巴基斯坦水稻产量投入研究的统计模型及其意义

Muhammad Islam, R. Siddiqui
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引用次数: 0

摘要

水稻产量下降和人口增长趋势是巴基斯坦面临的一个切实问题。目前的研究基于从旁遮普作物报告服务处收集的横断面数据。应用多元线性回归(MLR)模型对水稻作物增产的显著因素进行了研究。输入变量,即拥有的土地,种子率,DAP,尿素,no。水,不。犁,没有。在水稻产量的MLR模型中,研究了水稻产量水平、作物生育期天数、其他肥料、品种超适性、种子类型适性、喷施适性和病害侵袭适性。除土地、水平、作物寿命和超级品种外,其余因子均具有统计学显著性。发现Adj R2为0.422,与横截面数据拟合良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Modeling and Significance of Inputs Studies for the Rice Crop Productivity in Pakistan
Lower production of rice crop and increasing population trend is a tangible question for Pakistan. The current study based cross-sectional data collected from crop reporting service Punjab. The multiple linear regression (MLR) model is applied to investigate the significant factor for rice crop yield enhancement. The inputs variable i.e. owned land, seed rate, DAP, Urea, no. of water, no. of ploughs, no. of levels, crop life periods days, other fertilizers, variety super yes or no, seed type yes or no, spray no or yes and disease attack yes or no are studied in MLR model for rice productivity. All the factors found to be statistical significant except land, level, crop life period and super variety. Adj R2 is found to be 0.422 and it is good fit for cross-sectional data.
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