Field experiment evaluates nitrogen application strategies for alfalfa yield across different precipitation regimes, suggesting optimal rates.
Scientific nitrogen management is essential for maximizing crop growth potential while minimizing resource waste and environmental impacts. Alfalfa (Medicago sativa L.) is the most widely cultivated high-quality leguminous forage crop globally, and is capable of providing nitrogen through nitrogen fixation. However, there remains some disagreement regarding its nitrogen management strategies. This study conducted a three-year field experiment and calibrated the APSIM-Lucerne model. Based on the calibrated model, three typical precipitation year types (dry, normal, and wet years) were selected. Combining field experiments, eight nitrogen application scenarios (0, 80, 120, 140, 160, 180, 200, and 240 kg·ha−1) were set up. With the objectives of increasing alfalfa yield, nitrogen partial productivity, and nitrogen agronomic efficiency, this study investigates the appropriate nitrogen application thresholds for alfalfa under different precipitation year types. The results showed the following: (1) Alfalfa yield increased first and then decreased with the increase in nitrogen application level. The annual yield of the N160 treatment was the highest (13.39 t·ha−1), which was 5.15% to 32.39% higher than that of the other treatments. (2) The APSIM-Lucerne model could well reflect the growth process and yield of alfalfa under different precipitation year types. The R2 and NRMSE between the simulated and observed values of the former were 0.85–0.91 and 5.33–7.44%, respectively. The R2 and NRMSE between the simulated and measured values of the latter were 0.74–0.96 and 2.73–5.25%, respectively. (3) Under typical dry, normal, and wet years, the optimal nitrogen application rates for alfalfa yield increases were 120 kg·ha−1, 140 kg·ha−1, and 160 kg·ha−1, respectively. This study can provide a basis for precise nitrogen management of alfalfa under different precipitation year types.
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Wang et al. (2025) studied this question.
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