The detection of fungi contaminating maize grain and the effect of four plant extracts Azadirachta indica, Eucalyptus globulus Glycyrrhiza glabra and Zingiber officinale on the growth of A. flavus and its ability to produce AflatoxinB1. The results showed that the incidence of Aspergillus spp., was 52.75% of the isolated fungi, of which 29.50% was due to Aspergillus flavus, followed by Penicillium spp., with an incidence of 21.06%, and then Fusarium spp., with a rate of 18.13%. The percentage of toxin-producing A. flavus isolates reached 70.8% out of 24 isolates. The results showed the effect of alcoholic plant extracts at a concentration of 10 mg/ml on the fungal growth activity of A. flavus, the alcoholic extract of neem leaves was superior to the alcoholic extract with an inhibition rate of 92.79% than that of the control treatment, followed by ginger extract with an inhibition of 60.14%, then eucalyptus extract with a medium inhibition rate of 53.88%. While the licorice extract showed a weak inhibition rate of 17.77 %. The lowest inhibitory concentration for the growth of the fungus for neem extract was 24 mg/ml. While the lowest inhibitory concentration of ginger extract was 48 mg/ml, while eucalyptus and licorice extract did not achieve complete inhibition of fungal growth despite using a concentration higher than 48 mg/ml for both types. The results indicated that the neem plant extract inhibited the production of AFB1 toxin in YES media by 100% at a concentration of 12 mg/ml, followed by ginger extract at a concentration of 24 mg/ml, while the eucalyptus extract achieved a complete inhibition of AFB1 production at the last concentration (48 mg/ml). The extract of licorice plant did not show a complete inhibition of toxin production, as the highest percentage of inhibition was 39.98% at a concentration of 48 mg/ml.
The pollution producing from textile industries effluents is growing since the years, due to at discharged lots of it in water without treatment. The resulting effluent is colourful, highly toxic, and poses a significant environmental hazard. This problem can be solved by using enzymic biological treatment, where the Congo red dye was used with concentrations (100,200,300,500) mg /L, pH values (3,4,5,6,7,8), and variable temperatures (25,35,45)°C, the best removal of Congo red (CR) dye under optimum conditions for degradation was at concentration of 100 mg/L, at (pH 6, 25 °C) with efficiency of 99.85 % using the peroxidase enzyme extracted from red radish plant, while the removal percentage decreased when increase dye concentration
... Show MoreSaccharomyces Cerevisiae cells were immobilized in calcium alginate beads and activated charcoal for use in the
production of ethanol from batch fermentation of sugar beet waste. Treatment of the waste with NaOH to increase the
ability of lignocellulose material to hydrolysis by acid (2N H2SO4) to monosaccharide and disaccharide (mainly glucos).
The high reducing sugar concentration obtained was equal to 9.2gm/100ml (10Brix) after treatment. Fermentation
parameters, are (pH, glucose concentration (2.5-25 gm/100ml), immobilized agent concentration (2.5-25 gm/100ml)
were studied to find the optimum physiological condition. And the highest ethanol concentration obtained from the
fermentation in the presence of 20%(wt/v) ca
The present work concerns with simulating unsteady state equilibrium model for production of methyl oleate (biodiesel) from reaction of oleic acid with methanol using sulfuric acid as a catalyst in batch reactive distillation. MESHR equations of equilibrium model were solved using MATLAB (R2010a). The validity of simulation model was tested by comparing the simulation results with a data available in literature. UNIQUAC liquid phase activity coefficient model is the most appropriate model to describe the non-ideality of OLAC-MEOH-MEOL-H2O system. The chemical reactions rates results from EQ model indicating the rates are controlled by chemical kinetics. Several variables was studied such as molar ratio of methanol to oleic acid 4:1, 6:1
... Show MoreAggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req
... Show MoreBacteria could produce bacterial nanocellulose through a procedure steps: polymerization and crystallization, that occur in the cytoplasm of the bacteria, the residues of glucose polymerize to (β-1,4) lineal glucan chains that produced from bacterial cell extracellularly, these lineal glucan are converted to microfbrils, after that these microfbrils collected together to shape very pure three dimensional pored net. It could be obtained a pure cellulose that created by some M.O, from the one of the active producer organism like Acetic acid bacteria (AAB), that it is a gram -ve, motile and live in aerobic condition. The bacterial nanocellulose (BNC) have great consideration in many fields because of its flexible properties, features
... Show MoreBis-anthraquinones with a unique molecular backbone, (+)-2,2’-epicytoskyrin A (epi) and (+)-1,1′-bislunatin (bis), was produced by endophytic fungi Diaporthe sp GNBP-10 associated with Gambir plant (Uncaria gambier). Epi and bis possess robust antimicrobial activity toward various pathogens. This study focus on knowing the optimum condition of epi and bis production from Diaporthe sp GNBP-10. A series of culture media with various nutrient compositions was investigated in epi and bis production. The content of epi and bis was determined by measuring the area under the curve from TLC-densitometric (scanner) experiment. The linear regression analysis was then applied to obtain the results. The optimi
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