IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v173y2016icp67-75.html
   My bibliography  Save this article

Effect of water availability on growth, water use efficiency and omega 3 (ALA) content in two phenotypes of chia (Salvia hispanica L.) established in the arid Mediterranean zone of Chile

Author

Listed:
  • Herman, Silva
  • Marco, Garrido
  • Cecilia, Baginsky
  • Alfonso, Valenzuela
  • Luis, Morales
  • Cristián, Valenzuela
  • Sebastián, Pavez
  • Sebastián, Alister

Abstract

Chia (Salvia hispanica L.), has achieved economic importance due to the products which are obtained from its leaves with antioxidant capacity and especially its seeds, because they contain omega 3. However, there is a lack of information on optimal agronomic management practices and especially the influence of water availability on its establishment and production. The objective of this study was to evaluate the effect of different irrigation rates on growth and water use efficiency (WUE) in the production of leaf biomass, seeds and omega 3 in two phenotypes of chia, black and white. We applied three irrigation treatments calculated to be 100, 70 and 40% of the mean evaporative demand (ET0) calculated weekly, designated as T1, T3, T5 black phenotype and T2, T4 and T6 white phenotype; T1 and T2 irrigated to 100%; T3 and T4 irrigated to 70% and T5-T6 irrigated to 40% ETo. There was no difference between phenotypes, however, water treatment affected the gas exchange parameters photosynthesis, stomatal conductance and transpiration, which ranged from 26 to 4μmolm−2s−1; 4.5 to 1.5mmolm−2s−1 and 0.6 to 0.1molm−2s−1 from treatment (54 days after sowing) to harvest, respectively. A significant effect of water availability on WUE was observed in biomass production and yield, with 0.87 and 0.11kgm−3, respectively. Biomass production and yield were higher in plants irrigated at 100% ET0. Finally, reduced availability of water increased oil yield by 27% and the WUE for ALA from 3.4 to 8.6mgL−1. These findings demonstrate that WUE for biomass and yield is a constant value; that chia is highly sensitive to water deficit but adopts adaptive strategies that maintains its yield andincreases the percentage of lipids and omega3.

Suggested Citation

  • Herman, Silva & Marco, Garrido & Cecilia, Baginsky & Alfonso, Valenzuela & Luis, Morales & Cristián, Valenzuela & Sebastián, Pavez & Sebastián, Alister, 2016. "Effect of water availability on growth, water use efficiency and omega 3 (ALA) content in two phenotypes of chia (Salvia hispanica L.) established in the arid Mediterranean zone of Chile," Agricultural Water Management, Elsevier, vol. 173(C), pages 67-75.
  • Handle: RePEc:eee:agiwat:v:173:y:2016:i:c:p:67-75
    DOI: 10.1016/j.agwat.2016.04.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377416301536
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2016.04.028?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.

    References listed on IDEAS

    as
    1. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Jing & Zhang, Huihui & Sima, Matthew W. & Trout, Thomas J. & Malone, Rob W. & Wang, Li, 2021. "Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2," Agricultural Water Management, Elsevier, vol. 246(C).
    2. Samantha J. Grimes & Timothy D. Phillips & Volker Hahn & Filippo Capezzone & Simone Graeff-Hönninger, 2018. "Growth, Yield Performance and Quality Parameters of Three Early Flowering Chia ( Salvia hispanica L.) Genotypes Cultivated in Southwestern Germany," Agriculture, MDPI, vol. 8(10), pages 1-20, October.

    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. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    2. S. A. Abu Bakar & Saralees Nadarajah & Z. A. Absl Kamarul Adzhar, 2018. "Loss modeling using Burr mixtures," Empirical Economics, Springer, vol. 54(4), pages 1503-1516, June.
    3. Jaewoong Yun, 2023. "Strategies for Improving the Sustainability of Fare-Free Policy for the Elderly through Preferences by Travel Modes," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    4. Malerba, Martino E. & Connolly, Sean R. & Heimann, Kirsten, 2015. "An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake," Ecological Modelling, Elsevier, vol. 317(C), pages 30-40.
    5. Friederike Paetz, 2016. "Persönlichkeitsmerkmale als Segmentierungsvariablen: Eine empirische Studie [Personality traits for market segmentation: An empirical study]," Schmalenbach Journal of Business Research, Springer, vol. 68(3), pages 279-306, August.
    6. Rosbergen, Edward & Wedel, Michel & Pieters, Rik, 1997. "Analyzing visual attention tot repeated print advertising using scanpath theory," Research Report 97B32, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    7. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.
    8. Golob, Thomas F. & Regan, A C, 2002. "Trucking Industry Preferences for Driver Traveler Information Using Wireless Internet-enabled Devices," University of California Transportation Center, Working Papers qt40q8h6sf, University of California Transportation Center.
    9. Golob, Thomas F. & Regan, A C, 2003. "Traffic Congestion and Trucking Managers' Use of Automated Routing and Scheduling," University of California Transportation Center, Working Papers qt74z234n4, University of California Transportation Center.
    10. Naiara Escalante Mateos & Eider Goñi Palacios & Arantza Fernández-Zabala & Iratxe Antonio-Agirre, 2020. "Internal Structure, Reliability and Invariance across Gender Using the Multidimensional School Climate Scale PACE-33," IJERPH, MDPI, vol. 17(13), pages 1-24, July.
    11. Lee, Jaehyung & Lee, Euntak & Yun, Jaewoong & Chung, Jin-Hyuk & Kim, Jinhee, 2021. "Latent heterogeneity in autonomous driving preferences and in-vehicle activities by travel distance," Journal of Transport Geography, Elsevier, vol. 94(C).
    12. Jung, Hyekyung & Schafer, Joseph L. & Seo, Byungtae, 2011. "A latent class selection model for nonignorably missing data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 802-812, January.
    13. Emmanuel Afuecheta & Idika E. Okorie & Saralees Nadarajah & Geraldine E. Nzeribe, 2024. "Forecasting Value at Risk and Expected Shortfall of Foreign Exchange Rate Volatility of Major African Currencies via GARCH and Dynamic Conditional Correlation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 271-304, January.
    14. Simona Buscemi & Antonella Plaia, 2020. "Model selection in linear mixed-effect models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 529-575, December.
    15. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    16. Durrant Gabriele B. & Maslovskaya Olga & Smith Peter W. F., 2017. "Using Prior Wave Information and Paradata: Can They Help to Predict Response Outcomes and Call Sequence Length in a Longitudinal Study?," Journal of Official Statistics, Sciendo, vol. 33(3), pages 801-833, September.
    17. Richartz, P. Christoph & Abdulai, Awudu & Kornher, Lukas, 2020. "Attribute Non Attendance and Consumer Preferences for Online Food Products in Germany," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 69(1), March.
    18. Golob, Thomas F. & Recker, Wilfred W. & Alvarez, Veronica M., 2004. "Safety aspects of freeway weaving sections," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(1), pages 35-51, January.
    19. Sun-Joo Cho & Allan Cohen & Brian Bottge, 2013. "Detecting Intervention Effects Using a Multilevel Latent Transition Analysis with a Mixture IRT Model," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 576-600, July.
    20. Sarah Brown & William Greene & Mark Harris, 2020. "A novel approach to latent class modelling: identifying the various types of body mass index individuals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 983-1004, June.

    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:agiwat:v:173:y:2016:i:c:p:67-75. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.