Digital Ag Global

Ten years ago, a drone over a farm was a novelty. Today drones count plants, map weeds, spot crop stress and spray fields. But do farmers actually get decisions out of all that data?Hosts Clyde and Yuri Kovalchuk talk with Rastko Čarapić, co-founder of Agremo, the AI platform that turns drone imagery into field insights for growers from Australia to Canada. They cover:

• Why drones and satellites work best together
• Where AI analytics are reliable today, and where they’re still overpromised
• How drones helped document storm damage for crop insurance in Iowa
• The spraying-drone boom and DJI’s roughly 90% market share
• The US push to move away from Chinese drones
• Drone-in-a-box automation and the farmer’s future role as manager

Rastko’s main point is that the industry is too focused on the technology and not focused enough on the farmer’s workflow. Farmers want less work and better information.🎙️ Digital Ag Global: your podcast for ag tech around the world.

What does it really take to move agricultural autonomy from an impressive demonstration to a reliable, commercially viable system working in real fields?
Join the next episode of the Digital Ag Global podcast, “What It Really Takes to Build Autonomy in Agriculture,” broadcast live on LinkedIn and YouTube on September 23 at 9:00 AM ET.
Our guest is Michael McGuire, CTO of EarthSense, where he leads the development of AI perception and autonomy systems for agricultural robots and machinery. Michael has worked on autonomous robotic fleets, tractors, and commercial oil palm fertilization systems across the United States and Southeast Asia.
His experience covers the entire journey from prototype to production: computer vision, localization, navigation, systems architecture, hardware integration, manufacturability, field reliability, and the operational workflows required to make autonomous technology practical for farmers.
In this episode, we will explore what “real autonomy” means in agriculture—and why a robot completing one successful demonstration is very different from a machine that can work reliably through heat, dust, mud, dense crop canopies, unreliable connectivity, and changing field conditions.
The conversation will cover:
• What is inside an agricultural autonomy stack, from perception and localization to navigation, safety, edge computing, and data
• How vision-based navigation can operate beneath dense crop canopies without relying entirely on RTK GPS
• The roles of cameras, LiDAR, radar, sensor fusion, and low-cost perception systems
• Why traversability, terrain, mud, slopes, vegetation, people, and animals make off-road autonomy uniquely difficult
• How autonomous systems should degrade gracefully and stop safely when conditions change
• What it takes to move from a field prototype to a reliable commercial product
• Why hardware durability, manufacturing, maintenance, field service, and unit economics can matter as much as algorithms
• Where autonomy is already creating measurable value in fertilizing, spraying, orchards, vineyards, and oil palm plantations
• How per-plant precision can improve input application, coverage, traceability, and operational visibility
• Why service-based and retrofit models may accelerate adoption
• Which autonomous agricultural use cases are commercially realistic today—and which remain aspirational
We will also discuss the “autonomy ladder”: beginning with better field records, moving into driver assistance, and eventually reaching full autonomy where the economics and operating conditions justify it.
Michael will share lessons from deploying agricultural robots in demanding environments, including the transition from research robots in Illinois to commercial systems operating on palm estates in Southeast Asia.

Where do fertilizer recommendations actually come from?Samuel Njoroge of the African Plant Nutrition Institute (APNI) joins Digital Ag Global to open up the black box — how agronomic knowledge is made in African farming systems, which digital tools are part of that work, and why so much good research never reaches a farmer.If you build agtech, you're shipping somebody else's science. This one is about where it comes from.

Remote sensing is transforming agriculture by giving growers and agribusinesses access to field insights at an unprecedented scale. But how does satellite imagery become actionable intelligence, and how are these technologies being used in real farming operations?
In this episode of Digital Ag Global, we're joined by Yevhenii Marchenko, Crop Monitoring Intelligence Specialist at EOS Data Analytics, and Luděk Novák, CEO of Agrinova Consulting.
Together, we'll explore how satellite data is converted into agronomic insights, how remote sensing supports crop monitoring and farm management, and what it takes to turn complex analytics into practical decisions. We'll discuss real-world applications, common misconceptions, current limitations, and the evolving role of AI in making remote sensing more accessible and valuable for agriculture.
Bringing together perspectives from both a leading satellite analytics provider and an agricultural consulting company working directly with farmers, this conversation offers a unique look at how remote sensing is being applied across the agricultural value chain today—and where it's headed next.
Whether you're a farmer, agronomist, agribusiness professional, AgTech innovator, or simply interested in the future of digital agriculture, this episode will provide valuable insights and practical perspectives.

Join Digital Ag Global hosts Clyde Graham and Yurii Kovalchuk for a live conversation with Cory Willness, CEO and Co-Founder of Croptimistic Technology Inc.
Topic: Beneath the Surface: How SWAT Maps Define Field Variability
Croptimistic is known for its proprietary SWAT MAPS (Soil, Water And Topography Maps), which integrate multiple layers of soil data into a single foundation zone map used for soil sampling and soil-applied product prescriptions.
In this episode, we'll discuss how field variability can be better understood through the integration of soil, water, and topography data, and the role of SWAT Maps within modern precision agriculture.
Cory has spent his career working hands-on with agronomy and agtech tools and leads Croptimistic with a vision of becoming the global leader in premium precision agriculture services.
Digital Ag Global brings together agricultural leaders, innovators, and technology experts to discuss the trends, technologies, and ideas shaping the future of agriculture.

