Nolan Paul

🐔 KKR acquires poultry infrastructure operator ProTen from Aware Super for A$1.3bn ($856 million; €725 million), reports Daniel Kemp. The sale represents a significant success for Aware Super, which first invested in ProTen in 2018 for around A$350m and has grown the business from having 11 percent of Australia’s poultry sector to around 25 percent. The investment will be made through KKR’s Asia Pacific Infrastructure Investors II fund, the largest APAC-focused infra fund to date. “We consider agricultural infrastructure a high-conviction thematic,” said Andrew Jennings, head of Australia and New Zealand infrastructure at KKR. 🔗 Read it on Agri Investor 👉 https://lnkd.in/eZ2HgBRV #AgricultureInvestment #PrivateEquity #FoodSupplyChain #Australia #InstitutionalInvestment #Poultry #Protein

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Category Theory as a Foundation for Precision Agriculture Data Systems Precision agriculture has made huge advances in sensing and analytics. Yet many systems still treat measurements as isolated data points, rather than as parts of a coherent physical system. Our work applies category theory not as abstract math, but as a practical way to structure real-world agricultural data. From data points to structured objects Agricultural regions—blocks, canopy segments, or plant clusters—are modeled as objects with internal structure, not just pixels or rows. Each object carries chemistry (e.g., sugar development, moisture), biology (stress or disease signals), geometry (depth, slope, occlusion), optical context, and time/provenance. These attributes are defined together in the schema, reflecting physical reality from the start. Transformations matter In category theory, morphisms represent transformations. In agriculture, these include sensor motion, temporal evolution, environmental variation, and estimation steps from raw signals to chemistry. Because transformations compose, the system preserves meaning: what can be compared, what is compatible, and where uncertainty enters. Chemistry and disease as state evolution Rather than labels or predictions, chemistry and disease emerge as state changes within the schema—persistent deviations, spatial coherence changes, and temporal patterns that survive multiple transformations. This supports earlier detection and full traceability back to measurements. Why this scales Because the approach is schema-driven, not crop-specific, it generalizes across fruits, grains, vegetables, and beyond—across field, orchard, and controlled environments, and across ground, aerial, and fixed sensors. References: Spivak, Category Theory for the Sciences; Spivak, The Operad of Wiring Diagrams; Lawvere, Functorial Semantics of Algebraic Theories

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Beyond the Bulk Bin: Decoding Retail Potato Assortment for Strategic Grower Insights BE PROFY IN POTATOES NEWS Beyond the Bulk Bin: Decoding Retail Potato Assortment for Strategic Grower InsightsFor potato producers, understanding end-market dynamics is as crucial as managing a healthy crop. A detailed snapshot from leading Southeastern U.S. grocery chains like Piggly Wiggly

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This piece from EMILI does a great job grounding what it actually takes to validate a new agtech technology (linked in the first comment below). The ideas and the tech matter. But they only go somewhere if they stay in a tight loop with real farms. The EMILI post gets into some of the work behind validating Geco Strategic Weed Management’s predictive weed control. Early on it was: can we even see weed patches from satellite data? Then: how well can we predict where they’ll be? Now: what is the agronomic and economic outcome when you actually act on those predictions? All of that has had to happen alongside real deployment with farmers across the Canadian prairies. Figuring out how (or if!) this fits into a farm operation is just as important as the model itself. It ends up touching a lot of decisions. Targeted residual herbicides. Variable rate seeding. In-season sprays. Now even harvest weed seed control. All aimed at the same thing: dealing with the weedy parts of the field, not the average. But mostly this is just a thank you to EMILI. They’ve backed us from day one and have been a big part of making this real. We are extending and expanding that relationship along with them into 2026 (more on that soon!). And Jen’s article is well worth the read!

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John Deere Partners With The Reservoir To Accelerate High-value Crop Innovation John Deere (NYSE: DE) announced today the start of a strategic collaboration with the Reservoir, a California-based agricultural technology on-farm incubator platform that brings together grower networks and deep tech R&D studios to accelerate innovation in high-value crop (HVC) agriculture. The partnership links John Deere’s innovative world-class agricultural technology and equipment, and deep grower relationships with the Reservoir’s startup residents, field testing platforms and commercialization support. Through this collaborative effort, John Deere and the Reservoir aim to help HVC growers adopt new solutions that help them do more with less by addressing labor shortages, increasing efficiency and improving long-term sustainability. Read more: https://lnkd.in/d_92ah3e

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Hybrid canola seed testing has quietly become one of the most advanced — and data-intensive — areas in the seed industry, says Carey Matthiessen of 20/20 Seed Labs Inc. As hybrid systems expand and seed value rises, traditional germination tests no longer tell the whole story. Predicting emergence under stress, storage potential, and real-world performance now requires multiple testing methods and secure, automated data management. Hybrid canola is setting the standard for what seed testing will look like across future crops. Read the full INSIDERS column here: https://hubs.li/Q03_85Wb0

