Fast-forwarding plant breeding with deep learning-based genomic prediction

文献类型： 外文期刊

第一作者： Gao, Shang

作者： Gao, Shang;Yu, Tingxi;Wang, Jiankang;Li, Huihui;Gao, Shang;Yu, Tingxi;Wang, Jiankang;Li, Huihui;Rasheed, Awais;Crossa, Jose;Hearne, Sarah

作者机构：

关键词： artificial intelligence; deep learning; genomic prediction; plant breeding

期刊名称：JOURNAL OF INTEGRATIVE PLANT BIOLOGY （ 影响因子：9.3； 五年影响因子：10.8 ）

ISSN： 1672-9072

年卷期： 2025 年 67 卷 7 期

页码：

收录情况： SCI

摘要： Deep learning-based genomic prediction (DL-based GP) has shown promising performance compared to traditional GP methods in plant breeding, particularly in handling large, complex multi-omics data sets. However, the effective development and widespread adoption of DL-based GP still face substantial challenges, including the need for large, high-quality data sets, inconsistencies in performance benchmarking, and the integration of environmental factors. Here, we summarize the key obstacles impeding the development of DL-based GP models and propose future developing directions, such as modular approaches, data augmentation, and advanced attention mechanisms.

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