High-Performance Thin-Layer Chromatography for Rapid Sugar Profiling in Commercial Dairy Products

High-Performance Thin-Layer Chromatography for Rapid Sugar Profiling in Commercial Dairy Products | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article High-Performance Thin-Layer Chromatography for Rapid Sugar Profiling in Commercial Dairy Products Napatcha Kasinthorn, Nannapas Rueangwiriyajit, Nolaphan Roongrojpanawan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9091519/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract High-performance thin-layer chromatography (HPTLC) was evaluated as a rapid screening method for sugar analysis in commercial dairy products. Various milk and yogurt samples, including plain, flavored, lactose-free, and plant-based alternatives, were analyzed to identify and quantify their sugar compositions. Following derivatization, sugars were differentiated based on both Rf values and characteristic spot coloration. HPTLC demonstrated superior chromatographic performance compared to conventional TLC, providing well-resolved spots for lactose, fructose, sucrose, glucose, and galactose, whereas standard TLC suffered from band broadening and overlapping zones. This method offers a cost-effective, rapid screening tool for dairy product authentication, quality control, and verification of sugar composition, with potential applications in nutritional labeling verification and detection of sugar adulteration in food products. HPTLC sugar analysis dairy products lactose sucrose quality control food authentication Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The accurate determination of sugar content in dairy products is importance for nutritional labeling, quality control, detection of adulteration, and compliance with food safety regulations. Dairy products contain naturally occurring sugars, primarily lactose, as well as its hydrolyzed products glucose and galactose. Processed dairy formulations may contain added sugars such as sucrose and fructose (Ng et al. 2012 ). The quantification of these carbohydrates is essential for monitoring lactose-free product claims, assessing technological processes such as fermentation, and verifying product authenticity. Various analytical techniques have been employed for sugar analysis in dairy matrices, including high-performance liquid chromatography (HPLC) with refractive index detection (Warthesen and Kramer 1979 ; Chávez-Servín et al. 2004 ; Sharma et al. 2009 ), gas chromatography-mass spectrometry (GC-MS) (Jariyasopit et al. 2021 ), enzymatic methods (Steegmans et al. 2004 ), and electrochemical analysis (Conzuelo et al. 2010 ; Ammam and Fransaer 2010 ). While HPLC remains the reference method due to its sensitivity and reproducibility, it requires expensive instrumentation, extensive sample preparation, high solvent consumption, and considerable analysis time. Enzymatic methods, though specific, are typically limited to individual sugar determination. High-performance thin-layer chromatography (HPTLC) has emerged as an alternative for food analysis, offering several advantages including simultaneous analysis of multiple samples, reduced solvent consumption, lower cost per analysis, and minimal sample preparation (Gupta et al. 2022 ; Pawar et al. 2025 ). HPTLC has been successfully applied to the analysis of various food components including sugars in food samples (Morlock and Sabir 2011 ), or sugar adulteration in honeys (Puscas et al. 2013 ; Islam et al. 2020 ). The present study aims to develop and validate a rapid and cost-effective HPTLC method for the simultaneous separation and semi-quantification of major sugars (lactose, glucose, galactose, sucrose, and fructose) in milk and yogurts. Materials and methods Reagents and Samples D-glucose, lactose, and boric acid were purchased from Ajax Finechem. D-Galactose, D-fructose, and sucrose were purchased from Kemaus. Methanol, acetic acid, n -butanol, 85% phosphoric acid were purchased from RCI Labscan. Diphenylamine and isopropanol were purchased from Loba Chemie. Aniline was purchased from Sigma-Aldrich. All chemicals were analytical-grade reagents. Distilled water Chromatography was performed on HPTLC plates silica gel 60 (20 x 20 cm, layer thickness 0.20 mm, Merck). For comparison, standard TLC plates silica gel 60 with fluorescent indicator UV 254 (20 x 20cm, layer thickness 0.20 mm, Macherey-Nagel) were used. The plates were cut to 12 x 8.5 cm. All milk and yogurt samples were purchased at local convenience stores. Preparation of Sugar Standards and Dairy Samples Calibration standards were prepared in three sets. The first standards contained both D-glucose and D-fructose, with each sugar present at final concentrations of 0.5, 1, 2, and 4 mg/mL (four calibration points). The second standards contained both sucrose and lactose at the same concentrations. The third standards contained only D-galactose at 0.5, 1, 2, and 4 mg/mL. Stock solutions were prepared by accurately weighing each sugar and dissolving in distilled water at a concentration of 40 mg/mL. Working standards were prepared by appropriate dilution of stock solutions. Each yogurt and milk samples were prepared by mixing 0.5 g of product in 10 mL of methanol and centrifuged at 5000 rpm for 15 minutes at 4 ºC to precipitate proteins and fats. The sugar-containing supernatants were used for analysis. HPTLC Analysis Chromatographic separation and development were carried out manually. An aliquot of 0.4 µL of working standards and samples were spotted on the HPTLC plate using a 10-µL micro syringe. The chamber was saturated with the mobile phase for chromatographic development, which was 12 mL of n -butanol: 2-propanol: acetic acid: boric acid solution (200 mg boric acid dissolved in 10 mL distilled water) 6:14:1:3 (v/v/v/v) (Morlock and Sabir 2011 ). The migration distance was 10.5 cm. After development, sugar spots were visualized using a spray reagent composed of aniline-diphenylamine-phosphoric acid, which reacts with reducing and some non-reducing sugars to form colored spots. The reagent was prepared by dissolving 2 g of diphenylamine in 50 mL of acetone. In a separate beaker, 2 mL of aniline was added to 50 mL acetone. Both solutions were combined, followed by adding 10 mL of phosphoric acid, and mixed until homogenized (Márquez et al. 2022 ). The homogenized solution was transferred to a spray bottle. The HPTLC plate was placed in a