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🚜🌱 AgTech is growing smarter every day! The latest breakthrough in AgTech comes from the rise of AI-powered soil sensors that provide real-time insights into soil health, moisture, and nutrient levels. 🌍✨ Instead of waiting for costly lab results, farmers can now get instant data right from their fields—helping them make faster, data-driven decisions. The results? ✅ Higher yields 🌾 ✅ Lower input costs 💰 ✅ Sustainable farming practices 🌳 This is more than just technology—it’s the future of farming. A future where innovation and sustainability go hand in hand. What’s your take? Could AI-driven soil insights be the game-changer farmers have been waiting for? 🤔💡 #AgTech #Sustainability #Innovation #FutureOfFarming #AI

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🌱💶 Portugal Boosts Agri-Innovation with €11M Funding Package Strong signal from Lisbon for applied innovation in agriculture and forestry. The Ministry of Agriculture and the Sea has announced €11 million in additional funding for Operational Groups for Innovation, reinforcing the link between research, farmers, and real-world implementation. Key highlights 👇 🔹 Higher support intensity Grant rate increased from 75% → 80% Non-refundable support Up to €350,000 per Operational Group 🔹 Clear cost rules Direct personnel costs capped at: 40% for the managing entity 30% for each partner entity 🔹 Simplified governance One single managing entity represents all partners No preliminary budgets required at application stage Max 8 partners per group → more focus, less bureaucracy 🔹 Strategic priorities Plant & animal health (pests and diseases) Climate resilience Sustainability & resource efficiency Energy transition Farm digitalisation As stated by José Manuel Fernandes, this measure aligns with the Innovation Agenda for Agriculture 2030, responding to strong demand already seen from research centers, producer groups, and agri-tech partnerships. 📌 Applications will be submitted digitally via the PEPAC / Agricultural Funds Desk portal (opening shortly). 👉 Bottom line: more money, simpler rules, clearer priorities - exactly what innovation ecosystems in agriculture need to move faster from lab to field. #AgriculturalInnovation #PortugalAgri #PEPAC #CAP #Sustainability #DigitalFarming #PlantHealth #AgTech #EUAgri https://lnkd.in/dhfK53D8

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Why Collaboration Beats Competition in the Biologicals Race Biologicals are moving from “nice-to-have” to core crop protection—& the market is projected to double in the next five years. No single player can meet the speed and scale growers need. The fastest wins I’m seeing come from alliances that combine discovery, regulatory muscle, manufacturing, and last-mile agronomy. Proof that partnerships accelerate adoption: Scale through JV + platform sharing. Bayer brought its biologicals R&D together with Ginkgo Bioworks, Inc., maturing the Joyn Bio joint venture into a long-term partnership to industrialise nitrogen optimisation, carbon sequestration and pest control microbes—marrying a discovery engine with a global commercial channel. That's how game-changing tech bridges the lab–field divide more quickly. Distribution + portfolio fit through M&A. Syngenta's acquisition of Valagro added more than SKUs; it combined Valagro's biostimulant technology & production capacity with Syngenta's global presence—giving rise to Syngenta Biologicals & accelerating science-to-acre deployment. Scale up the "last mile." Corteva Agriscience's acquisitions of Symborg & Stoller paired robust farmer relationships and technical extension with established biologicals, providing Corteva with immediate scale in >60 countries—the key to rapid, compliant rollouts. Co-develop for going global. BASF × AgBiome partnered to bring an already-proven microbial fungicide (Howler®) into Europe, MEA & turf/ornamental markets—tapping BASF registration & market access to speed up availability to growers. Ambition + acres. The BioAg Alliance (Novozymes × Monsanto Company) had ambitious acreage goals. It delivered strong multi-year field results—a case of how a discovery SME combined with a row-crop behemoth can condense evidence generation and farmer adoption timelines. Why collaboration succeeds (and solo competition doesn't): Regulatory velocity: Multinationals provide dossier expertise & country-by-country registration scale; SMEs add new modes of action. Combined, time- Call to action: If you're an SME with a differentiated microbe, a multinational in search of rapid innovation, or a research facility with breakthrough results—select partnership over parity wars. Co-develop, co-validate, and co-scale. Growers, soil, and the climate don't have time for siloed improvement. Let's construct a pre-competitive framework: common test protocols, data standards, and stewardship guidelines—so that we can compete once we've elevated the baseline for biological performance and trust. If you’re open to an alliance (co-R&D, licensing, regional launches), drop a comment or DM—I’m compiling a shortlist of teams to connect across SMEs ↔ multinationals ↔ universities for 2025 pilots.

