Danang International Institute of Technology (DNIIT), The University of Danang organized the Toxin-Checker Science Conference 2020 and launched the FADOTO Project on analysis and quality control of seafood

17/12/2020

Recently, the Danang International Institute of Technology (DNIIT), The University of Danang (UD) has successfully organized the Toxin-Checker scientific conference 2020 on methods to ensure food hygiene and safety, and launched the FADOTO project "Research and application of rapid analysis methods combined with multidimensional data processing and machine learning in quality control of some seafood".

Panorama of the workshop 

Attending the workship were Assoc.Prof.Dr. Le Quang Son-Vice President of UD, Prof.Dr.Sc. Le Thanh Nhan-Director of DNIIT, Honorary Professor of UD, Assoc.Prof.Dr. Vo Trung Hung - Vice Rector of University of Technology and Education - UD, representatives of International Cooperation Department - UD and scientists, staff, and research experts in the fields related to projects ensuring food hygiene and safety.

Assoc.Prof.Dr. Le Quang Son

UD's Vice President speaks

Speaking at the workshop, Assoc.Prof.Dr. Le Quang Son - Vice President of UD congratulated the scientists of DNIIT for research and implementation many projects with  practical significance, contributing to the application to solve the urgent needs of the community, ensuring food hygiene and safety.

UD highly appreciated and acknowledged the efforts of DNIIT and groups of authors and always supports and facilitates the process of researching, implementing applications of topics and projects, bringing research science results to apply and serve the socio-economic development of Vietnam.

Prof.Dr.Sc. Le Thanh Nhan

Director of DNIIT speaks

The Toxin Checker project was chaired by DNIIT under the support and companionship of many partners such as University of Côte d'Azur (France), UD, National University of Laos (NUOL), Create Capital Vietnam Company.

This year's workshop with the theme "Machine learning algorithms applied in food safety" was an opportunity for domestic and foreign scientists and experts to exchange experiences, share and publish research results.

The presentation of congratulatory flowers

Scientific reports had been presented and discussed at the workshop, such as: "Identifying some characteristics to build machine learning model to identify poor quality food" (Dr. Pham Ngoc Hung- School Biotechnology and Food Technology, Hanoi University of Science and Technology); "Identifying fruit based on near infrared spectrum using neural networks" or "Analysis of Nano Vector networks for fast identification of fruit" (Research group-DNIIT, UD); “Generic IDE for the graphical design of learning models” (Dr. Chaka Kone – University of Côte d’Azur); “Low-cost VNA for advance sensing: Concept and application exemples” (Prof. Fabien Ferrero, University of Côte d’Azur), etc.

The reports are of scientific and practical significance

These were research projects and solutions to contribute to researching and applying new technologies to management practice to actively respond to food hygiene and safety issues in Vietnam.

On this occasion, DNIIT also launched the FADOTO project "Research and application of rapid analysis methods combined with multidimensional data processing and machine learning in quality control of some seafood", signed with partners involved include: DNIIT-UD, University of Science and Technology-Vietnam National University of Ho Chi Minh City, School of Biotechnology and Food Technology-Hanoi University of Sience and Technology.

Signing agreement of FADOTO project

This project was under the framework of the state-level topic to build a specific database for controlling some safety attributes of tuna, mackerel, and scad; develop fast analytical methods combined with multidimensional data processing and machine learning; develop software systems to control and warn the quality and safety of the above-mentioned seafood; at the same time, test the application in the supply chain.

Group photo session 

 

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