APPLIED FRUIT SCIENCE, sa.2, 2025 (SCI-Expanded)
The study aims to estimate the production of cherries, a popular consumer fruit, for leading countries, other countries, and the world between 2024 and 2028 using the FAOSTAT dataset, spanning 63 years from 1961 to 2023. Production estimates were made with the SAS 9.4 statistical program and the Autoregressive Integrated Moving Average (ARIMA) model. The Statistical Analysis System (SAS) program employs the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF) capabilities to identify the optimal model. Several parameters were considered to determine which of the estimated models was optimal. These criteria included the lowest Akaike Information Criterion (AIC), Bayesian Information Criteria (BIC), Schwarz's Bayesian Criterion (SBC), Sum of Squared Errors (SSE), Mean Squared Error (MSE), and Mean Percentage Error (MPE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) values, as well as the Durbin Watson (DW) value that was closest to two and the highest R2 (R-squared) results. This study predicts that global cherry output will reach 3.08 million tons between 2024 and 2028. T & uuml;rkiye contributes 26.06% of the average production quantity, Chile 18.15%, the United States 11.27%, Uzbekistan 8.00%, Iran 4.58%, Spain 3.78%, Greece 3.53%, Italy 2.94%, Syria 2.18%, Poland 2.10% and other countries will contribute 17.40%. Countries that generate more income in exports by producing quality and durable cherry varieties in the production of this product, which offers an oligopoly market structure, and that will take more precautions against climate change by allocating more resources to cherry production will be one step ahead in the market. Thus, countries that take steps to turn cherry production into an advantage will be able to become the dominant producer and marketer country in the market if they offer more products to markets where they can sell higher quality products at higher prices.