Changing scenario of Kerala agriculture- an overview
By: Unnikrishnan T.
Contributor(s): Ajitha T K (Guide).
Material type:
BookPublisher: Vellanikkara Department of Agricultural Statistics, College of Horticulture 2009DDC classification: 630.31 Online resources: Click here to access online Dissertation note: MSc Abstract: The present investigations on “Changing scenario of Kerala agriculture – an overview”
was carried out in the Department of Agricultural Statistics, College of Horticulture, Vellanikkara
during 2006 – ’09. The secondary data on area, production, productivity and price of major
crops of Kerala viz; coconut, rubber, paddy(season wise), pepper, cashew, arecanut, coffee,
tapioca and banana collected from the Directorate of Economics and Statistics for the period
from 1952-53 to 2006-07 were used for the analysis. The main objectives of the study
included assessment of trend and growth rates of area, production, productivity and price,
testing of the cointegrated movement of price and respective area of each crop, identification
of the best ARIMA(Auto Regressive Integrated Moving Average) model for prediction of
area, production, productivity and price and comparison of predictability of forecasting models
developed by different techniques.
Modified P-Gan’s method helped to understand whether the growth rate in crop
production was mainly due to area or productivity. The series of prices and areas of respective
crops could be co-integrated and the regression models evolved through this technique resulted
in moderately high values of predictability.
ARIMA models were superior to other models developed achieving a maximum value
of R2 = 99.8% for the prediction of area of rubber with a very low value of MAFPE = 1.23%.
Excellent parsimonious forecasting equations could be generated using the ARIMA technique
for all the crops studied.
The general findings of the study showed that there was a shift in area from food
crops to non-food crops. The production of major food crops, rice and tapioca reached at
negative growth rates due to the declining trend of their areas. But production rate of banana
has increased due to increase in both area and yield. Among cash crops, both area and
productivity growths influenced the production rates. The major cash crops coconut, arecanut
and pepper showed positive growth rates. Compared to food crops, cash crops in general
showed better growth trends in production. Negative growth rate in the production of cashewnut
was due to the decline in area. Among plantation crops, rubber and coffee attained a high
production growth rate due to the combined growth of area and productivity. The highest
production growth rate and area growth rate were recorded by rubber among all the crops
studied.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
Theses
|
KAU Central Library, Thrissur Theses | 630.31 UNN/CH PG (Browse shelf) | Available | 172922 |
MSc
The present investigations on “Changing scenario of Kerala agriculture – an overview”
was carried out in the Department of Agricultural Statistics, College of Horticulture, Vellanikkara
during 2006 – ’09. The secondary data on area, production, productivity and price of major
crops of Kerala viz; coconut, rubber, paddy(season wise), pepper, cashew, arecanut, coffee,
tapioca and banana collected from the Directorate of Economics and Statistics for the period
from 1952-53 to 2006-07 were used for the analysis. The main objectives of the study
included assessment of trend and growth rates of area, production, productivity and price,
testing of the cointegrated movement of price and respective area of each crop, identification
of the best ARIMA(Auto Regressive Integrated Moving Average) model for prediction of
area, production, productivity and price and comparison of predictability of forecasting models
developed by different techniques.
Modified P-Gan’s method helped to understand whether the growth rate in crop
production was mainly due to area or productivity. The series of prices and areas of respective
crops could be co-integrated and the regression models evolved through this technique resulted
in moderately high values of predictability.
ARIMA models were superior to other models developed achieving a maximum value
of R2 = 99.8% for the prediction of area of rubber with a very low value of MAFPE = 1.23%.
Excellent parsimonious forecasting equations could be generated using the ARIMA technique
for all the crops studied.
The general findings of the study showed that there was a shift in area from food
crops to non-food crops. The production of major food crops, rice and tapioca reached at
negative growth rates due to the declining trend of their areas. But production rate of banana
has increased due to increase in both area and yield. Among cash crops, both area and
productivity growths influenced the production rates. The major cash crops coconut, arecanut
and pepper showed positive growth rates. Compared to food crops, cash crops in general
showed better growth trends in production. Negative growth rate in the production of cashewnut
was due to the decline in area. Among plantation crops, rubber and coffee attained a high
production growth rate due to the combined growth of area and productivity. The highest
production growth rate and area growth rate were recorded by rubber among all the crops
studied.
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