Some say the world is at a new frontier — artificial intelligence’s technological frontier. And while self-driving Teslas seem a bit overkill for farms, cutting-edge technology in agriculture is revolutionizing how farmers produce food. Farmers have used autonomous farming methods with manual oversight for nearly 20 years.
The second annual Western Growers Specialty Crop Automation Report revealed a 25 percent increase in the average year-over-year agtech investments. According to the report, growers spent an average of $500,000 yearly on automation in response to ag labor shortages. Meanwhile, farmers are reportedly looking for more agtech-trained personnel, meaning that the ag workforce is likely looking to elevate and upskill in the process.
Across the board, AI enables farmers to make informed decisions, optimize resource allocation, increase yields, and mitigate environmental impact while addressing labor shortage issues. The prices of different technologies, specifically more advanced options, may be cost-prohibitive for smaller and medium-sized farmers, but the time it takes to build automation solutions is getting shorter, and costs are going lower.
Technological advances in agriculture aren’t going anywhere. From robotic milkers to face detection in cattle, laser weed sprayers, robotic harvesters, self-driving tractors, and more, AI in farming is on the move. According to a market survey by Persistence Market Research, the precision market farming industry is projected to grow 12.7 percent over the next decade.
Precision agriculture boils down to farming management concepts based on observing, measuring, and responding to crop variability. AI algorithms analyze real-time data from sensors, satellites, and drones to provide farmers with valuable insights into crop health, soil conditions, and weather patterns.
Farmers can precisely monitor and manage irrigation, fertilizer application, and pesticide use by employing AI-powered systems. This targeted approach not only maximizes crop yields but also minimizes the use of resources, resulting in cost savings and reduced environmental impact.
Precision farming has been making its way into harvesting as well. GPS technologies and other autonomous technologies have been improving harvests and yields for over a decade, but harvesters such as John Deere’s new combine promise to recognize grain type, quality, and even the terrain and weather where farmers are harvesting, adjusting accordingly.
Crop monitoring and disease detection
This year, most of the progress in farming AI was made in the weeding and harvest segments.
AI-based systems can monitor crops at an unprecedented scale and detect early signs of diseases, nutrient deficiencies, and pest infestations. By analyzing images captured by drones or cameras mounted on agricultural machinery, AI algorithms can quickly identify anomalies in plant health and alert farmers to potential issues.
With early detection, farmers can take immediate action, preventing the spread of diseases and minimizing crop losses. Such proactive measures not only enhance productivity but also reduce the dependence on inputs, leading to more sustainable farming practices.
AI has facilitated the development of autonomous agricultural machinery and robots, which are transforming labor-intensive farming processes. Robotic systems equipped with computer vision and machine learning capabilities can perform tasks such as seeding, weeding, and harvesting with exceptional precision and efficiency.
These AI-driven machines can work tirelessly without the constraints of human fatigue, thus increasing productivity and reducing operational costs. Moreover, they can navigate complex terrains and work in adverse weather conditions, ensuring a higher level of operational reliability.
Climate and resource management
Climate change poses significant challenges to agriculture, making resource management more critical than ever. AI and IoT sensors allow farmers to monitor soil moisture, temperature, humidity, and other environmental parameters in real-time.
By leveraging AI’s predictive capabilities, farmers can optimize irrigation schedules, conserve water, and mitigate the impact of droughts or extreme weather events. AI-driven models can also provide valuable insights into sustainable land management practices, helping farmers make informed decisions to minimize soil erosion and preserve biodiversity.
One thing is for certain, ag automation is going to continue to grow. And with continued technological advances and automation, the agricultural workforce and how farmers grow food will continue to change.
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Author: Heidi Crnkovic