Iranian Journal of Field Crops Research

Iranian Journal of Field Crops Research

Spatiotemporal Analysis of Irrigated and Dryland Wheat (Triticum aestivum L.) Yield Variations in Khorasan Razavi Province

Document Type : Research Article

Authors
Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
Abstract
Introduction
Wheat is the most important strategic crop both globally and nationally. It is one of the most critical staple crops in Iran, playing a vital role in food security and economic stability. However, its production is highly sensitive to climatic fluctuations, including temperature changes, precipitation variability, and extreme weather events. In semi-arid and arid regions such as Khorasan Razavi province, where agriculture is heavily dependent on climatic conditions, understanding yield trends and their underlying drivers is crucial for optimizing production and ensuring sustainability. This study aims to analyze the spatiotemporal variations in irrigated and rainfed wheat yield in Khorasan Razavi over an 11-year period (2011–2021) across 29 counties and identify key climatic and management-related factors influencing these changes. The findings provide essential insights into the spatial and temporal patterns of yield fluctuations and help inform adaptive strategies for mitigating agroclimatic risks.
Materials and Methods
This study was conducted in Khorasan Razavi province, located in northeastern Iran, covering 29 counties with diverse climatic and agronomic conditions. The data for this study were obtained from the Agricultural Jihad Organization's website, including annual yield records for irrigated and rainfed wheat. To model the yield trends, polynomial functions were employed. Linear, quadratic, and cubic regression models were applied, and the best-fitting model was selected using the Akaike Information Criterion (AIC). Based on yield trends, counties were classified into four classes: (1) Increasing, where yield has shown a significant and consistent upward trend; (2) Stagnating, where yield has remained relatively stable with no substantial increase or decrease; (3) Never Improved, where no significant improvement in yield was observed throughout the study period; and (4) Collapsed, where a sharp decline in yield occurred. The spatial distribution of yield variations was also analyzed to identify regional patterns.
Results and Discussion
The results of the study showed that in Khorasan Razavi province, the average irrigated wheat yield increased by about 1000 kilograms per hectare (kg ha-1) over an 11-year period. However, this increase was not uniformly distributed across all counties; in half of the counties, an improvement in yield was observed, while in the other half, stagnation or no improvement in yield was observed. Furthermore, only one county experienced a significant decrease in yield. Regarding rainfed wheat, the average yield over the 11-year period increased by about 800 kilograms per hectare (kg ha-1), indicating the product's sensitivity to environmental and management factors in different regions of the province. Spatial analysis revealed that the pattern of wheat yield changes across the province was heterogeneous; central counties such as Torbat Heydarieh, Fariman, and Nishapur experienced yield improvements, while areas like Khushab and some northern and southern counties faced decreases, stagnation, or no improvement in yield. Temporal variation charts showed that both types of wheat (irrigated and rainfed) were influenced by long-term climatic and management changes. Overall, management practices in the province have led to yield improvements, but in some counties, climatic changes and severe weather fluctuations, especially in the final year of the study, neutralized the positive effects of agricultural management, resulting in stagnation or no improvement in wheat yield. This study investigates the variations in precipitation and temperature over the agricultural years 2011 to 2021, with precipitation ranging from 60 to 430 mm and mean temperature varying between 10°C and 22.5°C. Significant fluctuations in both factors are highlighted, particularly the severe drought in 2020-2021 (the final year of the study), which had a notable impact on agricultural productivity. This suggests that even with improved farming techniques, climate adaptation measures including changes in sowing date, drought-resistant cultivars, soil moisture conservation techniques, and enhanced irrigation systems are necessary to sustain long-term productivity. Also, several counties classified as Collapsed, Stagnating or Never Improved may require additional investment in agricultural extension services, farmer training, and climate-smart agricultural practices to bridge the yield gap.
Conclusion
The results emphasize the need for adaptive management strategies to enhance wheat yield stability in Khorasan Razavi. Although agronomic improvements have led to yield increases in many areas, the effects of climate fluctuations remain a major challenge. Policymakers and agricultural planners should prioritize climate adaptation measures, such as changes in sowing date, improved irrigation techniques, using drought-resistant crop varieties, and precision agriculture, to mitigate climate-related yield losses and ensure sustainable wheat production in the region.
Keywords

Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

  1. Akaike, H. (1974). A new look at the statistical model identification. IEEE Automation and Control, 19(6), 716-723.
  2. Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B., Cammarano, D., Kimball, B. A., Ottman, M. J., Wall, G. W., White, J. W., Reynolds, M. P., Alderman, P. D., Prasad, P. V. V., Aggrawal, P. K., Anothai, J., Basso, B., Biernath, C., Challinor, A. J., De Sanctis, G., Doltra, J., Fereres, E., Garcia-Vila, M., Gayler, S., Hoogenboom, G., & Zhu, Y. (2015). Rising temperatures reduce global wheat production. Nature Climate Change, 5(2), 143-147. https://doi.org/10.1038/nclimate2470
  3. Bivand, R., Pebesma, E., & Gómez-Rubio, V. (2008). Applied Spatial Data Analysis With R. Springer Science+ Business Media.
  4. Bouras, E., Jarlan, L., Khabba, S., Er-Raki, S., Dezetter, A., Sghir, F., & Tramblay, Y. (2019). Assessing the impact of global climate changes on irrigated wheat yields and water requirements in a semi-arid environment of Morocco. Scientific Reports, 9(1), 19142. https://doi.org/10.1038/s41598-019-55251-2
  5. Brisson, N., Gate, P., Gouache, D., Charmet, G., Oury, F. X., & Huard, F. (2010). Why are wheat yields stagnating in Europe? A comprehensive data analysis for France. Field Crops Research, 119(1), 201-212. https://doi.org/10.1016/j.fcr.2010.07.012
  6. Burnham, K. P., Anderson, D. R., & Huyvaert, K. P. (2011). AIC model selection and multimodel inference in behavioral ecology: Some background, observations, and comparisons. Behavioral Ecological Sociobiology, 65(1), 23-35. https://doi.org/10.1007/s00265-010-1029-6
  7. Chen, H. (2018). The spatial patterns in long-term temporal trends of three major crops’ yields in Japan. Plant Production Scienc, 21(3), 177-185. https://doi.org/10.1080/1343943x.2018.1459752
  8. Deihimfard, R., Eyni-Nargeseh, H., & Mokhtassi-Bidgoli, A. (2018). Effect of future climate change on wheat yield and water use efficiency under semi-arid conditions as predicted by APSIM-wheat model. International Journal of Plant Production, 12(2), 115-125. https://doi.org/10.1007/s42106-018-0012-4
  9. Draper, N. R. (2002). Applied regression analysis bibliography update 2000-2001. Communication in Statictics Theory and Methods, 31(11), 2051-2075. https://doi.org/10.1081/sta-120015017
  10. FAO, Food and Agriculture Organization. (2021). The State of Food and Agriculture 2021. https://www.fao.org/
  11. Farajzadeh-Asl, S., Kashki, M., & Shayan, M. (2009). Analysis of rain-fed wheat yield product variability using climate change approach (Case study area: Khorasan Razavi province). The Journal of Spatial Planning and Geomatics, 13(2), 227-257. (in Persian with English abstract). http://hsmsp.modares.ac.ir/article-21-3068-fa.html
  12. Farajzadeh, M., Khoorani, A., Bazgeer, S., & Zeaeian, P. (2011). Modeling and predicting of rainfed wheat yield in attention to phenological phases of plant growth (a case study for Kurdistan province). Physical Geography Research, 43(76), 21-34. (in Persian with English abstract.(
  13. Farhadi, M., Bannayan, M., Fallah, M. H., & Jahan, M. (2024). Identification of climatic and management factors influencing wheat’s yield variability using AgMERRA dataset and DSSAT model across a temperate region. Discover Life, 54, 8. https://doi.org/10.1007/s11084-024-09651-8
  14. Finger, R. (2010). Evidence of slowing yield growth - The example of Swiss cereal yields. Food Policy, 35(2), 175-182. https://doi.org/10.1016/foodpol.2009.11.004
  15. Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., & Toulmin, C. (2010). Food security: The challenge of feeding 9 billion people. Science, 327(5967), 812-818. https://doi.org/10.1126/science.1185383
  16. Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2000). Geographical Information Systems: Principles, Techniques, Management and Applications. Wiley.
  17. Hatfield, J. L., Boote, K. J., Kimball, B. A., Ziska, L. H., Izaurralde, R. C., Ort, D., Thomson, A. M., & Wolfe, D. (2011). Climate impacts on agriculture: Implications for crop production. Agronomy Journal, 103(2), 351-370. https://doi.org/10.2134/agronj2010.0303
