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首页> 外文OA文献 >Studies for Predicting the Amount of Each Yield Component in Paddy Rice by Meteorological Conditions in Japan. II Relations among Thousand-Kernel-Weight, Grain Yield and Meteorological Conditions.
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Studies for Predicting the Amount of Each Yield Component in Paddy Rice by Meteorological Conditions in Japan. II Relations among Thousand-Kernel-Weight, Grain Yield and Meteorological Conditions.

机译：日本通过气象条件预测稻米中各产量成分含量的研究。 II千粒重，粮食产量与气象条件之间的关系。

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In the paper, the relations among the thousand-kernel-weight, the gross-grain-yield and the meteorological elements after the heading date were examined by the statistical methods. The routine crop experiment data by Statistics and Information Department of Ministry of Agriculture and Forestry from 1968 to 1982 were used for analyses as same as in the previous paper (Liu et al., 1988). The results obtained in the analyses can be summarized as follows: (1) The fraction of grain yield which fluctuated due to the change in thousand-kernel-weight was estimated by about 50f the total. (2) The increasing rate of thousand-kernel-weight was affected greatly by meteorological conditions for 35 days after the heading date. (3) The increasing rate increased straightly after the heading date and reached to its maximum rate during 13 to 18 days after the heading data. Thereafter, it decreased gradually, and the thousand-kernel-weight ripened by 9527777750420f the final thousand-kernel-weight on around 30th to 35th day after the heading date. (4) The positive correlation was recognized among the increasing rate on 10th day after the heading date and the mean maximum air temperature for 5 days from 5th to 10th day and the mean air temperature and the mean duration of sunshine for 10 days after the heading date.. (5) The correlation coefficient between the relative thousand-kernel-weight and the effective accumulated temperature higher than 10℃ was 0.996, and the accumulated value needed for perfect ripening was 800 to 900 degree-days. (6) Days of ripening period was affected mainly by temperature for first 20 to 30 days after the heading date. (7) Some estimating models for the thousand-kernel-weight were constructed by the multiple regression analysis with backward elimination method. The model constructed by using the meteorological data for a longer period from heading date brought about better estimates than that of for a shorter period. (8) By using the yield components, a model to estimate the grain yield could be const
机译：本文采用统计方法研究了抽穗期后千粒重，总产与气象要素之间的关系。与以前的论文（Liu et al。，1988）相同，使用了农业和林业部统计信息局从1968年至1982年的常规作物试验数据。分析得出的结果可归纳如下：（1）估计由于千粒重的变化而波动的谷物产量的总和约为50f。 （2）抽穗日期后35天内，气象条件极大地影响了千粒重的增长速度。 （3）抽穗日期结束后，增加率直线上升，在抽穗数据结束后的13至18天内达到最高值。此后，它逐渐减少，并且在抽穗日期后的第30到35天左右，千粒重达到9527777750420f的最终千粒重。 （4）抽穗日后第10天的增长率与第5天至第10天的5天的平均最高气温以及抽穗后10天的平均气温和平均日照时间之间存在正相关关系（5）相对千粒重与10℃以上的有效积温之间的相关系数为0.996，完全成熟所需的积温为800至900度日。 （6）抽穗日期后的前20至30天，成熟期的天数主要受温度影响。 （7）采用后向消除法进行多元回归分析，建立了千粒重的一些估计模型。从航向算起，使用较长时间的气象数据所建立的模型比较短时间的模型具有更好的估计。 （8）通过使用产量成分，估计谷物产量的模型可以是常数

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