IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i11p1089-d671652.html
   My bibliography  Save this article

Production Efficiency and Total Protein Yield in Quinoa Grown under Water Stress

Author

Listed:
  • Antonio A. Pinto

    (Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de Concepción, Concepción 4030000, Chile)

  • Susana Fischer

    (Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de Concepción, Concepción 4030000, Chile)

  • Rosemarie Wilckens

    (Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de Concepción, Concepción 4030000, Chile)

  • Luis Bustamante

    (Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de Concepción, Concepción 4030000, Chile)

  • Marisol T. Berti

    (Department of Plant Sciences, North Dakota State University, Fargo, ND 58108, USA)

Abstract

The increasing water scarcity affects the agricultural sector, and it is a significant constraining factor for crop production in many areas of the world. Water resource management and use related to crop productivity is the most important factor in many crops. Since consumer demands healthy food, the nutritive quality and the active ingredient need to be considered within the productive issue. The objective of this study was to determine water technical efficiency related to seed yield and seed protein content and composition in quinoa ( Chenopodium quinoa Willd.) under water stress using data envelopment analysis (DEA). The study was conducted in Chillan, Chile in two growing seasons. As water availability increased, seed yield, globulin, and albumin yield increased, particularly in the genotype Cahuil. The higher average efficiency levels for the DEA were 46.7% and 39.2% in Cahuil in both seasons at 20% available water (AW). The highest average efficiency of globulin yield was recorded in the same genotype (Cahuil). The highest multi-product technical efficiency levels in all input and output included in this study were observed in Cahuil, Regalona, and Morado under water scarcity in both seasons. In future studies related to crop management, DEA provides a good framework for estimating efficiency under restricted factors and multi-product results.

