Assessment of multiple regression equations for yield estimation of rain-fed wheat and barley in different Iran’s climates

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Environment Science and Engineering, Faculty of Agriculture and Environment, Arak University, Iran.

2 Assistant Professor, Department of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Iran.

3 Assistant Professor, Department of Water Engineering, College of Aburaihan, University of Tehran, Tehran, Iran.

Abstract

Iran is located in the arid and semi-arid area and it is very necessary to assess the conditions of rainfed farming of strategic plants. In order to assessment of wheat and barley yield under rainfed climatic conditions collected data from 44 stations were studied during the period of 1981-2020 (40 years). Weather data after spatial interpolation between stations and converting to daily values were used as inputs of a multiple regression model for estimating wheat and barley yield. In this study, Iran was divided into six coastal wet, mountain, semi mountain, semi desert, desert and, coastal desert. The results showed that the highest and lowest annual rainfall was observed in stations Bandar Anzali (1748 mm y-1) and Zabol (57.7 mm y-1), respectively. The greatest and lowest decrease in rainfall occurred in Bandar-Anzali station (gradient 5.8 percent) and, in Kermanshah station (gradient -0.8 percent) respectively. Only 11.36 percent of the stations were in good condition and, in other stations were in a critical situation (88.64 percent). The results of this study showed that the coefficient of determination of predicted yield for rainfed wheat in humid climates was more accurate than in other climates (R2=0.83). The lowest coefficient of determination predicted yield was obtained for rain-fed wheat (R2=0.71) and rain-fed barley (R2=0.53) in desert climates.