cardboard box in a fume hood. The reagent solution was carefully sprayed on the HPTLC plate, ensured all surface areas were damped. After spraying, the plate was removed and heated in a hot-air oven at 90ºC for 5 minutes until visible colored spots appeared. Quantification of Image using ImageJ The resulting HPTLC plate was photographed under white light provided by a light box for lighting consistency using a smartphone (iPhone 15 Pro Max). Densiometric analysis was performed using ImageJ, a free, open-source image processing and analysis software (Schneider et al. 2012 ). For each sample track, a rectangular region of interest (ROI) was defined extending from the point of sample application to the solvent front. The width of the ROI was adjusted to capture the complete lateral diffusion of each spot. Chromatographic profiles were generated using the "Analyze Gels" function in ImageJ. Intensity values were plotted as a function of migration distance using the Plot Lanes command. Baseline correction was applied manually by drawing a straight line connecting the baseline regions before and after each peak of interest. Peak areas were calculated by integrating the area under each peak above the baseline using the "Wand tool". The integrated peak areas, expressed in arbitrary units (AU), served as the analytical signal for quantification purposes. Overlapping peaks were separated by drawing a straight line from the valley to the baseline, and the area of each peak was then determined. Results HPTLC Separation and Retention Factors The High-Performance Thin-Layer Chromatography (HPTLC) method provided effective separation of the sugar profiles across various milk and yogurt samples. As shown in Fig. 1 , the sugars migrated at distinct distances, enabling both qualitative identification and densitometric quantification. However, at higher concentrations, chromatographic spots for galactose, sucrose and glucose overlapped due to band broardening. Therefore, these standard sugars were spotted separately to ensure peak resolution. Using this derivatization reagent, fructose and sucrose exhibited characteristic red and purple spots at Rf values of 0.301 and 0.366, respectively, while other sugars appeared blue (Fig. 1 , Table 1 ). The distinct color of each sugar provides orthogonal identification information to complement Rf value determination. Table 1 Color and Rf values of different sugar standards. The Rf are represented as mean ± standard deviation from triplicates of four concentrations, ranging from 0.5 to 4 mg/mL. Sugar Color Rf Lactose Blue 0.223 ± 0.001 Fructose Red 0.301 ± 0.001 Galactose Blue 0.349 ± 0.005 Sucrose Purple 0.366 ± 0.001 Glucose Blue 0.408 ± 0.004 Quantification of peak areas using ImageJ showed that, the calibration curves for fructose, sucrose and lactose exhibited excellent linearity over the concentration range of 0.2–1.6 µg/spot ( R 2 = 0.98, Fig. 2 ). However, the calibration curves for glucose and galactose showed lower correlation coefficients, but acceptable for semi-quantitative determination ( R 2 = 0.90 and 0.94, Fig. 2 ). Qualitative and quantitative analyses of sugars in milk and yogurt products The developed method was employed to determine the sugar composition and their concentrations in three milk and four yogurt samples: plain milk, flavored milk, lactose-free milk, plain yogurt, flavored yogurt, and soy yogurt (Fig. 1 ). The experiment was performed in triplicate on three different plates. HPTLC analysis of plain milk revealed a single spot corresponding to lactose. Flavored milk exhibited two distinct spots identified as lactose and sucrose (Fig. 3 A). Lactose-free milk contained galactose and glucose. Sugar concentrations were estimated using standard calibration curves from each respective plate. All yogurt samples in this study except lactose-free yogurt contained added sucrose. Plain yogurt showed well-resolved spots for lactose and sucrose (Fig. 1 ). In flavored yogurt samples, spot overlap was observed; however, complementary evaluation of Rf values and spot coloration enabled qualitative sugar identification. Flavored yogurt was found to contain lactose, fructose, sucrose, and glucose. Lactose-free yogurt contained galactose and glucose, while soy yogurt contained sucrose. Table 2 Determination and quantification of sugar in milk and yogurt samples. The mean concentrations are reported in g/100 mL for milk and g/100 g for yogurt samples together with the RSD from triplicate runs. Sample Rf RSD (%) Sugar Concentration RSD (%) Plain milk 0.222 4.3 Lactose 1.79 45 Flavored milk 0.225 0.368 4.2 4.8 Lactose Sucrose 2.18 2.69 78 88 Lactose-free milk 0.346 0.405 4.6 5.1 Galactose Glucose 0.74 1.80 256 77 Plain yogurt 0.221 0.364 3.7 4.4 Lactose Sucrose 6.54 6.06 20 23 Flavored yogurt 0.220 0.291 0.362 0.401 3.9 3.9 5.0 4.7 Lactose Fructose Sucrose Glucose 2.45 1.75 4.94 0.45 26 26 12 133 Lactose-free yogurt 0.346 0.389 3.3 3.2 Galactose Glucose 3.84 4.58 13 13 Soy yogurt 0.353 1.3 Sucrose 5.24 9.7 Comparison with Conventional TLC To evaluate the performance advantage of HPTLC for sugar separation, a parallel analysis was conducted using conventional TLC under identical mobile phase conditions. Conventional TLC exhibited several limitations that compromised sugar resolution and identification. Notably, glucose, sucrose, and galactose produced similar Rf values that precluded unambiguous identification (Fig. 4 ). Additionally, extensive band broadening resulted in wider, more diffuse spots compared to the compact zones obtained with HPTLC (Fig. 1 ). Discussion The total sugar content determined for lactose-free milk was consistent with nutritional labeling, whereas plain and flavored milk samples yielded lower values than indicated on product labels (Fig. 3 a and 3 b, Table 2 ). Sugar concentrations in plain and soy yogurt samples corresponded well with nutritional labeling (Fig. 3 c and 3 d, Table 2 ). However, flavored yogurt exhibited lower-than-expected values. The discrepancies may be attributed to incomplete extraction of sugars from particulate fruit matter present in the flavored yogurt sample, which were not fully solubilized during sample preparation. Lactose-free yogurt showed higher values. Quantification of overlapping spots was limited by using baseline-to-valley interpolation to determine peak areas, which introduced measurement uncertainty. Given the moderate linearity of calibration curves (R² = 0.90–0.94), the method demonstrated greater utility for qualitative sugar identification than for precise quantitative determination for glucose and galactose. The Rf values obtained with conventional TLC were generally higher than those observed in HPTLC, consistent with the differences in stationary phase particle size and plate efficiency between the two techniques (Variyar et al. 2011 ). In particular, band broadening caused overlap between fructose and lactose spots that would otherwise be clearly resolved in HPTLC analysis. This reduced chromatographic resolution severely limited both qualitative identification and quantitative analysis of sugar mixtures in complex food matrices. In contrast, HPTLC provided superior resolution with well-defined, compact spots and greater discrimination between sugars of similar polarity. The enhanced separation efficiency of HPTLC rendered it more suitable for the analysis of multi-component sugar profiles in dairy products. Conclusions HPTLC successfully resolved sugar profiles in commercial dairy products, demonstrating clear advantages over conventional TLC in terms of separation efficiency and spot identification. The method enabled qualitative identification of lactose, fructose, sucrose, glucose, and galactose across plain, flavored, lactose-free, and plant-based milk and yogurt samples, with spot coloration providing additional discrimination when Rf values were similar. While quantitative accuracy was limited by moderate calibration linearity for glucose and galactose (R² = 0.90 and 0.94) and incomplete sugar extraction from particulate fruit components, the method proved valuable for semi-quantitative screening and product authentication. The obtained sugar profiles were generally consistent with product labeling and expected compositions, confirming the presence of lactose in conventional products, added sugars in flavored varieties, and hydrolysis products in lactose-free alternatives. This HPTLC approach offers a rapid, cost-effective screening tool for dairy product quality control and sugar composition verification. Future work could focus on optimizing extraction procedures for samples containing particulate matter and improving calibration linearity through refined spotting techniques and densitometric methods. Implementation of automated sample application, plate development and densitometric scanning would substantially enhance repeatability and quantitative accuracy of the analysis. Such improvements would expand the method's utility from screening applications to precise quantitative determination of sugar content in dairy products. The technique holds potential for broader application in food authentication and nutritional labeling verification. Declarations Competing interests The authors have no relevant financial or non-financial interests to disclose. Author Contribution N.K., N.R. and N.R. conducted the experiments, and performed data analysis. M.D. conducted the experiments, performed data analysis, prepared all figures and wrote the manuscript. All authors reviewed the manuscript. Acknowledgement The authors would like to thank Miss Warangkana Yimkosol for experimental assistance. The project was funded by the science laboratory operating budget of the college. References Ammam M, Fransaer J (2010) Two-enzyme lactose biosensor based on β-galactosidase and glucose oxidase deposited by AC-electrophoresis: Characteristics and performance for lactose determination in milk. 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Current Issues in Pharmacy and Medical Sciences 35:224–228. https://doi.org/10.2478/cipms-2022-0039 Islam MK, Sostaric T, Lim L, et al (2020) A validated method for the quantitative determination of sugars in honey using high-performance thin-layer chromatography. JPC – Journal of Planar Chromatography – Modern TLC 33:489–499. https://doi.org/10.1007/s00764-020-00054-9 Jariyasopit N, Khamsaeng S, Panya A, et al (2021) Quantitative analysis of nutrient metabolite compositions of retail cow’s milk and milk alternatives in Thailand using GC-MS. Journal of Food Composition and Analysis 97:103785. https://doi.org/10.1016/j.jfca.2020.103785 Márquez DBM, Cervantes MAM, Martinez A, et al (2022) A simple quantitative method using TLC-image analysis to determine fructooligosaccharides (FOS) in food samples. Turkish Journal of Chemistry 46:1297–1305. https://doi.org/10.55730/1300-0527.3436 Morlock G, Sabir G (2011) Comparison of two orthogonal liquid chromatographic methods for quantitation of sugars in food. Journal of Liquid Chromatography & Related Technologies 34:902–919. https://doi.org/10.1080/10826076.2011.571118 Ng SW, Slining MM, Popkin BM (2012) Use of caloric and noncaloric sweeteners in US consumer packaged foods, 2005-2009. Journal of the Academy of Nutrition and Dietetics 112:1828-1834.e6. https://doi.org/10.1016/j.jand.2012.07.009 Pawar KN, Kadam SP, Redasani VK (2025) A systematic review on high performance thin layer chromatography (HPTLC). International Journal of Pharmaceutical Research and Applications. https://doi.org/10.35629/4494-1003402416 Puscas A, Hosu A, Cimpoiu C (2013) Application of a newly developed and validated high-performance thin-layer chromatographic method to control honey adulteration. Journal of chromatography A 1272:132–135. https://doi.org/10.1016/j.chroma.2012.11.064 Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9:671–675. https://doi.org/10.1038/nmeth.2089 Sharma R, Rajput YS, Poonam, et al (2009) Estimation of sugars in milk by HPLC and its application in detection of adulteration of milk with soymilk. Int J of Dairy Tech 62:514–519. https://doi.org/10.1111/j.1471-0307.2009.00532.x Steegmans M, Iliaens S, Hoebregs H (2004) Enzymatic, spectrophotometric determination of glucose, fructose, sucrose, and inulin/oligofructose in foods. Journal of AOAC INTERNATIONAL 87:1200–1207. https://doi.org/10.1093/jaoac/87.5.1200 Variyar PS, Chatterjee S, Sharma A (2011) Fundamentals and theory of HPTLC-based separation. In: Srivastava M (ed) High-Performance Thin-Layer Chromatography (HPTLC). Springer Berlin Heidelberg, Berlin, Heidelberg, pp 27–39 Warthesen JJ, Kramer PL (1979) Analysis of sugars in milk and ice cream by high pressure liquid chromatography. Journal of Food Science 44:626–627. https://doi.org/10.1111/j.1365-2621.1979.tb03853.x Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 16 Apr, 2026 Reviews received