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Influence of Interannual Climate Variability on Wheat Quality During Long-Term Storage: Comparative Analysis and
Diana Petronela Poetelea1, Emilian Mosnegutu1, Claudia Tomozei1
1Department of Environmental Engineering, Mechanical Engineering and Agritourism, Faculty of Engineering, "Vasile Alecsandri" University of Bacau, 600115 Bacau, Romania.
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This study investigates the influence of interannual climate variability on wheat quality during long-term storage under identical technological conditions. The same wheat cultivar was stored during two consecutive periods (2023-2024 and 2024-2025) in a flat warehouse without mechanical aeration or forced cooling, while environmental parameters (temperature and relative humidity) and quality indicators (grain moisture content, test weight, gluten content, and protein content) were continuously monitored. Based on the experimental data, empirical predictive models describing the relationships between storage time, environmental conditions, and wheat quality indicators were developed using nonlinear regression and curve-fitting techniques implemented in TableCurve 3D. Two model categories were established: a transfer model for moisture and temperature evolution and a degradation model for test weight, gluten, and protein changes. The models showed good predictive performance, with coefficients of determination ranging from R2 = 0.82 to 0.97. Model performance was assessed using residual analysis and statistical performance indicators, yielding low prediction errors and high Nash-Sutcliffe efficiency coefficients (0.95-0.99). The 2024-2025 period exhibited slightly greater thermal variability, with atmospheric thermal amplitude increasing from approximately 33 °C to 34 °C and grain thermal amplitude increasing from approximately 30 °C to 32 °C compared with the 2023-2024 storage period. This was accompanied by differences in moisture evolution patterns and more pronounced reductions in test weight, gluten, and protein content. These findings suggest that climate variability is associated with changes in hygrothermal conditions and wheat quality deterioration processes, while the proposed models provide reliable tools for predicting quality evolution and supporting adaptive grain storage management under changing climatic conditions.
