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A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum

Author

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  • O'Shaughnessy, Susan A.
  • Evett, Steven R.
  • Colaizzi, Paul D.
  • Howell, Terry A.

Abstract

Variations of the crop water stress index (CWSI) have been used to characterize plant water stress and schedule irrigations. Usually, this thermal-based stress index has been calculated from measurements taken once daily or over a short period of time, near solar noon or after and in cloud free conditions. A method of integrating the CWSI over a day was developed to avoid the noise that may occur if weather prevents a clear CWSI signal near solar noon. This CWSI and time threshold (CWSI-TT) was the accumulated time that the CWSI was greater than a threshold value (0.45); and it was compared with a time threshold (CWSI-TT) based on a well-watered crop. We investigated the effectiveness of the CWSI-TT to automatically control irrigation of short and long season grain sorghum hybrids (Sorghum bicolor (L.) Moench, NC+ 5C35 and Pioneer 84G62); and to examine crop response to deficit irrigation treatments (i.e. 80%, 55%, 30% and 0% of full replenishment of soil water depletion to 1.5-m depth). Results from automated irrigation scheduling were compared to those from manual irrigation based on weekly neutron probe readings. In 2009, results from the Automatic irrigation were mixed; biomass yields in the 55% and 0% treatments, dry grain yields in the 80% and 0% treatments, and WUE in the 80%, 55%, and 0% treatments were not significantly different from those in the corresponding Manual treatments. However, dry grain yields in the 55% and 30% treatments were significantly less than those in the Manual control plots. These differences were due mainly to soil water variability in the beginning of the growing season. This conclusion is reinforced by the fact that IWUE for dry grain yield was not significantly different for 30% and 55% treatments, and was significantly greater for Automatic control at 80%. In 2010, there were no significant differences in biomass, dry grain yield, WUE, or IWUE for irrigation control methods when compared across the same amount treatments. Similar results between irrigation methods for at least the highest irrigation rate (80% of soil water depletion) in 2009 and among all irrigation treatment amounts in 2010 indicate that the CWSI-TT method can be an effective trigger for automatically scheduling either full or deficit irrigations for grain sorghum in a semi-arid region.

Suggested Citation

  • O'Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D. & Howell, Terry A., 2012. "A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum," Agricultural Water Management, Elsevier, vol. 107(C), pages 122-132.
  • Handle: RePEc:eee:agiwat:v:107:y:2012:i:c:p:122-132 DOI: 10.1016/j.agwat.2012.01.018
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    References listed on IDEAS

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    1. Olufayo, A. & Baldy, C. & Ruelle, P., 1996. "Sorghum yield, water use and canopy temperatures under different levels of irrigation," Agricultural Water Management, Elsevier, vol. 30(1), pages 77-90, March.
    2. Gontia, N.K. & Tiwari, K.N., 2008. "Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry," Agricultural Water Management, Elsevier, vol. 95(10), pages 1144-1152, October.
    3. Yuan, Guofu & Luo, Yi & Sun, Xiaomin & Tang, Dengyin, 2004. "Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 64(1), pages 29-40, January.
    4. Emekli, Yasar & Bastug, Ruhi & Buyuktas, Dursun & Emekli, Nefise Yasemin, 2007. "Evaluation of a crop water stress index for irrigation scheduling of bermudagrass," Agricultural Water Management, Elsevier, vol. 90(3), pages 205-212, June.
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    1. repec:eee:agiwat:v:187:y:2017:i:c:p:173-189 is not listed on IDEAS
    2. O’Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D., 2015. "Dynamic prescription maps for site-specific variable rate irrigation of cotton," Agricultural Water Management, Elsevier, vol. 159(C), pages 123-138.
    3. Vasilenko, Alexandr & Ulman, Miloš, 2015. "Concept of Horticulture Ambient Intelligence System," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 7(4), December.
    4. Laouisset, M. B. & Dellal, A., 2016. "Estimation of Barley (Hordeum Vulgare L.) Crop Water Requirements Using Cropwat Software in Ksar-Chellala Region, Algeria," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 8(3), September.
    5. DeJonge, Kendall C. & Taghvaeian, Saleh & Trout, Thomas J. & Comas, Louise H., 2015. "Comparison of canopy temperature-based water stress indices for maize," Agricultural Water Management, Elsevier, vol. 156(C), pages 51-62.
    6. Zhang, Xiaoyu & Zhang, Xiying & Liu, Xiuwei & Shao, Liwei & Sun, Hongyong & Chen, Suying, 2015. "Incorporating root distribution factor to evaluate soil water status for winter wheat," Agricultural Water Management, Elsevier, vol. 153(C), pages 32-41.

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