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Improving High-Latitude Rice Nitrogen Management with the CERES-Rice Crop Model

机译:利用CERES-水稻作物模型改善高纬水稻的氮素管理

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Efficient use of nitrogen (N) fertilizer is critically important for China’s food security and sustainable development. Crop models have been widely used to analyze yield variability, assist in N prescriptions, and determine optimum N rates. The objectives of this study were to use the CERES-Rice model to simulate the N response of different high-latitude, adapted flooded rice varieties to different types of weather seasons, and to explore different optimum rice N management strategies with the combinations of rice varieties and types of weather seasons. Field experiments conducted for five N rates and three varieties in Northeast China during 2011–2016 were used to calibrate and evaluate the CERES-Rice model. Historical weather data (1960–2014) were classified into three weather types (coolormal/warm) based on cumulative growing degree days during the normal growing season for rice. After calibrating the CERES-Rice model for three varieties and five N rates, the model gave good simulations for evaluation seasons for top weight ( R 2 ≥ 0.96), leaf area index ( R 2 ≥ 0.64), yield ( R 2 ≥ 0.71), and plant N uptake ( R 2 ≥ 0.83). The simulated optimum N rates for the combinations of varieties and weather types ranged from 91 to 119 kg N ha ?1 over 55 seasons of weather data and were in agreement with the reported values of the region. Five different N management strategies were evaluated based on farmer practice, regional optimum N rates, and optimum N rates simulated for different combinations of varieties and weather season types over 20 seasons of weather data. The simulated optimum N rate, marginal net return, and N partial factor productivity were sensitive to both variety and type of weather year. Based on the simulations, climate warming would favor the selection of the 12-leaf variety, Longjing 21, which would produce higher yield and marginal returns than the 11-leaf varieties under all the management strategies evaluated. The 12-leaf variety with a longer growing season and higher yield potential would require higher N rates than the 11-leaf varieties. In summary, under warm weather conditions, all the rice varieties would produce higher yield, and thus require higher rates of N fertilizers. Based on simulation results using the past 20 years of weather data, variety-specific N management was a practical strategy to improve N management and N partial factor productivity compared with farmer practice and regional optimum N management in the study region. The CERES-Rice crop growth model can be a useful tool to help farmers select suitable precision N management strategies to improve N-use efficiency and economic returns.
机译:有效使用氮肥对中国的粮食安全和可持续发展至关重要。作物模型已被广泛用于分析产量变异性,协助制定N处方并确定最佳N比例。这项研究的目的是使用CERES-Rice模型来模拟不同高纬度,适应淹水水稻品种对不同天气类型的氮素响应,并探索结合水稻品种的不同水稻最佳氮素管理策略。和天气类型。使用中国东北地区2011–2016年对5个氮素和3个品种的田间试验进行校准和评估CERES-Rice模型。根据水稻正常生长期的累积生长日数,历史天气数据(1960–2014年)分为三种天气类型(凉/常/暖)。在对三个品种和五个氮比率的CERES-Rice模型进行校准之后,该模型对最高体重(R 2≥0.96),叶面积指数(R 2≥0.64),产量(R 2≥0.71)的评估季节给出了良好的模拟。 ,植物吸收氮(R 2≥0.83)。在55个季节的天气数据中,品种和天气类型组合的模拟最佳氮肥浓度在91至119 kg N ha?1范围内,与该地区的报告值一致。根据农民的实践,区域最佳氮素比率以及针对20个天气数据季节中不同品种和天气季节类型组合模拟的最佳氮素比率,评估了五种不同的氮素管理策略。模拟的最佳氮肥率,边际净收益率和氮偏因子生产率对天气年份的变化和类型均敏感。根据模拟,气候变暖将有利于选择12叶品种龙井21,在所有评估的管理策略下,龙井21的产量和边际收益均高于11叶品种。生长期更长,单产潜力更高的12叶品种比11叶品种需要更高的氮素含量。总之,在温暖的天气条件下,所有水稻品种将产生更高的产量,因此需要更高比例的氮肥。基于过去20年天气数据的模拟结果,与研究区域的农民实践和区域最佳氮管理相比,针对特定品种的氮管理是提高氮管理和氮分项生产力的实用策略。 CERES-Rice作物生长模型可以作为帮助农民选择合适的精确氮素管理策略以提高氮素利用效率和经济回报的有用工具。

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