{
  "id": 17183145,
  "title": "From extreme weather to agricultural consequences with agentic AI",
  "url": "https://urgent.news/2026/10/29/from-extreme-weather-to-agricultural-consequences-with-agentic-ai",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-29T17:58:53.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.40641v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Extreme weather is forecast days ahead, yet its consequences for agriculture remain hard to predict: a forecast says where a storm will strike, not which crops will suffer or how much is at risk, and the records that could tell span many sources. We present WxCrop, the first agent that judges agricultural hazards from physically interpretable weather indices examined by causal analysis, and the…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}