Modeling the Effects of Citrus sinensis Essential Oil and Nitrite on Growth Probability of Clostridium botulinum Type A in Broth Media

Background: Nitrite is a multifunctional food additive used for control of toxigenic Clostridium botulinum in foodstuffs. However, there is a growing concern about the carcinogenic and teratogenic effects of nitrite. The present research was done to assess the effects of Citrus sinensis essential oil and nitrite on the growth probability of C. botulinum type A using predictive mathematical modeling technique in broth media. Methods: Essential oil of C. sinensis was collected using Clevenger. Multifactorial design included diverse C. sinensis, nitrite and NaCl concentrations and also different pH ranges and storage temperatures were arranged in BHI broth medium. C. botulinum type A strains were then inoculated and their growth model was analyzed. Results: The synergistic inhibitory effects of nitrite and C. sinensis were significant (P<0.05). C. sinensis (0.045%) and nitrite (20 ppm) strongly decreased the growth of C. botulinum (log P%= - 2.2 versus log P%= 1.15). Decreasing temperature up to 25°C significantly affected growth probability of C. botulinum (P<0.05). Increasing NaCl concentration up to 3% did not cause any significant differences in the growth of C. botulinum (P= 0.062). Bacterial growth in broth media was completely inhibited at pH 5.5 and also in media contained C. sinensis (0.045%) and nitrite (60 ppm) at pH 6.5 (log P%= -3.76). Conclusion: Using certain concentrations of C. sinensis essential oil with other suboptimal factors (pH and temperature) and nitrite can control the growth of C. botulinum in broth media.

Determinants of Micro and Small Enterprises Growth in Selected Towns of West Shoa Zone, Oromia Regional State, Ethiopia

MSEs have an important contribution to economic growth and employment creation in Ethiopia. However, due to different bottlenecks that hinder the growth, MSEs found in these three towns were not grown as it was expected. Therefore, this study aimed at identifying the major determinants of MSEs growth in West Shoa Zone, Oromia region, Ethiopia. In the study, both qualitative and quantitative research methods were used. Primary data was obtained using questionnaires. Stratified sampling was used to select proportional number of samples from the study area. The study used Chi-square and logistic regression to measure the association and determine growth probability of MSEs, respectively. The result of the study revealed, Entrepreneurial competency, managerial skills, market access, innovation, high initial investment size, access to finance and manufacturing sector variables were identified as a major determinant of growth of the MSEs in the study area. MSEs Owner/manager characteristics such as gender and age were found not to have an influence on the growth of the enterprises as the descriptive result showed. The probability of growth of MSEs were positively influenced by entrepreneurship competency, management skill, market access, initial investment size, and sector in manufacturing; however, getting access to finance and engaging in innovation activity have negative impact on the growth probability of MSEs based on the binary logit model result. The variables included in the model explain about 73.38% of the influences on the MSEs Growth so as, the model is fit. The study recommends that proper understanding of these factors constitutes an essential starting point and important for the Owner/manager of MSEs, government and non-governmental organizations to formulate policies and strategies in order to reduce unemployment, poverty and income inequality thereby promote MSEs and their growth in the country and particularly in West Shoa Zone.

Accumulation of liquid hydrocarbons during cobalt-catalyzed Fischer–Tropsch synthesis - influence of activity and chain growth probability

It may take over one year in order to fill FT catalyst pores, depending on activity and chain growth probability.

Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety

The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (Pt), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety.

Kinetic aspects of chain growth in Fischer–Tropsch synthesis

Microkinetics simulations are used to investigate the elementary reaction steps that control chain growth in the Fischer–Tropsch reaction. Chain growth in the FT reaction on stepped Ru surfaces proceeds via coupling of CH and CR surface intermediates. Essential to the growth mechanism are C–H dehydrogenation and C hydrogenation steps, whose kinetic consequences have been examined by formulating two novel kinetic concepts, the degree of chain-growth probability control and the thermodynamic degree of chain-growth probability control. For Ru the CO conversion rate is controlled by the removal of O atoms from the catalytic surface. The temperature of maximum CO conversion rate is higher than the temperature to obtain maximum chain-growth probability. Both maxima are determined by Sabatier behavior, but the steps that control chain-growth probability are different from those that control the overall rate. Below the optimum for obtaining long hydrocarbon chains, the reaction is limited by the high total surface coverage: in the absence of sufficient vacancies the CHCHR → CCHR + H reaction is slowed down. Beyond the optimum in chain-growth probability, CHCR + H → CHCHR and OH + H → H2O limit the chain-growth process. The thermodynamic degree of chain-growth probability control emphasizes the critical role of the H and free-site coverage and shows that at high temperature, chain depolymerization contributes to the decreased chain-growth probability. That is to say, during the FT reaction chain growth is much faster than chain depolymerization, which ensures high chain-growth probability. The chain-growth rate is also fast compared to chain-growth termination and the steps that control the overall CO conversion rate, which are O removal steps for Ru.

Development of kinetic model for CO hydrogenation reaction over supported Fe–Co–Mn catalyst

After determining CO consumption rate, the production rate of methane, paraffin, olefin and chain growth probability factor (α) was derived and described.