Abstract:
In time yield estimation of a crop is essential for the economy of a country. It
is also important for planners to have an accurate and precise estimate of a
crop and this especially important when the crop is insufficient to meet the
demand of the country. As among all the crops, wheat is the most important
staple food of Pakistan, so the most of government agricultural polices are
wheat oriented. Pakistan faced a very serious shortage of wheat and in the
late 2007 and this created a serious challenge to law and order.
The prime objective of this research is to build a statistical model in a scientific
way, using all available ground information, so that a good and reliable
estimate of wheat crop can be achieved at least two months prior to the arrival
of actual production of the crop. Also a comprehensive descriptive study has
been conducted regarding the wheat production in the Punjab taking various
dimensions of explanatory variables.
In the detailed descriptive study, impact of irrigated / un-irrigated areas,
sowing time, fertilizers, pesticides spray, seed quantity, number of water
(number of turns same amount of water is supplied to one acre of wheat on
different times during the whole growing season of the crop), number of
plough, number of level (number of turns ground level of the field is
smoothened for even distribution of water throughout the field and for
moisture conservation) , seasonal rainfall, seasonal humidity level, maximum /
minimum average temperature of the season and also different combination
of these variables on the quantity of yield of the crop has been examined,
which has revealed many folded dimensions.
A new methodology titled as ‘Weighted Rainfalls’ is created to develop a
stronger relationship between yield of wheat and seasonal rainfalls because
rainfalls of different months of Rabi season have varying impact on the final
yield of wheat, which leads to the need of weighted rainfalls. The concept of
weighted rainfalls verified very effective in estimation of wheat production
through the statistical model. Different criteria like MSE, AIC and SIC for
competing models have also supported that estimates of wheat using
weighted rainfalls concept are better than the estimates using total rainfalls of
the season.
After the development of the model, its validity has been examined through
different confirmation runs. All validity runs also have supported that the
developed model is working properly and can be used as general wheat’s
model for its projection in any year. This concept can be easily extended for
other crops using weighted rainfall pattern for that crop.
As, this study is based on the sample data taken from the whole province, so
a method of unequal probability sampling using more than one measure of
sizes has also been proposed for the sake of an improvement in the sample
selection of villages giving priorities to more than one parameter of interest.
Obviously a suitable sample of villages having a reasonable representation of
all the major surveyed crops of the province will ultimately give a good
estimate of a crop.