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Okanagan Specialty Fruits experiments with AI harvest forecasts

Washington‑state apple grower Okanagan Specialty Fruits is testing AI‑driven tools to predict optimal harvest dates after a heat wave forced workers off the field early last season. The company has mounted cameras from Canadian firm Vivid Machines on tractors to capture imagery of buds, flowers and fruit, which an AI system then analyses to estimate crop volume and timing. Joel Carter, the…

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Key points

  • Vivid Machines cameras mounted on tractors capture apple tree imagery for AI analysis
  • FruitCast forecasts claim 90% accuracy one week out and 83% accuracy three weeks out
  • Adoption hurdles include data quality, cost and growers' trust in AI decisions

UK‑based FruitCast offers a similar AI forecasting service for berries and tomatoes, using drone or smartphone footage and weather and irrigation inputs. The firm claims its predictions are within 10% of actual pick volume a week out (90% accurate) and within 17% three weeks out (83% accurate). Researchers at Princeton and several universities are also exploring millimetre‑wave and smartphone‑based methods to gauge fruit ripeness, though adoption remains uncertain as growers weigh cost, data privacy and the need for human judgment.

Full story from BBC Technology · by https://www.facebook.com/bbcnewsOpen source ↗

The AI telling farmers when to harvest

BBC Technology · 30 September 2026

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This text was published by BBC Technology and written by https://www.facebook.com/bbcnews. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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Okanagan Specialty FruitsVivid MachinesFruitCastDriscoll'sAngus Soft FruitsNorth Carolina State UniversityJoel CarterRaymond MartinNeill FinlaysonYasaman GhasempourJing ZhangKevin Wang

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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