Akademik Veri Yönetim Sistemi
International Journal of Agriculture, Environment and Food Sciences, cilt.7, sa.1, ss.213-222, 2023 (TRDizin)
This paper proposes a model that forecasts the weather and then, based
on that forecast, uses an income-oriented linear programming method to
optimize the harvesting process. Data representing a total yearly output
capacity of 472,878 tons from 214 different field locations were used to test
the model for sugar beet production. Prior to optimization, long-term oneyear weather rainfall forecasting was done using 10 years of actual weather
data for the field locations. Weather precipitation was forecasted using
logistic regression with an accuracy of 84.16%. The outcome of the weather
precipitation prediction model was a parameter in the optimization model.
The weather forecast for precipitation led to the 120-day harvest planning
being optimized. Comparative analysis was done on the outcomes of the
developed model and the current scenario. Comparing the current situation
to the proposed one, revenue would have increased by 16.7%. Given that
it incorporates weather forecasts into the harvest optimization process, the
methodology presented in this paper is more practical than other harvest
optimization models.