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Development of Weather based Yield Models for Wheat Crop in Western Zone of Haryana


Affiliations
1 Department of Mathematics and Statistics, CCSHAU, Hisar, Haryana, India
2 Department of Agricultural Economics, CCS HAU, Hisar, Haryana, India
     

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Based on weather data from 1980-1981 to 2013-2014 for the districts of Hisar, Bhiwani, and Sirsa, as well as from 1997-1998 to 2011-2012 for the district of Fatehabad, the western zone of Haryana has generated zonal wheat yield models. Multiple linear regression and main component analysis were employed to achieve this objective. The models' validity was confirmed for the post-sample years 2014-15, 2015-16, 2016-17, 2017-18, and 2018-19. The overall results show a preference for using prediction equations based on principal component analysis for recording % deviations from real-time yields. The zonal weather models can forecast the district-level wheat production four to five weeks before crop harvest.

Keywords

multiple linear regression, Eigen values, PC components, higher loading displaying weather variables
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  • Development of Weather based Yield Models for Wheat Crop in Western Zone of Haryana

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Authors

Chetna
Department of Mathematics and Statistics, CCSHAU, Hisar, Haryana, India
Pushpa
Department of Mathematics and Statistics, CCSHAU, Hisar, Haryana, India
Aditi
Department of Mathematics and Statistics, CCSHAU, Hisar, Haryana, India
Nisha
Department of Agricultural Economics, CCS HAU, Hisar, Haryana, India
Ajay Sharma
Department of Mathematics and Statistics, CCSHAU, Hisar, Haryana, India
Monika Devi
Department of Agricultural Economics, CCS HAU, Hisar, Haryana, India

Abstract


Based on weather data from 1980-1981 to 2013-2014 for the districts of Hisar, Bhiwani, and Sirsa, as well as from 1997-1998 to 2011-2012 for the district of Fatehabad, the western zone of Haryana has generated zonal wheat yield models. Multiple linear regression and main component analysis were employed to achieve this objective. The models' validity was confirmed for the post-sample years 2014-15, 2015-16, 2016-17, 2017-18, and 2018-19. The overall results show a preference for using prediction equations based on principal component analysis for recording % deviations from real-time yields. The zonal weather models can forecast the district-level wheat production four to five weeks before crop harvest.

Keywords


multiple linear regression, Eigen values, PC components, higher loading displaying weather variables