Produção de glicosiltransferase de Klebsiella sp 18 e otimização do processo de conversão de sacarose em isomaltulose

Orientador: Helia Harumi SatoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosMestrad

Isomaltulose production using free and immobilized Serratia plymuthica cells

Isomaltulose is a low cariogenic sweetener used as a substitute for sucrose in the food industry. In this study, isomaltulose production by Serratia plymuthica ATCC 15928 was performed using free and immobilized cells. Response Surface Methodology was employed to evaluate the influence of temperature, wet cell mass concentration and sucrose concentration during the conversion of sucrose into isomaltulose by free cells. After 2 h of reaction time in shake flasks, a high production of isomaltulose (85.23%) was obtained with a temperature of 25ºC, wet cell mass of 20% (w/v) and sucrose solution of 25% (w/v). The free cells were reused during seven successive batches and resulted in efficient isomaltulose conversion between 83.74 and 67.37%. The production of isomaltulose by immobilized cells in calcium alginate was studied in a packed bed bioreactor during seven days in a continuous process. A conversion yield of sucrose into isomaltulose between 81.26 and 70.89% was obtained, using immobilized cells in calcium alginate Synth® 2% (w/v), sucrose solution of 35% (w/v), wet cell mass of 30% (w/v) and temperature of 25ºC. The conversion of sucrose into isomaltulose remained high using free cells and using immobilized cells in calcium alginate during the period of execution of the experiments.Key words: Isomaltulose, glucosyltransferase, free cells, immobilized cells, Serratia plymuthica

Aproveitamento tecnológico da fruta do conde, atemóia e graviola para elaboração de geleias : composição química e sensorial

Fruta do conde, atemóia e graviola são frutos tropicais muito apreciados por seu sabor agradável, aromático e marcante. Neste trabalho, constatou-se que as polpas de frutas frescas tiveram altos valores nutricionais, uma vez que estas continham níveis significativos de carboidratos. Os resultados para a análise da composição química das polpas de frutas frescas, obtidos para fruta do conde, atemóia e graviola foram respectivamente: umidade (79,65, 77,06 e 85,30 g.100 g-1), carboidratos (20,52, 22,01 e 13,83 g.100 g-1), açúcares totais (19,57, 21,93 e 10,12 g.100 g-1) e sólidos solúveis (22,00 25,10 e 12,83 ºBrix). Com o objetivo de processar as frutas maduras para agregar valor a essas frutas, geleias foram desenvolvidas. Os resultados da análise da composição química das geleias de pinha, atemóia e graviola foram respectivamente: umidade (26,23, 27,94 e 21,52 g.100 g-1), carboidratos (73,05, 71,44 e 77,83 g.100 g-1), pH (3,41, 3,34 e 3,41) e sólidos solúveis (63,00, 65,00 e 68,60 ºBrix). As geleias foram submetidas à Análise Descritiva Quantitativa. Um total de 12 provadores treinados avaliaram os atributos sabor, consistência, aparência e aceitabilidade global das geleias em uma escala hedônica de 9 pontos. Baseado na avaliação sensorial, as geleias apresentaram uma boa aceitação global e a geleia de atemóia foi à preferida dos provadores.Sugar apple, atemoya and soursop are tropical fruits very prized for their pleasant, aromatic and distinctive flavor. In this work, the fresh fruits pulps had high nutritional values, since they contain significant levels of carbohydrates. The results for the analysis of chemical composition of the fresh fruits pulps obtained for sugar apple, atemoya and soursop were respectively: moisture (79.65, 77.06 and 85.30 g.100 g-1), carbohydrates (20.52, 22.01 and 13.83 g.100 g-1), total sugars (19.57, 21.93 and 10.12 g.100 g-1) and soluble solids (22.00, 25.10 and 12.83 ºBrix). With the aim of processing the pulps of ripe fruits to add value to these fruits, jams have been developed. The results for the chemical composition analysis of sugar apple, atemoya and soursop jams were respectively: moisture (26.23, 27.94 and 21.52 g.100 g-1), carbohydrates (73.05, 71.44 and 77.83 g.100 g-1), pH (3.41, 3.34 and 3.41) and soluble solids (63.00, 65.00 and 68.60 ºBrix). The jams were subjected to Quantitative Descriptive Analysis. A total of 12 trained panelists evaluated the attributes flavor, consistency, appearance and overall acceptability of the jams on a 9-point hedonic scale. Based on sensory evaluation, jams presented a good overall acceptability and atemoya jam was the most preferred by the panelists

Microbiological quality of minimally processed vegetables commercialized in Brasilia, DF, Brazil

This study evaluated the microbiological quality of minimally processed vegetables commercialized in the city of Brasilia, DF, Brazil. A total of 32 samples of different vegetables were purchased from 10 supermarkets. In most samples (78.1%) the populations of psychrotrophic bacteria had a high count ranging from 106 to 108 CFU/g. Thermotolerant coliforms were found in all samples, with populations higher than 102 MPN/g in 15 samples (46.9%). After molecular analyses, E. coli was identified in 16 samples (50.0%) and Salmonella spp. in 4 samples (12.5%). S. aureus was found in 14 samples (43.8%), with counts higher than 103 CFU/g in 4 samples (12.5%). The results obtained in this study showed that 16 samples (50%) were unfit for consumption according to Brazilian legislation. These results indicated the need of adoption of better hygienic practices in the production of minimally processed vegetables to improve quality and microbiological safety

Concentration reducing system of microorganisms in air through capture and sterilization - a product for health, for handling and for infection control of Covid-19

Muitas ações estão baseadas na proteção individual em relação ao agente biológico ou isolamento do infectados. Historicamente a ventilação reduz a contaminação de novas pessoas e promove a recuperação de infectados. A ventilação é vista como medida de controle coletivo, que é protagonista na mitigação de risco. Como exemplo, o uso de máscaras reduz a exposição de uma determinada região, mas a concentração aumenta, ao longo do tempo, em todas as superfícies expostas a contaminação, inclusive na máscara. Dessa forma, a ideia é reduzir a concentração do meio contaminado e, consequentemente, a exposição do corpo humano como um todo, aumentando a biossegurança para com o COVID-19

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost