Gene edition and AI promise a faster selection of crops

For millennia, the development of resilient cultures was based on pollination by nature or by man, which makes the process long and often expensive. Now, scientists from the Institute of Development Genetics and Biology (IGDB) of the Chinese Science Academy have redesigned the pollination process by developing a new system that uses genes to create flowers that can be easily pollinated by Robots controlled by AI working 24 hours a day.

The system, known as the genome modification with robots based on artificial intelligence (Geair), addresses a long -standing pollination obstacle: hybrid reproduction – which involves cross -pollination between different parental plants – produces more rigid and more rigid crops. However, it is based on slow and expensive manual work to manage pollination, because the built -in stigma (female organs) and complex floral structures in key crops such as tomatoes and soy have thwarted robotic automation.

These results were detailed in the newspaper Cell August 11.

“Human hands can sail in these flowers, but at a high price,” noted Professor Xu Cao, the corresponding author of the study.

In China alone, manual pollination eats more than 25% of the reproduction costs of fresh tomatoes. In particular, emasculation – where the male parties are eliminated to deactivate self -pollination – consists of 40% of this work. The narrowly sealed flowers of soybeans block natural cross pollination, forcing such manual reproduction with a high intensity of workforce that farmers cannot still access more than 30% reinforcement of hybrid vigor yield.

Inspired by the Green Revolution – when the cultures have been re -aged for the machines – The team was the development of “Cro -design – robot” to create crops well suited to robotic technology. As for culture design, they used CRISPR-CAS9, a precision gene editing tool, to target class B Mads-Box genes such as GLO2 in tomatoes, which regulate the development of flowers.

The result is plants which are both male-steric (eliminating the need for emasculation) and which have protruding stigma, which makes them easy to access the robots. “We have given flowers a youthful treatment for the machines,” said Professor Xu.

To complete the newly designed crops, the personalized gear robot is equipped with a computer vision based on depth learning which identifies the ready -made flowers and uses a precision arm to deposit pollen – corresponding to human efficiency while working 24/7.

Its versatility extends beyond cross pollination: it can help self-pollination (potentially replace bumblebees in controlled environments), collect pollen and even select sterile or fertile plants by identifying exposed stigma-obtaining costly DNA tests.

When associated with speed reproduction (acceleration of growth via extended light cycles) and the domestication of NOVO (quickly incorporating wild lines), GEAIR cuts reproductive calendars. The team has demonstrated this by developing new tomato lines with a richer flavor and better stress tolerance – and the approach also works for soy, pointing general agricultural applications.

“Geaire is not only a tool – it is a paradigm shift,” said Professor XU. “We rethink crops to unlock AI and robotics, and these technologies overeating our ability to create better cultures, more quickly.”

The study underlines a new era of agriculture: by factories and co -engineering machines, scientists open the way to a faster, cheaper and more sustainable cultures – a critical need as global demand for resilient food systems increases.

Above all, the strategy has proven transferable. The edition of Multiplex genes has successfully summarized the male-sterile and stigmatic exertred phenotype in soybeans, a legume on a global scale. This indicates the potential appliability of jay through a wide range of large crops hampered by bottlenecks of similar floral morphology in hybrid reproduction.