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Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/8221
Title: Forecasting of growth rates of wheat yield of Uttar Pradesh through non-linear growth models
Other Titles: Not Available
Authors: Sanjeev Panwar
K.N. Singh
Anil Kumar
Susheel Kumar Sarkar
Ranjeet Paul
Abhishek Rathore
N. Sivaramane
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Indian Agricultural Statistics Research Institute
ICRISAT
ICAR::National Academy of Agricultural Research and Management
Published/ Complete Date: 2014-07-01
Project Code: Not Available
Keywords: Forecasting
Gauss Newton method
Goodness of fit
Non-linear growth models
Nonlinear growth rate
Randomness
Theil statistic
Publisher: Indian Council of Agricultural Research, New Delhi
Citation: Panwar, Sanjeev, singh, K.N., Kumar, Anil, Sarkar, Susheel Kumar, Paul, Ranjeet, Rathore, Abhishek, and Sivaramane, N. (2014). Forecasting of growth rates of wheat yield of Uttar Pradesh through non-linear growth models. Indian Journal of Agricultural Sciences, 84 (7), 856–9.
Series/Report no.: Not Available;
Abstract/Description: Wheat production in India is about 70 million tonnes per year which counts for approximately 12 per cent of world’s production. Being the second largest in population, it is also the second largest in wheat consumption after China, with a huge and growing wheat demand. Major wheat growing states in India are Uttar Pradesh, Punjab, Haryana, Rajasthan, Madhya Pradesh, Gujarat and Bihar. All of north is replenished with wheat cultivation. Uttar Pradesh, the largest wheat growing region of the country, produces around 28 million tonnes of wheat and Bihar produces around 5 million tonnes. The usual parametric approach for growth rate analysis is to assume multiplicative error in the underlying nonlinear geometric model and then fit the linearized model by ‘method of least squares’. This paper deals with a critical study of wheat yield of Uttar Pradesh with a non-linear approach. The available data of rice during different years is taken into consideration and different statistical models are fitted for that. The time series data on annual yield of wheat in UP from 1970-2010 were collected from various sources. Growth rates are computed through non-linear models, viz. Logistic, Gompertz and Monomolecular models. Different nonlinear procedures such as Gauss-Newton Method, Steepest-Descent Method, Levenberg-Merquadt Technique and Do Not Use Derivative (DUD) Method were used in this study to estimate the nonlinear growth rates. The results showed that logistic model performed better followed by Gompertz and monomolecular.
Description: Not Available
ISSN: Not Available
Type(s) of content: Research Paper
Sponsors: Not Available
Language: English
Name of Journal: Indian Journal of Agricultural Sciences
NAAS Rating: 6.21
Volume No.: 84 (7)
Page Number: 856-859
Name of the Division/Regional Station: Not Available
Source, DOI or any other URL: http://epubs.icar.org.in/ejournal/index.php/IJAgS/article/view/42005/18669
URI: http://krishi.icar.gov.in/jspui/handle/123456789/8221
Appears in Collections:AEdu-IASRI-Publication

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