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首页> 外文期刊>Field Crops Research >Decline in rice grain yields with temperature: models and correlations can give different estimates.
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Decline in rice grain yields with temperature: models and correlations can give different estimates.

机译:水稻籽粒产量随温度下降:模型和相关性可以得出不同的估计值。

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摘要

Based on an analysis of yield and weather data for the years 1992-2003, it has been suggested that rice crop models are inadequate because they fail to predict that rice yields decline by 15% degrees C-1 (mean daily air temperature) or 10% degrees C-1 (mean minimum temperature), temperatures averaged over the crop growth duration (about 100 days). We investigate that claim. A mechanistic and an empirical model of rice crop growth were used to make predictions of yield using the same weather data sets used in the regression analyses that supported the 15 and 10% claims. The models were used to predict yield with temperature changed by -2, -1, 0, +1 and +2 degrees C relative to the average for all the years (26 degrees C) with solar radiation held constant. Over the 4 degrees C temperature range, ORYZA2000 and EEQ predicted yield declines of about 0.37 and 0.71 t ha-1 degrees C-1 (3.5 and 7.6% degrees C-1 from the base yield at 26 degrees C). When the actual weather data for each year were used in the models, there was no significant relationship between the predictions for each year and mean daily air temperature. Even though minimum temperature was not used for the simulation of any processes in the models, predicted grain yields were significantly correlated with minimum temperature. The slope of the regression line between predicted yield and minimum temperature for the models gave a yield decline of about 1.5 t ha-1 degrees C-1 (which was 13.7% degrees C-1 from the base yield at a minimum temperature of 22.1 degrees C). When the weather data for the years 1992-2003 were analysed, there was a significant negative correlation between solar radiation and minimum temperature. The lowest yields occurred in the wettest years and there was a significant negative relationship between harvest index and rainfall. We conclude that temperature responses of the models are adequate for predicting the observed results. Crop responses to temperature (below the high temperatures that cause infertility in rice) are of the order of -0.5 t ha-1 degrees C-1 (or about -6% degrees C-1 at the base yield at average mean daily temperature of 26 degrees C), once they are separated from the effects of other environmental factors. Yield declines calculated by regression from selected weather elements can be misleading because of correlations among the weather elements..
机译:根据对1992年至2003年的单产和天气数据的分析,有人提出水稻作物模型不充分,因为它们无法预测水稻单产下降了15%C-1(平均每日气温)或10。 %C-1(平均最低温度),整个作物生长期间(约100天)的平均温度。我们对此索赔进行了调查。使用水稻作物生长的机械模型和经验模型,使用支持15%和10%声明的回归分析中使用的相同天气数据集来进行产量预测。该模型用于预测相对于所有年(26摄氏度)的平均值在温度保持恒定的情况下温度相对于-2,-1、0,+ 1和+2摄氏度变化的产量。在4摄氏度的温度范围内,ORYZA2000和EEQ预测单产下降约0.37和0.71 t ha-1摄氏度(与26摄氏度的基础产量相比分别下降3.5和7.6%摄氏度)。在模型中使用每年的实际天气数据时,每年的预测与平均每日气温之间没有显着关系。即使模型中没有使用最低温度来模拟任何过程,但预测的谷物产量仍与最低温度显着相关。模型的预测产量和最低温度之间的回归线斜率给出了约1.5 t ha-1 C-1的产量下降(与最低温度22.1度时的基本产量相比降低了13.7%C-1 C)。在分析1992-2003年的天气数据时,太阳辐射与最低温度之间存在显着的负相关。最低的年份发生在最潮湿的年份,并且收获指数与降雨量之间存在显着的负相关关系。我们得出结论,模型的温度响应足以预测观察到的结果。作物对温度的响应(在引起水稻不育的高温以下)约为-0.5 t ha-1摄氏度-1(或在平均日平均气温为1摄氏度的基础上约为-6%摄氏度-1)一旦将它们与其他环境因素的影响分开,则温度为26摄氏度。由于天气要素之间的相关性,根据所选天气要素进行回归计算得出的产量下降可能会产生误导。

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