados para MIS

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Neste trabalho, objetivou-se analisar isotopicamente méis comercializados nas regiões Sul e Sudeste do Brasil, para a detecção de fraude. Foram colhidas amostras comerciais com registro no Serviço de Inspeção Federal, Estadual ou Municipal. As amostras foram submetidas à combustão no Analisador Elementar EA 1108 CHN e analisadas no espectrômetro de massas de razão isotópica DELTA-S (Finningan Mat). Os valores isotópicos (δ13C) dos méis in natura foram comparados aos de suas respectivas proteínas (padrão interno). Foram consideradas adulteradas as amostras cuja diferença entre o valor isotópico da proteína e do mel foi igual ou inferior a -1 . As amostras consideradas adulteradas pela análise isotópica foram submetidas a testes químicos qualitativos que não foram capazes de indicar adulteração para algumas delas. Das 61 amostras analisadas, 18,0% encontram-se adulteradas, sendo 11,5% na Região Sudeste e 6,5% na Região Sul. Ao contrário dos testes químicos, a análise isotópica mostrou-se eficaz em identificar e quantificar a adulteração de méis comerciais.

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The honey of Melipona fasciculata is few known in terms of composition, and therefore generally associated with the characteristics of the honey of Apis mellifera. This study contributes to the knowledge of the physico-chemical characteristics of honey of M. fasciculata of the municipalities of Barra do Corda, Jenipapo dos Vieiras, Fernando Falcão, Carolina and Riachão, in cerrado region from Maranhão. The parameters studied were: moisture, pH, acidity, reducing sugars, apparent sucrose, hydroxymethylfurfural, diastase activity, insoluble solids, ash and color. Some of the observed patterns may conform to the established for A. mellifera, but others must be accompanied by a specific legislation.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This study aimed to produce beer, using different botanical origins of honeys (orange, eucalyptus and wild), as malt adjuncts, and their Physical-chemical and sensorial characterizations. The production was made with malt, water, hops and honey. All musts were adjusted to 12 Brix, and the concentration of honey in the formulation was 45% (based on the extract), except for the control (0%). The physical and chemical analysis were performed on malt (extract content), honey (pH, free acidity, lactonic acidity, total acidity, color, turbidity, extract content, moisture content, reducing sugar, total reducing sugar and sucrose) in wort (content extract, pH, color, turbidity, fermentability ,bitterness and total acidity) and beer apparent extract, apparent fermentability, real extract, real fermentability, alcohol content, pH, total acidity, total foam, foam density , bitterness, carbon dioxide, color and turbidity). Sensory analysis was performed by nine-points hedonic scale testing. The attributes evaluated were appearance, aroma, flavor and overall. The results were submitted to ANOVA and means compared by Tukey testing at a 5% of probability. Beer with honey as adjuncts’ had high fermentability and low content of fat, compared to the pure malt beer. The addition of honey as an adjunct did not affect the majority of the physical-chemical parameters, except for turbidity, whereas beer with honey showed the highest value for this feature, in addition, it has also presented their biterness differences the values for beer with honey were lower. The different types of honeys did not affect the acceptability of beer, however, the beer with honey showed greater acceptance between beer with malt and honey

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The present study had as objective contribute to the characterization of beekeeping in the Pernambuco State and evaluate the physical-chemical quality of the honeys produced in the region. For this, was applied a directed formulary to the representative organ of beekeeping class aboutthe productives and technicals aspects of beekeepers. Was obtained 14 samples of honey by Apis mellifera africanized, stored in sterile plastic vessels was sent to the Beekeeping Products Quality Control Laboratory (CEA-UNITAU). Was observed that the most of beekeepers have of 50 to 100 hives (57,14%), 28,57% of 100 to 200 hives and 14,28% more than 500 hives, being that 85,71% produce 30 to 50 kg honey/hives/flowering. All use the standard hive Langstroth and 85,71% obtain their swarm by capture. About the physical-chemical quality of the honey, was observed that moisture content varied from 18,2% to 22,0%, with mean value of 19,80±1,11; the water activity varied from 0,70 to 0,84 aw, with mean value of 0,79±0,05 aw; the total acidity was 24,91±8,99 meq/kg and the average index of hydroxymethylfurfural was 16,32±17,88 meq/kg. The results obtained are according to the quality limits established by the brazilian legislation, excepted the water activity that exceeded the maximum limit of 0,65 aw. The datasobtained in this paper shows the development of beekeeping in Pernambuco State and the honey presents nice quality.

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The objective of this work was to typify, through physicochemical parameters, honey from Campos do Jordão’s microrregion, and verify how samples are grouped in accordance with the climatic production seasonality (summer and winter). It were assessed 30 samples of honey from beekeepers located in the cities of Monteiro Lobato, Campos do Jordão, Santo Antonio do Pinhal e São Bento do Sapucaí-SP, regarding both periods of honey production (November to February; July to September, during 2007 and 2008; n = 30). Samples were submitted to physicochemical analysis of total acidity, pH, humidity, water activity, density, aminoacids, ashes, color and electrical conductivity, identifying physicochemical standards of honey samples from both periods of production. Next, we carried out a cluster analysis of data using k-means algorithm, which grouped the samples into two classes (summer and winter). Thus, there was a supervised training of an Artificial Neural Network (ANN) using backpropagation algorithm. According to the analysis, the knowledge gained through the ANN classified the samples with 80% accuracy. It was observed that the ANNs have proved an effective tool to group samples of honey of the region of Campos do Jordao according to their physicochemical characteristics, depending on the different production periods.