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Assessing a crop water stress index derived from aerial thermal imaging and infrared thermometry in super-high density olive orchards

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  • Egea, Gregorio
  • Padilla-Díaz, Carmen M.
  • Martinez-Guanter, Jorge
  • Fernández, José E.
  • Pérez-Ruiz, Manuel

Abstract

Characterization of the spatio-temporal variability of tree water status is a prerequisite to conducting precise irrigation management in fruit tree orchards. This study assessed the suitability of a crop water stress index (CWSI) derived from high-resolution aerial thermal imagery for estimating tree water status variability in super high density (SHD) olive orchards. The experiment was conducted at a commercial SHD olive orchard near Seville (southwestern Spain), with drip irrigated trees under three irrigation treatments (four plots per treatment in a randomized block design): a full irrigation treatment to replace the crop water needs (ETc) and two regulated deficit irrigation treatments to replace ca. 45% of ETc. Meteorological variables, soil moisture content, leaf water potential, stem water potential and leaf gas exchange measurements were performed along the irrigation season. Infrared temperature sensors (IRTs) installed approximately 1m above the canopies were used to derive the required Non-Water-Stressed Baselines (NWSBs) for CWSI calculation. NWSBs were not common during the growing season, although the seasonal effect could be partly explained with solar angle variations. A thermal camera installed on a mini Remotely Piloted Aircraft System (RPAS) allowed for the recording of high-resolution thermal images on 5 representative dates during the irrigation season. The CWSI values derived from aerial thermal imagery were sensitive to the imposed variations in tree water status within the SHD olive orchard. Among the recorded variables, maximum stomatal conductance showed the tightest correlation with CWSI. We concluded that high-resolution thermal imagery captured from a mini RPAS is a suitable tool for defining tree water status variability within SHD olive orchards.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:agiwat:v:187:y:2017:i:c:p:210-221
    DOI: 10.1016/j.agwat.2017.03.030
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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. Egea, Gregorio & Diaz-Espejo, Antonio & Fernández, José E., 2016. "Soil moisture dynamics in a hedgerow olive orchard under well-watered and deficit irrigation regimes: Assessment, prediction and scenario analysis," Agricultural Water Management, Elsevier, vol. 164(P2), pages 197-211.
    3. Padilla-Díaz, C.M. & Rodriguez-Dominguez, C.M. & Hernandez-Santana, V. & Perez-Martin, A. & Fernández, J.E., 2016. "Scheduling regulated deficit irrigation in a hedgerow olive orchard from leaf turgor pressure related measurements," Agricultural Water Management, Elsevier, vol. 164(P1), pages 28-37.
    4. Alderfasi, Ali Abdullah & Nielsen, David C., 2001. "Use of crop water stress index for monitoring water status and scheduling irrigation in wheat," Agricultural Water Management, Elsevier, vol. 47(1), pages 69-75, February.
    5. Agam, N. & Cohen, Y. & Berni, J.A.J. & Alchanatis, V. & Kool, D. & Dag, A. & Yermiyahu, U. & Ben-Gal, A., 2013. "An insight to the performance of crop water stress index for olive trees," Agricultural Water Management, Elsevier, vol. 118(C), pages 79-86.
    6. Corell, M. & Pérez-López, D. & Martín-Palomo, M.J. & Centeno, A. & Girón, I. & Galindo, A. & Moreno, M.M. & Moreno, C. & Memmi, H. & Torrecillas, A. & Moreno, F. & Moriana, A., 2016. "Comparison of the water potential baseline in different locations. Usefulness for irrigation scheduling of olive orchards," Agricultural Water Management, Elsevier, vol. 177(C), pages 308-316.
    7. Cuevas, M.V. & Torres-Ruiz, J.M. & Álvarez, R. & Jiménez, M.D. & Cuerva, J. & Fernández, J.E., 2010. "Assessment of trunk diameter variation derived indices as water stress indicators in mature olive trees," Agricultural Water Management, Elsevier, vol. 97(9), pages 1293-1302, September.
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    7. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2022. "Effects of image spatial resolution and statistical scale on water stress estimation performance of MGDEXG: A new crop water stress indicator derived from RGB images," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Sánchez-Piñero, M. & Martín-Palomo, M.J. & Andreu, L. & Moriana, A. & Corell, M., 2022. "Evaluation of a simplified methodology to estimate the CWSI in olive orchards," Agricultural Water Management, Elsevier, vol. 269(C).

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