Selection and optimization of extracellular lipase production using agro-industrial waste

The aim of this study was to isolate and select lipase-producing microorganisms originated from different substrates, as well as to optimize the production of microbial lipase by submerged fermentation under different nutrient conditions. Of the 40 microorganisms isolated, 39 showed a halo around the colonies and 4 were selected (Burkholderia, Bacillus sp., Penicillium lanosum and Corynebac glutamyl), where strains showing lipolytic halo Radius (R) / colony radius (r) ratio greater than 2.0 were selected. The results of submerged fermentation expressed as enzymatic activity revealed that the genera of microorganisms significantly influenced the enzymatic reaction, and lipase obtained from Burkholderia cepacia was the most promising, with activity of 0.0058 U.mL-1. It was also observed in the optimization step of lipase production that the sodium nitrate content (NaNO3) had a positive effect on enzyme production, and its increase was indicative of higher enzymatic activity. The addition of sources of organic nitrogen (corn steep liquor, p = 0.2398), carbon (soybean oil, p = 0.3379), magnesium MgSO4.7H2O (p = 0.4189) and potassium KH2PO4 (p = 0.8562) had no significant effects on the lipase production and could result in decreased production of extracellular lipases.Keywords: Burkholderia cepacia, hydrolytic enzymes, residue, submerged fermentationAfrican Journal of Biotechnology, Vol. 13(4), pp. 566-573, 22 January, 201

Conventional drying of cassava peel from starch industry waste

Cassava peels from starch industry waste are highly perishable. The drying process is an alternative way to provide a safe storage, free from the development of microorganisms, for the production of flour destined to human consumption. This study aimed at evaluating the kinetics and modeling of the cassava peels drying process, with the aid of a central composite rotational experimental design. Eleven tests were performed with different temperatures (53ºC, 55ºC, 60ºC, 65ºC and 67ºC) and air flow rates (0.0159 m3 kg-1 s-1, 0.0166 m3 kg-1 s-1, 0.0183 m3 kg-1 s-1, 0.0199 m3 kg-1 s-1 and 0.0206 m3 kg-1 s-1). The drying process was carried out in a conventional dryer tray and the drying times, instrumental color parameters (lightness - L*; a* and b* coordinates), titratable acidity and pH of the flour samples obtained after grinding the dehydrated cassava peels from each drying test were evaluated. The temperature increase resulted in a tendency to bleach the material, and a slight variation was observed for titratable acidity and pH in the samples. Temperature and air flow speed affected the drying kinetics, since their increase reduced the time for drying the cassava peels. The minimum drying time (420 min.) was reached when the dryer temperature was set to 67ºC and the air flow to 0.0183 m3 kg-1 s-1. This was considered the ideal setting, because it minimized the processing time, without altering the product features. The Crank model for plane geometry fitted well the experimental data obtained from the cassava peel drying process

Bayesian Regularizers of Artificial Neural Networks applied to the reliability forecast of internal combustion machines in the short-term

Predictive as well as preventive maintenance are tools of maintenance programs that aim to increase or maintain the life expectancy of an equipment through computational techniques and tools. Bearing in mind that the power generation industry has a high maintenance rate with machines and / or electric generators stopped, this research aims to develop a computational model for predicting the Reliability Key Performance Indicator (KPI) to identify how available the equipment will be in a time span of 22 days, for this the methodology to be used will be based on analyzes and tests of artificial neural network (ANN) architectures using the Bayesian Regularizers training algorithm, alternating the transfer functions in the layers hidden to find the best state of convergence and the minimum Root Mean Square Error (RMSE) value calculated between the real and simulated outputs. According to the results obtained by the training, validation and test steps, the algorithm presented a RMSE rate of 0.0000104202 and a 99.9% correlation between the real and simulated values, thus the model is able to identify which machine will have the greatest efficiency and less efficiency within the defined time span