at journal 10 Apr, 2026 Reviewers agreed at journal 05 Apr, 2026 Reviewers agreed at journal 05 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviewers invited by journal 03 Apr, 2026 Editor assigned by journal 12 Mar, 2026 Submission checks completed at journal 12 Mar, 2026 First submitted to journal 11 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9091519","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617976857,"identity":"e900c5d6-25bb-4a5e-8715-733e3ddcb678","order_by":0,"name":"Napatcha Kasinthorn","email":"","orcid":"","institution":"Mahidol University International College, Mahidol University","correspondingAuthor":false,"prefix":"","firstName":"Napatcha","middleName":"","lastName":"Kasinthorn","suffix":""},{"id":617976858,"identity":"fdbadbec-033b-4ca5-99b2-6a79c7f1f27c","order_by":1,"name":"Nannapas Rueangwiriyajit","email":"","orcid":"","institution":"Mahidol University International College, Mahidol University","correspondingAuthor":false,"prefix":"","firstName":"Nannapas","middleName":"","lastName":"Rueangwiriyajit","suffix":""},{"id":617976859,"identity":"b19d9a47-f1a7-4243-b5a3-414773a5ecfa","order_by":2,"name":"Nolaphan Roongrojpanawan","email":"","orcid":"","institution":"Mahidol University International College, Mahidol University","correspondingAuthor":false,"prefix":"","firstName":"Nolaphan","middleName":"","lastName":"Roongrojpanawan","suffix":""},{"id":617976860,"identity":"609b9a83-ca9a-4acc-8f18-b33f2ab4014f","order_by":3,"name":"Manchuta Dangkulwanich","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYJACZgiVwMDwAUiyMSQwHgALSODVYgDWwjgDooUBrIWHGC3MPGC7CGjRbT978HNh2x95BvbkZ49tc+zy+NiTDxxgqLFjsJduwKrF7ExesvTMNgPDBp5n5sa525KL2XieJRxgOJbMwCNzALuWAzlmzLxtBowNEglm0rnbmBPbJHIMDjCwHQA6LAG7lvNvwFrsGyTSv0lbbquHavmHR8sNiC2JDRI5ZtKM2w5DtDC24dPyxlia55xxchvPmzLJ3m3HE9tAfknsS+bhuYHLYTmGn3nK5Gz72dO3SfzcVp04vz354IMP3+zk2Gdg1wIHbCg8oGIe/OpHwSgYBaNgFOADAEYGWWvuIM46AAAAAElFTkSuQmCC","orcid":"","institution":"Mahidol University International College, Mahidol University","correspondingAuthor":true,"prefix":"","firstName":"Manchuta","middleName":"","lastName":"Dangkulwanich","suffix":""}],"badges":[],"createdAt":"2026-03-11 07:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9091519/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9091519/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106518113,"identity":"c8886974-9a38-475d-8bef-df594b7bb5a1","added_by":"auto","created_at":"2026-04-09 12:20:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":184622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003eRepresentative image of the developed HPTLC plate. The first four lanes were a mixture of glucose and fructose standards (G+F) with the concentrations of 0.5, 1, 2, and 4 mg/mL, respectively. The second four lanes were a mixture of sucrose and lactose standards (S+L). The next four lanes were galactose standard (GL) with the same concentration. The last seven lanes were the samples: plain milk (PM), flavored milk (FM), lactose-free milk (LFM), plain yogurt (PY), flavored yogurt (FY), and soy yogurt (SY) respectively. \u003cstrong\u003e(b)\u003c/strong\u003e Densitograms of some tracks on the plate. The green vertical lines marked the starting point (0.0 cm) and the solvent front (10.5 cm). The vertical lines marked the travel distance of each sample. They are colored according to the appearance of spots for each sugar: blue for lactose, galactose, and glucose; red for fructose; and purple for sucrose.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9091519/v1/ef16493972aa0277e9b39cb4.png"},{"id":106518114,"identity":"d509c789-d22d-449b-b3ed-e6dd3c4daae8","added_by":"auto","created_at":"2026-04-09 12:20:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":133093,"visible":true,"origin":"","legend":"\u003cp\u003eStandard calibration curves for \u003cstrong\u003e(a)\u003c/strong\u003e glucose, fructose and sucrose. \u003cstrong\u003e(b)\u003c/strong\u003e lactose and galactose in the range of 0.5 – 4 mg/mL.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9091519/v1/ec06e1688bc367e2fe896eb9.png"},{"id":106518115,"identity":"e51ec267-63c6-4b5b-b2d0-848daa5611cc","added_by":"auto","created_at":"2026-04-09 12:20:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":153364,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eConcentration of various sugars found in plain, flavored and lactose-free milk samples in g/100 mL. \u003cstrong\u003e(b)\u003c/strong\u003e Total determined sugar (white) in comparison with the nutrition labels (gray) for each milk sample in g/100 mL. \u003cstrong\u003e(c)\u003c/strong\u003e Concentration of various sugars found in plain, flavored, lactose-free and soy yogurt samples in g/100 g. \u003cstrong\u003e(d)\u003c/strong\u003e Total determined sugar (white) in comparison with the nutrition labels (gray) for each yogurt sample in g/100 g. The error bars in (b and c) represent standard deviations from triplicate runs.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9091519/v1/caaf2bbf0e80638e703085e6.png"},{"id":106518116,"identity":"42607760-dba5-421f-afcf-941177502177","added_by":"auto","created_at":"2026-04-09 12:20:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":202080,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e An image of the developed TLC plate. The first four lanes were a mixture of glucose and fructose standards (G+F) with the concentrations of 0.5, 1, 2, and 4 mg/mL, respectively. The second four lanes were a mixture of sucrose and lactose standards (S+L). The next four lanes were galactose standard (GL). The last seven lanes were the samples: plain milk (PM), flavored milk (FM), lactose-free milk (LFM), plain yogurt (PY), flavored yogurt (FY), and soy yogurt (SY) respectively. \u003cstrong\u003e(b)\u003c/strong\u003e Densitograms of some tracks on the plate. The green vertical lines marked the starting point (0.0 cm) and the solvent front (10.5 cm). The vertical lines marked the travel distance of each sample. They are colored according to the appearance of spots for each sugar: blue for lactose, galactose, and glucose; red for fructose; and purple for sucrose.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9091519/v1/631ba307399b9147fdb935ea.png"},{"id":106725651,"identity":"6f4f4924-dcd6-4d71-9856-982ecd7e2900","added_by":"auto","created_at":"2026-04-12 18:33:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1275504,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9091519/v1/bc8cc721-aaa3-4f8a-bbbe-4227dbe8fb88.