What question did this study set out to answer?

This research aims to analyze changes in milk production in Türkiye from 2001 to 2025 using various nonlinear models.

May 17, 2026

Analysis of Changes in Mean Milk Production in Turkiye Using Nonlinear Models and Assessment from the Perspective of Food Security

Key Points

This research aims to analyze changes in milk production in Türkiye from 2001 to 2025 using various nonlinear models.
Analyzed annual raw milk production data from 2001 to 2025 using nonlinear models.
Compared models including Gompertz, Brody, and Cubic for their predictive capacity.
Evaluated model performance using metrics such as mean square error and Akaike information criterion.
The Cubic model provided the most accurate predictions with the lowest mean square error.
Cubic Piecewise and Logistic models performed second best but were less accurate.
Gamma and Wood models showed high error margins and low predictive performance.

Abstract

In this study, annual raw milk production data in Türkiye for the period 2001–2025 were analyzed using nonlinear models. The Gompertz, Gamma, Brody, Bertalanffy, Cubic, Cubic Piecewise, Logistic, Wilmink, and Wood models were compared in terms of their capacity to predict production changes. Model performance was evaluated using mean square error (MSE), adjusted coefficient of determination (R̅²), accuracy factor (AF), bias factor (BF), Durbin-Watson (DW), Akaike information criterion (AIC), corrected Akaike information criterion (AICc), and Bayesian information criterion (BIC). The results indicated that the Cubic model reflected changes in milk production most accurately, exhibiting the highest accuracy and lowest error. Cubic Piecewise and Logistic models ranked second. Gamma and Wood models showed low performance due to high error margins. The findings demonstrate the effectiveness of nonlinear modeling in Türkiye’s milk production and highlight the applicability of projections for food security strategies.

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