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Time-series modeling and forecasting of sugarcane yield in Haryana

KrishiKosh

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Title Time-series modeling and forecasting of sugarcane yield in Haryana
 
Creator Sanjeev
 
Contributor Verma, Urmil
 
Subject Yields, Sugarcane, Forecasting, Crops, Environmental degradation, Productivity, Yield forecasting, Land resources, Biological Phenomena, Seasons
 
Description Crop yield forecasting is one of the most important aspects of agricultural statistics system. An
efficient crop forecasting infrastructure is pre-requisite for information system about food supply, especially
export–import policies, procurement and price-fixation. The study has been categorized into two parts i.e.
the development of ARIMA and ARIMAX models for sugarcane yield estimation in Karnal, Ambala and
Kurukshetra districts of Haryana. The ARIMA models have been fitted using the time-series sugarcane yield
data for the period 1966-67 to 2009-10 of Karnal and Ambala districts and 1972-73 to 2009-10 of
Kurukshetra district. However, the fortnightly weather data taken from the study conducted by Verma et al.,
2011 have been utilized as input series from 1978-79 to 2009-10 for ARIMAX model building. Models have
been validated using the data on subsequent years i.e. 2010 to 2014, not included in the development of the
models. ARIMA(0,1,1) for Karnal and Ambala districts and ARIMA(1,1,0) for Kurukshetra district have
been fitted for sugarcane yield forecasting. Secondly, the ARIMA models with alternative combinations of
explanatory (weather) variables were tried for fitting the ARIMAX models. Following the steps required in
SAS; ARIMA(0,1,1) for Karnal & Ambala and ARIMA(1,1,0) for Kurukshetra districts along with
fortnightly weather variables (viz., tmx9, tmx11, arf10, arf11 over the crop growth period) as input series were
utilized in fitting the ARIMAX models for pre-harvest sugarcane yield estimation.
ARIMA and ARIMAX models individually could provide the suitable relationship(s) to reliably
estimate the sugarcane yield. The predictive performance(s) of the contending models were observed in
terms of the percent deviations of sugarcane yield forecasts in relation to the observed yield(s) and root mean
square error(s) as well. The level of accuracy achieved by ARIMA model(s) with weather as input series was
considered adequate for estimating the sugarcane yield(s) i.e. the ARIMAX models consistently showed the
superiority over ARIMA models in capturing the percent relative deviations pertaining to sugarcane yield
forecasts. The ARIMAX models performed well with lower error metrics as compared to the ARIMA
models in all time regimes. Five-steps ahead (out–of-model development period(s) i.e. 2010, 2011, 2012,
2013 and 2014) estimated values of sugarcane yield(s) favour the use of ARIMAX models to get the shortterm
forecasts of sugarcane yield in the districts under consideration.
 
Date 2016-10-19T09:09:40Z
2016-10-19T09:09:40Z
2015
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/80919
 
Language en
 
Format application/pdf
 
Publisher CCSHAU