Estimation of Rainfed Wheat Yield Functions Using Climatic Parameters and Multivariate Regression Methods

Document Type : Research Paper

Authors

1 Department of Water Science and Engineering, Faculty of Agriculture, University of Tabriz, Tabriz

2 Department of Irrigation and Reclamation Engineering, Faculty of Agriculture Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

3 Ph. D Candidate of Irrigation and Drainage, Department of Water Engineering, Tabriz University, Tabriz, Iran.

4 Associate Professor, Department of Water Engineering, Tabriz University, Tabriz, Iran

Abstract

More than half of the agricultural lands in arid and semi-arid climates are rainfed. Many climatic variables affect the yield of rainfed crops, among them rainfall is the most important variable. The aim of the present study is to determine the yield functions of rainfed wheat in Tabriz, Sarab and Maragheh stations located in the east of Lake Urmia basin, considering the changes of climatic variables during different stages of rainfed wheat growth. In order to model the yield using multivariate regression method, some precipitation variables such as, number of effective precipitation events, vegetation precipitation deficit, reference precipitation and evapotranspiration deficit in rainfed conditions during six stages of rainfed wheat growth including germination; End of germination until the beginning of flowering; Flowering stage; Finishing flowering until the seeds start to fill; Seed filling stage and whole growing season were used. In general, based on the obtained results, precipitation fluctuations have the greatest effect on wheat yield. Therefore, identifying the precipitation regime and analyzing its characteristics is important for assessing yield fluctuations of rainfed crops. Among the growth stages, the fluctuation of the proposed traits in the whole growth season has a greater role in determining yield functions. Yield functions were determined using variables that had a significant correlation with yield. For this purpose, 22-year and 3-year data were used for calibration and validation, respectively. The results of the model efficiency coefficient and normalized root mean square error indicated better effeciency of Enter method in the Sarab (EF=0.55 and NRMSE=0.19) and the Moderate accuracy of Stepwise method in estimating the rainfed wheat yield in Maragheh and Tabriz. In Maragheh and Tabriz, the Stepwise method with average relative error values of 21% and 15.6%, respectively, and in Sarab, the Enter method with an average relative error of 16.5% had better results in yield fitting.

