9b8a7760e63dfc5f3676e0d240873f67 pmc_11394621.pdf 4485c98b93dbc9e8578db8e195c41a4ef1715990 pmc_11394621.pdf 3a67136285ef2435968935e89638ce20c191fec635fb12a6a4118c9f4a733763 pmc_11394621.pdf Title: Validation of an Optical Technology for the Determination of pH in Milk during Yogurt Manufacture Subject: Current systems that allow inline pH control in the fermented dairy industry have drawbacks, such as protein adhesion on the non-glass pH probes, measurement distortion, frequent recalibration needs, and sensitivity to extreme pH conditions encountered during clean-in-place operations. Therefore, the objective of this study was to validate the feasibility of estimating the pH of milk during the yogurt making process by using a NIR light backscatter sensor measuring under different fermentation temperatures and milk protein concentrations using a mathematical model that correlates the light scatter signal with pH. Three replications of the experiment with two protein concentrations (3.5 and 4.0%) and two fermentation temperatures (43 and 46 C) were used to validate this inline pH prediction model. Continuous and discontinuous measurements of pH were collected as a reference during fermentation, simultaneously with the light backscatter data acquisition. Also, the effect of adjusting the initial voltage gain of the light scatter device on the accuracy of the pH prediction model was evaluated. Temperature and initial voltage were the main factors affecting the fitting accuracy of the model. The adjustment of the initial voltage gain improved the pH prediction model fit. The model has been successfully validated for both continuous and discontinuous measurements of pH, with SEP values < 0.09 pH units and CV < 1.78%. The proposed optical inline and non-destructive method was feasible for inline pH monitoring of milk fermentation, avoiding traditional manual pH measurement. Keywords: yogurt fermentation; NIR light backscatter; optic sensor; inline; pH monitoring; temperature; protein concentration Author: Siqi Liu, Fanny Contreras, Ricardo S. Alemán, Jhunior Marcía Fuentes, Oscar Arango and Manuel Castillo Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Fri Aug 30 06:52:45 2024 CEST ModDate: Fri Aug 30 07:36:56 2024 CEST Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 14 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 3906352 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- SSNIUI+VnURWPalladioL-Bold Type 1 Custom yes yes yes 10 0 JVDCIX+URWPalladioL-Bold Type 1 Custom yes yes yes 16 0 BBTJHJ+URWPalladioL-Roma Type 1 Custom yes yes yes 22 0 KHZDCY+URWPalladioL-Ital Type 1 Custom yes yes yes 27 0 WTAUCZ+CMSY10 Type 1 Builtin yes yes yes 32 0 OOXAOQ+VnURWPalladioL Type 1 Custom yes yes yes 37 0 XBNVAE+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 53 0 BCDEEE+PalatinoLinotype-Bold 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no 438 0 BCDEEE+PalatinoLinotype-Bold TrueType WinAnsi yes yes no 446 0 BCDFEE+PalatinoLinotype-Roman TrueType WinAnsi yes yes no 450 0 BCDGEE+PalatinoLinotype-Italic TrueType WinAnsi yes yes no 454 0 BCDIEE+PalatinoLinotype-Bold CID TrueType Identity-H yes yes yes 458 0 BCDJEE+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 464 0 TimesNewRomanPSMT TrueType WinAnsi no no no 470 0 TimesNewRomanPS-BoldMT TrueType WinAnsi no no no 473 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2025-02-20 02:13:11 CET RepresentationInformation: pmc_11394621.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2025-02-19 04:54:00 CET Size: 3906352 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 620 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Materials and Methods Destination: section.2 Children: Item: Title: Experimental Design Destination: subsection.2.1 Item: Title: Preparation of Milk Destination: subsection.2.2 Item: Title: Preparation of Starter Culture Destination: subsection.2.3 Item: Title: Acid Milk Coagulation Induction Destination: subsection.2.4 Item: Title: Measurement of the Light Backscatter Ratio and pH Destination: subsection.2.5 Children: Item: Title: Determination of NIR Light Scatter Parameters Destination: subsubsection.2.5.1 Item: Title: Adjustment of the Voltage Gain Destination: subsubsection.2.5.2 Item: Title: pH Measurement Destination: subsubsection.2.5.3 Item: Title: pH Electrode Calibration Destination: subsubsection.2.5.4 Item: Title: Statistical Analysis Destination: subsubsection.2.5.5 Item: Title: Results and Discussion Destination: section.3 Children: Item: Title: Results of the Model without Voltage Gain Adjustment (Vat #2) Destination: subsection.3.1 Item: Title: Results of the Model with Voltage Gain Adjustment (Vat #1) Destination: subsection.3.2 Item: Title: Results of the External pH Model with Voltage Gain Adjustment (pHE) Destination: subsection.3.3 Item: Title: Conclusions Destination: section.4 Item: Title: References Destination: section.5 Info: Title: Validation of an Optical Technology for the Determination of pH in Milk during Yogurt Manufacture Author: Siqi Liu, Fanny Contreras, Ricardo S. Alemán, Jhunior Marcía Fuentes, Oscar Arango and Manuel Castillo Subject: Current systems that allow inline pH control in the fermented dairy industry have drawbacks, such as protein adhesion on the non-glass pH probes, measurement distortion, frequent recalibration needs, and sensitivity to extreme pH conditions encountered during clean-in-place operations. Therefore, the objective of this study was to validate the feasibility of estimating the pH of milk during the yogurt making process by using a NIR light backscatter sensor measuring under different fermentation temperatures and milk protein concentrations using a mathematical model that correlates the light scatter signal with pH. Three replications of the experiment with two protein concentrations (3.5 and 4.0%) and two fermentation temperatures (43 and 46 C) were used to validate this inline pH prediction model. Continuous and discontinuous measurements of pH were collected as a reference during fermentation, simultaneously with the light backscatter data acquisition. Also, the effect of adjusting the initial voltage gain of the light scatter device on the accuracy of the pH prediction model was evaluated. Temperature and initial voltage were the main factors affecting the fitting accuracy of the model. The adjustment of the initial voltage gain improved the pH prediction model fit. The model has been successfully validated for both continuous and discontinuous measurements of pH, with SEP values < 0.09 pH units and CV < 1.78%. The proposed optical inline and non-destructive method was feasible for inline pH monitoring of milk fermentation, avoiding traditional manual pH measurement. 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