Diagnóstico da produção de cachaça no município de Paracatu

O presente estudo teve por objetivo diagnosticar aspectos importantes da cadeia produtiva da cachaça na região do município de Paracatu, Minas Gerais, verificando-se os pontos possíveis de serem melhorados e a adequação do produto aos limites de qualidade estabelecidos pela legislação Brasileira, no intuito de informar para que os produtores comercializem seus produtos com qualidade competitiva, tanto no mercado nacional como no internacional. Para tal, realizaram-se visitas técnicas nos alambiques dos componentes da Associação dos Produtores de Cachaça da Região de Paracatu, com entrevistas e aplicação de um questionário, além de coleta de amostras de cachaça, da safra de 2011. Estas foram submetidas às análises dos parâmetros instrumentais de cor, grau alcoólico, extrato seco e acidez volátil. Em apenas 16,6% das propriedades a cachaça foi a principal atividade. Apesar da assistência técnica ser restrita a apenas 75% dos produtores, somente uma cachaça não atendeu ao teor alcóolico e outra obteve teor de extrato seco superior ao permitido pela legislação. Os produtores apesar de se atualizarem através de treinamentos carecem de apoio tecnológico para alavancarem e tornar competitivo este mercado

Cassava bagasse flour: byproduct utilization and comparison with cassava starch

The production of cassava (Manihot esculenta Crantz) starch generates cassava bagasse, which is the fibrous residue from the root. Due to its economic, physical, chemical, nutritional and technological importance, this study aimed at developing a flour from cassava bagasse, evaluating its properties and comparing them with those of cassava starch, in order to promote its use and provide information for industry processors and consumers. Analysis of proximate composition, total energy value, particle size, water activity, color, microscopy, water absorption index (WAI), water solubility index (WSI) and oil absorption index (OAI) were carried out. In relation to cassava starch, the bagasse flour showed much higher contents of total [63.95 g (100 g) -1], soluble [3.51 g (100 g) -1] and insoluble [56.84 g (100 g)-1] dietary fiber, as well as proteins [1.97 g (100 g) -1], ashes [1.81 g (100 g)-1] and lipids [2.35 g (100 g)-1]. The cassava bagasse flour presents low cost and desirable technological properties, such as WAI [6.73 g of gel (g dry mass)-1] and WSI (1.23%), being also an alternative raw material, with differentiated technological characteristics. It can possibly be used in paps, puddings, baby food and especially in diet or light food

Viabilidade econômica da implantação de um sistema de coleta e secagem

O objetivo deste trabalho foi estudar a viabilidade econômica da implantação de um sistema de coleta e secagem da polpa residual de lavagem de batatas na linha de processamento de batatas fritas, para ser utilizada em snacks fritos, visando o aproveitamento de resíduos agroindustriais, como novo ingrediente para a indústria de alimentos. O método payback foi estudado, este é um método de avaliação direto, no qual calcula-se o número de anos que decorrerão até que os fluxos de caixa acumulados igualem ao montante do investimento inicial. De acordo com os resultados obtidos, a empresa irá economizar 19,8 % de farinha de trigo mensalmente, com a substituição da farinha de trigo por polpa residual de lavagem da batata desidratada (PRLBD), no processamento de snacks fritos. O payback para a compra e implantação do sistema de secagem da PRLBD será pago em aproximadamente 16 meses. Este estudo demonstrou que o projeto é viável do ponto de vista econômico, além de contribuir na diminuição do impacto ambiental e com sustentabilidade da empresa, proporcionando um destino adequado para os resíduos agroindustriais

Using blockchain technology for implementation of an android graphics simulation application

The Blockchain technology can be used for many purposes on the web, the main one being the financial branch, having in mind the present article clearly presents the technology concepts behind Bitcoin called Blockchain and is shown throughout the work to implementation of a mobile application developed in the Android platform, where it makes use of blockchain to simulate the operation of its own, being a practical guide to blockchain, can be used to teach technology to lay visually, the tool uses principles such as hash function, chain of blocks, consensus algorithm among others that are linked to the technology of crypto coin

Computational meta-heuristics based on Machine Learning to optimize fuel consumption of vessels using diesel engines

With the expansion of means of river transportation, especially in the case of small and medium-sized vessels that make routes of greater distances, the cost of fuel, if not taken as an analysis criterion for a larger profit margin, is considered to be a primary factor , considering that the value of fuel specifically diesel to power internal combustion machines is high. Therefore, the use of tools that assist in decision-making becomes necessary, as is the case of the present research, which aims to contribute with a computational model of prediction and optimization of the best speed to decrease the fuel cost considering the characteristics of the SCANIA 315 machine. propulsion model, of a vessel from the river port of Manaus that carries out river transportation to several municipalities in Amazonas. According to the results of the simulations, the best training algorithm of the Artificial Neural Network (ANN) was the BFGS Quasi-Newton considering the characteristics of the engine for optimization with Genetic Algorithm (AG)