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References

Allen, R.G., Pereira, L.S., Raes, D & Smith, M. (1998). Crop evapotranspiration guidelines for computing crop water requirements. In: Irrigation and Drainage Paper No. 56. Food and Agriculture Organization of the United Nations (FAO), Rome, Italy.
Bannayan, M., Asadi, S., Salehi, H., & Koozegaran, S. (2017). Evaluating the relationship between cumulative rainfall and yield of wheat and barley using a evenness index in the semi-arid region of Mashhad. Iranian Journal of Irrigation and Drainage, 4(11), 636- 646. (In Farsi)
Bannayan, M., Sanjani, S., Alizadeh, A., Sadeghi-Lotfabadi, S. & Mohammadian, A. (2010). Association between climate indices, aridity index, and rainfed crop yield in northeast of Iran. Field Crops Research, 118(2), 105–114.
Battisti, R., Sentelhas, P. & Boote, k. (2017). Inter-comparison of performance of soybean crop simulation modelsand their ensemble in southern Brazil. Field Crops Research, 200, 28-37.
De-Pauw, E. (2002). An Agroecological Exploration of the Arabian Peninsula. ICARDA, Aleppo, Syria, 77 pp.
Fakheri-Fard, A., Majnooni-Heris, A., Ahmadzade, H., Isazade, M. & Mousavi, M.M. (2018). Soil studies of Ajichai basin, 141pp.
Fateh, S., Rasouli, A.A., Sari-Saraf, B., & Kamali, G.A. (2016). Study on GDD for wheat growing season period in iran. Climate Research, 27, 1-9. (In Farsi)
Ghivi, J. (1997). Qualitative assessment of land suitability for crops. Soil and Water Research Institute. Issue 1015. (In Farsi)
Hadi, M.  Majnooni-Heris, A. & Delirhasannia, R. (2017).  Assessing rainfed wheat cultivation risk and suitable time for supplemental irrigation in tabriz plain. Water and Soil Science, 27(2), 307- 320. (In Farsi)
Hosseini, S.M.T., Siosemarde, A., Fathi, P. & Siosemarde, M. (2007). Application of artificial neural network (ANN) and multiple regressions for estimating assessing the performance of dry farming wheat yield in Ghorveh region, Kurdistan Province.  Agriculture research ,  7(1), 41-54.(In Farsi)
Hundal, S.S., Singh ,R & Dhaliva, L.K. (1997). Agro-climatic indices for predicting phonology of wheat (Triticum-aestivum) in Punjab. Agriculture Science, 67, 265- 268.
Kamali, G.A., Sadaghiani-Poor, A., & Sedaghatkerdar, A. (2008). The climatic zoning of dryland wheat in Eastern Azerbaijan. Water and Soil, 22(2), 467-483. (In Farsi).
Labus, M. P., Nielsen, G., Alawrence, R.L., Engeld, R. & Long, S., (2002). Wheat yield estimates using multi-temporal NDVI satellite imagery. International Journal of Remote Sensing, 23(20), 4169-4180.
Landau, S., Mitchell, R.A.C., Barnett V., Colls, J.H., Craigon, J. & Payne R.W. (2000). A parsimonious, multiple regression model of wheat yield response to environment; Agricultural and Forest Meteorology, (101), 151-161.
Mam-karimi, B. (2017).  Evaluating crop yield functions of rain-fed wheat in West Azarbaijan using water inputs. Master's thesis, Faculty of Agriculture, University of Tabriz. (In Farsi)
Mouneskhah, V. & Majnooni-Heris, A. (2017). Effect of supplemental irrigation on water requirement satisfaction index of rainfed wheat in the Tabriz plain semi-arid climate. Iranian Journal of irrigation and Drainage, 11(6), 1143-1151. (In Farsi)
Mousavi-Baygi, M., Bannayan, M., Ashraf, B. & Asadi-Oskuei, E. (2016). Assessment of climatic indices limiting rainfed wheat yield. Ecological Indicators, 62, 298–305.
Naserin, A.  & Saeed-Mousavi, S.M. (2017). Determining Climatic Model of Rain-fed Wheat Yield at North of Khouzestan Province. Irrigation and Water Engineering, 8(1), 125-138. (In Farsi)
Quiring, S.M., & Papakryiakou, T.N. (2003). An evaluation of agricultural drought indices for the Canadian prairies. Agricultural and Forest Meteorology, 118(1–2), 49–62.
Sabziparvar, A.A., Torkaman, M. & Maryanaji, Z. (2013). Investigating the Effect of Agro-climatic Indices and Variables on Optimum Wheat Performance (Case study: Hamedan Province). Water and Science, 26(6),1554-1567. (In Farsi)
Shokouhi, M. & Sanaei-Nejad, S.H. (2016).  Effect of precipitation period and SPI index as an indicator of moisture supply on rainfed Barley Crop Yield (Case Study: Tabriz County). Water and Soil, 30(1), 210-221. (In Farsi).
Singh A. K., Tripathy R., and Chopra U. K. (2008). Evaluation of CERESWheat and CropSystmodels for water-Nitrogen interactions in Wheat crop. Agricultural Water Management, 95: 776-786.
Sohrabie-Mollayousef, S., Fakheri-Fard, A. & BozorgHaddad, O. (2012). Assessment the effect of intermittent rainfall of autumn and winter on annual dry farming yield by using the time-rain indicator (RTI). Water and Science, 26(1), 75-84. (In Farsi)
Zare-abyaneh, H. (2013).  Evaluating roles of drought and climatic factors on variability of four dry farming yields in mashhad and birjand. Water and Soil Science, 23(1), 39-56. (In Farsi).
Iranian Journal of Soil and Water Research
Volume 52, Issue 2
May 2021
Pages 497-506

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