Predictive Modeling Study on the Critical Nitrogen Concentration and Accumulation in Cut Chrysanthemum Based on the Cumulative Photo-Thermal Effect

Critical nitrogen concentration (Nc) and accumulation (Na) throughout the entire growth period are key indicators for diagnosing N status and implementing precision N management in cut chrysanthemum. However, direct measurement of these two parameters is both time-consuming and destructive, and establishing accurate predictive models is fundamental to their practical application. From May 2021 to July 2022, five N-gradient experiments (ranging from 14 to 574 mgf·plant−1) were conducted on the cut chrysanthemum cultivar ‘Nannong Xiaojinxing’. Predictive models for Nc and Na were developed using environmental light and temperature data during growth as driving variables. The results showed that the aboveground dry matter (DM) prediction model, which utilized the cumulative photo-thermal effect (PTE) derived from these environmental factors, demonstrated superior accuracy compared to models relying on conventional driving variables. Subsequently, the Nc and Na prediction models were established with DM as the driving variable. These models indicated that at a DM level of 1 g·plant−1, Nc and Na values were 4.53% and 45.30 mg·plant−1, respectively. The Na reached a maximum of 236.50 mg·plant−1 at the flower harvesting stage, representing the minimum N accumulation required for optimal floral quality. Using the dry matter model as a process-based model, we successfully developed predictive models for Nc and Na driven by PTE. Validation using independent experimental data confirmed the models’ high predictive accuracy, with coefficients of determination of 0.9378 and 0.9612, and low errors—root mean square errors of 0.2736% and 19.18 mg·plant−1, and normalized RMSE of 10.79% and 14.94%, respectively. These models provide a foundation for implementing precision N management and reducing fertilizer application in cut chrysanthemum production.