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This study proposes a method for generating virtual samples using a weather generator and crop model to address the scarcity of low-temperature stress samples in winter wheat. Firstly, simulated meteorological data is generated using the weather generator, and then virtual meteorological yield and leaf area index (LAI) from jointing to heading stages are calculated using the crop model. These virtual samples integrate location information from weather stations, low-temperature statistics derived from simulated meteorological data, LAI data, and corresponding simulated meteorological yields. The impact of low-temperature stress on these virtual samples is assessed based on computed statistical data. Validation using real data from Henan Province confirms the similarity between generated low-temperature virtual samples and a low-temperature stress test set. The effectiveness of the created low-temperature …