Longhi Daniel Angelo, Martins Wiaslan Figueiredo, da Silva Nathália Buss, Carciofi Bruno Augusto Mattar, de Aragão Gláucia Maria Falcão, Laurindo João Borges
Federal University of Santa Catarina, Department of Chemical Engineering and Food Engineering, Center of Technology, Florianópolis, SC 88040-901, Brazil; Federal University of Paraná, Food Engineering, Campus Jandaia do Sul, Jandaia do Sul, PR 86900-000, Brazil.
Federal University of Santa Catarina, Department of Chemical Engineering and Food Engineering, Center of Technology, Florianópolis, SC 88040-901, Brazil.
Int J Food Microbiol. 2017 Jan 2;240:57-62. doi: 10.1016/j.ijfoodmicro.2016.06.042. Epub 2016 Jul 1.
In predictive microbiology, the model parameters have been estimated using the sequential two-step modeling (TSM) approach, in which primary models are fitted to the microbial growth data, and then secondary models are fitted to the primary model parameters to represent their dependence with the environmental variables (e.g., temperature). The Optimal Experimental Design (OED) approach allows reducing the experimental workload and costs, and the improvement of model identifiability because primary and secondary models are fitted simultaneously from non-isothermal data. Lactobacillus viridescens was selected to this study because it is a lactic acid bacterium of great interest to meat products preservation. The objectives of this study were to estimate the growth parameters of L. viridescens in culture medium from TSM and OED approaches and to evaluate both the number of experimental data and the time needed in each approach and the confidence intervals of the model parameters. Experimental data for estimating the model parameters with TSM approach were obtained at six temperatures (total experimental time of 3540h and 196 experimental data of microbial growth). Data for OED approach were obtained from four optimal non-isothermal profiles (total experimental time of 588h and 60 experimental data of microbial growth), two profiles with increasing temperatures (IT) and two with decreasing temperatures (DT). The Baranyi and Roberts primary model and the square root secondary model were used to describe the microbial growth, in which the parameters b and T (±95% confidence interval) were estimated from the experimental data. The parameters obtained from TSM approach were b=0.0290 (±0.0020) [1/(h°C)] and T=-1.33 (±1.26) [°C], with R=0.986 and RMSE=0.581, and the parameters obtained with the OED approach were b=0.0316 (±0.0013) [1/(h°C)] and T=-0.24 (±0.55) [°C], with R=0.990 and RMSE=0.436. The parameters obtained from OED approach presented smaller confidence intervals and best statistical indexes than those from TSM approach. Besides, less experimental data and time were needed to estimate the model parameters with OED than TSM. Furthermore, the OED model parameters were validated with non-isothermal experimental data with great accuracy. In this way, OED approach is feasible and is a very useful tool to improve the prediction of microbial growth under non-isothermal condition.
在预测微生物学中,模型参数已通过序贯两步建模(TSM)方法进行估计。在该方法中,首先将初级模型拟合到微生物生长数据,然后将次级模型拟合到初级模型参数,以表示它们与环境变量(如温度)的相关性。最优实验设计(OED)方法能够减少实验工作量和成本,并提高模型的可识别性,因为初级和次级模型是从非等温数据中同时拟合得到的。选择绿色乳杆菌进行本研究,是因为它是一种对肉类产品保鲜具有重要意义的乳酸菌。本研究的目的是通过TSM和OED方法估计绿色乳杆菌在培养基中的生长参数,并评估每种方法所需的实验数据数量、时间以及模型参数的置信区间。采用TSM方法估计模型参数的实验数据是在六个温度下获得的(总实验时间为3540小时,有196个微生物生长实验数据)。OED方法的数据来自四个最优非等温曲线(总实验时间为588小时,有60个微生物生长实验数据),两个温度上升曲线(IT)和两个温度下降曲线(DT)。使用Baranyi和Roberts初级模型以及平方根次级模型来描述微生物生长,其中参数b和T(±95%置信区间)是根据实验数据估计得到的。通过TSM方法得到的参数为b = 0.0290(±0.0020)[1/(h°C)]和T = -1.33(±1.2)[°C],R = 0.986,RMSE = 0.581;通过OED方法得到的参数为b = 0.0316(±0.0013)[1/(h°C)]和T = -0.24(±)[°C],R = 0.990,RMSE = 0.436。与TSM方法相比,OED方法得到的参数具有更小的置信区间和更好的统计指标。此外,使用OED估计模型参数所需的实验数据和时间比TSM更少。此外,OED模型参数通过非等温实验数据进行了高精度验证。因此,OED方法是可行的,并且是改善非等温条件下微生物生长预测的非常有用的工具。