RESEARCH TOPICS FOR XXXVIII CYCLE – Selection procedure for one position with grant on the specific topic "Quality control and safety of the Agri-Food chain: analysis of chemical / microbiological food quality, using innovative taylor-made IoT nanosensors. The setting-up of a data base and machine learning algorithms"
Title of the Research Topic: Quality control and safety of the Agri-Food chain: analysis of chemical / microbiological food quality, using innovative taylor-made IoT nanosensors. The setting-up of a data base and machine learning algorithms
1 (one) position with grant (DM 352/2022 Scholarship) co-funded by Kemin Industries, Inc.
Scientific Tutor: Prof. Andrea Pulvirenti - co-Tutor: Dr. Veronica Sberveglieri
Research topic:
The main objective of the research project will be to develop of new innovative green strategies through the use of IoT gas nano-sensors equipped with artificial intelligence algorithms for the digitization of food production processes improving environmental sustainability of the production chain.
The digitalization strategies in the production system are one of the main pillars of the Italian PNRR (Recovery and Resilience National Plan). Based on the aforementioned objective of the research project, the implementation of the produced gas sensors that will totally be part of an IoT system will contribute to create a connected food production system. Thanks to the machine learning algorithm, the implemented system will act as a rapid online alarm alert for manufacturing quality along the whole productive chain. The goal is to drastically reduce the material wastes as well as increasing the productivity, quality, standardization of the production and enhancing sustainability through a digitalized strategy.
Creation of a database concerning the volatile component of food matrices in standard conditions, under chemical and microbiological stress conditions and challenge tests. Using traditional microbiological and chemical techniques (GC-MS) and innovative ones (nanostructured gas sensors) in order to correlate the VOCs pulls between the different techniques.
During the PhD period, specific gas sensors will be developed for the online quality monitoring in the production chain. The fundamental aspects to investigate will be the selection of the materials of the sensitive element, type of deposition, optimization of the working temperature among other characteristics. Furthermore, the formation of a volatile compound consistent data base will be decisive to develop robust algorithm of machine learning to implement a fast alarm system.
During the doctoral period the person in charge will carry out the period in the company from a minimum of 6 to a maximum of 18 months and the period abroad from a minimum of 6 to a maximum of 12 months based on the results obtained.
Development of new innovative green strategies through the use of IoT gas nanosensors equipped with artificial intelligence algorithms for the digitization of production processes by improving environmental sustainability
The selected candidate will be involved in the following tasks:
- Publication of scientific papers;
- Supervision of master students in executing their research projects;
- Preparation and Submission of National and International Project;
- Set-up of the data-base;
- Integration of the sensors in the food chain.