Electronic nose as an innovative measurement system for the quality assurance and control of bakery products: A review

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Influence of Baking Temperature and Formulation on Physical, Sensorial, and Morphological Properties of Pogácsa Cake: An Image Analysis Study

Pogácsa is a high-demand bakery product with a unique texture, where crumb structure is a determining factor for its textural quality and consumer acceptability. At present, there is no non-destructive in-line inspection method for textural quality assessment of pogácsa. Therefore, this study was aimed to evaluate the texture of pogácsa using the image processing technique, which was prepared using different cheeses with varying moisture contents (MC) and was baked at 200 and 215 °C. Samples were assessed for textural, visual, physical, and sensorial properties. The findings indicated that the highest porosity (72.75%) was found for the sample baked at 215 °C with low-moisture cheese (58%), while the lowest porosity (32.66%) was observed for cheese-free sample baked at 200 °C. Pore volumetric ratio and MC showed strong correlations (p < 0.01) with hardness (−0.90 and −0.89), resilience (0.87 and 0.83), cohesiveness (0.84 and 0.82), springiness (0.87 and 0.90), gumminess (−0.92 and −0.92), and chewiness (−0.92 and −0.92), respectively. The pore volumetric ratio showed a strong correlation (p < 0.01) with reference porosity (0.71). Overall, the current study indicated that adding cheese with varying MC and baking temperature could affect the texture of pogácsa cake, which could be detected by image analysis.

Nondestructive evaluation of baking parameters on pogácsa texture

This study aimed to investigate the potential application of image texture processing method on visible crumb structure of salty cake pogácsa, which was prepared with different baking times (5 and 7 min) and temperatures (200, 215, and 230°C). For this purpose, changes in gray level co-occurrence matrix (GLCM) features including energy, contrast, correlation, homogeneity, and entropy were monitored and their relationship with the instrumental texture parameters (hardness, adhesiveness, cohesiveness, springiness, gumminess, and chewiness) were assessed. The pore ratios were also extracted and visualized using image processing technique. Texture profile parameters indicated strong correlation (p < .01) with the image pattern parameters in different pogácsa groups. Gumminess showed strong correlation with contrast (0.503), correlation (-0.498), and homogeneity (0.401). Hardness also exhibited correlation with contrast (0.517), entropy (0.341), and correlation (-0.476). The pore ratio showed marked variation in crumb structure when different times and temperatures were used. Baking at 230°C for 7 min maximized the pore ratio (0.56). Penalty analysis revealed that oiliness, pore structure, and color of products were linked with baking time and temperature. Overall, the results suggested that the GLCM-based technique had the potential to be used as a nondestructive method for rapid quality assessment of pogácsa.