National Academy of Agricultural Sciences (NAAS)
|
PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Parameter estimation in statistical modelling plays a crucial role in the real world phenomena. Several alternative analyses may be required for the purpose. An attempt has been made in this paper to estimate the yield of wheat crop using principal components of the weather parameters spread over the crop growth period. Principal component analysis has been used for the purpose of developing zonal yield forecast models because of multicollinearity present among weather variables. The results indicate the possibility of district-level wheat yield prediction, 4-5 weeks ahead of the harvest time in Haryana, India. Zonal weather models had the desired predictive accuracy and provided considerable improvement in the district-level wheat yield estimates. The estimated yield(s) from the selected models indicated good agreement with State Department of Agriculture (DOA) wheat yield(s) in most of the districts.
Citations |
 |
 |
 |
 |
