ANALYSIS OF SPATIAL AND TEMPORAL VARIATIONS IN AREA, PRODUCTION AND PRODUCTIVITY OF TOBACCO IN ANDHRA PRADESH
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Date
2016
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Acharya N.G. Ranga Agricultural University
Abstract
An attempt was made to study the spatial and temporal variations in area,
production and productivity of tobacco in the major tobacco growing districts of
Andhra Pradesh viz., Prakasam, Guntur, East Godavari, West Godavari and the
Andhra Pradesh state as a whole. The study was based on 28 years of tobacco
data from 1987 to 2014.
The graphical analysis was used to study the variations in area,
production and productivity of tobacco. An attempt was also made to measure
the growth in area, production and productivity of tobacco with due
consideration of discontinuity in the data.
Generally, the time series data on production of crops often exhibits a
discontinuity in the year to year variations. These disturbances are mainly due to
the impact of technological innovations in the crop. Under this situation, the
conventional time trend models fail to provide efficient forecasts, as these
models are based on the assumption of uniformity in the year to year variations.
To deal with this situation, the spline models were explored for forecasting the
tobacco production, as discontinuity in the year to year variations is the
fundamental assumption in these models.
The graphical analysis indicated that the time series data on area,
production and productivity of tobacco exhibited a discontinuous trend in all the
districts as well as in the state as whole.
The growth analysis revealed that the area of tobacco was increasing in
the districts of Prakasam and West Godavari and there is a considerable decline
in Guntur and East Godavari districts and in the whole state of Andhra Pradesh.
Production of tobacco was increasing in all the districts, except in the district of
East Godavari and there was a considerable increase in the average level of
productivity over the years due to the technological innovations in the crop.
The spline models were found to be relatively efficient than the
conventional trend fitting models in forecasting of tobacco
Description
D5300
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