Assessing the Carasau Bread Doughs Microwave Spectra

Foods, Journal Year: 2025, Volume and Issue: 14(7), P. 1177 - 1177

Published: March 27, 2025

Carasau bread (CB) is a traditional Sardinian flatbread with significant market potential, driving the need for advanced quality monitoring solutions in its production. Recent advancements automation and engineering have enhanced process control, but comprehensive understanding of CB dough properties remains essential. Dielectric spectroscopy (DS), particularly microwave (MW) range, has emerged as non-destructive, cost-effective tool food characterization, providing insights into microstructure composition. MW DS been applied to assess fermentation dynamics ingredient influence doughs, previous studies modeling dielectric using third-order Cole-Cole model up 8.5 GHz later extending 20 GHz. Despite these advancements, repeatability, reliability, consistency measurements on doughs not systematically assessed. This study aims fill this gap by analyzing ten samples standard composition (water 50%, yeast 1.5%, salt 1.5%) 0.5-6 both before after leavening, 10 different total 100 measurements. Even though correlation between spectra high, even if coefficient variation below 5% z-score analysis kernel density estimation highlighted that distribution data heterogeneous, showing variability across exists, especially leavening. Finally, pressure, temperature, relative humidity was excluded. statistical evaluation measurement provided critical robustness industrial applications.

Language: Английский

Trends in Sustainable Inventory Management Practices in Industry 4.0

Processes, Journal Year: 2025, Volume and Issue: 13(4), P. 1131 - 1131

Published: April 9, 2025

This study examines 52 recently published papers on sustainable inventory management in Industry 4.0, intending to bridge theory and practice through a comprehensive literature review. By analyzing the latest advancements discussed over past two years, covering 2024 2025, we identify key trends shaping field highlight existing gaps that may require further exploration. Focusing this time frame is particularly relevant because it reflects how companies have started using artificial intelligence more practically support sustainability goals. During these AI has been applied improve tracked, demand predicted, resources are managed reduce waste. These tools making supply chains efficient while helping organizations lower their environmental impact. In regard, our work aims provide deeper understanding of strategies evolving response technological innovations, offering insights for researchers practitioners seeking enhance efficiency responsibility modern chains.

Language: Английский