IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i16p12155-d1213278.html
   My bibliography  Save this article

Predicting Nutritional Quality of Dual-Purpose Cowpea Using NIRS and the Impacts of Crop Management

Author

Listed:
  • Junior Bruno Ndiaye

    (Regional Study Center for Improving Adaptation to Drought (CERAAS), Senegalese Institute of Agricultural Research (ISRA), Thies BP 3320, Senegal)

  • Augustine K. Obour

    (Agricultural Research Center-Hays, Kansas State University, Hays, KS 67601, USA)

  • Keith Harmoney

    (Agricultural Research Center-Hays, Kansas State University, Hays, KS 67601, USA)

  • Doudou Diouf

    (Regional Study Center for Improving Adaptation to Drought (CERAAS), Senegalese Institute of Agricultural Research (ISRA), Thies BP 3320, Senegal)

  • Aliou Faye

    (Regional Study Center for Improving Adaptation to Drought (CERAAS), Senegalese Institute of Agricultural Research (ISRA), Thies BP 3320, Senegal)

  • Lamine Diamé

    (Department of Animal Biology, Cheikh Anta Diop University of Dakar (UCAD), Km 1, Avenue Cheikh Anta Diop, Dakar BP 5005, Senegal)

  • Dioumacor Fall

    (National Agricultural Research Center, Bambey BP 0053, Senegal)

  • Yared Assefa

    (Agricultural Research Center-Hays, Kansas State University, Hays, KS 67601, USA)

Abstract

Cowpea fodder has been one of the favored livestock forages for centuries in sub-Saharan Africa, particularly in Senegal. However, little research has been conducted on quantifying the nutritional quality of cowpea fodder because of the costly wet chemistry analysis. The main objective of this study was to develop predictive equations for a sustainable quantification of the nutritional quality of dual-purpose cowpea fodder using near infrared spectroscopy (NIRS) and to investigate the influence of cropping system, fertilizer, genotype, and their interaction on biomass yield and cowpea forage nutritional value. In this study, 120 samples from a dual-purpose cowpea variety trial were used to develop NIRS equations to estimate forage quality parameters including concentrations of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), calcium (Ca), phosphorus (P), potassium (K), and iron (Fe). Partial least squares (PLS) regression generated prediction equations using NIRS wavelength measurements, and reference wet chemistry analysis from calibration samples were developed. The PLS prediction equations for the different forage quality parameters had an R 2 of calibration 0.94, 0.93, 0.88, 0.63, 0.69, 0.87, and 0.94 for CP, ADF, NDF, Ca, P, K, and Fe, respectively. Using these prediction equations, correlation of the predicted values of the calibration subset and the prediction test subset resulted in significant positive relationships, with R 2 of 0.83, 0.74, 0.70, 0.63, 0.59, 0.75, and 0.83 for CP, ADF, NDF, Ca, P, K, and Fe, respectively. The corresponding RMSE of these relationships was 0.91, 2.68, 3.45, 0.23, 0.06, 0.11, and 100 for CP, ADF, NDF, Ca, P, K, and Fe, respectively. The range and mean concentrations of the calibration subset overlapped with that of the prediction subset for all parameters evaluated. Cross-validation procedures indicated good correlations between wet chemistry analysis and NIRS forage quality estimates. Results of the second experiment showed that the cropping system had no significant effect on cowpea forage yield and nutritive value. However, cowpea variety and fertilizer, both individually and their interaction, had a significant effect on fodder yield and cowpea forage quality. We conclude that the NIRS calibration equations developed can be used to accurately predict the cowpea forage quality parameters evaluated in this study.

Suggested Citation

  • Junior Bruno Ndiaye & Augustine K. Obour & Keith Harmoney & Doudou Diouf & Aliou Faye & Lamine Diamé & Dioumacor Fall & Yared Assefa, 2023. "Predicting Nutritional Quality of Dual-Purpose Cowpea Using NIRS and the Impacts of Crop Management," Sustainability, MDPI, vol. 15(16), pages 1-14, August.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12155-:d:1213278
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/16/12155/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/16/12155/
    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:jsusta:v:15:y:2023:i:16:p:12155-:d:1213278. 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.