Artificial Intelligence: The Beauty Of Scaling Up Brainpower
Not only humans, but also computers can learn. Artificial intelligence is essential for progress in the digital world. Curious how this can also be useful in agriculture?
What is Artificial Intelligence in agriculture?
Artificial intelligence (AI) in agriculture applies computer learning from data to bring efficiencies and solutions to farming and the food supply. This allows more informed decisions to be made from large and complex and data sets than would be possible by a person alone. Image recognition is an example of AI that identifies patterns in data, like an algorithm to identify unknown weeds or pests from a smartphone photo. The performance of algorithms can be improved over time with more data, for example with more photos of known weeds or pests in the database, the more accurate the resulting identification becomes.
How can AI help farmers, society, and the planet?
Technology is opening possibilities in farming, along the entire value chain. Artificial intelligence is one of the technologies leading the transformation of agriculture for the better. Consider better decisions on which varieties to plant, recognition and prediction of pest outbreaks, and what and when to apply pest control products based on vast environmental data. Incorporation of more data in decision making allows farmers to protect yield and biodiversity at the same time.
Does BASF use AI to produce agriculture products?
Artificial intelligence has wide applications and is deployed across R&D and even out to the field where farmers are now using BASF’s xarvio™ Digital Farming Solutions. Image recognition is one of the flagships of artificial intelligence and deep learning, and it’s built into xarvio®
SCOUTING. It gives the farmer the ability to quickly and conveniently identify in-field problems - pests, diseases and weeds - from photos they take with their phones. In plant breeding operations, AI enables scientists and breeders to easily relate genomic sequences with beneficial traits, making genomic selection and trait mapping much more productive. Data use is accelerated, making breeding both faster and more cost effective. This translates to the production of more accurate and environmentally robust varieties so that farmers can produce enough for the growing population and earn a living.
BASF in AI
“Our collaboration with TECNALIA, started in 2014, enables us to employ state-of-the-art algorithms based on artificial intelligence and machine learning,” said Ramon Navarra-Mestre, Head of Global Agricultural Research Stations at BASF. “This new, efficient technology provides us with more reliable information from our global field trials network as the image recognition assessments can be done more frequently and deliver more objective data compared to traditional methods.”
“With the collaboration of BASF Digital Farming and Zen-noh the xarvio FIELD MANAGER will help farmers determine what kind of work and when is needed for each field across the farm, enabling farmers to plan and work more efficiently,” said Andree-Georg Girg, Managing Director and Head of Global Commercialization at BASF Digital Farming.
“This collaboration will explore the power of digitalization to improve and accelerate agricultural research, and aligns with our soybean crop system strategy,” said Rick Turner, Senior Vice President Seeds & Traits in BASF’s Agricultural Solutions division. “BASF and NRGene are both focused on developing and delivering technologies to support farmers to grow better harvests, protect their crops and deliver more to society in the face of mounting environmental challenges.”
“We all know we need to make agriculture even more efficient and environmentally friendly. We hear it from farmers, from partners and society. Our motivation at BASF Digital Farming: Enabling to produce crops more sustainably,” says Bjoern Kiepe, Head of Agronomy xarvio® Digital Farming.
Who else is talking about AI in Agriculture?
Interviewing Sachin Gupta, Global Agribusiness Industry Leader at IBM, "AI will drastically improve sustainable farming on land by helping farmers to forecast weather conditions," said Gupta. "Farming is a risky business. Farmers worldwide have always wrangled with weather – drought, flooding, or something in between. Stabilizing food security is a global priority."
In their section on AI as an enabler of scientific discovery, “The resulting predictions can then be used to provide strategies for building climate resilience that will decrease the impact of climate change on agriculture in the region.”
Dalvin Brown, innovation reporter for the Financial section writes, “It’s true that AI-powered farm machines may one day be able to perform most tasks that require people today. But for the time being, humans have a leg up in some areas, such as handling delicate objects. Robots tend to have dexterity problems, which can cause them to hold objects like fruit and vegetables too aggressively.”
Last Update April 20, 2022