...
首页> 外文期刊>International Journal of Agricultural and Statistical Sciences >MODELS FOR STUDYING RELATIONSHIP BETWEEN RAPESEED & MUSTARD YIELD AND WEATHER VARIABLES
【24h】

MODELS FOR STUDYING RELATIONSHIP BETWEEN RAPESEED & MUSTARD YIELD AND WEATHER VARIABLES

机译:芥末产量与天气变量关系的模型

获取原文
获取原文并翻译 | 示例
           

摘要

Various statistical models to study the effect of weather variables on rapeseed & mustard yield at different stages of crop and to forecast its yield for Faizabad District have been attempted. Time series data on yield for rapeseed & mustard crop 6f Faizabad district of Uttar Pradesh for 22 years (1990-91 to 2011 -12) have been used. Weekly weather data for the period (1991 -2012) on six weather variables viz. Minimum Temperature, Maximum Temperature, Relative Humidity at 7 hour, Relative Humidity at14 hour, Sun-shine hours and Wind-Velocity of Faizabad district have been utilised for the present study. Various models have been tried to know the relationship between rapeseed & mustard crop yield by generating new weather indices from weekly data. In all, eight statistical models were developed. The model involving total of value of weather variable over weeks and linear functions of respective correlation coefficients between adjusted crop yield for trend effect and weekly data and weather variables as the independent variables has been found to be the best one (model VII & VIII) for studying the effect of individual weather variables. A forecast model has been developed to forecast the pre-harvest crop yield. The results revealed that forecast at 21st week of the crop period i.e. during third week of February before one and half months of its harvest was found to be reliable one as percent standard errbr of forecast was obtained to be approximately 4 percent.
机译:研究了各种统计模型,研究了对不同作物阶段的油菜和芥末产量的效果,并试图预测其对Faizabad区的收益率。已经使用了22岁(1990-91至2011年)的北方牛头群岛6夫一刚刚苏拔巴德区的油菜籽和芥末作物6夫·佛罗里达州地区的产量序列数据。每周天气数据(1991 -2012)六个天气变量viz。最低温度,最高温度,相对湿度在7小时,相对湿度为14小时,阳光亮光小时和FAIZABAD区的风速已经用于本研究。通过从每周数据生成新的天气指数,已经试图了解油菜和芥末作物产量之间的关系。总而言之,开发了八种统计模型。涉及周数变量值的模型,在各个相关系数之间的调整后作物产量与每周数据和天气变量之间的相应相关系数的线性函数,作为独立变量,是最好的一个(型号vii&viii)研究个体天气变量的效果。已经开发了预测模型来预测收获前作物产量。结果表明,在一周的第21周的21天内预测,在2月的第三周之前,发现其收获的一个半月是可靠的,因为获得预测的标准误差百分比约为4%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号