Scheduling Maize Irrigation by Crop Water Stress Index (CWSI) in North of Isfahan

Document Type : Research Paper

Authors

1 Department of Water Science and Engineering, Science and Research Branch, Ismaic Azad University, Tehran, Iran.

2 Department of Water Engineering, Khorasgan Branch, Islamic Azad University, Isfahan, Iran

Abstract

Nowadays, the world is facing increasing population and demand for food as well as shortage of fresh water supplies (Mangus et al., 2016). Deficit irrigation (DI) and urban wastewater utilization are two management solutions for the purpose of reducing fresh water consumption in agriculture. Due to the shortage of irrigation water resources and the increase of the area under cultivation, farmers in the northern part of Isfahan (viz., Borkhar), Iran, employ these two strategies. Precise irrigation planning could be of help in preventing water stress and optimum performance in plants. Water stress is considered one of the most important plant stresses, which is the most common and limiting factor for yield (Jackson et al., 1981; Scherrer et al., 2011; Zia et al., 2013).
Since 1970, canopy temperature has been accepted as an indicator of water stress because plants under stress close their stomata for preserving water and reducing stomatal conduction, decreasing transpiration, and increasing leaf temperature (Ballester et al., 2013).
One of the most reliable indicators is the crop water stress index (CWSI). Several studies have been conducted on irrigation scheduling using leaf surface temperature measurements. (Candogan et al., 2013; Orta et al., 2003). The difference in air temperature and leaf area was calculated from the difference in vapour pressure for different irrigation treatments in soybean and watermelon plants. Also, sorghum was studied by O’Shaughnessy et al. (2010) in different irrigation systems and the crop water stress index (CWSI) was calculated.
Mangus et al. (2016) examined the water stress index of corn in four stages of plant growth; their results showed that in the third stage of corn growth (i.e., in the flowering stage), the surface temperature of the leaf was higher and that the plant used the most energy for cob growth and thus shrinking transpiration from the plant. Based on the aforementioned studies, this study sought to compute the water stress index (CWSI) under irrigation treatments in the climate of North Isfahan in order to identify the irrigation time.

