Korean Journal of Soil Science and Fertilizer (한국토양비료학회지)

Korean Society of Soil Science and Fertilizer (한국토양비료학회)
권호 표지
DOI QR코드

DOI QR Code

Infrared Estimation of Canopy Temperature as Crop Water Stress Indicator

  • Kim, Minyoung (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration) ;
  • Kim, Seounghee (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration) ;
  • Kim, Youngjin (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration) ;
  • Choi, Yonghun (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration) ;
  • Seo, Myungchul (Crop Production and Physiology Research Division, National Institute of Crop Science, Rural Development Administration)
  • Received : 2015.10.05
  • Accepted : 2015.10.26
  • Published : 2015.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

Decision making by farmers regarding irrigation is critical for crop production. Therefore, the precision irrigation technique is very important to improve crop quality and yield. Recently, much attention has been given to remote sensing of crop canopy temperature as a crop water-stress indicator, because it is a scientifically based and easily applicable method even at field scales. This study monitored a series of time-variant canopy temperature of cucumber under three different irrigation treatments: under-irrigation (control), optimal-irrigation, and over-irrigation. The difference between canopy temperature ($T_c$) and air temperature ($T_a$), $T_c-T_a$, was calculated as an indicator of cucumber water stress. Vapor pressure deficit (VPD) was evaluated to define water stress on the basis of the temperature difference between leaf and air. The values of $T_c-T_a$ was negatively related to VPD; further, cucumber growth in the under- and over-irrigated fields showed water stress, in contrast to that grown in the optimally irrigated field. Thus, thermal infrared measurements could be useful for evaluating crop water status and play an important role in irrigation scheduling of agricultural crops.

Keywords

References

  1. Ahi, Y., H. Orta, A. Gunduz, and H. Gultas. 2015. The canopy temperature response to vapor pressure deficit of Grapevine cv. Semillon and Razaki, Agri. & Agri. Sci. Procedia. 4: 399-407. https://doi.org/10.1016/j.aaspro.2015.03.045
  2. Baille, A. 1992. Water status monitoring in greenhouse crops. Acta Hortic. 304:15-27.
  3. Ehret, D.L., A. Lau, S. Bittman, W. Lin, and T. Shelford. 2001. Automated monitoring of greenhouse crops. Agronomie. 21:403-414. https://doi.org/10.1051/agro:2001133
  4. Esteves, B.S., L.L. Lousada, E.F. Sousa, and E. Campostrini. 2015. Advanced techniques using the plant as indicator of irrigation management. Cienc. Rural, Santa Maria. 45(5): 821-827. https://doi.org/10.1590/0103-8478cr20140501
  5. FAO. 2002. World Agriculture: Towards 2015/2030, an FAO Study. Rome.
  6. Farquhar, G.D., and T.D. Sharkey. 1982. Stomatal conductance and photosynthesis. Ann. Rev. Plant Photosynth. 33:317-345. https://doi.org/10.1146/annurev.pp.33.060182.001533
  7. Hackl, H., J.P. Baresel, B. Mistele, Y. Hu, and U. Schmidhalter. 2012. A comparison of plant temperatures as measured by thermal imaging and infrared thermometry. J. Agron. Crop Sci. 198(6):415-429. https://doi.org/10.1111/j.1439-037X.2012.00512.x
  8. Hashimoto, Y., T. Morimoto, and S. Funada. 1981. Computer processing of speaking plant for climate control and computer aided plantation (computer aided cultivation). Acta Hortic. 317-325.
  9. Idso, S.B., R.D. Jackson, P.J. Pinter, R.J. Reginato, and J.L. Hatfield. 1981. Normalizing the stress degree day for environmental variability. Agric. Meteorol. 24:45-55. https://doi.org/10.1016/0002-1571(81)90032-7
  10. Jensen, M.E., Burman, R.D., and R.G. Allen. 1990. Evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering Pratice N. 70, Am. Sco. Civil Engr., New York, NY. pp.332.
  11. Jackson, R.D., S.B. Idso, and R.J. Reginato. 1981. Canopy temperature as a crop water stress indicator. Water Resour. Res. 17:1133-1138. https://doi.org/10.1029/WR017i004p01133
  12. Kaukoranta, T., J. Murto, J. Takala, and R. Tahvonen. 2005. Detection of water deficit in greenhouse cucumber by infrared thermography and reference surfaces. Sci. Hortic. 106:447-463. https://doi.org/10.1016/j.scienta.2005.02.026
  13. Kim, G., K. Ryu, and H. Chae. 1999. Analysis of water stress of greenhouse crops using infrared thermography. Korean Soc. Agric. Machinery. 24:439-444.
  14. Kim, G., K. Ryu, and H. Chae. 1999. Measurement of stress related crop temperature variations. Proceedings of the Korean Society for Bio-Environment Control. 233-236.
  15. Kim, G., K. Lee, G. Kim, and B. Cho. 2015. Measurement and analysis of apparent temperature from the radiant heat of plant response. Proceedings of the Korean Society for Agricultural Machinery. 192-193.
  16. Levidow, R., D. Zaccaria, R. Maia, E. Vivas, M. Todorovic, and A. Scardigno. 2014. Improving water-efficient irrigation: Prospects and difficulties of innovative practices. Agricult. Water Manage. 146:84-94. https://doi.org/10.1016/j.agwat.2014.07.012
  17. Mershon, J. 2015 Infrared thermometry: Introduction, history and application. Available from: http://www.advanced-energy.com/upload/File/White_Papers/ENG-THERMOME-TRY-270-01.pdf
  18. Naeeni, A.E., E.M. Esfahani, M.B. Harchegani, M. Jafarpour, and M.A. Golabadi. 2014. Leaf temperature as an index to determine the irrigation interval. Research on Crop Ecophysiology. 9/1(2):89-95.
  19. Orta, A.H., T. Erdem, and Y. Erdem. 2002. Determination of water stress index in sun-flower. Helia. 37:27-38.
  20. Peters, R.T. 2015. Practical use of soil moisture sensors for irrigation scheduling. Available from: http://irrigation.wsu.edu/Content/Fact-Sheets/Practical-Soil-Moisture-Monitoring.pdf
  21. Penuelas, J., I. Filella, and G.A. Gamon. 1995. Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytologist. 131:291-296. https://doi.org/10.1111/j.1469-8137.1995.tb03064.x
  22. Reginato, R.J. 1983. Field quantification of crop water stress. Trans. ASAE. 26:772-775. https://doi.org/10.13031/2013.34021
  23. University of Alaska Fairbanks. 2015. Cucumber production in greenhouse. Available from: http://www.uaf.edu/files/ces/publications-db/catalog/anr/HGA-00434.pdf
  24. White, S.C. and S.R. Raine. 2008. A grower guide to plant based sensing for irrigation scheduling. NCEA publication 1001574/6.