AI Summary & Key Takeaways
AI InsightThe proposed method offers many advantages whencompared to classical methods, such as (sample and reagent) volume reduction (20-fold), simplicity, multiple sampleanalysis (32 samples in 4 h), and environmental friendliness
📌 3 Key Takeaways
Abstract
In the present work, a simple automated microplate method based on cupric ion reduction is described fordetermining total reducing sugars in food extracts and synthetic serum. The reaction of Cu(II)-Nc (cupric-neocuproine)with reducing sugars was performed in alkaline medium in microplates, and the absorbance of the formed highly coloredCu(I)-Nc chelate in a plate reader at 450 nm was recorded. The proposed method was applied to reducing sugars(glucose, fructose, galactose, maltose, and lactose) and their linear calibration curves were constructed. The detectionand quantification limits (LOD and LOQ) for glucose were 0.14 and 0.46 µ M, respectively. Absorbances of glucosewere linear within the concentration range 2.5–54.2 µ M and the method showed high linearity (r = 0 . 9998) over arelatively broad concentration range of analyte. This automated microplate method was validated through linearity,additivity, precision (RSD%, 2.33–6.65), and recovery (101%–103%), revealing that the method is reliable and robustfor determining reducing sugars. Total reducing sugar contents of synthetic sugar mixtures, fruit juices, milk, andsynthetic serum samples were successfully determined with the proposed method. The results were compared to thoseof the conventional alkaline Cu(II)-Nc spectrophotometric method. The proposed method offers many advantages whencompared to classical methods, such as (sample and reagent) volume reduction (20-fold), simplicity, multiple sampleanalysis (32 samples in 4 h), and environmental friendliness