Jeremy Bunch, like the executives of many food firms, is concerned about how climate change could affect his company.
“Climate and weather are potentially the biggest threat to our business,” states the CEO of US flour manufacturer Shepherd’s Grain.
The company, which has its headquarters in Idaho, purchases wheat from farmers in the US Pacific Northwest.
“I need to have a plan B, and plan C, in case plan A fails,” Mr. Bunch adds, referring to the increasing unpredictability of weather patterns.
Mr. Bunch’s business is currently utilising ClimateAi, an AI-powered software solution, to support these ambitions.
Using current and past data, such as from satellite imagery and temperature and rainfall readings, and combining that with future projections, ClimateAi aims to give farmers the most accurate possible, locally-tailored weather forecasts, from one hour to six months ahead.
It then advises on exactly when to plant and harvest particular crops, and predicts their yields.
Shepherd’s Grain only started using ClimateAi last year, but already most of its 40 plus farmers are now being guided by the app.
“They’re beginning to look at ClimateAi to help them plan for crop management decisions in their wheat crops, the primary crop grown in the region,” says Mr Bunch.
“A forward look at the weather helps our growers decide which crops to plant. The platform knows when to plant, and when the crop will start flowering and producing seed.”
Getting climate resilient seeds onto the market more quickly and affordably is one of the largest issues facing the seed industry, according to Himanshu Gupta, CEO of ClimateAi, a San Francisco-based company.
“The climate has already changed by the time some seed companies do this, in say 10 to 15 years,” Mr. Gupta claims. “There is not enough time left to introduce new seed varieties.”
According to him, ClimateAi assists these businesses in determining the effectiveness of particular test seeds in a given area or locale. “This can assist seed companies in determining the best sites for seed cultivation.”
A study that was published in the scientific journal Nature last year alerted readers to the potentially disastrous effects of many crop failures occurring simultaneously over the world due to the effects of climate change.
Global food security is at risk due to simultaneous harvest failures in major crop-producing regions, according to a paper headed by climate scientist Kai Kornhuber of Columbia University’s Lamont-Doherty Earth Observatory.
This warning coincides with the United Nations’ prediction that there would be 10 billion people on the planet by 2050, up from the current eight billion.
With the growing global population and increasing strain on crops, may artificial intelligence play a major role in creating new crop kinds that are more resilient to weather extremes?
In the city of Arusha in Tanzania, David Guerena, agricultural scientist at the International Center for Tropical Agriculture, is leading a project called Artemis.
Funded by the Bill and Melinda Gates Foundation, this is using AI to help breed more resilient crops. Specifically the AI is helping speed up work called phenotyping.
This is the visual studying of new crop varieties based on observations of their characteristics, such as how many flowers, pods or leaves that a plant has.
“Traditionally it takes around 10 years to develop a new crop variety,” explains Mr Guerena. “But given the pace of climate change, this timeframe is no longer viable.”
He adds that the phenotyping work traditionally relied on the human eye. “But humans are just not doing this consistently, with the high levels of precision necessary, to make subtle, yet important, plant selections,” says Mr Guerena.
“It can be over 30˚C in the field. It’s just tiring, and fatigue affects data quality.”
Instead, growers involved in the project are taking photos of their crops through an app on a smartphone. The trained AI can then quickly analyses, records, and reports what it sees.
“Computers can count every flower or pod, from every plant, every day without getting tired,” says Mr Guerena. “This is really important as the number of flowers in bean plants correlate to the number of pods which directly influence yields.
“Data can be so complicated, to understand what’s happening, but AI can be used to make sense of that complicated data and pick up patterns, show where we need resources, show recommendations.
“Our plant breeders estimate that with the better data from the AI computer vision they may be able to shorten the breeding cycle to only a few years.”
In North Carolina, Avalo is an agriculture technology or “agri-tech” business also working to create climate-resilient crops. It does this by using AI to help study a crop’s genetics.
“Our process starts with genomic data about crops, for example, the sequences of various varieties,” says Rebecca White, Avalo’s chief operating officer.
“For example, with different tomatoes, there’s some small differences in genomes that give them different traits, for example different flavours, pesticide-resilient profiles. Our machine-learning programme is able to take these small differences across a number of varieties and see which genomes are important for what traits.”
Using their tech they have been able to create a broccoli that matures in a greenhouse in 37 days rather than the standard 45 to 60 days, says Ms White.
“Broccoli produced on that timescale can get additional growth cycles, and it saves carbon footprint and improves the environmental impact.”
Avalo, which works with companies in Asia and North America, is also working to make rice resistant to frost, and potatoes more tolerant to drought.
“Our core technologies can identify the genetic basis of complex traits with minimal training and, via sequencing and predictive analysis, quickly and inexpensively assess and model new plant varieties,” says Ms White.
“We are creating new varieties for diverse crops that are developed five-times faster and for a fraction of the cost compared to traditional breeding.”
However, while AI can help mitigate the impact of climate-related weather, and enhance crop resilience, there are a number of challenges when it comes to using AI in agriculture, says Kate E Jones, professor of ecology and biodiversity at University College London.
“The effectiveness of AI in ensuring food security also depends on addressing challenges such as data quality, technology accessibility… while acknowledging that AI is one tool among many in a comprehensive strategy for sustainable and resilient agriculture.”
About The Author
