Objectives This study aims to investigate the combined effects of biochar and nitrogen fertilizer on the growth dynamics of rice leaf area index (LAI) and aboveground biomass, and to compare the simulation accuracy of Logistic growth models driven by different environmental factors. The findings are expected to provide a theoretical basis for optimizing fertilization regimes in rice fields and identifying the primary drivers of rice growth processes.

Methods Field observations were conducted at the Agricultural Meteorological Experimental Station of Nanjing University of Information Science and Technology from June to October 2023. A two-factor randomized block design was adopted, with four nitrogen application rates (0, 180, 225, and 300 kg/hm², denoted as N0, N180, N225, and N300, respectively) and three biochar application rates (0, 15, and 30 t/hm², denoted as B0, B15, and B30, respectively), resulting in a total of 12 treatments. The changes in rice leaf area index and aboveground biomass under different combinations of biochar and nitrogen fertilizer were analyzed. Normalized Logistic growth models were established using effective cumulative temperature, radiation heat accumulation, and climate suitability as independent variables, respectively, and the simulation accuracy of different models for rice leaf area index and aboveground biomass was compared.

Results Compared with the conventional nitrogen application treatment, the combined application of biochar and nitrogen fertilizer significantly increased rice leaf area index and aboveground biomass, with increases of 15.951%−25.897% for leaf area index and 16.028%−36.127% for aboveground biomass. Logistic model based on the three independent variables all showed good simulation performance. For the LAI models, the average coefficient of determination (R²) was greater than 0.94, the average relative root mean square error (RRMSE) ranged from 0.1 and 0.2, and the root mean square error (RMSE) was less than 10%, indicating high simulation accuracy, among which the effective cumulative temperature model performed best. For the aboveground biomass models, the average R² exceeded 0.99, and both RMSE and RRMSE were less than 0.1, indicating extremely high simulation accuracy, with the climate suitability model showing the best performance. Quantitative analysis based on the aboveground biomass models showed that the combined application of biochar and nitrogen fertilizer advanced the rapid growth period of rice aboveground biomass and increased the average growth rate during the rapid growth period. Although the B15N225 treatment had a slightly lower average growth rate during the rapid growth period than the B15N180 treatment, its rapid growth lasted longer and resulted in highest observed aboveground biomass. Therefore, the B15N225 treatment was identified as the optimal biochar-nitrogen fertilizer combination for promoting rice aboveground biomass accumulation.

Conclusions The combined application of biochar and nitrogen fertilizer significantly promoted the growth of rice leaf area and aboveground biomass by advancing the rapid growth period and improving the average growth rate during this stage. Compared with the radiation heat accumulation method and climate suitability method, the effective cumulative temperature method achieved higher accuracy in simulating LAI dynamics, indicating that temperature was the primary driving factor for rice leaf area development. In contrast, the climate suitability method showed higher accuracy in simulating aboveground biomass dynamics than the effective accumulated temperature and radiation heat accumulation methods, suggesting that the comprehensive effects of temperature and relative humidity had a more significant effect on rice biomass.