Keywords

Main Subjects

References

1-    Alderfasi, A. A. and Nielsen, D. C., 2001. Use of crop water stress index for monitoring water status and scheduling irrigation in wheat. Agricultural Water Management, 47, pp.69-75.
 2-    Alizadeh, A., 2010. Design of Surface Irrigation Systems. Astan Quds Razavi Publishing House. Fourth Edition, pp. 248-265. (In Persian).
 3-    Ballester, C., Jimenez-Bello, M.A., Castel, J.R. and Intrigliolo, D.S., 2013. Usefulness of thermography for plant water stress detection in citrus and persimmon trees. Agricultural Water Management. pp.120–129.
 4-    Boroomand Nasab, S., Taheri Ghanad, S. and Moayri, M., 2003. Use of green plant cover temperature to plan irrigation of spring corn in Khuzestan conditions. Scientific Journal of Agriculture, Ahvaz Agricultural College, 27, pp.56-47. (In Persian).
 5-    Candogan, B. K., Shncik, M., Buyukcangaz, H. and C, Demirtas., 2013. Yield, quality and crop water stress index relationships for deficit irrigated soybean [Glycine max (L.) Merr.] In sub-humid climatic conditions. Agricultural Water Management, 118, pp.113– 121.
 6-    Ghorbani, M., Broumand nassab, S., Mohammadi, A.S. and Minae, S., 2014. Summer Maize Irrigation Scheduling Under Surface and Sprinkler Irrigation Using CWSI in Ahvaz Climate Condition. Journal of Irrigation Science and Engineering, 38(4), pp. 63-73. (In Persian).
 7-    Grant, O.M., Chaves, M.M. and Jones, H.G., 2006. Optimizing thermal imaging as a technique for detecting stomatal closure induced by drought stress under greenhouse conditions. Physio logia Plant arum, 127, pp.507–518.
 8-    Herwitz, S. R., Johnson, L. F., Dunagan, S. E., Higgins, R. G., Sullivan, D. V., Zheng, J., Lobitz, B. M., Leung, J. G., Gallmeyer, B. A., Aoyagi, M., Slye, R. E. and Brass, J. A., 2017. Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support. Computers and Electronics in Agriculture, 44, pp. 49–61.
 9-     Idso, S.B., Jackson, R.D. and Reginato, R.J., 1977. Remote sensing of crop yields. Science 196, pp.19–25.
 10- Idso, S. B., Jackson, R. D., Pinter, P. J., Reginato, R. J. and Hatfield, J. L., 1981. Normalizing the stress degree-day parameter for environmental variability. Agricultural Meteorology, 24, pp.45-55.
 11- Idso, S. B., Reginato, R. J. and Radin, J.W., 1982. Leaf diffusion resistance and photosynthesis in cotton related to a foliage temperature based plant water stress index. Agricultural Meteorology, 27, pp.27-34.
12- Jackson, R.D., Idso, S.B., Reginato, R.J., and Pinter Jr, P.J., 1981. Canopy temperature as a drought stress indicator. Water Resources Research, 17, pp.1133–1138.
 13- Jones, H.G., 1999. Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant, Cell Environ, 22, pp.1043–1055.
 14- Judy, F., 2011. Use of infrared thermometer in plantation of irrigation of sunflower plant in Khuzestan. Master's thesis, Department of Irrigation and Drainage, Faculty of Water Engineering, Shahid Chamran University of Ahvaz. (In Persian).
 15- Leinonen, I. and Jones, H.G., 2004. Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. Journal of Experimental Botany, 55 (401), pp.1423–1431.
 16- Mangus, D.L., Sharda, A., and Zhang, N., 2016. “Development and evaluation of thermal infrared imaging system for high spatial and temporal resolution crop water stress monitoring of corn within a greenhouse”. Computer and Electro in Agric. 121, pp. 149–159.
 17- Mohammadi, H. 2013. Irrigation plan for spring corn under drip irrigation using infrared thermometer under climatic conditions of Ahwaz. Master's thesis, Department of Irrigation and Drainage, Faculty of Water Engineering, Shahid Chamran University of Ahvaz. (In Persian).
 18- Monteith, J.L. and Unsworth, M.H., 2013. Principles of Environmental Physics: Plants, Animals, and the Atmosphere, fourth ed. Elsevier Ltd, Oxford, UK.
 19- Orta, A. H., Erdem, Y. and Erdem, T., 2003. Crop water stress index for Watermelon. Scientia Horticulture, 98, pp.121-130.
 20- O’Shaughnessy, S. A., Evett, S. R., Colaizzi, P. D. and Howell, T. A., 2010. Automatic irrigation scheduling of grain sorghum using a CWSI and time threshold. Decennial Irrigation Association Conference, December, Michigan.
 21- Rodriguez, D., Sadras, V.O., Christensen, L.K. and Belford, R., 2005. Spatial assessment of the physiological status of wheat crops as affected by water and nitrogen supply using infrared thermal imagery. Australian Journal of Agricultural Research, 56, pp.983–993.
 22- Scherrer, D., Bader, M. and Karl-Friedrich Korner, C., 2011. Drought-sensitivity ranking of deciduous tree species based on thermal imaging of forest canopies. Agricultural and Forest Meteorology, 151, pp.1632–1640.
 23- Taghvaeian, S., Chavez, J., Altenhofen, J., Trout, T.J., and Dejonge, K.C., 2013. “Remote sensing for evaluating crop water stress at field scale using infrared thermography: potential and limitations”. Hydrology Days, pp.73–83.
 24- Verdiynezhad, S., Sohrabi, T. and Layyat A., 2007. Programming of corn irrigation in different growth stages using the difference in temperature of green plant cover. The 9th National Irrigation Seminar and Reduction of Evapotranspiration, February. (In Persian).
 25- Zia, S., Romano, G., Spreer, W., Sanchez, C., Cairns, J., Araus, J. L. and Müller, J., 2012. Infrared thermal imaging as a rapid tool for identifying water stress tolerant maize genotypes of different phenology. Journal of Agronomy and Crop Science 199(2), pp. 75–84.
Irrigation Sciences and Engineering
Volume 42, Issue 2
June 2019
Pages 105-118

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History

  • Receive Date: 16 May 2017
  • Revise Date: 23 September 2017
  • Accept Date: 25 September 2017
  • Publish Date: 22 June 2019

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