“DEVELOPMENT OF STATISTICAL MODELS FOR FORECASTING OF CHICKPEA CROP IN GUJARAT STATE”
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Date
2013-06
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jau,junagadh
Abstract
Weather is a major factor affecting crop production in advanced agricultural systems in our country. The large variation in yield is predominantly due to weather parameters. In view of fluctuating prices and weather effects a timely and reliable forecast of crop yield could help the planners in deciding the policies. Chickpea is an important pulse in the country and abroad. Therefore, an attempt has been made to identify the nature of the effect of weather parameters and technological advancement on chickpea crop and thereby to suggest suitable preharvest forecast models for major chickpea producing and growing districts of Gujarat state.
Timely and reliable forecast of crop yield is of great importance for monsoon dependent country like India, where the economy is mainly based on agricultural production. Chickpea crop grown mainly under irrigated as well as rainfed condition, the fluctuations in yield levels over the years are due to weather behavior.
The present investigation entitled “Development of statistical models for forecasting of chickpea crop in Gujarat state” was undertaken to develop pre-harvest forecasting models for chickpea yield based on weekly average data of weather parameters (maximum and minimum temperature, morning and afternoon relative humidity, sunshine hours and past year total rainfall) over a period of 30 years (1981 to 2010) covering five selected chickpea growing districts of Gujarat state.
The time period used for chickpea crop was from 42nd meteorological standard week (MSW) to 7th standard week of next year. The weekly average of weather variables used were maximum and minimum temperature, morning and afternoon relative humidity, sunshine hours and total annual rainfall of past year. The weather data were collected from respective observatories of each district. The data of area, production and productivity of chickpea from 1981 to 2010 were collected from Department of Economics, J.A.U., Junagadh.
The approach used for forecasting yield was original weather variables and week wise approach. The time trend was included as an explanatory variable in this approach. For early forecast, 4, 3, 2 and 1 weeks intervals were considered. The stepwise regression procedure was adopted using 30 years data for selection of variables. The prediction equations and forecasts of subsequent years were obtained separately for 25, 26, 27 and 28 years data set.
The influence of the time trend on chickpea yield was observed positive and significant in all the districts and each of the models fitted. It could be also observed from the results that the advances in chickpea production technology during last few years. The effects of all the weather variables, in relation to their quantum and direction, differed over the district. However, they were found important for prediction point of view in chickpea productivity.
In case of Jamnagar, Amreli and Valsad districts, the model of 14 week crop period (Using original weather variables, week wise approach) where as in Junagadh and Rajkot districts, the model of 13 and 12 week period (week wise approach) respectively were selected. These models for respective districts can be used for providing pre-harvest forecasts, 2 weeks before expected harvest in case of Jamnagar, Amreli and Valsad districts, while 3 and 4 weeks before expected harvest in case of Junagadh and Rajkot district respectively. These models explained highest predictability in yield and the forecasted yields were close to the observed values.
The result of the study showed that models selected for pre-harvest forecasts explained more than 60% variation for Junagadh district, more than 86% for Jamnagar and Rajkot districts, more than 83% for Amreli district and more than 49% for Valsad district. The errors of simulated forecasts were less than 1, 7, 6, 3 and 1 percent in respective models.
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agriculture statastics