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Air temperature variations and rice productivity in Bangladesh: a comparative study of the performance of the YIELD and the CERES-Rice models

机译:孟加拉国的气温变化和稻米生产力:YIELD和CERES-Rice模型的性能比较研究

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Potential increase in air temperature due to climatic change and inter-annual climatic variability and its impacts on crop productivity is of major concern to crop scientists. A number of physically-based models have been developed and applied to estimate crop-environment relationships. In the present study the performance of two such models (the YIELD and the CERES-Rice) are discussed. These two models are used to estimate bore rice productivity under normal and abnormal climate scenarios in Bangladesh. This study finds that bore rice productivity at Mymensingh predicted by the YIELD is higher than the prediction by the CERES-Rice. Productivity estimates for Barisal by these two models are almost identical. Assumptions of non-identical management practices, different soil characterization procedures, different methods for calculation of dry matter production by these two models and the range of diurnal temperature variations played an important role in productivity estimates. The YIELD model predicted the lengths of the growing season under the normal and abnormal thermal climate conditions and they are to be shorter than the lengths predicted by the CERES-Rice model. The YIELD model's assumption of higher threshold temperature and a relatively simple relationship between phenology and air temperature has produced such estimations (shorter growing season). The complex data required by CERES-Rice may be an impediment for its extensive use. If input data for the CERES-Rice is not available, the YIELD model can be considered as a possible tool for various applications in crop-environment relationships. (C) 1998 Elsevier Science B.V. All rights reserved. [References: 43]
机译:由于气候变化和年际气候变化而造成的气温潜在升高及其对作物生产力的影响是作物科学家的主要关切。已经开发了许多基于物理的模型并将其应用于估算作物与环境之间的关系。在本研究中,讨论了两种此类模型(YIELD和CERES-Rice)的性能。这两个模型用于估计孟加拉国正常和异常气候情景下的稻米产量。这项研究发现,YIELD预测的Mymensingh的稻米生产率高于CERES-Rice的预测。这两个模型对Barisal的生产率估计几乎相同。两种管理模式的假设不一致,不同的土壤表征程序,不同的干物质生产计算方法以及昼夜温度变化范围在生产率估算中起着重要作用。 YIELD模型预测了正常和异常热气候条件下的生长季节长度,并且比CERES-Rice模型预测的长度短。 YIELD模型假设阈值温度较高,并且物候与气温之间的关系相对简单,因此得出了这样的估计(生长季节较短)。 CERES-Rice所需的复杂数据可能会妨碍其广泛使用。如果CERES-Rice的输入数据不可用,则可以将YIELD模型视为作物与环境关系中各种应用的可能工具。 (C)1998 Elsevier Science B.V.保留所有权利。 [参考:43]

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