AI Applications In Agriculture

The future of our food system sustainability is being developed at the convergence of biology, human innovation, artificial intelligence - and hundreds of millions of bugs! Nature's most efficient protein factories have been hiding in plain sight. While we've been debating sustainable food futures, black soldier flies have been quietly demonstrating how to create abundance from what we've overlooked. I visited the Innovafeed facility in Nesle, France with Mathilde Barge to explore how AI is helping reshape our core food systems. Innovafeed has built something remarkable: a system where these flies - with metabolism 25x more efficient than cattle - transform agricultural by-products into high-quality protein and oils. These ingredients replace resource-intensive fishmeal and fish oil in aquaculture and animal feed, addressing our protein challenge without requiring additional farmland, driving deforestation, or depleting oceans. AI systems continuously analyze millions of data points across their facility, predicting growth patterns and optimizing conditions in real-time. It's running today and producing nutrition with 80% less carbon impact than conventional methods. When we talk about sustainability, we often frame it as a sacrifice. This approach reveals the opposite: abundance through smarter systems. Using technology not to extract more from our world, but to create regenerative loops where outputs become inputs. And it's proof that transformative AI doesn't only emerge from Silicon Valley, but often in unexpected sectors like agriculture where practical problems demand inventive solutions. The technologies pioneered in these unlikely places - where insects meet algorithms - will ultimately reshape how we feed our planet. The future belongs to those who see possibility in what others have overlooked. My gratitude to CEO Clément Ray for the warm welcome at the factory and to Nadège AUDIFFREN and Enzo Ballestra, for making this insightful visit possible! #CircularEconomy #FoodSystems #SustainableInnovation #AI #FutureFarming The Patrick J. McGovern Foundation

#AI, Food and #FoodSecurity: At What Cost, and Who Owns the Future? I’m just back from Davos, where I joined several meetings and many conversations on AI and food systems – and I’ve been thinking about it ever since, with equal parts curiosity and frustration. Davos looked like a crystal‑ball fair for AI: the Promenade wrapped in slogans, generative futures, predictive everything. Much less visible were the people who actually feed the world – farmers, pastoralists, fishers, food workers – and the fragile territories where soil, water and culture are under daily siege. In the AI & food sessions I joined, two narratives ran in parallel: 👉 the excitement: AI for farmer advisory, early‑warning systems, food safety, logistics and finance; 👉 the reality check: a lone farmer or practitioner reminding everyone that a model is useless if it arrives too late, doesn’t share risk, and ignores local priorities, and if it is deployed into a vacuum, without the social, cultural and basic infrastructure that make any innovation usable in real life.... without taking care of the essentials... One sentence keeps coming back to me: we will not feed humanity with microchips and algorithms. Food security is not an app; it’s a living infrastructure made of fertile soil, clean water, biodiversity, food cultures, and relations of peace. So the real issue is not “more AI”, but: - Who owns the data and controls the infrastructure? - Who carries the risk when predictions fail? - How do we ensure AI serves food security as a global public good, and not just private optimisation? - Where do you see AI truly adding value to fairer, more resilient food systems – and where do we need clear red lines, or to admit that here, AI is not the answer? https://lnkd.in/dfSs7gRZ Michael Wolf Daniele Quadrellaro Andrea Ciucci Antonio Gagliardi Roberto Mazzei

