Researchers in Chile built mathematical models that accurately predict when hazelnut trees will leaf out, flower, and set fruit — information growers need to time irrigation, pest control, and fertilization as climate patterns become less predictable.
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Models explained 80–94% of the variation in hazelnut phenological timing (R² = 0.80–0.94) for both 'Tonda di Giffoni' and 'Barcelona' cultivars.
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Validation showed prediction errors as low as 0.43 phenological units (RMSE range: 0.43–1.08) with model efficiency values of 0.94–0.99, indicating very high predictive accuracy.
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A stochastic component was added to quantify uncertainty, giving growers a range of likely outcomes rather than a single prediction — useful for planning under climate variability.
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