IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i4p280-d523731.html
   My bibliography  Save this article

Novel Two-Slope Equations to Predict Amino Acid Concentrations Using Crude Protein Concentration in Soybean Meal

Author

Listed:
  • Su A Lee

    (Department of Animal Science and Technology, Konkuk University, Seoul 05029, Korea
    Department of Animal Sciences, University of Illinois, Urbana, IL 61801, USA)

  • Chan Sol Park

    (Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA)

  • Beob Gyun Kim

    (Department of Animal Science and Technology, Konkuk University, Seoul 05029, Korea)

Abstract

Amino acid (AA)-to-crude protein (CP) ratios in soybean meal (SBM) may be different for different sources of SBM depending on the presence of additional hulls. Therefore, this study was conducted to develop novel two-slope equations to predict the concentrations of AAs in SBM using CP as an independent variable. Regression analyses were performed with each AA in SBM as the dependent variable and the CP as the independent variable. Among all AAs, the predicted Lys in SBM (% dry matter (DM)) was: Lys = 3.19 − 0.026 × (51.88 − CP) where CP < 51.88% DM and Lys = 3.19 + 0.072 × (CP − 51.88) where CP > 51.88% DM with R 2 = 0.51 and p < 0.001. In conclusion, the novel equations provided reasonable estimates of the AA concentrations from different ranges of CP in SBM.

Suggested Citation

  • Su A Lee & Chan Sol Park & Beob Gyun Kim, 2021. "Novel Two-Slope Equations to Predict Amino Acid Concentrations Using Crude Protein Concentration in Soybean Meal," Agriculture, MDPI, vol. 11(4), pages 1-8, March.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:280-:d:523731
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/4/280/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/4/280/
    Download Restriction: no
    ---><---

    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:gam:jagris:v:11:y:2021:i:4:p:280-:d:523731. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.