From Policy to Practice: A New Era of Agritech Innovation for Maharashtra As Maharashtra charts its path toward inclusive agritech transformation, AI is emerging as a powerful ally for smallholder farmers — not just in theory, but through real, ground-level impact. Here’s how AI is already making a difference: 1. Personalized Advisory in Marathi AI-powered apps like #MahaVISTAAR_AI deliver crop-specific guidance in local languages — from sowing to pest control — making precision farming accessible to all. 2. Crop Monitoring & Yield Forecasting Satellite imagery + AI models help forecast yields, detect vulnerabilities, and guide climate-resilient planning. 3. Disease & Pest Detection via Smartphones Farmers can snap a photo of a diseased leaf and receive instant AI-driven diagnoses and treatment suggestions. 4. Market Intelligence & Price Forecasting AI tools analyze mandi arrivals and demand trends to help farmers time their sales and avoid distress pricing. 5. Curbing Black Marketing of Inputs AI-backed traceability platforms ensure certified seeds and fertilizers reach the right hands. 6. AI-Based Credit Scoring New models bypass traditional CIBIL scores, unlocking formal credit and insurance for smallholders. 7. Sandbox Pilots for Local Innovation Startups can test AI tools using anonymized farm data from #CropSAP, Mahavedh, and #AgriStack — driving region-specific solutions. Maharashtra’s AI & Agritech Innovation Center is laying the groundwork for scalable, farmer-first solutions. The opportunity to co-create with startups, policymakers, and researchers has never been more exciting. What do you think? PoCRA: Nanaji Deshmukh Krushi Sanjivani Prakalp #Agritech #AIForFarmers #MaharashtraInnovation #InclusiveGrowth #StartupIndia #DigitalAgriculture #ThoughtLeadership

𝐈𝐧𝐝𝐢𝐚, 𝐭𝐡𝐞 𝐠𝐥𝐨𝐛𝐚𝐥 𝐥𝐞𝐚𝐝𝐞𝐫 𝐢𝐧 𝐫𝐞𝐝 𝐜𝐡𝐢𝐥𝐥𝐢 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧, 𝐜𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐬 𝐨𝐯𝐞𝐫 𝟒𝟎% 𝐨𝐟 𝐠𝐥𝐨𝐛𝐚𝐥 𝐞𝐱𝐩𝐨𝐫𝐭𝐬. However, traditional farming practices have often limited this potential. High input costs, pest infestations, and chemical residue issues in exports have historically posed significant challenges for farmers. The integration of Artificial Intelligence (AI) into agriculture is now transforming this scenario, creating success stories across the nation and revolutionizing farming practices. 𝐆𝐮𝐧𝐭𝐮𝐫, 𝐀𝐧𝐝𝐡𝐫𝐚 𝐏𝐫𝐚𝐝𝐞𝐬𝐡, famously known as the Chilli Capital of India, has emerged as a shining example of AI-powered precision farming. By leveraging satellite-based soil monitoring and automated irrigation systems, farmers in this region are achieving remarkable results. Production has surged by 25%, meeting both domestic and export demands. Simultaneously, pesticide usage has reduced by 40%, ensuring the produce is residue-free and compliant with international standards. This shift has opened up lucrative export opportunities, particularly in premium markets across Europe and the Middle East, significantly boosting farmers’ incomes. In Punjab, a state renowned for its wheat and paddy cultivation, AI tools are being seamlessly integrated into traditional agricultural practices. Farmers here are utilizing satellite imagery and real-time analytics to revolutionize water and disease management. AI-driven irrigation systems have reduced water consumption by 35%, addressing the critical challenge of groundwater depletion in the region. Additionally, during a recent yellow rust outbreak, AI-enabled early detection systems helped prevent a 10% yield loss, saving farmers from significant economic losses. Similarly, Karnataka's Belgaum district is embracing AI for effective crop disease management. Farmers are using computer vision technology to detect leaf blight in tomato and chilli crops with an impressive 96% accuracy. The Indian government is playing a pivotal role in facilitating AI adoption through initiatives under the Digital Agriculture Mission. Farmers can avail themselves of subsidies for drones, sensors, and other AI-based devices through the 𝐏𝐌-𝐊𝐈𝐒𝐀𝐍 𝐬𝐜𝐡𝐞𝐦𝐞. Furthermore, the Indian Council of Agricultural Research (ICAR) conducts 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 𝐭𝐨 𝐭𝐫𝐚𝐢𝐧 𝐟𝐚𝐫𝐦𝐞𝐫𝐬 in the practical use of AI tools, ensuring that even small-scale farmers benefit from these technological advancements. AI is effectively addressing some of the most pressing challenges in traditional farming. With the pesticide application, it minimizes chemical residues, making Indian produce export-ready. Weather analytics powered by AI predict rainfall and temperature changes, allowing farmers to adapt and mitigate risks proactively. AI adoption has led to a 20–30% reduction in overall input costs, improving farmers' profitability and financial resilience.

