Por: Maryna Kuzmenko

Welcome to the Future of Agriculture Podcast – AI Promise and Crop Production Reality. This weekly show highlights the most striking, useful, and educational innovations in agriculture and discusses current AI trends with a farmer-first lens. We cut through hype, translate research into plain English, and turn tools into practical SOPs that improve yield, quality, profitability, and sustainability.🎙️ What you’ll get every week• Field Note: a farm or greenhouse problem and how tech actually solved—or failed to solve—it.• Toolbench: hands-on looks at AI/ML, sensors, drones, robotics, computer vision, LLM copilots, and edge devices.• Paper-in-Plain-English: new research distilled into operational takeaways for agronomy and management.• Myth vs Reality: separating marketing from agronomic constraints, data limits, and regulation.• The 60-Second ROI: quick math on cost, benefit, risk, and break-even.• Listener Q&A: your challenges, answered with concrete next steps.🌾 Who this is forFarmers, agronomists, CEA/greenhouse growers, orchard and vineyard managers, crop advisors, ag retailers, input suppliers, agtech founders, investors, researchers, students, and policy shapers who want to know where AI truly creates value in crop production.🤖 Topics we coverPrecision agriculture; variable-rate irrigation and fertilization; soil health; satellite and drone imagery; multispectral and hyperspectral sensing; canopy vigor and greenness indices; computer vision phenotyping; plant counting and sizing; fruit load estimation; quality grading and defect detection; disease and pest scouting; early warning; LLMs as agronomy copilots; recordkeeping and traceability; on-device and edge AI; robotics; decision support; compliance; and economics.🧪 From lab to fieldWe connect machine learning advances (object detection, self-supervised features, multimodal transformers), statistics, and control to real constraints: sampling bias, lighting, occlusion, phenology, calibration plates, label drift, model drift, edge compute, connectivity, human workflow, and data governance. Expect frank talk about false positives, thresholds, and how to validate models against ground truth.🥕 Crops and systems featuredApples, berries, tomatoes, potatoes, grapes, kiwifruit, leafy greens, brassicas, citrus, stone fruit, cocoa, coffee, cassava, maize, wheat, rice, soy, sugar beet, greenhouse vegetables, vertical farms, and regenerative, organic, and conventional systems.📈 Why subscribeTo save time, money, and frustration. Each episode converts the week’s most useful ideas into takeaways you can test in a field, trial block, or lab. Learn when a simple SOP beats a fancy model, when to rent a drone versus hire a scout, and how to measure success so pilots become deployed systems—not shelfware.🧰 Workflows we unpack• Drone or phone: match sensor, altitude, and ground sampling distance to the job.• Spot-spray: detect → decide → actuate with rate cards and validation plots.• Fruit count and size: from flowering to packhouse reconciliation.• Leaf area, greenness, and nitrogen: when SPAD, when RGB, when multispectral.• Disease triage: early signs, thresholds, and escalation rules.• Greenhouse setpoints: combine vision, climate, and fertigation to steer vigor.🗓️ Publishing scheduleNew episodes every week. Expect rotating deep dives, farmer conversations, startup case studies, and research spotlights.⚖️ Our promisePlain talk, practical evidence, and transparent limitations. We disclose conflicts, avoid vendor hype, and always describe the context, dataset, and validation design behind any result. Hosted on Acast. See acast.com/privacy for more information.

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