Ag tech trends to watch in 2024
Author
Published
1/8/2024
The rise of artificial intelligence and evolution of cloud-based technologies will revolutionize the ag tech landscape in 2024, according to Ron Baruchi, CEO of Agmatix.
Various entities are using these cutting-edge technologies and crafting advanced software solutions to reshape the field of agronomy, Baruchi says.
He outlines five ag tech trends to watch in 2024:
#1: Generative Artificial Intelligence in Ag Tech
Of all the 2024 trends in digital agriculture, the role played by Gen AI, or generative AI, is likely to be one of the most significant. The potential of Gen AI on the global economy is already being calculated in trillions of dollars. There is a historic opportunity to optimize processes, cut costs and, importantly, fuel innovations through improved modeling to fuel decision-making.
Companies are already using Gen AI through Digital Crop Advisors, allowing agronomists to distill agronomic data into actionable recommendations for farmers. These tools enhance crop management by analyzing big agronomic data, providing AI-supported insights to optimize production practices. This helps farmers understand patterns affecting the performance of crop varieties and production on their specific farms and tracks climate trends to help farmers become more resilient to weather challenges.
#2: Using Digital Twins to Optimize Field Trials
Another emerging trend is increased integration of digital twins into field tests and field test planning. A digital twin is a digital model or a virtual representation of an actual physical product, system or process. These allow researchers and designers to experiment as though they were handling its physical counterpart, reducing the need for expensive and time-consuming field trials.
Generating real-world data is a costly and time-consuming process, averaging more than 150 studies and over 11 years to register a new active ingredient. From 2010-14, developing a new crop protection product costs around $286 million, of which $47 million (approximately 16%) was budgeted for field trials.
Synthetic data can supplement gaps in real-world data, significantly reducing the time, cost and effort in bringing agricultural products to market. These tools provide a competitive edge for agricultural input suppliers seeking regulatory approval or seed companies that rely heavily on experimentation to improve seed genetics.
#3 Technical Innovation in Regenerative Agriculture
Greater technical innovation and research into regenerative agriculture will continue over the coming year. The ultimate aim of regenerative agriculture is to improve soil health to boost yield.
Digital tools use accurate, up-to-date data to create tailored regenerative agriculture solutions. These consider soil conditions, weather conditions, microclimates and current crop growth or land use, as well as individual budgets and local regulations.
Platforms offering site specific data will likely reign supreme in 2024.
#4 Managing Data with Advanced Cloud Solutions
Agriculture is increasingly data-dependent, and the cloud gives researchers the ability to collate, manage and extrapolate information from data in a way that was previously unimaginable. It’s estimated that by 2036, the amount of data collected on the farm will increase by more than 800%.
Cloud tools enabling real-time access to field trial data reduces trial duration and cost, and the volume and scope of trials can be increased.
Cloud applications span every aspect of agriculture, optimizing crop management, soil insights, and multi-season crop monitoring and analysis, and leveraging local knowledge for decision-making.
#5 Innovation Across the Agricultural Spectrum
New sustainability and environmental protection efforts are marking a transformative era in agriculture. The new year will see progress in climate-resilient crop development.
Ag tech solutions can help farmers and agronomists measure and demonstrate the return on investment of agricultural technologies at the farm level. Amidst global challenges, stakeholders using AI and machine learning will drive unprecedented innovation in food production.
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