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Current and potential capabilities of UAS for crop water productivity in precision agriculture

Author

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  • Ezenne, G.I.
  • Jupp, Louise
  • Mantel, S.K.
  • Tanner, J.L.

Abstract

In order to feed growing populations under scare water resources, a suitable technology that improves crop water productivity (CWP) is crucial. Precision agriculture that utilizes digital techniques such as unmanned aerial systems (UAS) can play a significant role in improving CWP. CWP is an important indicator that quantifies the effect of agricultural water management. To improve CWP, implementation of suitable methods for early detection of crop water stress before irreversible damage on crops occurs, is vital. Conventionally, farmers have relied on in situ measurements of soil moisture and weather variables for detecting crop water status for irrigation scheduling. This method is time consuming and does not account for spatial and temporal variability associated with crop water status. Hence, the aim of this study is to give an overview of the current and potential capabilities of UAS for crop water productivity in precision agriculture. Identified in this study are the factors as well as the technology that can improve CWP. UAS thermal remote sensing is found to be the most suitable technology for monitoring and assessing crop water status using certain indices. Determining a crop water stress index (CWSI) from thermal imagery has the potential to detect instantaneous variations of water status. CWSI obtained from UAS thermal imaging camera can be adapted for real-time irrigation scheduling for maximum crop water productivity.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:agiwat:v:218:y:2019:i:c:p:158-164
    DOI: 10.1016/j.agwat.2019.03.034
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    1. Jiménez-Bello, M.A. & Ballester, C. & Castel, J.R. & Intrigliolo, D.S., 2011. "Development and validation of an automatic thermal imaging process for assessing plant water status," Agricultural Water Management, Elsevier, vol. 98(10), pages 1497-1504, August.
    2. 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.
    3. Gago, J. & Douthe, C. & Coopman, R.E. & Gallego, P.P. & Ribas-Carbo, M. & Flexas, J. & Escalona, J. & Medrano, H., 2015. "UAVs challenge to assess water stress for sustainable agriculture," Agricultural Water Management, Elsevier, vol. 153(C), pages 9-19.
    4. Igbadun, Henry E. & Mahoo, Henry F. & Tarimo, Andrew K.P.R. & Salim, Baanda A., 2006. "Crop water productivity of an irrigated maize crop in Mkoji sub-catchment of the Great Ruaha River Basin, Tanzania," Agricultural Water Management, Elsevier, vol. 85(1-2), pages 141-150, September.
    5. Léllis, B.C. & Carvalho, D.F. & Martínez-Romero, A. & Tarjuelo, J.M. & Domínguez, A., 2017. "Effective management of irrigation water for carrot under constant and optimized regulated deficit irrigation in Brazil," Agricultural Water Management, Elsevier, vol. 192(C), pages 294-305.
    6. Han, Ming & Zhang, Huihui & DeJonge, Kendall C. & Comas, Louise H. & Trout, Thomas J., 2016. "Estimating maize water stress by standard deviation of canopy temperature in thermal imagery," Agricultural Water Management, Elsevier, vol. 177(C), pages 400-409.
    7. Santesteban, L.G. & Di Gennaro, S.F. & Herrero-Langreo, A. & Miranda, C. & Royo, J.B. & Matese, A., 2017. "High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard," Agricultural Water Management, Elsevier, vol. 183(C), pages 49-59.
    8. Alessandro Matese & Salvatore Filippo Di Gennaro, 2018. "Practical Applications of a Multisensor UAV Platform Based on Multispectral, Thermal and RGB High Resolution Images in Precision Viticulture," Agriculture, MDPI, vol. 8(7), pages 1-13, July.
    9. Zwart, Sander J. & Bastiaanssen, Wim G. M., 2004. "Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize," Agricultural Water Management, Elsevier, vol. 69(2), pages 115-133, September.
    10. Araya, A. & Kisekka, I. & Gowda, P.H. & Prasad, P.V.V., 2018. "Grain sorghum production functions under different irrigation capacities," Agricultural Water Management, Elsevier, vol. 203(C), pages 261-271.
    11. Egea, Gregorio & Padilla-Díaz, Carmen M. & Martinez-Guanter, Jorge & Fernández, José E. & Pérez-Ruiz, Manuel, 2017. "Assessing a crop water stress index derived from aerial thermal imaging and infrared thermometry in super-high density olive orchards," Agricultural Water Management, Elsevier, vol. 187(C), pages 210-221.
    12. Barrios-Masias, Felipe H. & Jackson, Louise E., 2016. "Increasing the effective use of water in processing tomatoes through alternate furrow irrigation without a yield decrease," Agricultural Water Management, Elsevier, vol. 177(C), pages 107-117.
    13. 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.
    14. García-Tejero, I.F. & Costa, J.M. & Egipto, R. & Durán-Zuazo, V.H. & Lima, R.S.N. & Lopes, C.M. & Chaves, M.M., 2016. "Thermal data to monitor crop-water status in irrigated Mediterranean viticulture," Agricultural Water Management, Elsevier, vol. 176(C), pages 80-90.
    15. 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.
    16. 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.
    17. 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.
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