Digital evolution and twin miracle of sugarcane breeding
Xiaoding Wang, Qibin Wu, Haitao Zeng, Yang Xu, Yang Xu, Xuechao Yang, Xuechao Yang, Xun Yi, Ibrahim Khalil, Youxiong Que
Abstract
Sugarcane, as an important economic crop, faces challenges such as long breeding cycles, low genetic improvement efficiency, and complex breeding operations. 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. 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. 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. This paper envisions an innovative smart sugarcane breeding system driven by artificial intelligence (AI), blockchain and digital twin (DT). It utilizes AI to process extensive genetic and phenotypic data, enabling precise prediction and optimization of sugarcane traits. Blockchain technology ensures the security and traceability of breeding data, adding an additional layer of reliability and integrity to the breeding process. DT, as a method of representing the real world in data, enables data to circulate in real-time among breeding-related workers in a lifelike form. The system integrates these advanced technologies within a Human-Cyber-Physical Systems framework, providing a more efficient, secure, and intelligent method for sugarcane breeding • We envision a smart sugarcane breeding system powered by AI, blockchain, and DT. • It uses AI to analyze genetic and phenotypic data for optimizing sugarcane traits. • Blockchain secures and traces breeding data, ensuring its reliability and integrity. • DT allows real-time circulation of lifelike data among workers in breeding. • It enhances breeding by advanced interaction between physical and digital realms.