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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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Original Research Articles

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 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(8): 2517-2527
DOI: https://doi.org/10.20546/ijcmas.2018.708.256


Modeling Wheat Yield and Weather Variability using Classification and Regression Tree Approach in Samastipur District of Bihar
Nidhi, S.P. Singh and Subhash Kumar
Department of SMCA, FBSH, Dr. Rajendra Prasad Central Agriculture University, Pusa (Samstipur), Bihar, India
*Corresponding author
Abstract:

Climate change continues to have major impact on crop productivity all over the world. Researchers have evaluated the possible impact of global warming on crop yields. Predicting the potential effects of climate change on crop yields requires a model of crops respond to weather. Techniques commonly used for wheat yield estimation employ weather data over the growing season. Improved understanding of the potential effects of climate change on crop yields enables to plan for appropriate and timely responses. This study is to investigate how climate variability affects wheat yield at its different growth stages. Classification and regression tree (CART) analytical approach has been used to identify the relative importance of various weather parameters at different growth stages that are expected to affect the yield. Results from the CART models were able to explain 45 to 65% of the yield variability at different growth stages. Maximum temperature, relative humidity in morning and evaporation were found to be the important variables at most of the growth stages determining the yield variability. Increase in morning relative humidity during tillering, dough and maturity stages was observed to have a favorable impact on wheat yield. However an increase in maximum temperature above 24°C during the period of crown root initiation and ear head emergence led to decline in yield. CART proved a useful tool for arriving at less formal statistical inference that is expected to be comprehensible for the farmers as well.


Keywords: Wheat yield variability, Climate change, Crop growth stages; CART analysis
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How to cite this article:

Nidhi, S. P. Singh and Subhash Kumar. 2018. Modeling Wheat Yield and Weather Variability using Classification and Regression Tree Approach in Samastipur District of Bihar.Int.J.Curr.Microbiol.App.Sci. 7(8): 2517-2527. doi: https://doi.org/10.20546/ijcmas.2018.708.256