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Thermal Crop Water Stress Index Base Line Temperatures for Sugarbeet in Arid Western U.S

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  • King, B.A.
  • Tarkalson, D.D.
  • Sharma, V.
  • Bjorneberg, D.L.

Abstract

Sugarbeet is a deep-rooted crop in unrestricted soil profiles that can readily utilize stored soil water to reduce seasonal irrigation requirements. Soil water below 0.6 m is not commonly considered for irrigation scheduling due to the labor and expense of soil water monitoring at deeper depths and uncertainty in effective rooting depth and soil water holding capacity. Thermal-based crop water stress index (CWSI) irrigation scheduling for sugarbeet has the potential to overcome soil water monitoring limitations and facilitate utilization of stored soil water. In this study, canopy temperature of irrigated sugarbeet under full irrigation (FIT) and 25%FIT in 2014, 2015, 2017 and 2018 in southcentral Idaho and FIT and 60%FIT in 2018 in northwestern Wyoming USA was monitored from full cover through harvest along with meteorological conditions and soil water content. A neural network (NN) was used to predict well-watered canopy temperature based on 15-min average values for solar radiation, air temperature, relative humidity, and wind speed collected -1 to +2.5 hours of solar noon (13:00 – 16:00 MDT). A linear regression driven physical model for estimating the difference between a non-transpiring canopy and air temperature resulted in a value of 13.7 °C for the meteorological conditions of the study. A daily CWSI value calculated as the average 15-min CWSI calculated between 13:00 and 16:00 MDT was well correlated with irrigation amounts and timing. The daily CWSI value provided a more responsive indication of crop water stress than soil water monitoring in deficit irrigation treatments. The methodology used to calculate a daily CWSI could be used in irrigation scheduling to utilize soil water storage without knowledge of soil depth, crop rooting depth, or deep (> 0.6 m) soil water monitoring.

Suggested Citation

  • King, B.A. & Tarkalson, D.D. & Sharma, V. & Bjorneberg, D.L., 2021. "Thermal Crop Water Stress Index Base Line Temperatures for Sugarbeet in Arid Western U.S," Agricultural Water Management, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:agiwat:v:243:y:2021:i:c:s0378377419316191
    DOI: 10.1016/j.agwat.2020.106459
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    References listed on IDEAS

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    1. King, B.A. & Shellie, K.C., 2016. "Evaluation of neural network modeling to predict non-water-stressed leaf temperature in wine grape for calculation of crop water stress index," Agricultural Water Management, Elsevier, vol. 167(C), pages 38-52.
    2. Pou, Alícia & Diago, Maria P. & Medrano, Hipólito & Baluja, Javier & Tardaguila, Javier, 2014. "Validation of thermal indices for water status identification in grapevine," Agricultural Water Management, Elsevier, vol. 134(C), pages 60-72.
    3. 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.
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    2. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    3. Ramírez-Cuesta, J.M. & Ortuño, M.F. & Gonzalez-Dugo, V. & Zarco-Tejada, P.J. & Parra, M. & Rubio-Asensio, J.S. & Intrigliolo, D.S., 2022. "Assessment of peach trees water status and leaf gas exchange using on-the-ground versus airborne-based thermal imagery," Agricultural Water Management, Elsevier, vol. 267(C).
    4. Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).

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