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Development of yield forecast model using multiple regression analysis and impact of climatic parameters on spring wheat

作     者:Purbasha Mistry Ganesh Bora 

作者机构:Natural Resources ManagementNorth Dakota State UniversityFargoND 58102USA Agricultural and Biological Engineering DepartmentMississippi State UniversityStarkvilleMS 39762USA 

出 版 物:《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报(英文))

年 卷 期:2019年第12卷第4期

页      面:110-115页

核心收录:

学科分类:09[农学] 0901[农学-作物学] 

主  题:yield forecast modelling multiple regression climatic parameters spring wheat 

摘      要:Understanding the impacts of climate change in agriculture is important to ensure optimal and continuous crop *** agricultural sector plays a significant role in the economy of Upper Midwestern states in the USA,especially that of North Dakota(ND).Spring wheat contributes most of the wheat production in ND,which is a major producer of wheat in the *** study focuses on assessing possible impacts of three climate variables on spring wheat yield in ND by building a regression ***-five years of field data were collected and the trend of average minimum temperature along with average maximum temperature,average precipitation,and spring wheat yield was analyzed using Mann-Kendall *** study area was divided into 9 divisions based on physical *** minimum temperature plays an important role in the region as it impacts the physiological development of the *** trend was noticed for 6 divisions for average minimum temperature and average precipitation during growing *** and Southeast division showed the strongest increasing trend for average minimum temperature and average precipitation,***-central division had the most decreasing trend for average maximum temperature.A significant relationship was established between spring wheat yield and climatic parameters as the p-value is lower than 0.05 level which rejects the null *** regression model was tested for forecasting *** percentage deviation of error for the model is approximately±30%in most of the years.

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