IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v228y2025ics0308521x25001301.html
   My bibliography  Save this article

Assessment of climate resilience index: Insight from Murrah buffalo-based livestock production system of Western India

Author

Listed:
  • Singh, Ruchi
  • Maiti, Sanjit
  • Garai, Sanchita
  • Bhakat, Mukesh
  • Jha, Sujeet Kumar
  • Dixit, Anil Kumar
  • Aggarwal, Anjali

Abstract

India is largest milk producer in the world. The buffalo (Bubalus bubalis), particularly the Murrah breed is the major contributor to the total milk production of India. But this breed is highly susceptible to climate-change induced heat stress due to their physiological characteristics. Therefore, livelihoods depend on the Murrah based livestock production system is highly vulnerable even in its breeding tract i.e. Haryana, a state of western India. Hence, a system-based analysis provides an essential guide to policymakers and other stakeholders to understand the system comprehensively and develop targeted climate actions to enhance its resilience, contributing to India's position as a global leader in milk production.

Suggested Citation

  • Singh, Ruchi & Maiti, Sanjit & Garai, Sanchita & Bhakat, Mukesh & Jha, Sujeet Kumar & Dixit, Anil Kumar & Aggarwal, Anjali, 2025. "Assessment of climate resilience index: Insight from Murrah buffalo-based livestock production system of Western India," Agricultural Systems, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:agisys:v:228:y:2025:i:c:s0308521x25001301
    DOI: 10.1016/j.agsy.2025.104390
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X25001301
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2025.104390?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:agisys:v:228:y:2025:i:c:s0308521x25001301. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    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.