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Improving the precision of irrigation in a pistachio farm using an unmanned airborne thermal system

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Abstract

A study was conducted in a large pistachio farm in Madera County, California, to assess the spatial variability in water status and irrigation needs by using high-resolution thermal imagery acquired by an unmanned aerial system. We determined the Crop Water Stress Index (CWSI) of two fields, 130 ha each, based on canopy temperature measurements of individual tree crowns, thus assessing the spatial variations in tree water status within each field. The CWSI of each potential management unit (sectors encompassing about 175 trees) was then calculated and related to the days since last irrigation (DSLI) in F1 and F2. The relationship between CWSI and DSLI was established to calculate the average CWSI corresponding to the whole area that was irrigated on the same day. This value was afterward compared with the actual CWSI value of each management unit as a proxy of the spatial variability in CWSI. This information was used to calculate the deviation of each irrigation unit from the fixed irrigation schedule for the whole fields. Our results show that it is feasible to use high-resolution thermal imagery for integrating the crop response in irrigation performance assessment and for providing recommendations at the farm scale.

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References

  • Ambast SK, Keshari AK, Gosain AK (2002) Satellite remote sensing to support management of irrigation systems: concepts and approaches. Irrig Drain 51(1):25–39

    Article  Google Scholar 

  • Bellvert J, Zarco-Tejada PJ, Girona J, Fereres E (2014) Mapping crop water stress index in a “Pinot Noir” vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle. Precis Agric 15:361–376

    Article  Google Scholar 

  • Ben-Gal A, Agam N, Alchanatis V, Cohen Y, Yermiyahu U, Zipori I, Presnov E, Sprintsin M, Dag A (2009) Evaluating water stress in irrigated olives: correlation of soil water status, tree water status, and thermal imagery. Irrig Sci 27:367–376

    Article  Google Scholar 

  • Berni JAJ, Zarco-Tejada PJ, Sepulcre-Canto G, Fereres E, Villalobos F (2009a) Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery. Remote Sens Environ 113:2380–2388

    Article  Google Scholar 

  • Berni JAJ, Zarco-Tejada PJ, Suarez L, Fereres E (2009b) Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans Geosci Remote Sens 47(3):722–738

    Article  Google Scholar 

  • Bonachela S, Orgaz F, Villalobos FJ, Fereres E (2001) Soil evaporation from drip-irrigated olive orchards. Irrig Sci 20(2):65–71

    Article  Google Scholar 

  • Bresler E (1977) Trickle-drip irrigation: principles and application to soil-water management. Adv Agron 29:343–393

    Article  Google Scholar 

  • Evans RG, Sadler EJ (2008) Methods and technologies to improve efficiency of water use. Water Resour Res 44:W00E04. doi:10.1029/2007WR006200

  • Goldhamer DA, Fereres E (2001) Simplified tree water status measurements can aid almond irrigation. Calif Agric 55(3):32–38

    Article  Google Scholar 

  • Gonzalez-Dugo V, Zarco-Tejada P, Berni JAJ, Suarez L, Goldhamer D, Fereres E (2012) Almond tree canopy temperature reveals intra-crown variability that is water stress-dependent. Agric For Meteorol 154–155:156–165

    Article  Google Scholar 

  • Gonzalez-Dugo V, Zarco-Tejada P, Nicolas E, Nortes PA, Alarcon JJ, Intrigliolo DS, Fereres E (2013) Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard. Precis Agric 14(6):660–678

    Article  Google Scholar 

  • Hsiao TC (1990) Measurement of plant water status. In: Stewart BA, Nielsen DC (eds) Irrigation of agriculture crops, vol special publication no. 30. Am Soc Agron, Madison, WI, USA, pp 243–279

  • Idso SB, Jackson RD, Pinter PJ Jr, Reginato RJ, Hatfield JL (1981) Normalizing the stressdegree-day parameter for environmental variability. Agric Meteorol 24:45–55

    Article  Google Scholar 

  • Iniesta F, Testi L, Goldhamer D, Fereres E (2008) Quantifying reductions in consumptive water use under regulated deficit irrigation in pistachio (Pistachia vera L.). Agric Water Manag 95:877–886

    Article  Google Scholar 

  • Jackson RD, Reginato RJ, Idso SB (1977) Wheat canopy temperature: a practical tool for evaluating water requirements. Water Resour Res 13(3):651–656

    Article  Google Scholar 

  • Jackson R, Idso S, Reginato R, Pinter PJ (1981) Canopy temperature as a crop water stress indicator. Water Resour Res 17:1133–1138

    Article  Google Scholar 

  • Jury WA, Vaux HR (2007) The emerging global water crisis: managing scarcity and conflict between water users. Adv Agron 95:1–76

    Article  Google Scholar 

  • Kravchenko AN, Robertson GP, Thelen KD, Harwood RR (2005) Management, topographical and weather effects on spatial variability of crop grain yields. Agron J 97:514–523

