This paper presents a stochastic optimisation model for the annual harvest scheduling problem of the farmers’ entire cereal crop production at optimum maturity. Gathering the harvest represents an important stage for both agricultural cooperatives and individual farmers due to its high cost and considerable impact on seed quality and yield. The meteorological conditions represent the deciding factor that affects the harvest scheduling and progress. Using chance-constrained programming, a mixed-integer probabilistically constrained model is proposed, with a view to minimising the risk of crop quality degradation under climate uncertainty with a safe confidence level. The chance-constrained optimisation problem is tackled and solved via an equivalent linear mixed-integer reformulation jointly with scenario-based approaches. Moreover, a new concept of -scenario pertinence is introduced in order to defy efficiently the probabilistically constrained problem complexity and time limitations. From the practical standpoint, this study is aimed at helping an agricultural cooperative in decision-making on crop quality risk management and harvest scheduling over a medium time horizon (10–15 time periods).