Suggested Citation

  • Antonio A. Pinto & Susana Fischer & Rosemarie Wilckens & Luis Bustamante & Marisol T. Berti, 2021. "Production Efficiency and Total Protein Yield in Quinoa Grown under Water Stress," Agriculture, MDPI, vol. 11(11), pages 1-18, November.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1089-:d:671652
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/11/1089/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/11/11/1089/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    2. Mette Asmild & Tomas Baležentis & Jens Hougaard, 2016. "Multi-directional program efficiency: the case of Lithuanian family farms," Journal of Productivity Analysis, Springer, vol. 45(1), pages 23-33, February.
    3. Arjen Y. Hoekstra, 2014. "Water scarcity challenges to business," Nature Climate Change, Nature, vol. 4(5), pages 318-320, May.
    4. Nigel W. Arnell, 2016. "The global-scale impacts of climate change: the QUEST-GSI project," Climatic Change, Springer, vol. 134(3), pages 343-352, February.
    5. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    6. Hansson, Helena, 2007. "Strategy factors as drivers and restraints on dairy farm performance: Evidence from Sweden," Agricultural Systems, Elsevier, vol. 94(3), pages 726-737, June.
    7. Hafiz Muhammad Abrar Ilyas & Majeed Safa & Alison Bailey & Sara Rauf & Azeem Khan, 2020. "Energy Efficiency Outlook of New Zealand Dairy Farming Systems: An Application of Data Envelopment Analysis (DEA) Approach," Energies, MDPI, vol. 13(1), pages 1-14, January.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Thomas Fellmann & Peter Witzke & Franz Weiss & Benjamin Van Doorslaer & Dusan Drabik & Ingo Huck & Guna Salputra & Torbjörn Jansson & Adrian Leip, 2018. "Major challenges of integrating agriculture into climate change mitigation policy frameworks," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(3), pages 451-468, March.
    10. Kaoru Tone, 2011. "Slacks-Based Measure of Efficiency," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 195-209, Springer.
    11. Jara Laso & Daniel Hoehn & María Margallo & Isabel García-Herrero & Laura Batlle-Bayer & Alba Bala & Pere Fullana-i-Palmer & Ian Vázquez-Rowe & Angel Irabien & Rubén Aldaco, 2018. "Assessing Energy and Environmental Efficiency of the Spanish Agri-Food System Using the LCA/DEA Methodology," Energies, MDPI, vol. 11(12), pages 1-18, December.
    12. Laure Latruffe & Kelvin Balcombe & Sophia Davidova & Katarzyna Zawalinska, 2005. "Technical and scale efficiency of crop and livestock farms in Poland : does specialization matte r?," Post-Print hal-02392195, HAL.
    13. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    14. Nigel Arnell, 2016. "The global-scale impacts of climate change: the QUEST-GSI project," Climatic Change, Springer, vol. 134(3), pages 343-352, February.
    15. Nigel Arnell & Simon Gosling, 2016. "The impacts of climate change on river flood risk at the global scale," Climatic Change, Springer, vol. 134(3), pages 387-401, February.
    16. Resti, Andrea, 2000. "Efficiency measurement for multi-product industries: A comparison of classic and recent techniques based on simulated data," European Journal of Operational Research, Elsevier, vol. 121(3), pages 559-578, March.
    17. Garcia, Magali & Raes, Dirk & Jacobsen, Sven-Erik, 2003. "Evapotranspiration analysis and irrigation requirements of quinoa (Chenopodium quinoa) in the Bolivian highlands," Agricultural Water Management, Elsevier, vol. 60(2), pages 119-134, May.
    18. Simon Gosling & Nigel Arnell, 2016. "A global assessment of the impact of climate change on water scarcity," Climatic Change, Springer, vol. 134(3), pages 371-385, February.
    19. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-16, July.
    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. Sudheer Padikkal & K. S. Sumam & N. Sajikumar, 2018. "Sustainability indicators of water sharing compacts," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(5), pages 2027-2042, October.
    2. Mónica Maldonado-Devis & Vicent Almenar-Llongo, 2021. "A Panel Data Estimation of Domestic Water Demand with IRT Tariff Structure: The Case of the City of Valencia (Spain)," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    3. Maria Fitzner & Anna Fricke & Monika Schreiner & Susanne Baldermann, 2021. "Utilization of Regional Natural Brines for the Indoor Cultivation of Salicornia europaea," Sustainability, MDPI, vol. 13(21), pages 1-12, November.
    4. Babadjanova, Mashkhura & Bobojonov, Ihtiyor & Bekchanov, Maksud & Kuhn, Lena & Glauben, Thomas, 2024. "Can domestic wheat farming meet the climate change-induced challenges of national food security in Uzbekistan?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 40(3), pages 448-462.
    5. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    6. Jiangmei Xiong & Yulin Hswen & John A. Naslund, 2020. "Digital Surveillance for Monitoring Environmental Health Threats: A Case Study Capturing Public Opinion from Twitter about the 2019 Chennai Water Crisis," IJERPH, MDPI, vol. 17(14), pages 1-15, July.
    7. Wijesiri, Buddhi & Hettiarachchi, Akash, 2021. "How gender disparities in urban and rural areas influence access to safe drinking water," Utilities Policy, Elsevier, vol. 68(C).
    8. Rachel Warren & Oliver Andrews & Sally Brown & Felipe J. Colón-González & Nicole Forstenhäusler & David E. H. J. Gernaat & P. Goodwin & Ian Harris & Yi He & Chris Hope & Desmond Manful & Timothy J. Os, 2022. "Quantifying risks avoided by limiting global warming to 1.5 or 2 °C above pre-industrial levels," Climatic Change, Springer, vol. 172(3), pages 1-16, June.
    9. Arathy Nair Geetha Raveendran Nair & Shamla Dilama Shamsudeen & Meera Geetha Mohan & Adarsh Sankaran, 2023. "Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment," Sustainability, MDPI, vol. 15(19), pages 1-27, September.
    10. Helmi Hammami & Thanh Ngo & David Tripe & Dinh-Tri Vo, 2022. "Ranking with a Euclidean common set of weights in data envelopment analysis: with application to the Eurozone banking sector," Annals of Operations Research, Springer, vol. 311(2), pages 675-694, April.
    11. Vimal Mishra & Rohini Kumar & Harsh L. Shah & Luis Samaniego & S. Eisner & Tao Yang, 2017. "Multimodel assessment of sensitivity and uncertainty of evapotranspiration and a proxy for available water resources under climate change," Climatic Change, Springer, vol. 141(3), pages 451-465, April.
    12. Ricart, Sandra & Rico, Antonio M., 2019. "Assessing technical and social driving factors of water reuse in agriculture: A review on risks, regulation and the yuck factor," Agricultural Water Management, Elsevier, vol. 217(C), pages 426-439.
    13. Akbari, Negar & Jones, Dylan & Treloar, Richard, 2020. "A cross-European efficiency assessment of offshore wind farms: A DEA approach," Renewable Energy, Elsevier, vol. 151(C), pages 1186-1195.
    14. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    15. Khezrimotlagh, Dariush, 2022. "Simulation designs for production frontiers," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1321-1334.
    16. Madau, Fabio A., 2012. "Technical and scale efficiency in the Italian Citrus Farming: A comparison between Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis(DEA) Models," MPRA Paper 41403, University Library of Munich, Germany.
    17. Manevska-Tasevska, Gordana & Hansson, Helena, 2010. "Influence of rural development policy targets on farm efficiency: An efficiency study of labour intensive grape growing family farms," IAMO Forum 2010: Institutions in Transition – Challenges for New Modes of Governance 52696, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
    18. Vincent Charles & Ioannis E. Tsolas & Tatiana Gherman, 2018. "Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector," Annals of Operations Research, Springer, vol. 269(1), pages 81-102, October.
    19. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    20. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.

    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:11:y:2021:i:11:p:1089-:d:671652. 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.