    Article  Google Scholar 

  • Lee WS, Alchanatis V, Yang C, Hirafuji M, Moshou D, Li C (2010) Sensing technologies for precision specialty crop production. Comp Electron Agric 74:2–33

    Article  Google Scholar 

  • Lord JM, Ayars JE (2007) Evaluating performance. In: Hoffman GJ, Evans RG, Jensen ME, Martin DL, Elliot RL (eds) Design and operation of farm irrigation systems. ASABE, St. Joseph, MI, USA, pp 791–803

  • Maes WH, Steppe K (2012) Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review. J Exp Bot 63(13):4671–4712

    Article  CAS  PubMed  Google Scholar 

  • Martin DI, Stegman EC, Fereres E (1990) Irrigation scheduling principles. In: Hoffman GJ (ed) Management of farm irrigation systems. ASAE, St. Joseph, pp 105–203

    Google Scholar 

  • Merriam JL, Keller J (1978) Farm irrigation system evaluation: a guide for management. Utah State University, Logan

    Google Scholar 

  • Molden D (2007) Water for food, water for life: a comprehensive assessment of water management in agriculture. International Water Management Institute, London

    Google Scholar 

  • Moran MS, Clarke TR, Inoue Y, Vidal A (1994) Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sens Environ 49(3):246–263

    Article  Google Scholar 

  • O’Shaughnessy SA, Evett SR, Colaizzi PD, Howell TA (2011) Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton. Agric Water Manag 98(10):1523–1535

    Article  Google Scholar 

  • O’Shaughnessy SA, Evett SR, Colaizzi PD, Howell TA (2013) Wireless sensor network effectively controls center pivot irrigation of sorghum. Appl Eng Agric 29(6):853–864

    Google Scholar 

  • Peters RT, Evett SR (2004) Complete center pivot automation using the temperature-time threshold method of irrigation scheduling. ASAE paper no. 042096. St. Joseph, MI

  • Rodriguez D, Robson AJ, Belford R (2009) Dynamic and functional monitoring technologies for applications in crop management. In: Sadras VO, Calderini D (eds) Crop physiology. Applications for genetic improvement and agronomy. Elsevier, Amsterdam, pp 489–510

  • Sadler EJ, Camp CR, Evans DE, Millen JA (2002) Spatial variation of corn response to irrigation. Trans Am Soc Agric Eng 45(6):1869–1881

    Article  Google Scholar 

  • Testi L, Goldhamer D, Iniesta F, Salinas M (2008) Crop water stress index is a sensitive water stress indicator in pistachio trees. Irrig Sci 26:395–405

    Article  Google Scholar 

  • Zarco-Tejada PJ, Gonzalez-Dugo V, Berni JAJ (2012) Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sens Environ 117:322–337

    Article  Google Scholar 

  • Zarco-Tejada PJ, Gonzalez-Dugo V, Williams LE, Suarez L, Berni JAJ, Goldhamer D, Fereres E (2013) A PRI-based water stress index combining structural and chlorophyll effects: assessment using diurnal narrow-band airborne imagery and the CWSI thermal index. Remote Sens Environ 138:38–50

    Article  Google Scholar 

  • Zhang N, Wang M, Wang N (2002) Precision agriculture—a worldwide overview. Comp Electron Agric 36(2–3):113–132

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge the contribution of Dr. J.A.J. Berni and Dr. L. Suarez during the field campaigns and D. Notario, A. Vera, M. Salinas and K. Brooks for their technical support. Chris Wylie and Richard Paslay, from Agri-World Cooperative, are also acknowledged. This work was funded by the Spanish Ministry of Science and Innovation (CONSOLIDER CSD2006-0067 and AGL2009-13105).

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Authors and Affiliations

  1. Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, 14004, Córdoba, Spain

    V. Gonzalez-Dugo, P. J. Zarco-Tejada & E. Fereres

  2. Department of Land, Air and Water Resources, University of California, Davis, CA, 95616, USA

    D. Goldhamer

  3. Departmento de Agronomía, Universidad de Cordoba, Campus Universitario de Rabanales, 14014, Córdoba, Spain

    E. Fereres

Authors
  1. V. Gonzalez-Dugo
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  2. D. Goldhamer
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  3. P. J. Zarco-Tejada
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  4. E. Fereres
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Corresponding author

Correspondence to V. Gonzalez-Dugo.

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Communicated by B. Evans.

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Gonzalez-Dugo, V., Goldhamer, D., Zarco-Tejada, P.J. et al. Improving the precision of irrigation in a pistachio farm using an unmanned airborne thermal system. Irrig Sci 33, 43–52 (2015). https://doi.org/10.1007/s00271-014-0447-z

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  • DOI: https://doi.org/10.1007/s00271-014-0447-z

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