• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • Skip to navigation
Close Ad

The Spoon

Daily news and analysis about the food tech revolution

  • Home
  • Podcasts
  • Events
  • Newsletter
  • Connect
    • Custom Events
    • Slack
    • RSS
    • Send us a Tip
  • Advertise
  • Consulting
  • About
The Spoon
  • Home
  • Podcasts
  • Newsletter
  • Events
  • Advertise
  • About

Study: AI-Powered Drones Fuel Advances in Precision Ag for Early Detection of Crop Stress

by Michael Wolf
June 30, 2025June 30, 2025Filed under:
  • Ag Tech
  • AI
  • News
  • Click to share on Twitter (Opens in new window)
  • Click to share on LinkedIn (Opens in new window)
  • Click to share on Facebook (Opens in new window)
  • Click to share on Reddit (Opens in new window)
  • Click to email this to a friend (Opens in new window)

Early stress detection via precision agriculture just got a serious upgrade, according to new research out of the Hebrew University of Jerusalem. Led by Dr. Ittai Herrmann, the team developed a drone-based platform that blends hyperspectral, thermal, and RGB imaging with powerful deep learning technology to precisely identify nitrogen and water deficiencies in sesame crops.

Sesame, known for its resilience to climate variations, is rapidly growing in global importance. However, accurately identifying early-stage crop stress has historically posed a significant challenge, limiting the ability of farmers to respond quickly to potential catastrophic challenges. To tackle this, the researchers combined three advanced imaging technologies into a single drone system, creating a robust solution capable of decoding complex plant stress signals.

Hyperspectral imaging provides detailed spectral insights into plant chemistry, including nitrogen and chlorophyll levels, which are critical markers for plant nutrition. Thermal imaging spots subtle temperature changes in leaves that indicate water stress, while high-resolution RGB images provide clear visual context of overall plant health and structure.

What made this study cutting-edge was its use of multimodal convolutional neural networks (CNNs), an advanced AI approach that can unravel intricate data patterns and add context, which significantly enhances diagnostic precision. These advanced techniques unlocked the researchers’ ability to distinguish overlapping signals of plant stress, such as differentiating between nutrient and water deficiency, something that conventional methods often struggle to achieve. According to the researchers, by accurately pinpointing the exact stressor, farmers can now apply resources such as fertilizer and irrigation more strategically, reducing waste and environmental impact while increasing crop yields.

While other researchers have studied using advanced AI techniques with drones to aid in combatting stress in walnut and specialty crops, the use of deep multimodal CNN appears to be a leap forward in precision ag. It remains to be seen how quickly this technology reaches the farmer level, but given the challenges of climate change, its easy to envision that these types of advances in precision agriculture will be invaluable tools for farmers in the future to protect against climate-related crop stress.




Related

AeroFarms Partners With Nokia to Build Out Drone Control and Other Indoor Ag Tech

Vertical farming company AeroFarms announced today an official partnership with Nokia Bell Labs to further develop the technology capabilities of its industrial-scale indoor ag operation.  Currently, New Jersey-based AeroFarms uses a proprietary system that combines machine vision and machine learning technologies with the company’s agSTACK software, custom lighting, and aeroponics.…

Taranis Harvests $20M for Aerial Imaging Tech that Detects Crop Diseases

Today crop threat detection company Taranis announced that they closed a $20 million Series B funding round led by Viola Ventures, with participation from existing investors Finistere Ventures, Vertex Ventures, and others. This latest round brings the company's total funding to $30 million. Founded in 2014 and based in Tel Aviv, Taranis uses aerial…

Precision AI Raises $20M Seed Round for Drone-Powered Surgical Herbicide Application

Precision AI, an automated precision agriculture startup, announced today that it has raised a $20 million in Seed round of equity and grant funding. The round was co-led by At One Ventures and the Industrial Innovation Venture Fund of BDC Capital, with participation from Fulcrum Global Capital and Golden Opportunities,…

Get the Spoon in your inbox

Just enter your email and we’ll take care of the rest:

Find us on some of these other platforms:

  • Apple Podcasts
  • Spotify
Tagged:
  • AI
  • crops
  • drones
  • research

Post navigation

Previous Post Could Lasers Made From Olive Oil Be The Next-Gen Freshness Detector or Use-By Label?
Next Post From Red Bull to Zevia, Amy Taylor Shares Lessons Learned From a Career Built Around Buzzy Beverages

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Primary Sidebar

Get The Spoon in Your Inbox

The Spoon Podcast Network!

Feed your mind! Subscribe to one of our podcasts!

This Culinary Tech Inventor Thought He Could Build Some Parts For His Latest Gadget in the US. Then He Called Around.
Thermomix Has Long Been a Leader in Cooking Automation, But Now They’re Going Full Robot
Is IFT’s Launch of an AI Tool For Food Scientists an Indicator of Where Trade Associations Are Going in Age of AI?
From Red Bull to Zevia, Amy Taylor Shares Lessons Learned From a Career Built Around Buzzy Beverages
Study: AI-Powered Drones Fuel Advances in Precision Ag for Early Detection of Crop Stress

Footer

  • About
  • Sponsor the Spoon
  • The Spoon Events
  • Spoon Plus

© 2016–2025 The Spoon. All rights reserved.

  • Facebook
  • Instagram
  • LinkedIn
  • RSS
  • Twitter
  • YouTube
loading Cancel
Post was not sent - check your email addresses!
Email check failed, please try again
Sorry, your blog cannot share posts by email.