With the increase in world population, the efficient production of food becomes an ever more important goal. One of the particular tasks associated with this goal is to find an optimal crop planting time, considering the allowed planting time windows and the following objectives: 1) weekly harvest must not surplus the available storage capacity and produce waste, and 2) the labor force should be utilized in an efficient manner. To tackle this problem, we define the crop plant scheduling problem (CPSP), in the form of mixed integer linear problem, and solve it with a commercial mathematical programming solver. To estimate the harvest time, we also predict the time needed for accumulation of the sufficient amount of growing degree units (GDUs), using an ARIMA model. In this paper, we present the developed GDU forecasting and CPSP models, and the obtained results for the two selected problem instances.