Semnan University Press Applied Chemistry Today 2981-2437 20 77 2026 01 21 Enhanced Quantification of Co-eluting Amino Acids Using TLC based Image Analysis and Multivariate Calibration Enhanced Quantification of Co-eluting Amino Acids Using TLC based Image Analysis and Multivariate Calibration 69 72 9948 10.22075/chem.2025.37549.2365 FA Mehrdokht Hosseini Haghighi Department of Chemistry, Faculty of Basic Sciences, Semnan University, Semnan, Iran Maryam Rajabi Department of Chemistry, Faculty of Basic Sciences, Semnan University, Semnan, Iran Maryam Khoshkam Department of Chemistry, Faculty of Sciences, University of Mohaghegh Ardabili,56199-11367, Ardabil, Iran & Department of Environmental Science, Faculty of Science, University of Zanjan, 45371-38791, Zanjan, Iran Toktam Mohammadi Moghaddam Workplace Health Research Center, Neyshabour University of Medical Sciences, Neyshabour, Iran Journal Article 2025 04 28 L-Glutamine (Gln) and Glycine (Gly) are two amino acids with overlapping retention times in thin-layer chromatography (TLC). This overlap presents a significant analytical challenge, particularly when both compounds are present in the same mixture, as their spots on the TLC plate may not be fully resolved. Here, we used smartphone-based image analysis combined with PLS regression for semi-separated Gln/Gly quantification in TLC. A smartphone captured TLC plates images under consistent lighting conditions, and custom software processed them to generate chromatographic profiles. Calibration curves showed linear responses, with detection limits of 0.007 M and 0.008 M for Gln and Gly, respectively. Despite mobile-phase optimization, complete spot resolution was unachievable. To address this, partial least squares (PLS) regression deconvoluted the merged signals, enabling accurate quantification. The method was validated using a pharmaceutical product, yielding recovery rates of 100.4 ± 1.4% for Gln and 100.6 ± 1.0% for Gly, demonstrating its reliability for complex samples. L-Glutamine (Gln) and Glycine (Gly) are two amino acids with overlapping retention times in thin-layer chromatography (TLC). This overlap presents a significant analytical challenge, particularly when both compounds are present in the same mixture, as their spots on the TLC plate may not be fully resolved. Here, we used smartphone-based image analysis combined with PLS regression for semi-separated Gln/Gly quantification in TLC. A smartphone captured TLC plates images under consistent lighting conditions, and custom software processed them to generate chromatographic profiles. Calibration curves showed linear responses, with detection limits of 0.007 M and 0.008 M for Gln and Gly, respectively. Despite mobile-phase optimization, complete spot resolution was unachievable. To address this, partial least squares (PLS) regression deconvoluted the merged signals, enabling accurate quantification. The method was validated using a pharmaceutical product, yielding recovery rates of 100.4 ± 1.4% for Gln and 100.6 ± 1.0% for Gly, demonstrating its reliability for complex samples. https://chemistry.semnan.ac.ir/article_9948_352c18cc8827bc55a5cf31052eb51e6f.pdf