A portable and stable dry starch-KI sensor for headspace iodine vapor detection: A green approach for sensitive ascorbic acid quantification in colored juices - Ananya Paojinda; Tanaporn Sribunpeng; Aumpika Kongsatjaviwat; Nadia Mira Kusumaningtyas; Pichayaporn Nuihuaykaew; Sittisak Phoolpho; Thanthapatra Bunchuay; Wiboon Praditweangkum; Rattikan Chantiwas (Microchemical Journal, 2025)
• Dry starch-KI paper enables stable headspace detection for field analysis. • Enhanced sensitivity and stability compared to previous methods. • Uniform color spot formation ensures practical and reproducible results. • Improved detection method for ascorbic acid in colored juice matrices. • Aligned with green analytical chemistry principles with a high AGREE score of 0.7. This study introduces a stable and portable dry starch-KI paper sensor for detecting iodine vapor in the headspace of a microwell plate, enabling sensitive quantification of ascorbic acid (AA) in colored fruit and vegetable juices. The method leverages the reaction between AA and potassium iodate (KIO 3 ) to generate iodine vapor, producing a strong colorimetric response upon interaction with the starch-KI coating. The sensor maintains consistent color intensity for up to 90 min, ensuring reliable on-site analysis. Uniformity testing of 96-spot absorbance for 0.5 mM AA across three batches (n = 3) yielded a mean absorbance of 0.264 ± 0.016 with a %RSD of 6.1 %. Stability assessments at three AA concentrations produced %RSD values of 9.4 %, 5.0 %, and 5.1 %, respectively. The microwell plate format facilitates rapid analysis with minimal sample preparation, effectively minimizing interference from juice color and matrix effects. The sensor demonstrated a linear detection range of 0.1–0.75 mM (r 2 = 0.9942) with an LOD of 0.05 mM. Application to fresh juice samples yielded a %recovery of 80–120 % (n = 13). This approach addresses critical challenges such as stability, portability, and matrix interference by effectively separating analytical signals from juice pigments. With a high AGREE score of 0.7, reflecting strong alignment with green analytical chemistry principles, this innovative method offers a practical, eco-friendly solution for on-site AA quantification in nutritional analysis.
Keywords: Advanced Chemical Sensor Technologies; Analytical Chemistry and Sensors; Biosensors and Analytical Detection