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Climate and rainfed wheat yield

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Abstract

Planning for precision agriculture requires a better understanding of the plant’s response to climate. The economy of Qorveh, in Iran, is severely affected by wheat yield fluctuations. In this study, multivariate statistical methods were used to identify important climatic factors affecting rainfed wheat yield and to simulate yield variations based on these impact factors. A new method was introduced to initiate seed germination. After determining the germination time, the wheat growth period was divided into seven stages based on the growing degree day (GDD). Forty-four climatic variables and indices related to the first six stages were used to perform factor analysis and to develop a model for predicting pre-harvest yield. The results showed that 91.5% of the total variance of 44 variables can be explained by 9 factors. Eighty-five percent of yield variations can be explained and modeled (R = 0.92) using five of these factors. This indicates that rainfed wheat yield is highly correlated with climate conditions, and this relationship is well simulated by statistical methods. According to the results, the significant trend of climatic variables was identified as the main reason for the yield growth trend in Qorveh. The yield showed a direct relationship with precipitation and relative humidity and an inverse relationship with air temperature and sunshine. The impact intensity of variables on yield included precipitation, relative humidity, sunshine, and air temperature, respectively. The results also showed that the yield was more affected by climatic variables of spring and May than other seasons and months, respectively.

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References

  • Allen RG, Pereira LS, Smith DR (1998) Crop evapotranspiration (guidelines for computing crop water requirements). Rome, Italy: FAO Irrigation and Drainage Paper No. 56

  • Arkian F, Nicholson SE, Ziaie B (2018) Meteorological factors affecting the sudden decline in Lake Urmia’s water level. Theor Appl Climatol 131:641–651. https://doi.org/10.1007/s00704-016-1992-6

    Article  Google Scholar 

  • Bal S, Mukherjee J, Mallick K, Hundal SS (2004) Wheat yield forecasting models for Ludhiana district of Punjab state. J Agrometeorol 6:161–165

    Google Scholar 

  • Bazgeer S, Kamali G, Sedaghatkerdar A, Moradi A (2008) Pre-harvest wheat yield prediction using agrometeorological indices for different regions of Kurdistan province, Iran. Res J Environ Sci 2(4):275–280

    Article  Google Scholar 

  • Bowden P, Edwards J, Ferguson N, McNee T, Manning B, Roberts K et al (2008) Wheat growth and development. NSW Department of Primary Industries, New South Wales

    Google Scholar 

  • Ceglar A, Toreti A, Lecerf R, Van der Velde M, Dentener F (2016) Impact of meteorological drivers on regional inter-annual crop yield variability in France. Agric For Meteorol 216:58–67

    Article  Google Scholar 

  • Chen P, Jing Q (2017) A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images. Advances in Space Research 59:987–995

    Article  Google Scholar 

  • Draper NR, Smith H (2014) In: Draper NR, Smith H (eds) Applied regression analysis, 3rd edn. Wiley, Inc, Hoboken. https://doi.org/10.1002/9781118625590.ch7

    Chapter  Google Scholar 

  • Esfandiary F, Aghaie G, Dolati Mehr A (2009) Wheat yield prediction through agrometeorological indices for Ardebil district. World Acad Sci Eng Technol 49:32–35

    Google Scholar 

  • Faghih H (2018) Water requirement estimation of main field crops in Kurdistan. Soil and Water Research Institute, Karaj Iran (In Persian)

    Google Scholar 

  • Härdle WK, Simar L (2015) Applied multivariate statistical analysis. Verlag. Springer, Berlin. https://doi.org/10.1007/978-3-662-45171-7

    Book  Google Scholar 

  • Karamouz M, Szidarovszky F, Zahraie B (2003) Water resources system analysis. Lewis Publishers, Washington

    Book  Google Scholar 

  • Kheiri M, Soufizadeh S, Ghaffari A, AghaAlikhani M, Eskandari A (2017) Association between temperature and precipitation with dryland wheat yield in northwest of Iran. Clim Chang 141(4):703–717. https://doi.org/10.1007/s10584-017-1904-5

    Article  Google Scholar 

  • Kim S, Kim H (2016) A new metric of absolute percentage error for intermittent demand forecasts. Int J Forecast 32:669–679

    Article  Google Scholar 

  • Lee B, Kenkel P, Wade Brorsen B (2013) Pre-harvest forecasting of county wheat yield and wheat quality using weather information. Agric For Meteorol 168:26–35

    Article  Google Scholar 

  • Mukherjee A, Wang S, Promchote P (2019) Examination of the climate factors that reduced wheat yield in Northwest India during the 2000s. Water 11(2):343. https://doi.org/10.3390/w11020343

    Article  Google Scholar 

  • Nassiri M, Koochechi A, Kamali G, Shahandeh H (2006) Potential impact of climate change on rainfed wheat production in Iran. Arch Agron Soil Sci 52(0):1–12

    Google Scholar 

  • Pishbahar E, Darparnian S (2016) Factors creating systematic risk for rainfed wheat production in iran, using spatial econometric approach. J Agric Sci Technol 18(4):895–909

    Google Scholar 

  • Pohlert T (2018) Non-parametric trend tests and change-point detection. citation(package="trend")

  • Qian B, Jong R, Warren R, Chipanshi A, Hill H (2009) Statistical spring wheat yield forecasting for the Canadian Prairie provinces. Agric For Meteorol 149:1022–1031

    Article  Google Scholar 

  • Saei M, Mohammadi H, Ziaee S, Barkhordari S (2019) The impact of climate change on grain yield and yield variability in Iran. Iran Econ Rev 23(2):509–531

    Google Scholar 

  • Siosemarde M, Sakine A (2014) Prediction of rainfed wheat yield using meteorological parameters in Khoy County at West Azarbaijan province. J Appl Environ Biol Sci 4(1s):47–50

    Google Scholar 

  • Smith R, Adams J, Stephens D, Hick P (1995) Forecasting wheat yield in a Mediterranean-type environment from the NOAA satellite. Aust J Agric Res 46(1):113–125

    Article  Google Scholar 

  • Vashisth A, Singh R, Choudary M (2014) Crop yield forecast at different growth stage of wheat crop using statistical model under semi-arid region. J Agroecol Nat Resour Manag 1(1):1–3

    Google Scholar 

  • Yue S, Wang C (2004) The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18:201–218

    Article  Google Scholar 

  • Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421

    Article  Google Scholar 

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Homayoun Faghih. The first draft of the manuscript was written by Homayoun Faghih, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Javad Behmanesh.

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Faghih, H., Behmanesh, J., Rezaie, H. et al. Climate and rainfed wheat yield. Theor Appl Climatol 144, 13–24 (2021). https://doi.org/10.1007/s00704-020-03478-9

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