The capacity of alquitara (a traditional distillation system) to produce cider brandies is evaluated. To do so, the chemical composition of 12 fractions obtained during the distillation process and the cider brandies obtained from five ciders were analyzed (alcohol strength, methanol, volatile substances, furfural, and metals), taking into account European and Spanish legislation. During the course of distillation, an important increase in methanol, furfural, 2-phenylethanol, and metals in the last fractions was observed, while fusel oils were more abundant in the first fractions collected. Only acetaldehyde behaved differently, showing a minimum concentration in the middle fractions that might be explained by its formation on the surface of alquitara. On the other hand, the final distillates obtained by means of this method complied with the considered regulations. Worth highlighting in this regard are the low levels of a potential toxin such as methanol, as well as the detection of a constant ratio for methanol, ethanol, and fusel oil for the pairs of cider/spirits analyzed, which could be interpreted as an indication of good uniformity in the distillation system and method, thus guaranteeing product quality.
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http://dx.doi.org/10.1021/jf062316h | DOI Listing |
Environ Sci Technol
January 2025
Shandong Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, P. R. China.
Membrane distillation (MD) efficiently desalinizes and treats high-salinity water as well as addresses the challenges in handling concentrated brines and wastewater. However, silica scaling impeded the effectiveness of MD for treating hypersaline water and wastewater. Herein, the effects of humic acid (HA) on silica scaling behavior during MD are systematically investigated.
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January 2025
Bio-Circular-Green-Economy Technology and Engineering Center, BCGeTEC, Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
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December 2024
CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Zhejiang, Hangzhou, China.
Background: Gastrointestinal (GI) diseases pose significant challenges for healthcare systems, largely due to the complexities involved in their detection and treatment. Despite the advancements in deep neural networks, their high computational demands hinder their practical use in clinical environments.
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Sensors (Basel)
January 2025
School of Automation, Southeast University, Nanjing 210096, China.
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December 2024
Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
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