Abstract
In order to meet the increasing demand for food and beverage safety and quality, this study focused on the application of a back propagation (BP) neural network to determine the leaching rate of heavy metal in tea to improve the scientific health of tea drinking. The evaluation index and target expectations have been determined based on the extraction experiment of heavy metal Cd in tea soaking, with 3 evaluation index values taken as input layer parameters and the heavy metal extraction rate taken as output layer parameter. Then, employ the sample data standardized by min‐max linearization method to train and test the network model and get the satisfactory results, which showed that the constructed BP neural network expressed a fast convergence speed and the systematic error was as low as 0.0003509. Additionally, there was no significance between Cd leaching rate of experimental results and neural network model results by reliability testing with a correlation coefficient was .9895. These results revealed that the network model established possessed an outstanding training accuracy and generalization performance, which effectively reflected the extraction rate of heavy metal in tea soaking and improved the safety of tea drinking.
Highlights
Tea is one of the most popular nonalcoholic beverages in the world (Cabrera, Gimenez, & Lopez, 2003)
Just because the mapping of any nonlinear function from input layer to output layer can be obtained by choosing appropriate network structure and hidden layers, a BP neural network model is established to predict and analyze the leaching rate of heavy metal Cd in tea by using MATLAB 7.1 software combined with experimental analysis in this paper
The results revealed that the BP neural network model established can preferably approximate the regulation of leaching rate of heavy metal Cd for tea soaking by the training sample data
Summary
Tea is one of the most popular nonalcoholic beverages in the world (Cabrera, Gimenez, & Lopez, 2003). In order to better understand the extraction behavior of heavy metals in tea soaking, the leaching rate of heavy metal Cd was studied and simulated with a BP neural network model established on the basis of the experimental data.
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