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Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton

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  • O'Shaughnessy, S.A.
  • Evett, S.R.

Abstract

Cotton is a perennial plant with an indeterminate growth pattern that is typically produced like an annual, but requires proper management to effectively produce high yields and good fiber quality in a thermally limited environment like the northern Texas High Plains. In 2007 and 2008, we investigated the effect of irrigation scheduling/control method and amount on cotton (Gossypium hirsutum L.) yield and water use efficiency. Methods were automatic irrigation scheduling and control of a center pivot system, and manually scheduled irrigation to replenish soil-water to field capacity. Cotton was irrigated with LEPA (low energy, precision application) drag socks in furrow dikes; three blocks were irrigated manually and three were irrigated automatically. Six replicates of the manual and automatic irrigation treatments were included in the randomized block design. Manual irrigations were based on the weekly replenishment of soil-water to field capacity in the top 1.5m of the soil profile and included a fully irrigated treatment (I100), and treatments receiving 67% (I67) and 33% (I33) of the I100 amount, plus a non-irrigated treatment (I0). Automatic irrigations were triggered using a time temperature threshold (TTT) algorithm, which was designated as the I100 treatment, and treatments receiving 67%, 33%, and 0% of that amount (I67, I33 and I0, respectively). In 2007, overall mean lint yields (102.3 and 101.6gm-2, manual and automatic, respectively) were not significantly different. Similarly, yields were not significantly different across automatic and manual treatments in the same treatment level, with the exception of the I67 treatment where the manual treatment yields were 11% greater. In 2008, the mean yields were 70% less than those in 2007 for both methods of irrigation (30.3 and 30.9gm-2, manual and automatic, respectively) due to harsh climatic conditions at emergence and heavy rainfall and cooler temperatures in the month of August. Yields from the automatically irrigated plots in the I100 and I67 treatments, however, were significantly greater than yields from the corresponding manually irrigated plots; though there was no significant difference between yields in the drier treatments (I33 and I0) plots. These results indicate that the TTT algorithm is a promising method for auto-irrigation scheduling of short season cotton in an arid region. However, further studies are essential to demonstrate consistent positive outcomes.

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  • 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.
    • Handle: RePEc:eee:agiwat:v:97:y:2010:i:9:p:1310-1316
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    1. Al-Kaisi, Mahdi M. & Berrada, Abdel & Stack, Mark, 1997. "Evaluation of irrigation scheduling program and spring wheat yield response in southwestern Colorado," Agricultural Water Management, Elsevier, vol. 34(2), pages 137-148, August.
    2. Tennakoon, S. B. & Milroy, S. P., 2003. "Crop water use and water use efficiency on irrigated cotton farms in Australia," Agricultural Water Management, Elsevier, vol. 61(3), pages 179-194, July.
    3. 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.
    4. Hunsaker, D. J. & Clemmens, A. J. & Fangmeier, D. D., 1998. "Cotton response to high frequency surface irrigation," Agricultural Water Management, Elsevier, vol. 37(1), pages 55-74, June.
    5. Ibragimov, Nazirbay & Evett, Steven R. & Esanbekov, Yusupbek & Kamilov, Bakhtiyor S. & Mirzaev, Lutfullo & Lamers, John P.A., 2007. "Water use efficiency of irrigated cotton in Uzbekistan under drip and furrow irrigation," Agricultural Water Management, Elsevier, vol. 90(1-2), pages 112-120, May.
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    Cited by:

    1. Chen, Xiaoping & Qi, Zhiming & Gui, Dongwei & Sima, Matthew W. & Zeng, Fanjiang & Li, Lanhai & Li, Xiangyi & Gu, Zhe, 2020. "Evaluation of a new irrigation decision support system in improving cotton yield and water productivity in an arid climate," Agricultural Water Management, Elsevier, vol. 234(C).
    2. Fan, Yubing & Himanshu, Sushil K. & Ale, Srinivasulu & DeLaune, Paul B. & Zhang, Tian & Park, Seong C. & Colaizzi, Paul D. & Evett, Steven R. & Baumhardt, R. Louis, 2022. "The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 262(C).
    3. Ezenne, G.I. & Jupp, Louise & Mantel, S.K. & Tanner, J.L., 2019. "Current and potential capabilities of UAS for crop water productivity in precision agriculture," Agricultural Water Management, Elsevier, vol. 218(C), pages 158-164.
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    5. Kullberg, Emily G. & DeJonge, Kendall C. & Chávez, José L., 2017. "Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients," Agricultural Water Management, Elsevier, vol. 179(C), pages 64-73.
    6. Li, Xiumei & Zhao, Weixia & Li, Jiusheng & Li, Yanfeng, 2019. "Maximizing water productivity of winter wheat by managing zones of variable rate irrigation at different deficit levels," Agricultural Water Management, Elsevier, vol. 216(C), pages 153-163.
    7. Colaizzi, Paul D. & O’Shaughnessy, Susan A. & Evett, Steve R. & Mounce, Ryan B., 2017. "Crop evapotranspiration calculation using infrared thermometers aboard center pivots," Agricultural Water Management, Elsevier, vol. 187(C), pages 173-189.
    8. 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.
    9. O’Shaughnessy, Susan A. & Kim, Minyoung & Andrade, Manuel A. & Colaizzi, Paul D. & Evett, Steven R., 2020. "Site-specific irrigation of grain sorghum using plant and soil water sensing feedback - Texas High Plains," Agricultural Water Management, Elsevier, vol. 240(C).
    10. O'Shaughnessy, S.A. & Evett, S.R. & Colaizzi, P.D. & Howell, T.A., 2011. "Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton," Agricultural Water Management, Elsevier, vol. 98(10), pages 1523-1535, August.
    11. 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.
    12. Garibay, Victoria M. & Kothari, Kritika & Ale, Srinivasulu & Gitz, Dennis C. & Morgan, Gaylon D. & Munster, Clyde L., 2019. "Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    13. Romero, R. & Muriel, J.L. & García, I. & Muñoz de la Peña, D., 2012. "Research on automatic irrigation control: State of the art and recent results," Agricultural Water Management, Elsevier, vol. 114(C), pages 59-66.
    14. Liang, Xi & Liakos, Vasilis & Wendroth, Ole & Vellidis, George, 2016. "Scheduling irrigation using an approach based on the van Genuchten model," Agricultural Water Management, Elsevier, vol. 176(C), pages 170-179.

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