Keywords

Main Subjects

References

  1. Abeledo, L. G, Savin, R., & Slafer, G. A. (2008). Wheat productivity in the Mediterranean Ebro Valley: Analyzing the gap between attainable and potential yield with a simulation model. European Journal of Agronomy, 28, 541-550.
  2. Antle, J. M. (1996). Meteorological issues in assessing potential impacts of climate change on agriculture. Agricultural and Forest Meteorology, 80, 67-85.
  3. Becker, M., & Johnson, D. E. (1999). Rice yield and productivity gaps in irrigated systems of the forest zone of CoAte d'Ivoire. Field Crops Research, 60, 201-208.
  4. Boote, K. J., & Tollenaar, M. (1994). Modeling yield potential. In: Boote, K. J., Bennett, J. M., Sinclair, T. R., Paulsen, G. M. (Eds.), Physiology and Determination of Crop Yield. American Society of Agronomy, Madison, WI, USA.
  5. Chanasyk, D. S., Mapfumo, E., Willms, W. D., & Naeth, M. A. (2004). Quantification and simulation of soil water on grazed fescue watersheds. Journal of Range Management, 57(2), 169-177.
  6. Chow, T. T., Long, H., Mok, H. Y., & Li, K. W. (2011). Estimation of soil temperature profile in hong kong from climatic variables. Energy and Building Journal, 43, 3568-3575.
  7. Delbari, M., Sharifazari, S., & Mohammadi, E. (2108). Modeling daily soil temperature over diverse climate conditions in Iran-a comparison of multiple linear regression and support vector regression techniques. Theoretical and Applied Climatology, 131, 1-11.
  8. Fischer, G., Van Velthuizen, H., & Nachtergaele, F. (2000). Global Agroecological zones assessment: Methodology and results. Interim Report IR-00-064. IIASA, Vienna and FAO, Rome.
  9. Gholipoor, M. (2008). Quantifying threshold frost hardiness for overwintering survival of wheat in Iran, using simulation. International Journal of Plant Production, 2, 125-136.
  10. Hammera, G. L., Hansenb, J. W., Phillipsb, J. G., Mjeldec, J. W., Hillc, H., Lovec, A., & Potgietera, A. (2001). Advances in application of climate prediction in Agriculture. Agricultural Systems, 70, 515-553.
  11. Holden, N. M., & Brereton, A. J. (2004). Definition of agroclimatic regions in Ireland using hydro-thermal and crop yield data. Agricultural and Forest Meteorology, 122, 175-191.
  12. Imam, Y. (2002). Cereal farming. Shiraz University. Shiraz, Iran. (In Persian).
  13. Johnson, D. E. (1998). Applied multivariate methods for data analysts. Duxbury Press.
  14. Kamali, M. R. (2009). World situation of Wheat in the past, present and future. 10th congress of agronomy and modification of plants, Karaj, Iran. 23-45. (In Persian).
  15. Kamkar, B., Koocheki, A., Nassiri, A., & Rezvani Moghadam, P. (2006). Analysis of yield gap of Cumin in 9 regions of Great Khorasan by modeling approach. Agronomy Researches, 5, 332-342. (In Persian with English Abstract).
  16. Koocheki, A., Nassiri, M., Kamali, G., & Shahandeh, G. (2006). Potential impacts of climate change on agro-climatic indicators in Iran. Arid Land Research and Management, 20, 1-15.
  17. Krause, P., Boyle, D. P., & Base, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5, 89-97.
  18. Mohammadi, E., & Delbari, M. (2015). Simulation of Water and Salt Transport in Soil Using the HYDRUS-1D Software. Water and Soil Science, 25(1), 67-78. (In Persian).
  19. Nassiri, M., Koocheki, A., Kamali, G. & Shahandeh, G. (2006). Impacts of climatic change on rainfed wheat production in Iran. Archives in Agronomy and Soil Science, 25(1), 113-124.
  20. Nicholls, N. (2000). Impediments to the use of climate predictions. In: Hammer, G.L., N. Nicholls, C. Mitchell. (Eds.). Applications of Seasonal Climate Forecasting in Agricultural and Natural Ecosystems: The Australian Experience. Kluwer, Dordrecht, the Netherlands.
  21. Rosenzweig, C., & Parry, M. L. (1994). Potential Impact of Climate Change on World Food Supply. Nature, 367, 133-138.
  22. Sabziparvar, A. (2008). A Simple Formula for Estimating Global Solar Radiation in Central Arid Deserts of Iran, Journal of Renewable Energy, 33(5), 1002-1010.
  23. Sadeghi, A. R., Kamgar-Haghighi, A. A., Sepaskhah, A. R., Khalili, D., & Zand-Parsa, S. (2002). Regional classification for dryland agriculture in southern Iran. Journal of Arid Environments, 50, 333-341.
  24. Sharafi, S., & Ghaleni, M. M. (2021a). Calibration of empirical equations for estimating reference evapotranspiration in different climates of Iran. Theoretical and Applied Climatology, 1453, 1-15.
  25. Sharafi, S., & Ghaleni, M. M. (2021b). Evaluation of multivariate linear regression for reference evapotranspiration modeling in different climates of Iran. Theoretical and Applied Climatology, 143(3), 1409-1423.
  26. Sharafi, S., & Ghaleni, M. M. (2021c). Spatial assessment of drought features over different climates and seasons across Iran. Theoretical and Applied Climatology, 145(4), 1-17. ‏
  27. Sharafi, S., & Karim, N. M. (2020). Investigating trend changes of annual mean temperature and precipitation in Iran. Arabian Journal of Geosciences, 13(16), 1-11.
  28. Sharafi, S., Ramroudi, M., Nassiri, M., Galavi, M., & Kamali, G. A. (2017). Assessment of moisture status and crop production in different climates of Iran. Journal of Agriculture Knowledge and Sustainable Production, 7(1), 103-120. (In Persian).
  29. Sharafi, S., Ramroudi, M., Nassiri, M., Galavi, M., & Kamali, G. A. (2016). Role of Early Warning Systems for Sustainable Agriculture in Iran. Arabian Journal of Geoscience, 9, 734-754.
  30. Soltani, A., & Sinclair, T. R. (2012). Modeling Physiology of Crop Development, Growth and Yield. CABI publication.
  31. Soltani, A., Robertson, M. J., Mohammad Nejad, Y., & Rahemi Karizaki, A. (2006). Modeling chickpea growth and development: Leaf production and senescence. Field Crops Research, 99, 14-23.
  32. Torabi, B., Soltani, A., Galeshi, S., & Zeinali, A. (2012). The analysis of limited factors for wheat yield in Gorgan conditions. Journal of Crop Production, 4(4), 1-17. (In Persian).
  33. Zare Feizabadi, A., Koocheki, A. R., & Nassiri, M. (2007). Investigation of plantation area, yield and cereal production in Iran and forecasting of the future. Journal of Agronomy Researches, 4(1), 42-69. (In Persian).
Water and Irrigation Management
Volume 12, Issue 1
April 2022
Pages 201-211

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