  18. Heydari, N., & Taran, F. (2025). Effect of climate change on wheat yield and water productivity in Iran and the world. Iranica Journal of Energy & Environment, 16(2), 253-269. https://doi.org/10.5829/ijee.2025.16.02.08
  19. Hussain, J., Khaliq, T., Ahmad, A., Akhter, J., & Asseng, S. (2018). Wheat responses to climate change and its adaptations: A focus on arid and semi-arid environment. International Journal of Environmental Research, 12(1), 117-126. https://doi.org/10.1007/s41742-018-0074-2
  20. Hussain, J., Khaliq, T., Rahman, M. H. U., Ullah, A., Ahmed, I., Srivastava, A. K., Gaiser, T., & Ahmad, A. (2021). Effect of temperature on sowing dates of wheat under arid and semi-arid climatic regions and impact quantification of climate change through mechanistic modeling with evidence from field. Atmosphere (Basel), 12(7), 927. https://doi.org/10.3390/atmos12070927
  21. IPCC, I. P. C. C. (2014). Climate Change 2014: Synthesis Report (IPCC,
  22. Koochaki, A., & Nassiri-Mahallati, M. (2008). The impact of climate change along with increased carbon dioxide concentration on wheat yield in Iran and evaluation of adaptation strategies. Iranian Journal of Crop Research, 6(11), 139-153. (in Persian with English abstract). https://doi.org/10.22067/gsc.v6i1.1185
  23. Koocheki, A., & Nassiri Mahallati, M. (2019). Yield monitoring for wheat and sugar beet in Khorasan province: 2- estimation of yield gap. Iranian Journal of Field Crops Research, 17(1), 15-38. (in Persian with English abstract). https://doi.org/10.22067/gsc.v17i1.62557
  24. (2022). Annual Meteorological Report 2022. O. Khorasan Razavi Meteorological (Ed.). Khorasan Razavi Meteorological Office.
  25. Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333(6042), 616-620. https://doi.org/10.1126/science.1204531
  26. Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to Linear Regression Analysis (6 ed.). John Wiley & Sons.
  27. Pooya Nasab, K., Bannayan Aval, M., Ghorbani, R., Sanjani, S., & Yaghoubi, F. (2018). Temporal and spatial variation of wheat and bean yields, case study: Khorasan-e Razavi province. Iranian Journal of Field Crops Research, 16(2), 263-282. (in Persian with English abstract). https://doi.org/10.22067/gsc.v16i2.44536
  28. R Core Team. (2025). The R project for statistical computing. https://www.r-project.org/
  29. Rouhani, H., Ghorbani, M., & Kahansal, M. (2021). Analysis of the effective factors on dimensions of sustainable agricultural development in Khorasan Razavi province, using seemingly unrelated regression equations. Iranian Journal of Agricultural Economics and Development Research, 52(1), 33-52. (in Persian with English abstract). https://doi.org/10.22059/ijaedr.2021.308780.668977
  30. Tilman, D., Balzer, C., Hill, J., & Befort, B. L. (2011). Global food demand and the sustainable intensification of agriculture. Proceeding of National Academy of Science of USA, 108(50), 20260-20264. https://doi.org/10.1073/pnas.1116437108
  31. Vargas, M., Glaz, B., Alvarado, G., Pietragalla, J., Morgounov, A., Zelenskiy, Y., & Crossa, J. (2015). Analysis and interpretation of interactions in agricultural research. Agronomy Journal, 107(2), 748-762. https://doi.org/10.2134/agronj13.0405
  32. Venables, W. N., & Ripley, B. D. (2013). Modern Applied Statistics with R (4 ed.). Springer.
  33. Zeinali Mobarakeh, Z., Deihimfard, R., & Kambouzia, J. (2018). Modelling the impacts of climate change on irrigated wheat yield under water limited conditions in Khorasan Razavi province. Journal of Agricultural Science and Sustainable Production, 28(3), 155-169. (in Persian with English abstract).
  34. Zhang, F., Shen, J., Li, R., Rengel, Z., & Tang, C. (2003). Orthogonal polynomial models to describe yield response of rice to nitrogen and phosphorus at different levels of soil fertility. Nutrient Cycling in Agroecosystems, 65, 243-251. https://doi.org/10.1023/A:1022644520090
Send comment about this article
Enter Name.
Enter a valid email address.
Enter a vaid affiliation.
Enter comments (At leaset 10 words)
CAPTCHA Image
Enter Security Code Correctly.

  • Receive Date 02 February 2025
  • Revise Date 16 March 2025
  • Accept Date 06 April 2025
  • First Publish Date 13 April 2025