Digital Ag Global: Smart Algorithms in AgTech — Building Forecasting & Intelligence Solutions
Artificial intelligence in agriculture is evolving far beyond dashboards and marketing buzzwords.
In this episode of Digital Ag Global, we explore what it really takes to build forecasting and intelligence systems that can support real agricultural decisions — from yield forecasting and nitrogen efficiency to carbon quantification, climate reporting, and agronomic optimization.
Joining us is Tatiana Boussange, General Director & Co-founder of Armosys, a spin-off from the University of Milan behind ARMOSA — a process-based modelling engine designed to power carbon, climate, and productivity intelligence across agricultural supply chains.
Together, we’ll discuss:
• What “smart algorithms” in agriculture actually mean today
• The difference between scientific engines and simple analytics dashboards
• Which agricultural problems are truly ready for algorithmic decision-making
• Why data quality matters more than model complexity
• The role of soil, weather, satellite, and management data in forecasting systems
• How companies build defensible, audit-ready intelligence solutions for carbon and Scope 3 reporting
• Why regional calibration is critical for credible outputs
• The future of AI, process-based models, and algorithmic decision-making in agriculture
We’ll also examine one of the biggest shifts happening in AgTech right now: the move from isolated sustainability reporting toward integrated decision engines that combine productivity, carbon, climate, and operational intelligence into a single system.
This conversation is especially relevant for:
→ AgTech founders
→ Food & agrifood companies
→ Carbon and MRV platforms
→ Sustainability leaders
→ Agronomists and technical advisors
→ Precision agriculture innovators
→ Data and AI teams building agricultural solutions
Hosted by Yurii Kovalchuk and Clyde Graham on Digital Ag Global.

What is computer vision in agriculture, and what are its practical applications? We are talking about the real use cases for farmers, real challenges, and solutions on the market. The most pressing and inconvenient topics you need to know to apply computer vision with the most benefits.
🎤 Meet the speakers:
🔹 Clyde Graham
Ag Consultant based in Ottawa, Qaltivate’s local partner in Canada and co-host of Digital Ag Global.
🔹 Yurii Kovalchuk
CEO of Qaltivate and co-host, bringing a technology and product perspective on AgTech innovation.
🔹 Craig Ganssle
CEO & Founder of Farmwave, applying computer vision for agriculture in real-world farming operations.

🔴 In this episode of Digital Ag Global, we explore how financial innovation can unlock growth across the agri-food value chain.
🎙️ Our guest speaker
Oluwadara (Dara) Adekunle, Founder of Farmties Capital Limited
Dara Adekunle is a development finance professional with over 10 years of experience across agribusiness, renewable energy, and investment development.
She is the founder of Farmties Capital, a firm focused on innovative financing and market access solutions for agribusinesses across emerging markets.📍 What We’ll Discuss
1. How Farmties originally started as an AgTech platform
2. Why technology alone couldn’t solve the biggest barriers in agriculture
3. Financing the Agri-Food Value Chain
4. Where financing gaps appear across the value chain
5. How financial innovation can unlock participation in global commodity markets
🚀 Join the Conversation

In this episode of Digital Ag Global, we’re talking about commodities in the agri-food value chain with Dmitry Mykhalchuk, Partner at GrainTrack.


Commodities sit at the center of how modern agri-food markets work — from farm gate to processors, traders, and global buyers. But behind the headlines about prices and markets, there is a much more practical layer: data, logistics, contracts, risk management, and day-to-day operational decisions.
Together with Dmitry, we’ll discuss:
How commodity flows really move through the agri-food value chain
Where the biggest operational and data bottlenecks appear today
How companies think about transparency, tracking, and control in commodity operations
What role digital tools play in making these processes more predictable and manageable
And what changes matter in practice for producers, traders, and agri-food businesses
This is a practical conversation for people working in agriculture, food processing, trading, and agri-tech who want a clearer view of how commodity value chains actually function — and where technology and better data can make a real difference.

In this episode of Digital Ag Global, we explore how machine learning and AI are changing the landscape of food logistics — from forecasting demand to improving decision-making across the supply chain.
Our hosts are joined by Jan-Willem Snoeker, Founder & CEO of Merqato, a company applying AI and data science to the fruit and vegetable industry. The conversation looks at how food demand forecasting is evolving, why forecasting remains one of the biggest challenges in food logistics heading into 2026, and how AI-driven approaches can improve pricing, volume planning, and sustainability outcomes.
We discuss the role of AI demand forecasting, the limitations of traditional planning methods, and how modern food demand forecasting software helps businesses respond to volatile markets, shifting consumer behavior, and operational constraints. The episode also touches on the broader impact of data, machine learning, and forecasting accuracy on profitability and resilience in food supply chains.
This discussion is relevant for food producers, logistics providers, wholesalers, retailers, and AgTech professionals interested in the future of AI-powered food logistics and smarter, more sustainable supply chains.