Chinese Scientists Harness AI to Accelerate Precise Grape Breeding
Chinese scientists utilise AI to accelerate grape breeding, reducing the breeding cycle significantly. Research led by Zhou Yongfeng achieves an 85% prediction accuracy in grape breeding, quadrupling breeding efficiency. Published in Nature Genetics, the study focuses on analysing genomic data and developing innovative breeding strategies.
Typically, it takes years for a grape seed to grow and produce fruit, but with this new AI-driven approach, the breeding cycle has been drastically reduced.
Led by Zhou Yongfeng, a researcher from the Agricultural Genomics Institute at Shenzhen of the Chinese Academy of Agricultural Sciences, the research team has achieved an impressive 85 percent prediction accuracy in grape breeding, a substantial improvement compared to conventional methods. This innovative technique has the potential to quadruple breeding efficiency, paving the way for accelerated grape variety innovation.
Zhou Yongfeng expressed his optimism about the impact of this research, stating, "This research is expected to achieve precise breeding design for grapes, accelerate grape variety innovation, and provide a reference for breeding other perennial crops." The findings of this study were recently published in the prestigious journal Nature Genetics, highlighting the significance of this breakthrough in the field of agriculture.
To achieve precise grape breeding, the scientists delved into vast amounts of genomic and genetic data, focusing on grape design and breeding since 2015. By meticulously analysing over 400 representative grape varieties and investigating 29 agronomic traits, including cluster size, grape berry metabolite content, and fruit skin color, the team successfully constructed genetic and trait maps for grapes.
To further enhance their breeding strategies, the team integrated machine learning into their research, developing a predictive model that enables early predictions and selections based on scoring. This model empowers breeders to swiftly and accurately assess the genetic potential of numerous breeding materials, facilitating the selection of superior grape varieties at an early stage and streamlining the breeding process.
Zhou Yongfeng highlighted the practical implications of this AI-driven breeding technology, stating, "This breeding technology can predict the characteristics of grape seedlings at an early stage, allowing for the early removal of unsuitable seedlings and reducing unnecessary labor and investment costs." The research has already secured approval for six national invention patents and has applied for an international patent, underscoring its potential for widespread application and commercialisation.
Chinese scientists utilise AI to accelerate grape breeding, reducing the breeding cycle significantly.
Research led by Zhou Yongfeng achieves an 85% prediction accuracy in grape breeding, quadrupling breeding efficiency.
Published in Nature Genetics, the study focuses on analysing genomic data and developing innovative breeding strategies.
Source: XINHUA NET
