Adyghe State University Scientists Showcase Innovative Research at Prestigious International Conference on Advanced Technology in China

A delegation from Adyghe State University, comprising Elena Kukva, Director of the Research Initiatives Department; Murad Aliyev, Head of the Laboratory of Mathematical Methods in Precision Agriculture and Biotechnology; and Aidamir Stash, Head of the Laboratory of Differential Equations and Algorithmic Optimization, participated in the Chinese-Russian-Mongolian-Belarusian International Conference on Advanced Research and Technology. The conference was held at Heilongjiang University in Harbin. This visit was part of ASU's ongoing collaboration with Heilongjiang University, formalized through a memorandum of understanding signed by both institutions in 2024.

The conference was conducted in conjunction with the Russian-Chinese Expo in Harbin, one of the primary platforms for fostering Russian-Chinese trade, economic cooperation, and tourism development.

The conference was held in conjunction with the Russian-Chinese Expo in Harbin, China, a prominent venue for fostering Russian-Chinese trade, economic cooperation, and tourism development.

Scientists from ASU actively participated in the plenary session and sectional discussions. During the sectional session, Marat Aliyev presented a paper titled "An Integrated Platform for Genotyping and High-Throughput Phenotyping in Plant Breeding Using Computer Vision and Genomic Prediction." In his presentation, he highlighted the significance and core objectives of Adyghe State University's strategic technology initiative, the "Digital Assistant for Breeders," which is being developed within the framework of the Priority 2030 program. 

A dedicated team of university researchers and students is developing a domestic digital platform aimed at automating various breeding processes. This platform encompasses tasks from phenotypic data collection to analysis, prediction, and digital mating selection. The proprietary algorithms and software facilitate the automatic calculation of key parameters and the classification of test objects based on images of seeds and leaves, according to predefined traits. Furthermore, the university intends to establish comprehensive breeding databases to support these initiatives.

The digital assistant is projected to accelerate the development of new hybrids by 30%, reduce reliance on imported seeds, and enhance agricultural productivity by optimizing breeding processes and fostering the creation of new crop varieties, including those resistant to climate change.

Foreign colleagues have positively evaluated the report presented by Adyghe State University. 

Additionally, the conference featured a working meeting focused on exploring avenues for international cooperation and partnerships in research, education, and industry collaboration, as well as outlining immediate prospects for future development.