IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v8y2018i1p3-d124944.html
   My bibliography  Save this article

Nitrogen Use Efficiency and the Genetic Variation of Maize Expired Plant Variety Protection Germplasm

Author

Listed:
  • Adriano T. Mastrodomenico

    (Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
    Current address: PR-445 Road, km 56.5, Limagrain, Londrina, PR 86115-000, Brazil.)

  • C. Cole Hendrix

    (Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
    Current address: 718 Forest Park Blvd. Apt. D108, Oxnard, CA 93036, USA.)

  • Frederick E. Below

    (Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA)

Abstract

Nitrogen use efficiency (NUE) in maize ( Zea mays L.) is an important trait to optimize yield with minimal input of nitrogen (N) fertilizer. Expired Plant Variety Protection (ex-PVP) Act-certified germplasm may be an important genetic resource for public breeding sectors. The objectives of this research were to evaluate the genetic variation of N-use traits and to characterize maize ex-PVP inbreds that are adapted to the U.S. Corn Belt for NUE performance. Eighty-nine ex-PVP inbreds (36 stiff stalk synthetic (SSS), and 53 non-stiff stalk synthetic (NSSS)) were genotyped using 26,769 single-nucleotide polymorphisms, then 263 single-cross maize hybrids derived from these inbreds were grown in eight environments from 2011 to 2015 at two N fertilizer rates (0 and 252 kg N ha −1 ) and three replications. Genetic utilization of inherent soil nitrogen and the yield response to N fertilizer were stable across environments and were highly correlated with yield under low and high N conditions, respectively. Cluster analysis identified inbreds with desirable NUE performance. However, only one inbred (PHK56) was ranked in the top 10% for yield under both N-stress and high N conditions. Broad-sense heritability across 12 different N-use traits varied from 0.11 to 0.77, but was not associated with breeding value accuracy. Nitrogen-stress tolerance was negatively correlated with the yield increase from N fertilizer.

Suggested Citation

  • Adriano T. Mastrodomenico & C. Cole Hendrix & Frederick E. Below, 2018. "Nitrogen Use Efficiency and the Genetic Variation of Maize Expired Plant Variety Protection Germplasm," Agriculture, MDPI, vol. 8(1), pages 1-17, January.
  • Handle: RePEc:gam:jagris:v:8:y:2018:i:1:p:3-:d:124944
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/8/1/3/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/8/1/3/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gilmour, Arthur & Cullis, Brian & Welham, Sue & Gogel, Beverley & Thompson, Robin, 2004. "An efficient computing strategy for prediction in mixed linear models," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 571-586, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Urs Feller & Stanislav Kopriva & Valya Vassileva, 2018. "Plant Nutrient Dynamics in Stressful Environments: Needs Interfere with Burdens," Agriculture, MDPI, vol. 8(7), pages 1-6, July.

    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. Lee, Dae-Jin & Durbán, María, 2012. "Seasonal modulation mixed models for time series forecasting," DES - Working Papers. Statistics and Econometrics. WS ws122519, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Lee, Dae-Jin, 2017. "A general framework for prediction in penalized regression," DES - Working Papers. Statistics and Econometrics. WS 24607, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Brian R. Cullis & Alison B. Smith & Nicole A. Cocks & David G. Butler, 2020. "The Design of Early-Stage Plant Breeding Trials Using Genetic Relatedness," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 553-578, December.
    4. El-Bassiouni, M. Y. & Charif, H. A., 2004. "Testing a null variance ratio in mixed models with zero degrees of freedom for error," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 707-719, July.
    5. Ugarte, M.D. & Goicoa, T. & Militino, A.F. & Durbán, M., 2009. "Spline smoothing in small area trend estimation and forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3616-3629, August.
    6. Emi Tanaka, 2020. "Simple outlier detection for a multi‐environmental field trial," Biometrics, The International Biometric Society, vol. 76(4), pages 1374-1382, December.
    7. Pringle, M.J. & Baxter, S.J. & Marchant, B.P. & Lark, R.M., 2008. "Spatial analysis of the error in a model of soil nitrogen," Ecological Modelling, Elsevier, vol. 211(3), pages 453-467.

    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:8:y:2018:i:1:p:3-:d:124944. 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: 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.