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High-Performance Thin-Layer Chromatography for Rapid Sugar Profiling in Commercial Dairy Products","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe accurate determination of sugar content in dairy products is importance for nutritional labeling, quality control, detection of adulteration, and compliance with food safety regulations. Dairy products contain naturally occurring sugars, primarily lactose, as well as its hydrolyzed products glucose and galactose. Processed dairy formulations may contain added sugars such as sucrose and fructose (Ng et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The quantification of these carbohydrates is essential for monitoring lactose-free product claims, assessing technological processes such as fermentation, and verifying product authenticity.\u003c/p\u003e \u003cp\u003eVarious analytical techniques have been employed for sugar analysis in dairy matrices, including high-performance liquid chromatography (HPLC) with refractive index detection (Warthesen and Kramer \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Ch\u0026aacute;vez-Serv\u0026iacute;n et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Sharma et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), gas chromatography-mass spectrometry (GC-MS) (Jariyasopit et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), enzymatic methods (Steegmans et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and electrochemical analysis (Conzuelo et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ammam and Fransaer \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). While HPLC remains the reference method due to its sensitivity and reproducibility, it requires expensive instrumentation, extensive sample preparation, high solvent consumption, and considerable analysis time. Enzymatic methods, though specific, are typically limited to individual sugar determination.\u003c/p\u003e \u003cp\u003eHigh-performance thin-layer chromatography (HPTLC) has emerged as an alternative for food analysis, offering several advantages including simultaneous analysis of multiple samples, reduced solvent consumption, lower cost per analysis, and minimal sample preparation (Gupta et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pawar et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). HPTLC has been successfully applied to the analysis of various food components including sugars in food samples (Morlock and Sabir \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), or sugar adulteration in honeys (Puscas et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Islam et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study aims to develop and validate a rapid and cost-effective HPTLC method for the simultaneous separation and semi-quantification of major sugars (lactose, glucose, galactose, sucrose, and fructose) in milk and yogurts.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eReagents and Samples\u003c/h2\u003e \u003cp\u003eD-glucose, lactose, and boric acid were purchased from Ajax Finechem. D-Galactose, D-fructose, and sucrose were purchased from Kemaus. Methanol, acetic acid, \u003cem\u003en\u003c/em\u003e-butanol, 85% phosphoric acid were purchased from RCI Labscan. Diphenylamine and isopropanol were purchased from Loba Chemie. Aniline was purchased from Sigma-Aldrich. All chemicals were analytical-grade reagents. Distilled water Chromatography was performed on HPTLC plates silica gel 60 (20 x 20 cm, layer thickness 0.20 mm, Merck). For comparison, standard TLC plates silica gel 60 with fluorescent indicator UV\u003csub\u003e254\u003c/sub\u003e (20 x 20cm, layer thickness 0.20 mm, Macherey-Nagel) were used. The plates were cut to 12 x 8.5 cm. All milk and yogurt samples were purchased at local convenience stores.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePreparation of Sugar Standards and Dairy Samples\u003c/h3\u003e\n\u003cp\u003eCalibration standards were prepared in three sets. The first standards contained both D-glucose and D-fructose, with each sugar present at final concentrations of 0.5, 1, 2, and 4 mg/mL (four calibration points). The second standards contained both sucrose and lactose at the same concentrations. The third standards contained only D-galactose at 0.5, 1, 2, and 4 mg/mL. Stock solutions were prepared by accurately weighing each sugar and dissolving in distilled water at a concentration of 40 mg/mL. Working standards were prepared by appropriate dilution of stock solutions.\u003c/p\u003e \u003cp\u003eEach yogurt and milk samples were prepared by mixing 0.5 g of product in 10 mL of methanol and centrifuged at 5000 rpm for 15 minutes at 4 \u0026ordm;C to precipitate proteins and fats. The sugar-containing supernatants were used for analysis.\u003c/p\u003e\n\u003ch3\u003eHPTLC Analysis\u003c/h3\u003e\n\u003cp\u003eChromatographic separation and development were carried out manually. An aliquot of 0.4 \u0026micro;L of working standards and samples were spotted on the HPTLC plate using a 10-\u0026micro;L micro syringe. The chamber was saturated with the mobile phase for chromatographic development, which was 12 mL of \u003cem\u003en\u003c/em\u003e-butanol: 2-propanol: acetic acid: boric acid solution (200 mg boric acid dissolved in 10 mL distilled water) 6:14:1:3 (v/v/v/v) (Morlock and Sabir \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The migration distance was 10.5 cm.\u003c/p\u003e \u003cp\u003eAfter development, sugar spots were visualized using a spray reagent composed of aniline-diphenylamine-phosphoric acid, which reacts with reducing and some non-reducing sugars to form colored spots. The reagent was prepared by dissolving 2 g of diphenylamine in 50 mL of acetone. In a separate beaker, 2 mL of aniline was added to 50 mL acetone. Both solutions were combined, followed by adding 10 mL of phosphoric acid, and mixed until homogenized (M\u0026aacute;rquez et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The homogenized solution was transferred to a spray bottle. The HPTLC plate was placed in a cardboard box in a fume hood. The reagent solution was carefully sprayed on the HPTLC plate, ensured all surface areas were damped. After spraying, the plate was removed and heated in a hot-air oven at 90\u0026ordm;C for 5 minutes until visible colored spots appeared.