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From the cattle heartlands to the grain frontier, Brazil’s biggest companies by state reveal just how deeply food and farming drive the nation’s economy. JBS (São Paulo, US$ 72B) is the country’s largest food processor and meat exporter – no surprise at the top. Amaggi (Mato Grosso, US$ 9B) stands out as a pure agribusiness player, headquartered deep in the grain belt. Bunge (Santa Catarina, US$ 16B) beats local heavyweights BRF and WEG in its home state. Coamo Agroindustrial Cooperativa (Paraná, US$ 6B) and Copasul - Cooperativa Agrícola Sul-Mato-Grossense (Mato Grosso do Sul, US$ 2.3B) show the scale cooperatives can achieve. Even in finance-driven regions, ag pops up – Sicredi in Rio Grande do Sul (US$ 8.8B) is a co-op bank with deep rural roots.

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I had a great time speaking with M. Brett McMickell of Kubota North America for our latest episode of Agtech ... so what? There is so much there to put to use in your own strategies, but an item stood out for me as one that might not be so obvious — Sometimes we limit our ability to get the most out of new approaches by continuing to use old metrics to measure their potential. Perhaps this is some variant of Goodhart's Law - in any case an important principle to take into evaluation of innovation for broad scale adoption

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The AgriThority and Stratovation Group combination provides further support of the breadth and depth of services of these global players in the agri-business space.

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🌽🌱 Grains for Thoughts USDA’s September 12 report paints a record harvest picture. But dig deeper: - Surprise in corn planted area - Blind spots in national corn yield - Mystery in soybeans, fewer acres, late heat stress, and fragile yields The question is: what’s next? At SatYield, our satellite-driven & digital twin models often reveal what surveys miss, and this season may be no different. See the full breakdown here.

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Christine R Gould nailed a core bottleneck for Agtech at the World Agri-Tech Innovation Summit in Dubai: we have plenty of great point solutions - but too little integration. As she put it, “who’s building the integrated tech stack?” That’s exactly the mindset we’re applying at BetterSeeds - at least for gene editing. Instead of forcing seed companies to assemble (and fund) a patchwork of tools, partners, and know-how, we’re offering a complete, in-house-ready gene-editing stack: compact editors, efficient delivery, and trait programs designed to plug into elite germplasm and real breeding workflows. The goal: make advanced gene editing accessible beyond only the deepest pockets - and turn “innovation” into deployable impact. https://lnkd.in/dsbCgHcg AgTechNavigator #AgTech #RegenerativeAgriculture #GeneEditing #CRISPR #Seeds #PlantBiotech #FoodSystems #ClimateResilience #Innovation #Food30

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We’re seeing the emergence of a new layer in agtech: decision systems, not dashboards. Aimer Farming’s MPI-backed project accelerates exactly that — combining computer vision, forecasting, and now conversational AI to guide on-farm decisions in real time. Government co-investment backing the shift from “measurement software” to decision intelligence for agriculture — with real traction already (650+ farms, 10k+ measurements weekly). This is how you drive step-change gains in utilisation, profitability, and emissions — by improving decisions at the margin, every day. A category - and a company - worth watching closely. https://lnkd.in/eg5tBkH8

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GeoPard Agriculture has delivered a huge wave of updates, all built for very practical farming and agronomy use cases. Honestly, hard to name just one favorite: On-farm Trials design, Farm-level benchmarking and sorting, Synthetic Yield generation, and MCP for AI workflows. This is the kind of product work that really matters in the field. Very proud of the team behind it. Check it out live in GeoPard. #precisionag #agtech

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Machine learning models forecast harvest quantities while AI-powered notifications alert farmers to pest detection and weather risks. Technology integration transforms outcomes 🤖 AI integration across agricultural workflows creates compound benefits for farming operations. Multiple AI applications working together produce better results than individual point solutions. 🔮 Harvest Forecasting - Machine learning analyzes historical patterns and current conditions to predict crop yields 🚨 Early Warning Systems - AI monitors weather data and satellite imagery to alert farmers about potential risks 📱 Smart Notifications - Automated alerts deliver actionable recommendations at optimal timing for maximum impact 🎯 Precision Application - AI calculates exact amounts and locations for fertilizer, pesticide, and water application 📈 Continuous Learning - Machine learning models improve recommendations based on actual farming outcomes 🔗 System Integration - AI platforms connect multiple data sources for comprehensive farm management insights The combination of forecasting, monitoring, and optimization through AI creates competitive advantages for adopting farmers. Technology integration produces measurably better agricultural outcomes. AI-powered precision farming scales through mobile platforms that work on existing smartphone infrastructure. Farmers benefit from sophisticated technology without complex implementation requirements. Which AI applications would create the biggest impact on your agricultural operations?

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