Across Africa and South Asia, smallholder farmers—those who’ve contributed the least to climate change—are being hit hardest by its effects. A single extreme weather event—heat, cold, flooding—can create food shortages, loss of income, and push families deeper into poverty. I’ve witnessed the power of farmer-led solutions. From AI weather forecasting to mobile apps that offer planting advice—these innovations are helping farmers adapt to climate shocks, strengthen livelihoods, and secure a more resilient future for entire communities. That’s why the Gates Foundation is committing $1.4 billion over four years to support agricultural innovations that help smallholder farmers navigate a changing climate.   The potential is even greater if governments, philanthropies, and the private sector join us in advancing these resilience-focused solutions. Let’s invest in the people who feed us all. https://lnkd.in/gU_aZ3Q4

💧 Liters per kilogram of produce. That’s the metric that will define the future of agriculture. As clean water becomes more scarce, especially in climate-stressed regions, producers have two options: react later (when water access may be significantly restricted), or invest now and lead. Controlled environment agriculture (CEA) offers a better path forward. Smart greenhouses and vertical farms use sensors, automation, and AI to optimize light, water, nutrients, and temperature—cutting water use by up to 90% while dramatically increasing yields. In tomato farming, for example, these systems have been shown to produce over 600% more than open fields. CEA approaches maximize yield, minimize risk, and conserve precious resources. While it may not be feasible to have a smart greenhouse in every field around the planet, wouldn’t it make sense to invest in more of them now, to conserve water and improve our knowledge on how to make farms around the world more resilient in the face of increasing climate volatility? 💡 It’s time to stop asking "if" and start investing in the places where smart greenhouses will make the biggest difference. The weather volatility of the last few years is signaling what’s coming. Why wait longer and risk more when we can act now to conserve water and increase profitability? #SmartFarming #AgTech #WaterEfficiency #ClimateResilience #GreenInnovation #FutureOfFood

THE FUTURE OF COTTON GROWING? AVALO HARVESTS FIRST COMMERCIAL CROP OF COTTON, BRED USING AI: Harvesting has begun on the first crop of AI-bred cotton in Texas, in a development that could reshape how cotton is bred for sustainability.   What sets this apart is the machine-learning engine behind it. Instead of the slow, generational trial-and-error used in traditional breeding, agtech company Avalo runs whole-genome models that analyse thousands of data points from each plant. The AI predicts which parent seeds will produce the strongest combination of traits, such drought tolerance, fibre quality, or low fertiliser need, before the plants reach the field.   This means breeders don’t have to wait for plants to mature to see how they perform. Avalo can screen vast numbers of seedlings computationally, select only the most promising crosses, and cycle through generations at high speed. This cuts the breeding timeline from 8–10 years to around 2.5.   The first harvest now coming off Texas fields reflects these AI-driven selections, with cotton that needs far less nitrogen, and carries a smaller carbon footprint from the outset.   For brands chasing Scope 3 reductions, AI-guided plant breeding could improve cotton at seed level rather than relying solely on on-farm practices. Our story in the comments.

