IDEAS home Printed from https://ideas.repec.org/a/adp/artoaj/v25y2020i2p102-106.html
   My bibliography  Save this article

Physiological traits involved in grazing tolerance of alfalfa genotypes

Author

Listed:
  • Mariana Rockenbach de à vila

    (Embrapa Clima Temperado, Pelotas, RS, FAPEG, Brazil)

  • Raquel Esteban

    (University of the Basque Country (UPV/ EHU), Spain)

  • Miguel Dall Agnol

    (Department of Forage Plants and Agrometeorology, Federal University of Rio Grande do Sul, Brazil.)

  • José F Morán

    (Department of Sciences, Institute for Multidisciplinary Research in Applied Biology (IMAB), Public University of Navarre (UPNA), Spain)

Abstract

Alfalfa [1] is one of the most largely distributed forage legume species in the world and it is used on more hectares than any other forage legume. Even so, alfalfa production in Brazil is still limited by the low persistence of this species, especially when used for grazing. Therefore, the objective of this study was to evaluate and select grazing-tolerant germplasm by evaluating genotypes based on their physiological traits. Eight alfalfa genotypes were grown in two different and simultaneous experiments.

Suggested Citation

  • Mariana Rockenbach de à vila & Raquel Esteban & Miguel Dall Agnol & José F Morán, 2020. "Physiological traits involved in grazing tolerance of alfalfa genotypes," Agricultural Research & Technology: Open Access Journal, Juniper Publishers Inc., vol. 25(2), pages 102-106, November.
    • Handle: RePEc:adp:artoaj:v:25:y:2020:i:2:p:102-106
    DOI: 10.19080/ARTOAJ.2020.25.556303
    as

    Download full text from publisher

    File URL: https://juniperpublishers.com/artoaj/pdf/ARTOAJ.MS.ID.556303.pdf
    Download Restriction: no
    File URL: https://juniperpublishers.com/artoaj/ARTOAJ.MS.ID.556303.php
    Download Restriction: no
    File URL: https://libkey.io/10.19080/ARTOAJ.2020.25.556303?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Álvarez, S. & Rodríguez, P. & Broetto, F. & Sánchez-Blanco, M.J., 2018. "Long term responses and adaptive strategies of Pistacia lentiscus under moderate and severe deficit irrigation and salinity: Osmotic and elastic adjustment, growth, ion uptake and photosynthetic activ," Agricultural Water Management, Elsevier, vol. 202(C), pages 253-262.
    2. Vincenzo Tufarelli & Marco Ragni & Vito Laudadio, 2018. "Feeding Forage in Poultry: A Promising Alternative for the Future of Production Systems," Agriculture, MDPI, vol. 8(6), pages 1-10, June.
    3. Feng Qin & Dongxia Liu & Bingda Sun & Liu Ruan & Zhanhong Ma & Haiguang Wang, 2016. "Identification of Alfalfa Leaf Diseases Using Image Recognition Technology," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-26, December.
    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. Vivaldi, Gaetano Alessandro & Camposeo, Salvatore & Romero-Trigueros, Cristina & Pedrero, Francisco & Caponio, Gabriele & Lopriore, Giuseppe & Álvarez, Sara, 2021. "Physiological responses of almond trees under regulated deficit irrigation using saline and desalinated reclaimed water," Agricultural Water Management, Elsevier, vol. 258(C).
    2. Hamna Waheed & Noureen Zafar & Waseem Akram & Awais Manzoor & Abdullah Gani & Saif ul Islam, 2022. "Deep Learning Based Disease, Pest Pattern and Nutritional Deficiency Detection System for “Zingiberaceae” Crop," Agriculture, MDPI, vol. 12(6), pages 1-17, May.
    3. Ben Ali, Akram R. & Shukla, Manoj K. & Schutte, Brian J. & Gard, Charlotte C., 2020. "Irrigation with RO concentrate and brackish groundwater impacts pecan tree growth and physiology," Agricultural Water Management, Elsevier, vol. 240(C).
    4. Sen Lin & Yucheng Xiu & Jianlei Kong & Chengcai Yang & Chunjiang Zhao, 2023. "An Effective Pyramid Neural Network Based on Graph-Related Attentions Structure for Fine-Grained Disease and Pest Identification in Intelligent Agriculture," Agriculture, MDPI, vol. 13(3), pages 1-20, February.
    5. Jinzhu Lu & Lijuan Tan & Huanyu Jiang, 2021. "Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification," Agriculture, MDPI, vol. 11(8), pages 1-18, July.
    6. Joseph P. Gulizia & Kevin M. Downs, 2019. "A Review of Kudzu’s Use and Characteristics as Potential Feedstock," Agriculture, MDPI, vol. 9(10), pages 1-15, October.
    7. Álvarez, S. & Gómez-Bellot, M.J. & Acosta-Motos, J.R. & Sánchez-Blanco, M.J., 2019. "Application of deficit irrigation in Phillyrea angustifolia for landscaping purposes," Agricultural Water Management, Elsevier, vol. 218(C), pages 193-202.

    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:adp:artoaj:v:25:y:2020:i:2:p:102-106. 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: Robert Thomas (email available below). General contact details of provider: .

    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.