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    Closing yield gaps in Colombian direct seeding rice systems: a stochastic frontier analysis

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    Journal Article (950.0Kb)
    Authors
    Arango-Londoño, David
    Ramírez Villegas, Julián
    Barrios Pérez, Camilo
    Bonilla Findji, Osana
    Jarvis, Andy
    Uribe, Jorge Mario
    Date Issued
    2020-03
    Date Online
    2020-01
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    ISI journal
    Accessibility
    Open Access
    Usage rights
    CC-BY-NC-ND-4.0
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    Citation
    Arango-Londoño, D.; Ramírez-Villegas, J.; Barrios-Pérez, C.; Bonilla-Findji, O.; Jarvis, A.; Uribe, J.M.; 2020 Closing yield gaps in Colombian direct seeding rice systems: a stochastic frontier analysis. Agronomia Colombiana 38(1) 10 p. ISSN 2357-3732
    Permanent link to cite or share this item: https://hdl.handle.net/10568/108274
    External link to download this item: https://revistas.unal.edu.co/index.php/agrocol/article/view/79470/74928
    DOI: https://doi.org/10.15446/agron.colomb.v38n1.79470
    Abstract/Description
    Rice is one of the most important crops in terms of harvested area and food security both globally and for Colombia. Improvement of technical efficiency levels in rice production in order to close yield gaps in a context in which rice demand increases, natural resources are depleted, and where there are growing expectations about both climate changes and trade agreements is likely the most important challenge that farmers confront. This research assessed the main management factors that limit both rice crop productivity and the likely drivers of non-optimal technical efficiency levels (a proxy for yield gaps). This study focused on both upland and irrigated direct seeding systems across a variety of environments in Colombia. Stochastic frontier models were used to integrate microeconomic theory and empirical regression analysis in conjunction with a large commercial rice production database developed by the Colombian rice growers’ federation (Fedearroz). A large variation was found in technical efficiency (from 40 to 95%) levels for both upland and irrigated systems, and major differences were obtained in the limiting factors of the two systems (e.g. seed availability, variety type, market accessibility, fertilizer type, and use rate). This suggests both substantial and varied opportunities for improvements in current technical efficiency levels. Across systems, the correct choice of variety was identified as a common key factor for maximizing yield for a particular environment. For upland systems optimal choices were F174 and F2000, whereas for irrigated rice F473 was found to produce the highest yield. Additionally, numerical analysis suggests a yield impact of ca. 0.18% for each 1% increase in the nitrogen application rate for upland systems. For irrigated rice, phosphorous rather than nitrogen application rates were found to be more important. Since our analysis is based on farm-scale commercial production data, we argue that once our results are brought to consensus with local extension agents, technicians and agronomists, then management recommendations for closing yield gaps can be used to improve rice productivity.
    CGIAR Author ORCID iDs
    Julian Ramirez-Villegashttps://orcid.org/0000-0002-8044-583X
    Camilo Barrios-Perezhttps://orcid.org/0000-0001-8332-8746
    Osana Bonilla-Findjihttps://orcid.org/0000-0002-6098-000X
    Andy Jarvishttps://orcid.org/0000-0001-6543-0798
    Other CGIAR Affiliations
    Climate Change, Agriculture and Food Security
    AGROVOC Keywords
    models; modelos; food security; seguridad alimentaria; rice; arroz; demand; demanda; production functions; funciones de la producción; efficiency; eficacia
    Subjects
    CLIMATE CHANGE; FOOD SECURITY; RICE;
    Countries
    Colombia
    Regions
    Latin America; South America
    Organizations Affiliated to the Authors
    Alliance of Bioversity International and CIAT; Pontificia Universidad Javeriana; CGIAR Research Program on Climate Change, Agriculture and Food Security; University of Leeds; Universidad del Valle; University of Tokyo
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    • Alliance Bioversity CIAT Journal Articles [1100]

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