Neural networks in food industry

Abstract

In the present review we study the application of artificial neural networks in food industry, classifying the information obtained in different categories and the most used programs for its development. The prediction of parameter on operation such as drying, heat treatment, food classification and quality analysis are the main objective for RNA application. Multilayer with feedback propagation is the model most used being Matlab, the software par excellence for its development. Application of artificial neural network in food industry proved to be a useful tool to determine their quality through non-invasive, low-cost and real time processes.

Flavor quality evaluation system of Xinjiang milk knots by using SOM neural network and the fuzzy AHP

“…The relevant research results can provide a reference for further research on the origin of the difference between the two classes of milk knot samples. The results suggest that this model can be used as a guideline to automated assess the quality of the food and achieve the most important objective of providing a reference for the public and private sectors when making decisions on food quality management (Correa et al, 2018).…”

“…In addition to parameter prediction, the use of ANN is primarily used to classify food types with some of their characteristics, and a high percentage of correlation was obtained in most studies. A study conducted by Correa, Montero Castillo, and Martelo (2018) and Song, Perez‐Cueto, and Bredie (2018) evaluated the characteristics of the beer brand, which was returned the class is “good” or “bad” through the ANN. The implementation of the ANN allowed the quality of the sample to be distinguished at 100% efficiency in the prediction of the beverage under study.…”

Construction of a method for predicting the number of enterobacteria in milk using artifical neural networks

“…It was then necessary to choose software for forecasting. The principle of artificial neural networks has been selected, as it was established that they provide the best modeling and predicting approach [26,29]. ANNs consist of many interconnected processors, called neurons, which ensure a more accurate processing of numerous data simultaneously.…”

“…ANN is a mathematical model that simulates the structure and function of the biological nervous system; it has been discovered that it offers a better modeling and predicting approach in addressing the uncertainties and fluctuations that are often associated with microbial growth. Currently, a given approach that employs ANN is applied in economics, politics, technology, ecology, and other biological sciences [24][25][26]. In addition, the scientific literature cites more researchers from different countries that devise methods for predicting the behavior of microorganisms in raw materials and food products [24,25,27].…”

“…Most scientific papers [7,19,24,26] report results on predicting the number of certain types of microorganisms in milk, rather than groups of microorganisms. For instance, a group of conditionally pathogenic bacteria.…”