A multiple regression model for predicting groundnut (Arachis hypogea L.) yields in arid zones using weather parameters. (477)

Authors

  • M.G. Ramakrishna Reddy Agricultural Research Station (Dry Farming) DCMS Building, Andhra Pradesh Agricultural University, Anantapur 515 001, India
  • M. Murali Rao Agricultural Research Station (Dry Farming) DCMS Building, Andhra Pradesh Agricultural University, Anantapur 515 001, India
  • S.K. Krishna Murthy Agricultural Research Station (Dry Farming) DCMS Building, Andhra Pradesh Agricultural University, Anantapur 515 001, India

Keywords:

Multiple regression model, Groundnut, Arid zones, Weather parameters

Abstract

The weather parameters used in developing a simulation model for predicting groundnut (Arachis hypogaea L.) pod yields under rainfed conditions were total rainfall (mm), total number of rainy days, total number of dry days, and maximum and minimum temperatures (°C) for the period from pod development to maturity. A comparison of simulation and observed pod yields of groundnut in 1992 and 1993 showed that a multiple regression simulation model can be used to estimate the pod yields under rainfed conditions with a reasonable degree of accuracy even before crop harvest. A close relationship between pod yields and weather parameters was established (R2 = 0.93). A simulation model was developed with the data for 1992 and 1993 and the model was found to be a suitable fit for the arid region of Anantapur.

Issue

Section

Research Notes