Seed World

We Don’t Have a Time Machine to Breed for a Warming World — or do we?

The other day I was flipping channels and came upon the movie Back to the Future Part II, released in 1989. In the movie, Michael J. Fox’s character travels forward to the year 2015 and gets to see how people live in “the future”. 

Of course, the 2015 we see in the movie looks a lot different from the 2015 we all experienced for real, which is already eight years ago. Can you believe it? We still don’t have flying cars and, unfortunately, still cannot predict the weather with perfect accuracy as in the movie.

But imagine if we didn’t need to. Imagine having a technology that could tell you how plants would respond to any future climate conditions.

Let me digress for a moment. 

Where I live, in the center of France, we used to have seven to eight cycles of aphids every year. However, by 2030, according to researchers, we will have around 15 cycles.

Why? A warming climate that allows these insect pests to mate more often. Hence, more generations of aphids who love the increasingly warmer climate they live in.

The solution to this problem may once have been insecticides, but with more awareness around toxicology and sustainability, many of these insecticide products are no longer an option for growers. 

The solution? Plant breeding, specifically breeding for tolerance to threats like pest pressure and the unpredictable weather we’re going to increasingly encounter.

With regards to the latter, heat and drought are additional challenges growers face. It’s a global challenge with each crop facing a different environmental factor. For orchards, late frosts pose a major threat. Fruit trees will flower later when frost becomes a greater risk. Wheat will see delays in its vegetative growth.

Thankfully, stress tolerance is a known and well-studied breeding goal. There’s a big difference between tolerance and resistance: Resistance is usually not sustainable long-term. It breaks down. Tolerance, on the other hand, is a long-term solution, allowing the plant to survive in its environment.

Anne Buchwalder

Breeding for tolerance requires a shift in thinking. Plants aren’t being created to be simply immune to threats, but to be resilient in the face of them. Most studies looking at tolerance to biotic stresses define tolerance as the ‘reduction in the severity of the symptoms induced by pathogen infection.’ Tolerance to abiotic stresses follows a similar line of thinking — plants will still suffer some damage as a result of extreme heat, for example, but that damage will be less severe.

Of course, breeders need tools that allow them to do this quickly and cost-effectively. That brings me back to my original question — what if we had a technology that predicts the performance of crosses in these changing environments and takes out the guesswork? 

Machine learning-based technologies are allowing this. I’ve had the pleasure of being part of a team that designs breeding tools based on a technology that can literally halve the breeding cycle and create the stress-tolerant crops of the future.

Using machine learning tools like this can not only help breeders identify ten times more candidates for their commercial pipeline, but help them learn the performance of all possible crosses across all expected environments, and increase genetic gain.

This helps breeders predict the best performers, both for today and future climates. Even the ones we haven’t observed yet and which can therefore not be field trialed. Breeders can reduce time to market by three to six years — meaning they can offer these stress-tolerant crops in a far timelier fashion.

I said at the beginning of this column that it would be great to have a machine that could tell you how plants would respond to future climatic conditions.

The world has access to that technology and is increasingly making use of it to help growers make food for the future and breed forward. Stay tuned to this space as we delve deeper into how machine learning can help us adapt by staying a few steps ahead of a changing climate.