\u003c/p\u003e\n\u003ch3\u003eQuantification of Image using ImageJ\u003c/h3\u003e\n\u003cp\u003eThe resulting HPTLC plate was photographed under white light provided by a light box for lighting consistency using a smartphone (iPhone 15 Pro Max). Densiometric analysis was performed using ImageJ, a free, open-source image processing and analysis software (Schneider et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For each sample track, a rectangular region of interest (ROI) was defined extending from the point of sample application to the solvent front. The width of the ROI was adjusted to capture the complete lateral diffusion of each spot. Chromatographic profiles were generated using the \"Analyze Gels\" function in ImageJ. Intensity values were plotted as a function of migration distance using the Plot Lanes command.\u003c/p\u003e \u003cp\u003eBaseline correction was applied manually by drawing a straight line connecting the baseline regions before and after each peak of interest. Peak areas were calculated by integrating the area under each peak above the baseline using the \"Wand tool\". The integrated peak areas, expressed in arbitrary units (AU), served as the analytical signal for quantification purposes. Overlapping peaks were separated by drawing a straight line from the valley to the baseline, and the area of each peak was then determined.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHPTLC Separation and Retention Factors\u003c/h2\u003e \u003cp\u003eThe High-Performance Thin-Layer Chromatography (HPTLC) method provided effective separation of the sugar profiles across various milk and yogurt samples. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the sugars migrated at distinct distances, enabling both qualitative identification and densitometric quantification. However, at higher concentrations, chromatographic spots for galactose, sucrose and glucose overlapped due to band broardening. Therefore, these standard sugars were spotted separately to ensure peak resolution.\u003c/p\u003e \u003cp\u003eUsing this derivatization reagent, fructose and sucrose exhibited characteristic red and purple spots at Rf values of 0.301 and 0.366, respectively, while other sugars appeared blue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The distinct color of each sugar provides orthogonal identification information to complement Rf value determination.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eColor and Rf values of different sugar standards. The Rf are represented as mean \u0026plusmn; standard deviation from triplicates of four concentrations, ranging from 0.5 to 4 mg/mL.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRf\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.223\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.301\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGalactose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.349\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePurple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.366\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.408\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eQuantification of peak areas using ImageJ showed that, the calibration curves for fructose, sucrose and lactose exhibited excellent linearity over the concentration range of 0.2\u0026ndash;1.6 \u0026micro;g/spot (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.98, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, the calibration curves for glucose and galactose showed lower correlation coefficients, but acceptable for semi-quantitative determination (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.90 and 0.94, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQualitative and quantitative analyses of sugars in milk and yogurt products\u003c/h3\u003e\n\u003cp\u003eThe developed method was employed to determine the sugar composition and their concentrations in three milk and four yogurt samples: plain milk, flavored milk, lactose-free milk, plain yogurt, flavored yogurt, and soy yogurt (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The experiment was performed in triplicate on three different plates.\u003c/p\u003e \u003cp\u003eHPTLC analysis of plain milk revealed a single spot corresponding to lactose. Flavored milk exhibited two distinct spots identified as lactose and sucrose (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Lactose-free milk contained galactose and glucose. Sugar concentrations were estimated using standard calibration curves from each respective plate.\u003c/p\u003e \u003cp\u003eAll yogurt samples in this study except lactose-free yogurt contained added sucrose. Plain yogurt showed well-resolved spots for lactose and sucrose (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In flavored yogurt samples, spot overlap was observed; however, complementary evaluation of Rf values and spot coloration enabled qualitative sugar identification. Flavored yogurt was found to contain lactose, fructose, sucrose, and glucose. Lactose-free yogurt contained galactose and glucose, while soy yogurt contained sucrose.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetermination and quantification of sugar in milk and yogurt samples. The mean concentrations are reported in g/100 mL for milk and g/100 g for yogurt samples together with the RSD from triplicate runs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRSD (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSugar\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConcentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRSD (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlain milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLactose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlavored milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLactose\u003c/p\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78\u003c/p\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactose-free milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGalactose\u003c/p\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e256\u003c/p\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlain yogurt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLactose\u003c/p\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.54\u003c/p\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlavored yogurt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003cp\u003e0.291\u003c/p\u003e \u003cp\u003e0.362\u003c/p\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003cp\u003e3.9\u003c/p\u003e \u003cp\u003e5.0\u003c/p\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLactose\u003c/p\u003e \u003cp\u003eFructose\u003c/p\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003cp\u003e1.75\u003c/p\u003e \u003cp\u003e4.94\u003c/p\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactose-free yogurt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGalactose\u003c/p\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003cp\u003e4.