Recent Papers

Aiming to increase the shelf life of food, researchers are moving toward new methodologies to maintain the quality of food quality as there is more spoilage of food due to several other reasons like humidity, temperature and variety other influences. As a result, efficient food spoilage tracking schemes are required to maintain the food quality levels. Machine learning (ML) has proven to be a useful technology for data analysis and modeling in a wide variety of domains, including food science and engineering. The use of ML models for the monitoring and prediction of food safety is growing in recent years Currently, several studies have reviewed ML applications on foodborne disease and deep learning applications on food. Monitoring potential food safety hazards along the entire food supply chain is important in order to guarantee the correct functioning of food safety management systems. A monitoring plan that describes what will be monitored and how this will be done is essential to the implementation of food safety monitoring Food safety prediction here is defined as a model-based process that seeks to predict future food safety events or outcomes by analyzing patterns from historical food safety and other related data.

Copyright © 2023 Sudheethi Vakicherla. This is an open access article distributed under the Creative Commons Attribution License.