Marijuana breeders may be able to design new strains and speed up their growing cycles by utilizing artificial intelligence (AI), a new study suggests.
Researchers found that by feeding genetic markers, growth measurements, environmental data and chemical assays into AI models, breeders could simulate thousands of potential crosses and stimulate “speed breeding” through machine learning before ever planting a seed.
The authors argue this approach could cut traditional breeding cycles, which currently last between six to eight years, down to a fraction of that time, while also improving consistency—a perennial challenge that commercial cannabis growers grapple with.
“Machine learning allows for iterative simulations of breeding outcomes…while ensuring chemical consistency,” the authors concluded.
The paper also highlights the role of metabolomics, an emerging field that catalogs the vast array of chemicals produced by living organisms.
“AI systems correlate these datasets to predict how specific genetic combinations will influence chemical composition and growth traits, enabling precise selection of parental strains for crossbreeding,” they observed.
Read the full article at Marijuana Moment
