‘We’re creating new crops five times faster’ – BBC News

Like the bosses of many food companies, Jeremy Bunch is concerned about the impact of climate change on his business.

“The weather and climate are perhaps the biggest risk to our business,” says the boss of the American flour company Shepherd’s Grain.

The company is based in Idaho and sources wheat from farmers in the Pacific Northwest.

As weather patterns become more unpredictable, Mr. Bunch says, “I need a plan B, and a plan C, in case plan A fails.”

To help amplify these plans, Mr. Bunch’s company is now using an AI-powered software system called ClimateAi.

By using current and past data, such as satellite images and temperature and precipitation measurements, and combining this with future projections, ClimateAi aims to give farmers the most accurate, locally tailored weather forecasts possible, from one hour to six months in advance.

It then provides advice on exactly when to plant and harvest certain crops and predicts their yields.

Shepherd’s Grain only started using ClimateAi last year, but already most of its more than forty farmers are guided by the app.

“They are starting to look to ClimateAi to help them plan crop management decisions for their wheat crops, the most important crop grown in the region,” says Mr Bunch.

“A preview of the weather helps our growers decide which crops to plant. The platform knows when to plant and when the crop starts to flower and produce seed.”

One of the biggest issues facing the seed industry is how to bring climate-resilient seeds to market faster and cheaper, says Himanshu Gupta, CEO of San Francisco-based ClimateAi.

“By the time some seed companies do this, say 10 to 15 years from now, the climate will have already changed,” says Mr Gupta. “We are running counterclockwise to launch new seed varieties.”

He says ClimateAi helps these companies see how specific test seeds performed in a particular region or locality. “This can help seed companies find the optimal locations for growing seeds.”

Last year, a study published in the scientific journal Nature warned of the potentially serious consequences of numerous crop failures happening simultaneously around the world due to the impact of climate change.

“Simultaneous crop failures in major crop-producing regions threaten global food security,” said the report, which was led by climate scientist Kai Kornhuber of Columbia University’s Lamont-Doherty Earth Observatory.

The warning comes as the world’s population is expected to reach ten billion people by 2050, up from eight billion now, according to the United Nations.

As pressure on crops increases and the world population continues to grow, could AI hold the key to developing new varieties that are more resistant to extreme weather conditions?

In the city of Arusha, Tanzania, David Guerena, an agricultural scientist at the International Center for Tropical Agriculture, leads a project called Artemis.

This is funded by the Bill and Melinda Gates Foundation and uses AI to help breed more resilient crops. Specifically, the AI ​​helps speed up the work called phenotyping.

This is the visual study of new crop varieties based on observations of their characteristics, such as how many flowers, pods or leaves a plant has.

“Traditionally, it takes about ten years to develop a new crop variety,” explains Mr Guerena. “But given the pace of climate change, this time frame is no longer feasible.”

He adds that phenotyping work has traditionally relied on the human eye. “But people just don’t do this consistently and with the high precision needed to make subtle, yet important plant selections,” says Mr. Guerena.

“In the field it can be more than 30˚C. It’s just tiring, and fatigue affects data quality.”

Instead, growers involved in the project take photos of their crops via an app on a smartphone. The trained AI can then quickly analyze, record and report what it sees.

“Computers can count every flower or pod, from every plant, every day without getting tired,” says Mr Guerena. “This is very important because the number of flowers in bean plants correlates with the number of pods, which directly affects yield.

“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, and make recommendations.

“Our plant breeders estimate that with the better data from AI computer vision, they may be able to shorten the breeding cycle to just a few years.”

In North Carolina, Avalo is an agricultural technology or “agritech” company that is also working to create climate-resilient crops. It does this by using AI to help study the genetics of a crop.

“Our process starts with crop genomic data, for example the sequences of different varieties,” said Rebecca White, Chief Operating Officer of Avalo.

“For example, different tomatoes have some small differences in their genomes that give them different properties, for example different flavors and pesticide-resistant profiles. Our machine learning program is able to analyze these small differences between a number of varieties and see which genomes are important for which traits.”

Using their technology, they have managed to create a broccoli that ripens in a greenhouse in 37 days instead of the standard 45 to 60 days, Ms. White says.

“Broccoli produced at that timeframe can receive additional growth cycles, reducing carbon footprint and improving 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, through sequencing and predictive analytics, quickly and cheaply assess and model new plant varieties,” said Ms White.

“We are creating new varieties for various crops that are developed five times faster and at a fraction of the cost compared to traditional breeding.”

While AI can help mitigate the impact of climate-related weather and increase 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 recognizing that AI is one of many tools in a comprehensive strategy for a sustainable and resilient Agriculture.”