Digital evolution and twin miracle of sugarcane breeding

文献类型： 外文期刊

第一作者： Wang, Xiaoding

作者： Wang, Xiaoding;Wu, Qibin;Que, Youxiong;Wang, Xiaoding;Zeng, Haitao;Yang, Xu;Yang, Xuechao;Yi, Xun;Khalil, Ibrahim

作者机构：

关键词： Sugarcane breeding; Smart breeding; Artificial intelligence; Blockchain; Human-Cyber-Physical System; Digital twin

期刊名称：FIELD CROPS RESEARCH （ 影响因子：6.4； 五年影响因子：6.6 ）

ISSN： 0378-4290

年卷期： 2024 年 318 卷

页码：

收录情况： SCI

摘要： Context: Sugarcane, as an important economic crop, faces challenges such as long breeding cycles, low genetic improvement efficiency, and complex breeding operations. Method: In order to address these challenges and improve the economic benefits of sugarcane breeding, this paper proposes an innovative smart sugarcane breeding system driven by artificial intelligence (AI), blockchain and digital twin technologies. Results: The system integrates these technologies within a Human-Cyber-Physical System framework to offer a more efficient, secure, and smart strategy for sugarcane breeding. Firstly, AI processes extensive genetic and phenotypic data to enable precise prediction and optimization of sugarcane traits, resulting in shortened breeding cycles and enhanced efficiency and accuracy in selecting elite sugarcane varieties. Secondly, blockchain technology ensures the security and traceability of breeding data, enhancing the reliability and integrity of the breeding process. Thirdly, digital twin technology enables the real-time circulation of lifelike representations of real-world data among breeding-related workers. The system architecture consists of three layers: a physical layer for data collection, a cyber layer responsible for data analysis, storage and circulation managed by AI, blockchain and digital twin, and a human layer comprised of breeders and stakeholders. This multi-layered approach allows for sophisticated interaction and collaboration between the physical and digital realms, enhancing decision-making and breeding outcomes. Conclusion: Taken together, the system utilizes AI, blockchain, and digital twin technologies to support sugarcane breeding, offering a promising solution to overcome the limitations of traditional methods and establish a more sustainable and profitable sugarcane breeding system.

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