• Contact Us
    • Send Feedback
    • Login
    View Item 
    •   Home
    • Theses and Dissertations
    • Theses and Dissertations
    • View Item
    •   Home
    • Theses and Dissertations
    • Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    Whole Repository
    CollectionsIssue DateRegionCountryHubAffiliationAuthorsTitlesSubject
    This Sub-collection
    Issue DateRegionCountryHubAffiliationAuthorsTitlesSubject

    My Account

    Login

    Welcome to the International Institute of Tropical Agriculture Research Repository

    What would you like to view today?

    Rapid detection of adulterated fermented maize (Ogi) with sorghum leaf sheath (Poroporo) using visible-near infrared spectroscopy

    Thumbnail
    View/Open
    Thesis (205.8Kb)
    Date
    2022-03
    Author
    Onifade, J.O.
    Type
    Thesis
    Review Status
    Internal Review
    Target Audience
    Scientists
    Metadata
    Show full item record
    Abstract/Description
    Food adulteration is a very old and common problem, which is often seen in both the low-and middle-income countries and even in some developed countries. Maize-based porridge especially ogi is a high-value commodity and common indigenous complementary food that is a target for adulteration, leading to loss of quality and encroachment on the rights and interests of consumers. This study investigated the characterization of the microorganisms found in ogi fermented for 0 to 120 hours and the feasibility of using visible - near Infrared (VIS-NIR) spectroscopy combined with multivariate analysis for detection and quantification of ogi adulterated with sorghum leaf sheath extract at different concentrations. NIR spectra of the adulterated and pure ogi were measured between the regions 400 – 2498 nm. The multivariate methods included Principal component analysis (PCA), multiplicative scatter correction (MSC), Savitzky-Golay derivatization, and partial least square – discriminant analysis (PLS-DA). PCA gave visible cluster trends for authentic samples and adulterated ones. PLS-DA was used to detect the discrimination between the pure and adulterated ogi samples. The PLS-DA model with MSC and fist derivative Savitzky-Golay normalization with five smoothing points was able to cross validate adulteration better at 5% adulteration level successfully compared to other adulteration levels. Standard microbiological characterization of the isolates conducted and results revealed that Saccharomyces cerevisiae, Candida and Lactobacillus species were the main microorganisms found in the fermentation medium within 96 hours of fermentation. There was an increase in the population of the bacteria and yeasts (measured in CFU ml-1) as the fermentation progressed. The results suggested that the predominant microorganisms during the fermentation period was the LABs and that NIR spectroscopy associated with multivariate analysis has the great potential for a rapid and non-destructive detection of adulteration in maize gruel (ogi).
    Acknowledgements
    First and foremost, my gratitude goes to God Almighty for His grace that was so sufficient, without it this work would not have been possible. My special gratitude to my supervisors Dr. Kolawole Banwo and co-supervisor Dr. Titilayo Falade for providing invaluable scholarly comments, guidance and support that greatly shaped my research work, and for creating time to read this work at different stages despite their busy schedules. I also wish to thank all the members of Aflasafe and Pathology ...
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/7944
    IITA Subjects
    Food Security; Food Systems; Maize; Plant Production; Post-Harvesting Technology; Value Chains
    Agrovoc Terms
    Food Security; Maize; Food Systems; Processing
    Regions
    Africa; West Africa
    Countries
    Nigeria
    Hubs
    Headquarters and Western Africa Hub
    Collections
    • Theses and Dissertations59
    copyright © 2019  IITASpace. All rights reserved.
    IITA | Open Access Repository