Rapid monitoring of milk fat using Image processing coupled with ANN and PSO methods

Rapid monitoring of milk fat using Image processing coupled with ANN and PSO methods | 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 Rapid monitoring of milk fat using Image processing coupled with ANN and PSO methods Behzad Nouri, Seyed Saeid Mohtasebi, Lena Beheshti Moghadam, Mahmoud Omid, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2384714/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 Monitoring the main compositions of milk content like fat, lactose, protein and total solids, has become a major challenge in dairy cattle farming. For quantitative determination of fat content in milk based on the relation of milk color features different methods have been used, but long time, high cost, and need for experts for analysis are some disadvantages of them. In this study, for rapid monitoring of milk fat content, novel technology of image processing coupled with artificial neural network (ANN) and Particle swarm optimization (PSO) methods has been applied. The estimated milk fat content of the best proposed method was extensively compared with the reference sample (R 2 =0.99, MAE=0.22, and MSE=0.05). Moreover, effect of water on color components of milk with different percentages of fat content have been investigated. Results approved the proposed method as a reliable, rapid and low-cost method for monitoring milk fat content. Analysis ANN Color Milk processing Quality Full Text Additional Declarations No competing interests reported. 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-2384714","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":161762802,"identity":"691e4f05-b7fa-4ddf-bc80-de8847f3b140","order_by":0,"name":"Behzad Nouri","email":"","orcid":"","institution":"Zhejiang Gongshang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Behzad","middleName":"","lastName":"Nouri","suffix":""},{"id":161762803,"identity":"9fd12e40-7200-4750-b123-3cc64f36e36a","order_by":1,"name":"Seyed Saeid Mohtasebi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYFACHjCZwI/CJaCFsQGkRbKBmVQtBgeYiXSWbnvv8Qc//tjkGd/IP8Dwo4ZBxryBgBazM+cSG3vb0orNbiQzMPYcY+CROUBIy40cwwbehsOJ24BaGHgbGHgkCDkMpKXxz5//iZtnAG35S6yWZh62A4kbJJIZmImz5cwZw9mybcnFEmceGxyWOSZBhJbjPQYf3/yxy+NvT3z48E2NjT1BLSjgAAMDaRpGwSgYBaNgFOAAAIHVPZWTcjxGAAAAAElFTkSuQmCC","orcid":"","institution":"University of Tehran","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Saeid","lastName":"Mohtasebi","suffix":""},{"id":161762804,"identity":"d987962c-808a-42a5-bcf1-8e0c58e4e2af","order_by":2,"name":"Lena Beheshti Moghadam","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lena","middleName":"Beheshti","lastName":"Moghadam","suffix":""},{"id":161762805,"identity":"6148abc0-476d-4240-8e82-c8c831240032","order_by":3,"name":"Mahmoud Omid","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mahmoud","middleName":"","lastName":"Omid","suffix":""},{"id":161762806,"identity":"aeb18253-e8b4-4d98-b957-5cd4f1669f3f","order_by":4,"name":"Seyed Morteza Mohtasebi","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Morteza","lastName":"Mohtasebi","suffix":""}],"badges":[],"createdAt":"2022-12-16 09:14:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2384714/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2384714/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30711299,"identity":"4009af8a-22ae-4574-b0c9-bd4a1a6d825f","added_by":"auto","created_at":"2022-12-23 11:38:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":763486,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2384714/v1_covered.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rapid monitoring of milk fat using Image processing coupled with ANN and PSO methods","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Analysis, ANN, Color, Milk processing, Quality","lastPublishedDoi":"10.21203/rs.3.rs-2384714/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2384714/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMonitoring the main compositions of milk content like fat, lactose, protein and total solids, has become a major challenge in dairy cattle farming. For quantitative determination of fat content in milk based on the relation of milk color features different methods have been used, but long time, high cost, and need for experts for analysis are some disadvantages of them. In this study, for rapid monitoring of milk fat content, novel technology of image processing coupled with artificial neural network (ANN) and Particle swarm optimization (PSO) methods has been applied. The estimated milk fat content of the best proposed method was extensively compared with the reference sample (R\u003csup\u003e2\u003c/sup\u003e=0.99, MAE=0.22, and MSE=0.05). Moreover, effect of water on color components of milk with different percentages of fat content have been investigated. Results approved the proposed method as a reliable, rapid and low-cost method for monitoring milk fat content.\u003c/p\u003e","manuscriptTitle":"Rapid monitoring of milk fat using Image processing coupled with ANN and PSO methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-23 11:38:15","doi":"10.21203/rs.3.rs-2384714/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":"1093309e-c05b-4ccb-9636-b7b71044cef0","owner":[],"postedDate":"December 23rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-12-23T11:38:18+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-23 11:38:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2384714","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2384714","identity":"rs-2384714","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}