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- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
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Vol. 12, Issue 2 (2023)
Forecasting of chickpea yield using nonlinear model in Darbhanga district of Bihar
Author(s):
Mahesh Kumar and Kalyan Singh Paikra
Mahesh Kumar and Kalyan Singh Paikra
Abstract:
This research paper entitled “Forecasting of Chickpea yield using nonlinear model in Darbhanga district of Bihar” is based on the secondary data. Data was collected for the years 1966 to 2017 from the official sites of Department of Statistics and Economics of Bihar and ICRISAT, Hyderabad for achieving objective, data from 1966 to 2015 were analysed through R- Software and two years data 2016 and 2017 were kept for model validation of yield forecasting of Chickpea in Darbhanga district. For forecasting chickpea yield in Darbhanga district of Bihar, three different nonlinear models namely Logistic, Gompertz and Monomolecular were used.
This research paper entitled “Forecasting of Chickpea yield using nonlinear model in Darbhanga district of Bihar” is based on the secondary data. Data was collected for the years 1966 to 2017 from the official sites of Department of Statistics and Economics of Bihar and ICRISAT, Hyderabad for achieving objective, data from 1966 to 2015 were analysed through R- Software and two years data 2016 and 2017 were kept for model validation of yield forecasting of Chickpea in Darbhanga district. For forecasting chickpea yield in Darbhanga district of Bihar, three different nonlinear models namely Logistic, Gompertz and Monomolecular were used.
All three non-linear models were fitted to data by using Statistical software R. For validation of assumptions of residuals i.e., randomness and normality of residuals, Run’s test and Shapiro wilk’s tests were employed respectively while for goodness of fit and validation of models, Chi-square test and eight steps ahead forecasting were done. For getting best fitted models for forecasting yield, models are compared by seven different statistics R2, RSS, MAPE, MAE, MSE, RMSE. So, after analysing the data, Logistic model is found better for Darbhanga district (Bihar) with FE% of 0.89% and 3.57% for year 2016 and 2017 respectively. Forecasting of chickpea yield is made for 2023 will be 1.18 t/h. Forecasting model of chickpea yield is best fitted model (i.e. Logistic) as below.
Ŷ =1.3613/(1+(1.3613/0.3684-1) *exp(-0.0497*t))
Pages: 1900-1905 | 282 Views 158 Downloads
How to cite this article:
Mahesh Kumar, Kalyan Singh Paikra. Forecasting of chickpea yield using nonlinear model in Darbhanga district of Bihar. Pharma Innovation 2023;12(2):1900-1905.
Journal code(s)
- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
Main Menu
Special Issue
Copyright Form
Identifier
The Pharma Innovation Journal
