Editorial: Applications of artificial intelligence, machine learning, and deep learning in plant breeding

In recent years, the field of plant breeding has witnessed a paradigm shift driven by advancements in artificial intelligence (AI) technologies, including machine learning (ML) and deep learning (DL) technologies. These cutting-edge techniques have transformed our understanding of plant biology. From decoding the intricate molecular mechanisms of plant defense to automating disease detection and optimizing nutrient levels, AI is reshaping the landscape of plant breeding.

Авторы
Ефтекхари М.1 , Ма Ч.2, 3 , Орлов Ю.Л. 4, 5, 6
Издательство
Frontiers Media S.A.
Язык
Английский
Страницы
1420938
Статус
Опубликовано
Подразделение
Аграрно-технологический Институт РУДН
Том
15
Год
2024
Организации
  • 1 Department of Horticultural Sciences, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
  • 2 State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Xianyang, Shaanxi, China
  • 3 Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Xianyang, Shaanxi, China
  • 4 Systems Biology Department, Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), Novosibirsk, Russia
  • 5 Agrarian and Technological Institute, Patrice Lumumba Peoples’ Friendship University of Russia, Moscow, Russia
  • 6 Chair of Information and Internet Technologies, Institute of Biodesign and Complex System Modelling, Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), Moscow, Russia
Ключевые слова
artificial intelligence; machine learning; deep learning; plant breeding
Дата создания
02.12.2024
Дата изменения
02.12.2024
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/157754/
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