SSOAR Logo
    • Deutsch
    • English
  • Deutsch 
    • Deutsch
    • English
  • Einloggen
SSOAR ▼
  • Home
  • Über SSOAR
  • Leitlinien
  • Veröffentlichen auf SSOAR
  • Kooperieren mit SSOAR
    • Kooperationsmodelle
    • Ablieferungswege und Formate
    • Projekte
  • Kooperationspartner
    • Informationen zu Kooperationspartnern
  • Informationen
    • Möglichkeiten für den Grünen Weg
    • Vergabe von Nutzungslizenzen
    • Informationsmaterial zum Download
  • Betriebskonzept
Browsen und suchen Dokument hinzufügen OAI-PMH-Schnittstelle
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Volltext herunterladen

(externe Quelle)

Zitationshinweis

Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):
https://doi.org/10.22178/pos.75-12

Export für Ihre Literaturverwaltung

Bibtex-Export
Endnote-Export

Statistiken anzeigen
Weiterempfehlen
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

Determinants of Drought Tolerant Rice Variety Adoption: Evidence from Rural farm Household in Northern Part of Bangladesh

[Zeitschriftenartikel]

Sultana, Razia
Rahman, Md. Habibur
Haque, Mohammad Rashidul
Sarkar, Md. Mohsin Ali
Islam, Syful

Abstract

The drought-tolerant rice variety Binadhan-19 study was conducted in five districts: Mymensingh, Ranpur, Pabna, Rajshahi and Chapainwabganj of Bangladesh. A total of 200 farmers were randomly selected (40 from each location) to collect the data with a pre-designed questionnaire. Tabular, descriptive... mehr

The drought-tolerant rice variety Binadhan-19 study was conducted in five districts: Mymensingh, Ranpur, Pabna, Rajshahi and Chapainwabganj of Bangladesh. A total of 200 farmers were randomly selected (40 from each location) to collect the data with a pre-designed questionnaire. Tabular, descriptive statistics and Probit model were used to fulfil objectives. The estimated log-likelihood value of gender, farm size, yield, agricultural extension services have a statistically and significant positive effect on the adoption of the variety. The household characteristic related variables such as age, experience, annual income, human labour, duration of the variety have no statistically significant effect on the adoption of the variety. Marginal coefficients indicate that if male farmers increased by 100%, the probability of adopting the Binadhan-19 variety would increase at 38 times more likely to adopt the variety. If the farm size of Binadhan-19 increased by 100%, the probability of adopting the variety would be increased by 0.07%. A farmer who has access to agricultural extension service is about 39 times more likely to adopt the variety. Again, if the yield increased by 100%, adopting the varieties would increase by 0.08%. The marginal coefficients of locations and soil fertility are negatively significant, indicating that if these two variables increased by 100%, the probability of adopting the varieties would decrease by 0.06% and 30%, respectively.... weniger

Thesaurusschlagwörter
Landwirtschaft; Bangladesch; Determinanten

Klassifikation
Naturwissenschaften, Technik(wissenschaften), angewandte Wissenschaften

Freie Schlagwörter
Drought tolerant; Rice; Adoption; Probit model; Binadhan-19

Sprache Dokument
Englisch

Publikationsjahr
2021

Seitenangabe
S. 7001-7010

Zeitschriftentitel
Path of Science, 7 (2021) 10

ISSN
2413-9009

Status
Veröffentlichungsversion; begutachtet (peer reviewed)

Lizenz
Creative Commons - Namensnennung 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.