Introduction to AI in Agriculture
AI is the cream of the crop in today’s tech field, with industries relying on generative AI to improve operations and boost productivity. One sector that is using AI with measurable results is agriculture, with vegetable seed companies harnessing the technology to identify the best vegetable varieties out of thousands of options. This facility can help growers in diverse markets who work in very different conditions from one another.
The Challenge of Finding the Best Vegetable Seeds
Finding the best vegetable seeds is not just down to yield – growers look for varieties that address unique local climate patterns and growing conditions. The traditional route of variety selection involves several manual processes, including testing and comparing different seed varieties, running field trials, mass data collection, and gathering feedback from growers. Now, seed companies are now turning to AI technology that runs alongside traditional selection methods, to analyze such information. This saves time and resources between selection and first crop.
Companies at the Forefront of AI Adoption
Syngenta Vegetable Seeds and Heritable Agriculture are at the forefront of AI adoption in this sector, and are collaborating to enhance commercial crop portfolios. Heritable is a new company spun out of the innovation lab at Alphabet (Google’s parent company) that develops AI tools to analyze agricultural data. The two companies combine to create software systems that can recommend which vegetable seed varieties should be offered to which growers and where.
How AI Tools Work
Using AI tools with Syngenta’s global product portfolio, Heritable relies on crop trialling and existing data on localized geographical conditions to predict the best-performing commercial seed varieties for different regions. The aim is to forecast how well vegetable seed varieties will perform for growers worldwide yet on a micro-level, accurately predicting the best choices down to an accuracy of around 10 meters x 10 meters.
The Potential of AI in Agriculture
Matthew Johnston, Global Head of Vegetable Seeds and Flowers at Syngenta, said AI has considerable potential in agriculture. “Planting the right seed is important to a grower’s success. New technologies like AI can help us bring the best innovation to the field or greenhouse.” Syngenta has already been using AI in its business, in areas like bio-stimulant and fertilizer development. Recently, the company added an AI chatbot called ‘Cropwise AI‘ to its Cropwise digital platform to help growers make informed decisions about crop choices by analyzing data.
The Goal of AI in Agriculture
Ultimately, the goal is to improve food security and ensure growers around the world can produce food that is affordable, resilient, and reliable. That’s particularly important as climate conditions change and become more unpredictable.
Conclusion
The use of AI in agriculture is a rapidly growing field, with companies like Syngenta and Heritable leading the way. By harnessing the power of AI, these companies are able to analyze vast amounts of data and make predictions about which seed varieties will perform best in different regions. This technology has the potential to improve food security and help growers produce food that is affordable, resilient, and reliable.
FAQs
Q: What is the main goal of using AI in agriculture?
A: The main goal of using AI in agriculture is to improve food security and ensure growers around the world can produce food that is affordable, resilient, and reliable.
Q: How do AI tools work in agriculture?
A: AI tools work by analyzing data on localized geographical conditions and crop trialling to predict the best-performing commercial seed varieties for different regions.
Q: Which companies are at the forefront of AI adoption in agriculture?
A: Syngenta Vegetable Seeds and Heritable Agriculture are at the forefront of AI adoption in agriculture.
Q: What is the potential of AI in agriculture?
A: The potential of AI in agriculture is considerable, with the ability to improve food security, increase productivity, and help growers make informed decisions about crop choices.