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy yogurt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eComparison with Conventional TLC\u003c/h3\u003e\n\u003cp\u003eTo evaluate the performance advantage of HPTLC for sugar separation, a parallel analysis was conducted using conventional TLC under identical mobile phase conditions. Conventional TLC exhibited several limitations that compromised sugar resolution and identification. Notably, glucose, sucrose, and galactose produced similar Rf values that precluded unambiguous identification (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Additionally, extensive band broadening resulted in wider, more diffuse spots compared to the compact zones obtained with HPTLC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe total sugar content determined for lactose-free milk was consistent with nutritional labeling, whereas plain and flavored milk samples yielded lower values than indicated on product labels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Sugar concentrations in plain and soy yogurt samples corresponded well with nutritional labeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, flavored yogurt exhibited lower-than-expected values. The discrepancies may be attributed to incomplete extraction of sugars from particulate fruit matter present in the flavored yogurt sample, which were not fully solubilized during sample preparation. Lactose-free yogurt showed higher values. Quantification of overlapping spots was limited by using baseline-to-valley interpolation to determine peak areas, which introduced measurement uncertainty. Given the moderate linearity of calibration curves (R\u0026sup2; = 0.90\u0026ndash;0.94), the method demonstrated greater utility for qualitative sugar identification than for precise quantitative determination for glucose and galactose.\u003c/p\u003e \u003cp\u003eThe Rf values obtained with conventional TLC were generally higher than those observed in HPTLC, consistent with the differences in stationary phase particle size and plate efficiency between the two techniques (Variyar et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In particular, band broadening caused overlap between fructose and lactose spots that would otherwise be clearly resolved in HPTLC analysis. This reduced chromatographic resolution severely limited both qualitative identification and quantitative analysis of sugar mixtures in complex food matrices.\u003c/p\u003e \u003cp\u003eIn contrast, HPTLC provided superior resolution with well-defined, compact spots and greater discrimination between sugars of similar polarity. The enhanced separation efficiency of HPTLC rendered it more suitable for the analysis of multi-component sugar profiles in dairy products.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHPTLC successfully resolved sugar profiles in commercial dairy products, demonstrating clear advantages over conventional TLC in terms of separation efficiency and spot identification. The method enabled qualitative identification of lactose, fructose, sucrose, glucose, and galactose across plain, flavored, lactose-free, and plant-based milk and yogurt samples, with spot coloration providing additional discrimination when Rf values were similar.\u003c/p\u003e \u003cp\u003eWhile quantitative accuracy was limited by moderate calibration linearity for glucose and galactose (R\u0026sup2; = 0.90 and 0.94) and incomplete sugar extraction from particulate fruit components, the method proved valuable for semi-quantitative screening and product authentication. The obtained sugar profiles were generally consistent with product labeling and expected compositions, confirming the presence of lactose in conventional products, added sugars in flavored varieties, and hydrolysis products in lactose-free alternatives.\u003c/p\u003e \u003cp\u003eThis HPTLC approach offers a rapid, cost-effective screening tool for dairy product quality control and sugar composition verification. Future work could focus on optimizing extraction procedures for samples containing particulate matter and improving calibration linearity through refined spotting techniques and densitometric methods. Implementation of automated sample application, plate development and densitometric scanning would substantially enhance repeatability and quantitative accuracy of the analysis. Such improvements would expand the method's utility from screening applications to precise quantitative determination of sugar content in dairy products. The technique holds potential for broader application in food authentication and nutritional labeling verification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eN.K., N.R. and N.R. conducted the experiments, and performed data analysis. M.D. conducted the experiments, performed data analysis, prepared all figures and wrote the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank Miss Warangkana Yimkosol for experimental assistance. The project was funded by the science laboratory operating budget of the college.