This study evaluated the physicochemical and rheological characteristics of wheat flours sourced from different processors in southern Brazil, covering the harvest seasons from 2021 to 2025. Rheological analysis is essential for predicting dough behavior during processing and ensuring the quality of flours. Samples were evaluated in relation to alveographic tests that measured gluten strength (W), tenacity (P), and extensibility (L), as well as gluten content, Falling Number (FN), moisture, mineral content (ash), and color parameters (L*, a*, and b*). High values for W, P, L, gluten content, and FN showed strong flours with good enzymatic stability and a well-developed protein structure. These characteristics are not desirable for biscuit doughs, which require lower resistance and greater extensibility. These findings reflected the edaphoclimatic conditions and the predominant cultivars in the region. The comparative analysis among processors and harvest seasons showed variability in quality parameters. Some processors demonstrated positive progress, producing lighter and stronger flours with improved rheological performance in the 2024 and 2025 seasons. Other processors showed greater variability within the same harvest, indicating the need for adjustments in industrial processing. Multivariate analysis (PCA) identified flour strength, gluten index, and FN as the most important variables for distinguishing processors and harvest seasons. The results support the strategic selection of suppliers and the development of specific formulations, contributing to improved control and standardization across the industry. PRACTICAL APPLICATIONS: Physicochemical and rheological variability of wheat flours supplied by different processors across harvest seasons directly affects dough performance and industrial process stability. The identification of flour strength, gluten characteristics, and enzymatic activity as critical quality parameters supports more accurate supplier qualification and targeted formulation adjustments. The multivariate approach enables efficient monitoring of quality fluctuations associated with harvest year and climatic conditions, contributing to improved process control and risk management in biscuit manufacturing.
Centenaro et al. (Sun,) studied this question.