👏📰🧑🌾 I enjoyed reading an AFR article yesterday that combined two of my favorite things: soil and technology. It highlighted one of the major opportunities AI offers today—helping reduce emissions and improving environmental management. Why does this matter? The sheer volume and complexity of the data we're dealing with is one of the biggest challenges. For instance, FarmLab's most recent carbon model for Australia processed 774 billion pixels, drawing on over 40 features from multiple satellite constellations across a 3+ year time series. This level of data processing is beyond human capacity and would have been impossible just 5 or 10 years ago. Today, it can be done overnight (and tomorrow, a few hours?) This isn't all hypothetical either, using these models our clients have already been able to reduce the amount of soil samples required over an area to estimate carbon, and therefore the cost by about 30% - something akin to about $5-10k savings on a $30,000 project. The same can be said for the likes of AgriProve and CarbonLink™ using similar technologies to bring down the price of measurement. Although AI may be a bit of a buzzword in the tech community today - it's use behind the scenes in industries like agriculture are already being felt. https://lnkd.in/gfxtDJkr

It does not have to be big factory farms versus small organic ones. There is another way. AI robots fill in for weed killers and farm hands. A solar-powered, AI-driven robot autonomously weeds fields without chemicals. It offers a sustainable solution to labour shortages and herbicide resistance. Designed by former Tesla engineer Richard Wurden, the robot mimics human weeding and runs on sunlight. The robot's AI system takes in data from onboard cameras, allowing it to follow crop rows and identify weeds. Farms are struggling: → Chemical resistance is growing Herbicide-resistant weeds are now found in 101 crops across 72 countries. → Labor shortages are real The share of U.S. farmers reporting labor shortages jumped from 14% in 2014 to 53% during the pandemic—making automation not just a luxury, but a necessity. But here's how AI and robotics can change that: → AI that thinks like a farmer → Powered by pure sunlight → 97% accuracy in weed removal → Zero chemical footprint The Real Impact: → 96% less chemicals needed → Healthier soil microbiome → Stronger crop yields → Sustainable farming at scale BUT one big challenges remains. Commercial entry-level robots often cost around $13,000–$20,000 each. Innovation with new modular robots are being developed for as little as $2,500 to make technology accessible to small and mid-sized farms. While humankind has never before produced as much food, feed and other agricultural produce on this planet, the number of people going to bed hungry tonight has also never been as high as today. Food production is an important contributor to climate change and at the same time is acutely threatened by its consequences.  Follow me Dr. Martha Boeckenfeld for more on Tech impacting our Future. ♻️ Repost to learn about organic farming with technology. #AgTech #Sustainability #FutureOfFood

AI, agriculture and the future… How can AI help smallholder farmers adapt and increase productivity? This week, on Episode #166 of the Unlocking Africa Podcast, I sat down with Dr. William Derban, Head of Programs and Partnerships at the Digital Innovations Group for Opportunity International, an organisation that is using AI-driven solutions to support smallholder farmers across Africa. 🌍 Agriculture is the backbone of Africa’s economy, yet many farmers lack access to timely, reliable information to improve yields and protect their livelihoods. That’s where AI-powered tools like UlangiziAI and FarmerAI come in, providing real-time, localised agricultural advice through WhatsApp and other accessible platforms. But here’s what makes Dr. Derban’s approach unique… Instead of just deploying AI, Opportunity International integrates human-centred design, working closely with farmers, local governments, and agricultural experts to ensure solutions are both practical and scalable. One of my favourite insights from our conversation… Many assume access to finance is the biggest challenge for smallholder farmers. But according to Dr. Derban, the real issue is access to information, knowing what to plant, when to plant, and how to respond to shifting climate patterns. AI is now helping bridge that gap. What we discuss with Dr. Derban: ✅ How AI-powered chatbots are transforming smallholder farming across Malawi, Kenya, and Ghana. ✅ The biggest challenges in last-mile AI adoption, from digital literacy to infrastructure limitations. ✅ Why partnerships with telcos, agritech firms, and financial institutions are essential for scaling AI solutions. ✅ The ethical considerations of deploying AI in vulnerable communities—and how to ensure inclusion. AI in agriculture isn’t just about efficiency; it’s about climate resilience, food security, and financial empowerment for millions of farmers. If you’re interested in AI, agriculture, and financial inclusion, this episode is for you. ⬇️ Listen now by clicking the link in the comments below ⬇️ #AI #Agriculture #FinancialInclusion #EmergingMarkets #Africa #ClimateResilience #Podcast #PodcastHost