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Corn yield responses under crop evapotranspiration-based irrigation management

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  • Ko, Jonghan
  • Piccinni, Giovanni

Abstract

Improving irrigation water management is becoming important to produce a profitable crop in South Texas as the water supplies shrink. This study was conducted to investigate grain yield responses of corn (Zea mays) under irrigation management based on crop evapotranspiration (ETC) as well as a possibility to monitor plant water deficiencies using some of physiological and environmental factors. Three commercial corn cultivars were grown in a center-pivot-irrigated field with low energy precision application (LEPA) at Texas AgriLife Research Center in Uvalde, TX from 2002 to 2004. The field was treated with conventional and reduced tillage practices and irrigation regimes of 100%, 75%, and 50% ETC. Grain yield was increased as irrigation increased. There were significant differences between 100% and 50% ETC in volumetric water content ([theta]), leaf relative water content (RWC), and canopy temperature (TC). It is considered that irrigation management of corn at 75% ETC is feasible with 10% reduction of grain yield and with increased water use efficiency (WUE). The greatest WUE (1.6gm-2mm-1) achieved at 456mm of water input while grain yield plateaued at less than 600mm. The result demonstrates that ETC-based irrigation can be one of the efficient water delivery schemes. The results also demonstrate that grain yield reduction of corn is qualitatively describable using the variables of RWC and TC. Therefore, it appears that water status can be monitored with measurement of the variables, promising future development of real-time irrigation scheduling.

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  • Ko, Jonghan & Piccinni, Giovanni, 2009. "Corn yield responses under crop evapotranspiration-based irrigation management," Agricultural Water Management, Elsevier, vol. 96(5), pages 799-808, May.
    • Handle: RePEc:eee:agiwat:v:96:y:2009:i:5:p:799-808
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    7. Kögler, F. & Söffker, D., 2017. "Water (stress) models and deficit irrigation: System-theoretical description and causality mapping," Ecological Modelling, Elsevier, vol. 361(C), pages 135-156.
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    11. Babalola, Toju Esther & Adabembe, Bolaji Adelanke & Faloye, Oluwaseun Temitope, 2022. "Water use - yield relationship of maize as influenced by biochar and inorganic fertilizer applications in a tropical sandy clay loam soil," Agricultural Water Management, Elsevier, vol. 271(C).
    12. Gheysari, Mahdi & Sadeghi, Sayed-Hossein & Loescher, Henry W. & Amiri, Samia & Zareian, Mohammad Javad & Majidi, Mohammad M. & Asgarinia, Parvaneh & Payero, Jose O., 2017. "Comparison of deficit irrigation management strategies on root, plant growth and biomass productivity of silage maize," Agricultural Water Management, Elsevier, vol. 182(C), pages 126-138.
    13. Araya, A. & Kisekka, Isaya & Gowda, Prasanna H. & Prasad, P.V. Vara, 2017. "Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM," Agricultural Systems, Elsevier, vol. 150(C), pages 86-98.
    14. Campana, P.E. & Lastanao, P. & Zainali, S. & Zhang, J. & Landelius, T. & Melton, F., 2022. "Towards an operational irrigation management system for Sweden with a water–food–energy nexus perspective," Agricultural Water Management, Elsevier, vol. 271(C).
    15. Zhao, Wenzhi & Chang, Xuexiang & Chang, Xueli & Zhang, Dengrong & Liu, Bing & Du, Jun & Lin, Pengfei, 2018. "Estimating water consumption based on meta-analysis and MODIS data for an oasis region in northwestern China," Agricultural Water Management, Elsevier, vol. 208(C), pages 478-489.
    16. Nandan, Rohit & Woo, Dong K. & Kumar, Praveen & Adinarayana, J., 2021. "Impact of irrigation scheduling methods on corn yield under climate change," Agricultural Water Management, Elsevier, vol. 255(C).
    17. Ertek, A. & Kara, B., 2013. "Yield and quality of sweet corn under deficit irrigation," Agricultural Water Management, Elsevier, vol. 129(C), pages 138-144.
    18. O'Shaughnessy, S.A. & Evett, S.R., 2010. "Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton," Agricultural Water Management, Elsevier, vol. 97(9), pages 1310-1316, September.
    19. Sotirios Kontogiannis & George Kokkonis & Soultana Ellinidou & Stavros Valsamidis, 2017. "Proposed Fuzzy-NN Algorithm with LoRaCommunication Protocol for Clustered Irrigation Systems," Future Internet, MDPI, vol. 9(4), pages 1-23, November.
    20. DeJonge, K.C. & Ascough, J.C. & Andales, A.A. & Hansen, N.C. & Garcia, L.A. & Arabi, M., 2012. "Improving evapotranspiration simulations in the CERES-Maize model under limited irrigation," Agricultural Water Management, Elsevier, vol. 115(C), pages 92-103.

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