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmmam M, Fransaer J (2010) Two-enzyme lactose biosensor based on \u0026beta;-galactosidase and glucose oxidase deposited by AC-electrophoresis: Characteristics and performance for lactose determination in milk. Sensors and Actuators B: Chemical 148:583\u0026ndash;589. https://doi.org/10.1016/j.snb.2010.05.027\u003c/li\u003e\n\u003cli\u003eCh\u0026aacute;vez-Serv\u0026iacute;n J, Castellote A, Lopez-Sabater M (2004) Analysis of mono- and disaccharides in milk-based formulae by high-performance liquid chromatography with refractive index detection. Journal of chromatography A 1043 2:211\u0026ndash;215. https://doi.org/10.1016/j.chroma.2004.06.002\u003c/li\u003e\n\u003cli\u003eConzuelo F, Gamella M, Campuzano S, et al (2010) An integrated amperometric biosensor for the determination of lactose in milk and dairy products. J Agric Food Chem 58:7141\u0026ndash;7148. https://doi.org/10.1021/jf101173e\u003c/li\u003e\n\u003cli\u003eGupta M, Ghuge A, Parab M, et al (2022) A comparative review on high-performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC) \u0026amp; high-performance thin layer chromatography (HPTLC) with current updates. Current Issues in Pharmacy and Medical Sciences 35:224\u0026ndash;228. https://doi.org/10.2478/cipms-2022-0039\u003c/li\u003e\n\u003cli\u003eIslam MK, Sostaric T, Lim L, et al (2020) A validated method for the quantitative determination of sugars in honey using high-performance thin-layer chromatography. JPC \u0026ndash; Journal of Planar Chromatography \u0026ndash; Modern TLC 33:489\u0026ndash;499. https://doi.org/10.1007/s00764-020-00054-9\u003c/li\u003e\n\u003cli\u003eJariyasopit N, Khamsaeng S, Panya A, et al (2021) Quantitative analysis of nutrient metabolite compositions of retail cow\u0026rsquo;s milk and milk alternatives in Thailand using GC-MS. Journal of Food Composition and Analysis 97:103785. https://doi.org/10.1016/j.jfca.2020.103785\u003c/li\u003e\n\u003cli\u003eM\u0026aacute;rquez DBM, Cervantes MAM, Martinez A, et al (2022) A simple quantitative method using TLC-image analysis to determine fructooligosaccharides (FOS) in food samples. Turkish Journal of Chemistry 46:1297\u0026ndash;1305. https://doi.org/10.55730/1300-0527.3436\u003c/li\u003e\n\u003cli\u003eMorlock G, Sabir G (2011) Comparison of two orthogonal liquid chromatographic methods for quantitation of sugars in food. Journal of Liquid Chromatography \u0026amp; Related Technologies 34:902\u0026ndash;919. https://doi.org/10.1080/10826076.2011.571118\u003c/li\u003e\n\u003cli\u003eNg SW, Slining MM, Popkin BM (2012) Use of caloric and noncaloric sweeteners in US consumer packaged foods, 2005-2009. Journal of the Academy of Nutrition and Dietetics 112:1828-1834.e6. https://doi.org/10.1016/j.jand.2012.07.009\u003c/li\u003e\n\u003cli\u003ePawar KN, Kadam SP, Redasani VK (2025) A systematic review on high performance thin layer chromatography (HPTLC). International Journal of Pharmaceutical Research and Applications. https://doi.org/10.35629/4494-1003402416\u003c/li\u003e\n\u003cli\u003ePuscas A, Hosu A, Cimpoiu C (2013) Application of a newly developed and validated high-performance thin-layer chromatographic method to control honey adulteration. Journal of chromatography A 1272:132\u0026ndash;135. https://doi.org/10.1016/j.chroma.2012.11.064\u003c/li\u003e\n\u003cli\u003eSchneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9:671\u0026ndash;675. https://doi.org/10.1038/nmeth.2089\u003c/li\u003e\n\u003cli\u003eSharma R, Rajput YS, Poonam, et al (2009) Estimation of sugars in milk by HPLC and its application in detection of adulteration of milk with soymilk. Int J of Dairy Tech 62:514\u0026ndash;519. https://doi.org/10.1111/j.1471-0307.2009.00532.x\u003c/li\u003e\n\u003cli\u003eSteegmans M, Iliaens S, Hoebregs H (2004) Enzymatic, spectrophotometric determination of glucose, fructose, sucrose, and inulin/oligofructose in foods. Journal of AOAC INTERNATIONAL 87:1200\u0026ndash;1207. https://doi.org/10.1093/jaoac/87.5.1200\u003c/li\u003e\n\u003cli\u003eVariyar PS, Chatterjee S, Sharma A (2011) Fundamentals and theory of HPTLC-based separation. In: Srivastava M (ed) High-Performance Thin-Layer Chromatography (HPTLC). Springer Berlin Heidelberg, Berlin, Heidelberg, pp 27\u0026ndash;39\u003c/li\u003e\n\u003cli\u003eWarthesen JJ, Kramer PL (1979) Analysis of sugars in milk and ice cream by high pressure liquid chromatography. Journal of Food Science 44:626\u0026ndash;627. https://doi.org/10.1111/j.1365-2621.1979.tb03853.x\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HPTLC, sugar analysis, dairy products, lactose, sucrose, quality control, food authentication","lastPublishedDoi":"10.21203/rs.3.rs-9091519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9091519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHigh-performance thin-layer chromatography (HPTLC) was evaluated as a rapid screening method for sugar analysis in commercial dairy products. Various milk and yogurt samples, including plain, flavored, lactose-free, and plant-based alternatives, were analyzed to identify and quantify their sugar compositions. Following derivatization, sugars were differentiated based on both Rf values and characteristic spot coloration. HPTLC demonstrated superior chromatographic performance compared to conventional TLC, providing well-resolved spots for lactose, fructose, sucrose, glucose, and galactose, whereas standard TLC suffered from band broadening and overlapping zones. This method offers a cost-effective, rapid screening tool for dairy product authentication, quality control, and verification of sugar composition, with potential applications in nutritional labeling verification and detection of sugar adulteration in food products.\u003c/p\u003e","manuscriptTitle":"High-Performance Thin-Layer Chromatography for Rapid Sugar Profiling in Commercial Dairy Products","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 12:20:42","doi":"10.21203/rs.3.rs-9091519/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-16T05:52:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T04:04:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185023895078831710171073143233004309210","date":"2026-04-06T03:42:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48292360323404780447853613375217455787","date":"2026-04-05T17:40:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155847351605004389022744577487323181179","date":"2026-04-03T18:41:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-03T13:09:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-12T12:00:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T12:00:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Analytical Methods","date":"2026-03-11T07:35:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"711594d7-1098-4de8-97cf-168071416b86","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T12:20:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 12:20:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9091519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9091519","identity":"rs-9091519","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}