A technique that boosts resilience in production
By the time crops have landed on kitchen tables, or become infused in cosmetics bottles or woven through shirts, they will have changed hands throughout the supply chain countless times, Saskia Henn reports.
Once crops are ready to leave the soil, they begin their journey from the harvester to grain silos, marketers and processing and packaging facilities, with each step along the way bumping up the final price and contributing to emissions.
The common use of pesticides occasionally adds an extra step to the process as well. Some supply chains may include a washing procedure to rid the crops of pesticide residue.
Crops requiring refrigeration may also face further difficulties, depending on the temperature technology used and the distance between facilities.
Overall, a crop’s journey is a tumultuous one. It needs to be part of a substantial yield and, more importantly, comprise high quality cotton to withstand the challenging trip.
Crops and climate change
It’s no secret that climate change is threatening crop quality. At the mercy of increasingly volatile conditions, tomatoes bruise and shrivel under the sun, cotton’s fibrous elasticity weakens without water and the biodiversity loss from rubber plantations becomes less and less justifiable.
Climate change’s rapid encroachment also means that currently unproblematic locations could look completely different very soon, potentially no longer able to support the same crops as before.
To preserve the reliability of crop supply chains, the crops themselves must be able to withstand increasingly demanding and unpredictable conditions so they can survive the many steps from the field to the consumers.
But what if there was a way to increase crop quality as well as optimise supply chain steps? That’s where plant biology company Avalo AI comes in.
About Avalo
Avalo AI’s machine learning capabilities identify the genetic components of desirable crop phenotypes and amplify them through selective breeding.
Built on the fundamental practice of crossbreeding, the company uses data-driven insights to enable more precise selections by breeders more quickly. Since the algorithm can predict the performance of a seed without needing to grow it, the process of obtaining desirable traits such as heat and drought tolerance is accelerated by up to 70%.
“The problems of farming are universal in that, just being in the industry that they are in, they’re getting squeezed from both sides,” says Avalo co-founder and CEO Brendan Collins.
With input costs rising while customers seek cheaper end products, farmers are experiencing a compression that could affect every aspect of the supply chain.
Collins and co-founder and CSO Mariano Alvarez created Avalo in a bid to outrace climate change by breeding crops for future environments. Optimisation of the supply chain is a byproduct of the work.
Crop breeding requires a two-to-three-year development cycle, so focussing on what an environment may be like in 10 or 20 years enables proactive farming that shields crops from immediate environmental damages as well as transportation, processing and packaging challenges.
Avalo begins the machine learning process by choosing 500 seeds representing the most genetic diversity among all the crops in the world. The phenotypes, genetic information and environmental data are all added to the algorithm, which helps to determine which combination of genetic markers could be best suited for a particular desired outcome.
“If you’re able to measure all these different traits and find a genetic basis with them, you can get potentially really interesting outcomes owing to the AI component,” says Collins.
Indeed, there are many aspects of crop growth that can be explored with the algorithm. So far, this technology has led to accomplishments such as the production of heat-resistant tomatoes, non-tropical sugar cane, resilient cotton and pesticide-free broccoli that matures in only 37 days.
Avalo and the supply chain
Crops with this level of protection are better able to survive the supply chain, especially if that supply chain is highly streamlined, according to the company.
“We’ve explored the different places within the supply chain,” says Collins. “One thing that we’re trying to do is work with the mills, garment manufacturers and brands to collect data on how fibres react to each step in the process – this knowledge will help us create a resilient product that can better withstand the industrial process.
Cotton density, for example, decreases when touched repeatedly with a physical saw blade while it is being purified and woven into the final garment.
“By the time cotton has passed all the industrial steps to become a t-shirt, more than 50% of the original cotton will have been degraded,” says Collins.
Optimising a crop using AI could lead to farmers using less fertiliser, saving them money or lowering prices for end customers. The prices would also depend on factors, such as the supply chain being used and how competitively farmers sell their crops.
While there are many potential outcomes for introducing a certain level of flexibility into the supply chain, one thing is certain: Breeding resilience is becoming easier.
Avalo AI is featured in a London exhibition titled Taste of tomorrow: What will we be eating in 2050?. Located at The Mills Fabrica, the free exhibition is running until 31st July 2025.
