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Karslioglu, Betul,Cicek, Umran Ensoy,Kolsaric, Nuray,Candogan, Kezban Korean Society for Food Science of Animal Resource 2014 한국축산식품학회지 Vol.34 No.1
In this study, the effects of two different commercial starter culture mixes and processing methodologies (traditional and heat process) on the lipolytic changes of fermented sausages manufactured with turkey meat were evaluated during processing stages and storage. Free fatty acid (FFA) value increased with fermentation and during storage over 120 d in all fermented sausage groups produced with both processing methodologies (p<0.05). After drying stage, free fatty acid values of traditional style and heat processed fermented sausages were between 10.54-13.01% and 6.56-8.49%, respectively. Thiobarbituric acid (TBA) values of traditionally processed fermented sausages were between $0.220-0.450mg{\cdot}kg^{-1}$, and TBA values of heat processed fermented sausages were in a range of $0.405-0.795mg{\cdot}kg^{-1}$. Oleic and linoleic acids were predominant fatty acids in all fermented sausages. It was seen that fermented sausage groups produced with starter culture had lower TBA and FFA values in comparison with the control groups, and heat application inhibited the lipase enzyme activity and had an improving effect on lipid oxidation. As a result of these effects, heat processed fermented sausages had lower FFA and higher TBA values than the traditionally processed groups.
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Betül Karsloğlu,Ümran Ensoy Çiçek,Nuray Kolsar,Kezban Candoğan 한국축산식품학회 2014 한국축산식품학회지 Vol.34 No.1
In this study, the effects of two different commercial starter culture mixes and processing methodologies (traditional andheat process) on the lipolytic changes of fermented sausages manufactured with turkey meat were evaluated during process-ing stages and storage. Free fatty acid (FFA) value increased with fermentation and during storage over 120 d in all fer-mented sausage groups produced with both processing methodologies (p<0.05). After drying stage, free fatty acid values oftraditional style and heat processed fermented sausages were between 10.54-13.01% and 6.56-8.49%, respectively. Thiobar-bituric acid (TBA) values of traditionally processed fermented sausages were between 0.220-0.450 mg·kg-1, and TBA val-ues of heat processed fermented sausages were in a range of 0.405-0.795 mg·kg-1. Oleic and linoleic acids were predominantfatty acids in all fermented sausages. It was seen that fermented sausage groups produced with starter culture had lowerTBA and FFA values in comparison with the control groups, and heat application inhibited the lipase enzyme activity andhad an improving effect on lipid oxidation. As a result of these effects, heat processed fermented sausages had lower FFAand higher TBA values than the traditionally processed groups.
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Fahri Murat,İrfan Kaymaz,Abdullah Tahir Şensoy,İsmail H. Korkmaz 대한금속·재료학회 2023 METALS AND MATERIALS International Vol.29 No.1
Manufacturing high-quality and desired products from additive manufacturing necessitate careful adjustment of the processparameters. Various methods can be utilised to determine optimum process parameters, such as the Taguchi method, Designof Experiments (DoE). Rather than evaluating limited information obtained from statistical analysis of the experiments, optimisationmethods can help find the best possible combination for the process parameters. Therefore, an optimisation approachbased on Particle Swarm Optimization (PSO) was utilised to find the optimum process parameters. The most importantprocess parameters of Selective Laser Melting (SLM) such as laser power, layer thickness, scan speed, and build orientationwere selected as input parameters, and their effects on the tensile properties of the manufactured part were investigated to findout the optimal operating conditions for the SLM process. Since there is not any explicit mathematical expression relatingthese process parameters to the tensile strength, the Response Surface Method (RSM) was used to obtain a meta-model sothat it can be used as an objective function in the optimisation formulation. This approach enabled us to predict the optimumprocess parameters to maximise the tensile strength without conducting an excessive number of experiments. Moreover, themathematical model can also predict tensile strength corresponding to the parameter values that are not tested according tothe DoE chosen for such studies. Furthermore, it was also shown that the PSO outperforms the Genetic Algorithm (GA),which is widely employed to find out the optimum process parameters, in terms of less number of iteration.
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