In 2024, the emergence of Generative AI, the influence of digital twins on field trials, and the advancement of cloud-based technologies will transform the AgTech sector. This article discusses some major trends to watch in the AgTech landscape.
Fremont, CA: In the past year, the agricultural sector encountered difficulties ranging from severe weather conditions to disruptions in the supply chain. But the situation has changed; the present-day agricultural sector is witnessing technology revolutions. The AgTech landscape has also forecasted certain trends that could impact the agricultural sector in the following years.
They are:
Generative Artificial Intelligence in AgTech:
Among the various trends in digital agriculture for 2024, the influence of generative AI, commonly called Gen AI, is expected to be particularly impactful. The economic implications of Gen AI are projected to reach trillions of dollars on a global scale. This presents a unique opportunity to enhance operational efficiencies, reduce expenses, and drive innovation by refining modeling techniques that support informed decision-making. Organizations are leveraging Gen AI through Digital Crop Advisors, enabling agronomists to transform agronomic data into practical farmer recommendations.
These instruments improve agricultural management by analyzing extensive agronomic data, offering AI-driven insights to refine production methods. This enables farmers to discern patterns that influence the performance of various crop types and their overall yield on individual farms while monitoring climate trends to bolster farmers' resilience against climate change.
Using Digital Twins to Optimize Field Trials:
A notable trend for 2024 is the growing incorporation of digital twins in field testing and planning such tests. A digital twin is a digital model or replica of a real-world product, system, or process. This technology enables researchers and designers to conduct experiments as if interacting with the physical version, thereby minimizing the necessity for costly and time-intensive field trials.
Generating real-world data is expensive and labor-intensive, typically requiring over 150 studies and more than 11 years to introduce a new active ingredient. In contrast, synthetic data can improve the efficacy of digital twins. Synthetic data can fill in data deficiencies by utilizing real-world data, considerably decreasing the time, costs, and resources needed to launch new agricultural products. These tools offer a significant advantage to agricultural input suppliers pursuing regulatory approval and seed companies that depend on extensive experimentation to enhance their seed genetics.
Technical Innovation in Regenerative Agriculture:
In the upcoming year, there will be significant advancements in technical innovation and research focused on regenerative agriculture. This approach seeks to replicate natural processes and enhance biodiversity within agricultural systems, with the primary objective of improving soil health to increase crop yields.
Implementing regenerative agriculture is essential to tackling the pressing issues posed by climate change and sustaining a global population exceeding 8 billion. Digital technologies leverage precise and current data to develop customized solutions for regenerative practices. These solutions consider various factors, including soil conditions, weather patterns, microclimates, crop development, land usage, individual financial constraints, and local regulatory frameworks.
Platforms that provide site-specific data are expected to dominate the landscape in 2024. A comprehensive approach to sustainability, which goes beyond basic carbon metrics and generic solutions, is essential. This approach will facilitate the development of practical and achievable goals for growers, thereby enhancing sustainability and creating strategies customized to local conditions.
