文献类型： 外文期刊
作者： Wang, Xiaoding 1 ; Zeng, Haitao 1 ; Lin, Limei 1 ; Huang, Yanze 2 ; Lin, Hui 1 ; Que, Youxiong 3 ;
作者机构： 1.Fujian Normal Univ, Coll Comp & Cyber Secur, Fujian Prov Key Lab Network Secur & Cryptol, Fuzhou, Peoples R China
2.Fujian Univ Technol, Sch Comp Sci & Math, Fujian Prov Key Lab Big Data Min & Applicat, Fuzhou, Peoples R China
3.Fujian Agr & Forestry Univ, Key Lab Sugarcane Biol & Genet Breeding, Minist Agr & Rural Affairs, Fuzhou, Peoples R China
4.Chinese Acad Trop Agr Sci, Inst Trop Biosci & Biotechnol, Natl Key Lab Trop Crop Breeding, Haikou, Hainan, Peoples R China
关键词： crop breeding; deep learning; smart breeding; challenge; prospect
期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：5.6； 五年影响因子：6.8 ）
ISSN： 1664-462X
年卷期： 2023 年 14 卷
页码：
收录情况： SCI
摘要： Crop breeding is one of the main approaches to increase crop yield and improve crop quality. However, the breeding process faces challenges such as complex data, difficulties in data acquisition, and low prediction accuracy, resulting in low breeding efficiency and long cycle. Deep learning-based crop breeding is a strategy that applies deep learning techniques to improve and optimize the breeding process, leading to accelerated crop improvement, enhanced breeding efficiency, and the development of higher-yielding, more adaptive, and disease-resistant varieties for agricultural production. This perspective briefly discusses the mechanisms, key applications, and impact of deep learning in crop breeding. We also highlight the current challenges associated with this topic and provide insights into its future application prospects.
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