Nestlé experts develop new database to better identify more climate-resilient coffee plants. With climate change threatening coffee cultivation, Nestlé experts are exploring how advanced data science and artificial intelligence can be leveraged to help select and breed more climate-resilient plants.
While more than 120 species of coffee exist, around 70% of the world’s coffee production is arabica. However, arabica has a lower tolerance to rising temperatures and is more susceptible to disease than other coffee plants, such as Robusta. Additionally, climate change is reducing the amount of arable land it is possible to cultivate coffee on, and water shortages are significantly reducing yields.
To help ensure a sustainable future for coffee cultivation, and support farmer livelihoods, Nestlé plant scientists are exploring new, higher yielding arabica varieties with greater resistance to disease and drought.
As part of this work, the experts have developed a very high quality arabica reference genome using advanced data science methods. The reference genome, which is available in a publicly available digital database, makes it easier to analyze different traits of coffee varieties to identify specific traits such as better yield, coffee cherry size and greater resilience to disease or drought, as well as flavor or aroma characteristics.
Jeroen Dijkman, Head of Nestlé’s Institute of Agricultural Sciences, said: “In simple terms, our new reference is like a high-quality map of a big city. It will help us identify key genetic markers in the arabica genome that are responsible for specific traits in adult plants. This will help our plant scientists, and other experts to better identify, select and breed new and improved arabica coffee varieties.”
The reference genome represents a significant advancement in the field of plant research. The innovative work was recently published in Nature Genetics, a high impact scientific journal.
Patrick Descombes, Senior Expert in Genomics at Nestlé Research, and one of the paper’s co-authors, said: “While other public references for arabica do exist, the quality of our team’s work is extremely high. We used state-of-the-art genomics approaches – including long and short reads high throughput sequencing – to create an advanced, complete and continuous arabica reference.”
