Droplet Based Image Colorimetry Method for Quantitative Detection of Milk Adulterants

Droplet Based Image Colorimetry Method for Quantitative Detection of Milk Adulterants | 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 Droplet Based Image Colorimetry Method for Quantitative Detection of Milk Adulterants Rohit Rohit, Rishabh Tomar, Aayush Khaire, Raj Nandini, Abhishek Raj This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9055709/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Rapid and low‑volume analytical tools are needed to support on‑site milk quality screening. This study presents a microliter droplet‑based image colorimetry platform for quantifying three common milk adulterants—water dilution, urea, and alkali neutralizers (alkalinity response). Milk droplets (5–20 µL) deposited on hydrophobic substrates were imaged under controlled illumination, and optical descriptors including grayscale luminance, apparent absorbance from the p‑DMAB reaction, and chromatic ratios from phenolphthalein‑induced color shifts were extracted. Water dilution produced a strong inverse linear trend (R² ≈ 0.98), with detection possible above ~ 17% dilution. Urea quantification showed a linear response (R² ≈ 0.96) with LOD = 0.174% and LOQ = 0.527%, while alkali neutralizers yielded a robust chromatic response (R² > 0.94) with LOD = 0.081%. Predicted concentrations for unknown samples deviated by only 7–16% from reference spectrophotometric values. The method requires no spectrophotometer or specialized fabrication, and offers simple, low‑cost, and rapid screening capability for routine dairy quality assessment, particularly in resource‑limited settings. Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9055709","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618466554,"identity":"7c457433-5a30-4dbb-8b53-1da65ab21a42","order_by":0,"name":"Rohit Rohit","email":"","orcid":"","institution":"Indian Institute of Technology Patna","correspondingAuthor":false,"prefix":"","firstName":"Rohit","middleName":"","lastName":"Rohit","suffix":""},{"id":618466555,"identity":"4be7a34f-0e6f-4e93-8bf6-fb516efcd85c","order_by":1,"name":"Rishabh Tomar","email":"","orcid":"","institution":"Indian Institute of Technology Patna","correspondingAuthor":false,"prefix":"","firstName":"Rishabh","middleName":"","lastName":"Tomar","suffix":""},{"id":618466556,"identity":"2e745986-3850-41ad-bcd0-9b48a6a4499b","order_by":2,"name":"Aayush Khaire","email":"","orcid":"","institution":"Shri Ramdeobaba College of Engineering and Management","correspondingAuthor":false,"prefix":"","firstName":"Aayush","middleName":"","lastName":"Khaire","suffix":""},{"id":618466557,"identity":"feb9858b-ca18-45e9-964a-1036adefebc4","order_by":3,"name":"Raj Nandini","email":"","orcid":"","institution":"Jaypee Institute of Information Technology","correspondingAuthor":false,"prefix":"","firstName":"Raj","middleName":"","lastName":"Nandini","suffix":""},{"id":618466558,"identity":"d304ec32-669d-401f-8c25-e8055f0089c0","order_by":4,"name":"Abhishek Raj","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYJACgw8GEjAmkVoMZxhISJCmhZmHgUGCsDIY4J99+EGxTYFFnTkD88MPDAV3CGuROJdmYJwDdJhlA5uxBIPBMyKsOcMA0WJwgMEM6JfDhHXIn2H/YGwB1sL+jTgtBmd4DIwZwFp4iLTF8AxPgWGPgYTkzmaeYokEYrTInWHfZvDjTx2/OXv7xg8f/hChBQjYwPFnwAwkEojSAIzJB2AtRKoeBaNgFIyCEQgA+4wtxMF2lrQAAAAASUVORK5CYII=","orcid":"","institution":"Indian Institute of Technology Patna","correspondingAuthor":true,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Raj","suffix":""}],"badges":[],"createdAt":"2026-03-07 05:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9055709/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9055709/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109058850,"identity":"240d67a9-2f61-46bf-9ef5-6f16c5a8a26a","added_by":"auto","created_at":"2026-05-12 08:02:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":530625,"visible":true,"origin":"","legend":"","description":"","filename":"MilkPaperFAM28thFeb.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9055709/v1_covered_b2cf0d08-54a5-4870-afcb-652496460d12.pdf"},{"id":109058842,"identity":"eda60c5b-4b88-418b-8457-55bca927d576","added_by":"auto","created_at":"2026-05-12 08:01:54","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14442310,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-9055709/v1/0f8a0ee85df884b7c58040a1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Droplet Based Image Colorimetry Method for Quantitative Detection of Milk Adulterants","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9055709/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9055709/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRapid and low‑volume analytical tools are needed to support on‑site milk quality screening. This study presents a microliter droplet‑based image colorimetry platform for quantifying three common milk adulterants\u0026mdash;water dilution, urea, and alkali neutralizers (alkalinity response). Milk droplets (5\u0026ndash;20 \u0026micro;L) deposited on hydrophobic substrates were imaged under controlled illumination, and optical descriptors including grayscale luminance, apparent absorbance from the p‑DMAB reaction, and chromatic ratios from phenolphthalein‑induced color shifts were extracted. Water dilution produced a strong inverse linear trend (R\u0026sup2; \u0026asymp; 0.98), with detection possible above ~\u0026thinsp;17% dilution. Urea quantification showed a linear response (R\u0026sup2; \u0026asymp; 0.96) with LOD\u0026thinsp;=\u0026thinsp;0.174% and LOQ\u0026thinsp;=\u0026thinsp;0.527%, while alkali neutralizers yielded a robust chromatic response (R\u0026sup2; \u0026gt; 0.94) with LOD\u0026thinsp;=\u0026thinsp;0.081%. Predicted concentrations for unknown samples deviated by only 7\u0026ndash;16% from reference spectrophotometric values. The method requires no spectrophotometer or specialized fabrication, and offers simple, low‑cost, and rapid screening capability for routine dairy quality assessment, particularly in resource‑limited settings.\u003c/p\u003e","manuscriptTitle":"Droplet Based Image Colorimetry Method for Quantitative Detection of Milk Adulterants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 08:01:34","doi":"10.21203/rs.3.rs-9055709/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"49478a1d-161d-41e0-a10a-2f8c0b18401f","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T08:01:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 08:01:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9055709","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9055709","identity":"rs-9055709","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}