Internet of Things ( IoT ) Ultrasound Assisted Extraction of Bioactive Compounds From Sugar Beet Leaves

This paper focuses on the application of non‐thermal Internet‐of‐Things (IoT) extraction of bioactive compounds from sugar beet leaves. High power ultrasound was used as a non‐thermal processing unit and was integrated with IoT hardware and software. In parallel, two other extraction methods were employed—thermal extraction and cold extraction. The bibliometric review showed that ultrasound extraction of sugar beet leaves has a research potential. Sugar beet leaves contain high levels of macronutrients, including sodium (9138.35 mg/kg), potassium (7275.87 mg/kg), calcium (6276.36 mg/kg), and magnesium (3612.79 mg/kg), as well as micronutrients such as zinc (39.63 mg/kg), manganese (51.85 mg/kg), copper (6.36 mg/kg), and boron (11.96 mg/kg). When it comes to extraction, the highest concentrations of amino acids were estimated for Glx b (193.00 and 134.41 μg/mL) in the ultrasound and thermal extracts. The ultrasound sample had a higher total polyphenol content (≈4.9 mg gallic acid equivalent/g d.m.) and total flavonoid content (≈6.1 mg quercetin eq./g d.m.) compared to the other two samples. The ultrasound method, applied within a non‐thermal IoT processing framework, resulted in higher concentrations of proteins. The highest concentration of the Ribulose bisphosphate carboxylase large chain peptides was obtained by the ultrasound and cold extraction procedures.