{
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  "@type": "article",
  "@id": "https://anchorfact.org/kb/ai-for-agriculture",
  "headline": "AI for Agriculture: Precision Farming, Plant Disease Detection, and Crop Yield Prediction",
  "description": "AI is feeding the world — detecting crop diseases from smartphone photos, predicting harvest yields months in advance from satellite imagery, and optimizing irrigation down to individual plants. With global food demand projected to increase 60% by 2050 and 20-40% of crops lost to pests and diseases annually, AI-driven precision agriculture is becoming essential to food security.",
  "dateCreated": "2026-05-24T02:56:03.544Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
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      "@type": "CreativeWork",
      "name": "AI-driven smart agriculture using hybrid Transformer-CNN for high-precision plant disease detection",
      "sameAs": "https://www.nature.com/articles/s41598-025-10537-6"
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      "@type": "CreativeWork",
      "name": "Precision agriculture in the age of AI: A systematic review of crop disease detection methodologies",
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