IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v9y2022i4p110-123.html
   My bibliography  Save this article

Evaluation and Optimization of the Physical and Sensory Properties of Enhanced Bread Produced From Wheat Flour and Chemically Modified African Yam Bean and Cassava Starches

Author

Listed:
  • Elemuo, Godswill Kodili

    (Department of Food Science and Technology, Federal University of Technology Owerri, Imo State, Nigeria)

  • Obasi, Nneoma Elechi

    (Department of Food Science and Technology, Michael Okpara University of Agriculture, Umudike, Abia State. Nigeria.)

Abstract

Composite breads were made by supplementing wheat flour with chemically modified African yam bean and cassava starches after the flour – starch blends were produced from the cleaned seeds and roots using hammer milling system. Three mixture components were obtained from the D-optimal mixture design of Response Surface Methodology (RSM). The physical and sensory properties of the bread was determined and subjected to statistical analysis of variance (ANOVA) using cubic models to generate the regression equations from the experimental values. The linear, binary and ternary effects of the dependent responses and their interactions was generated and graphically represented using 3D response surface plots. The developed models were tested for adequacy and validated using criterion at p 0.05) lack-of-fit (LoF), >0.7 adjusted R2 and >4 adequate precision to confirm adequate model signals. The numerical optimization outcomes had the desirability value of 0.86 depicting the ideal value. The optimized values for the optimum blends selected were 80.15 g wheat flour, 11.23 g African yam bean starch and 8.53 g cassava starch which will give the best composite flour -starch blends for enhanced bread products. The optimization was confirmed by performing confirmatory runs determining the 95 % confidence levels of the blends. The D – optimal mixture design of response surface methodology with three experimental components was adequate (propagated the design space) in evaluating and optimizing of the dependent responses tested; bread height, oven spring, loaf weight, loaf volume, specific volume and bulk density, appearance, crumb and crust, taste, aroma and acceptability.

Suggested Citation

  • Elemuo, Godswill Kodili & Obasi, Nneoma Elechi, 2022. "Evaluation and Optimization of the Physical and Sensory Properties of Enhanced Bread Produced From Wheat Flour and Chemically Modified African Yam Bean and Cassava Starches," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 9(4), pages 110-123, April.
  • Handle: RePEc:bjc:journl:v:9:y:2022:i:4:p:110-123
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-9-issue-4/110-123.pdf
    Download Restriction: no

    File URL: https://www.rsisinternational.org/virtual-library/papers/evaluation-and-optimization-of-the-physical-and-sensory-properties-of-enhanced-bread-produced-from-wheat-flour-and-chemically-modified-african-yam-bean-and-cassava-starches/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. G. Geoffrey Vining & John A. Cornell & Raymond H. Myers, 1993. "A Graphical Approach for Evaluating Mixture Designs," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(1), pages 127-138, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eweama, A.U. & Nwosu, J.N. & Owuamanam, C.I. & Obeleagu, S.O, 2021. "Modelling and optimization of proximate and anti-nutritional composition of breakfast cereals produced from blends of millet, mungbean and tigernut flour using response surface methodology," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(8), pages 103-118, August.
    2. Kadri Ulas Akay, 2014. "A graphical evaluation of logistic ridge estimator in mixture experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1217-1232, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjc:journl:v:9:y:2022:i:4:p:110-123. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://www.rsisinternational.org/journals/ijrsi/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.