Agro-ecological Zoning of Iran for Plant Production

Document Type : Research Article

Authors

1 PhD Student of Agroecology, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

3 PhD graduate of Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

Introduction
For optimal production and maintaining its stability, environmental and weather conditions must be determined from the perspective of capabilities and limitations. For this purpose, it requires reliable regional data such as planting date, ripening time, plant density, soil, and meteorological information, which are generally not available for most regions. Obtaining this information is very time-consuming and expensive in many areas and is often simply not possible. Therefore, zoning can facilitate access to this information on a large scale. In other words, if the regions that are similar in terms of climate, soil, and management conditions are identified, the time and cost needed to collect information on a wide scale will be minimal.  
Materials and Methods
The present study was conducted for the agro-ecological zoning of the country. In this research, the existing climatic zones of the country were analyzed based on GYGA, and the existing soil zones of the country were analyzed based on the HC27 method.
Results and Discussion
The combination of climatic zones and soil, 198 polygons or agro-ecological zones were obtained for all agricultural lands of the country. The zones in which more than 1% of the country's agricultural lands are located include 28 zones, and in total, about 80% of the agricultural lands are located in these zones. The highest frequency percentage is related to agro-ecological zone 4103-5 with a frequency of 85.11%. Also, the frequency of agro-ecological codes (climate code 5003 with soil code 5) 5003-5 (28.7%) and (climate code 4003 with soil code 5) 5-4003 (93.4%) were placed next. Zoning can facilitate the selection of points for plant studies and other planning.
Conclusion
Each of these areas has a different climate and soil code, which indicates the specific production conditions of that area. From these agro-ecological zones, to improve studies and make agricultural management decisions, it is possible to prepare and complete the climate and soil information bank in each zone for use in simulation models of plant production, to facilitate the collection of information (such as management information, cultivar information plant) and the implementation of plant production simulation model to be used in studies related to the food security of the country. The current research was conducted to determine the main agro-ecological areas of agricultural production in the country so that simulation studies and other studies can be carried out in the main production location in each province. Therefore, it is necessary to know where the main production centers of each province were, what kind of climate and soil it has, and which meteorological station is the indicator of that region. In this research, the climate zones of irrigated, rainfed, garden, and pasture lands of the country were determined by using the Giga climate map. Based on this, more than 50% of water lands are located in climates 5003, 4003, 5002, 8003, and 6003, respectively. Also, the rainy lands are located in 4103, 4003, and 3103 climates respectively. Also, by using the HC27 soil map, the soil areas in the irrigated, rainfed, garden, and pasture lands of the country were determined. Therefore, more than 50% of water lands in soil codes 5 and 17; Rainy lands in Kodkhak 5 and 12; Garden lands were located in soil codes 5 and 12 and pastures were located in soil codes 5 and 17. By combining climatic zones and soil zones, agricultural-ecological zoning of the country was done, and finally, 198 zones were obtained. The zones in which more than 1% of the country's agricultural lands are located include 28 zones, in total, about 80% of the agricultural lands are located in these zones (Figure 7). The highest frequency percentage (11.85%) was related to the area with agroe-cological code 4103-5, which covered 1789965.8 hectares of agricultural land. Also, after that, the agro-ecological code 5003-5 has the highest frequency (7.28 percent), which covers 1100599.25 hectares of agricultural land in the country. In this research, after the agro-ecological zoning of the country's agricultural lands, several 198 zones were obtained, and after calculating the area covered by each zone, finally, 28 agro-ecological zones have an abundance percentage of more than 1%, and together they are about 80% (11813518.66 hectares). They cover the country's agricultural lands. These climate zones obtained can be used for food security studies and calculating and determining the production capacity of each region. On the other hand, considering that in agricultural studies, extensive and comprehensive information about climate and soil is needed for each region and access to this information is usually expensive and time-consuming, the use of agro-ecological zones resulting from this research can be necessary.

Keywords

Main Subjects

Open Access

©2022 The author(s). This article is licensed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.

References

  1. Bagat, M. R., Sharda, S., Sood, C., Rana, R. S., Kalia, V., Pradhan, S., Immerzeel, W., & Shrestha, B. (2009). Land suitability analysis for cereal production in Himachal Pradesh (India) using geographical information system. Indian Society Remote Sensing Journal, 37, 233-240. https://doi.org/10.1007/s12524-009-0018-6
  2. Bouman, B. A. M., & Lansigan, F. P. (1994). Agroecological zonation, characterization and optimization of rice-based cropping systems. SARP Research Proceedings, Wageningen and Los Banos, p.1-8.
  3. Caldiz, D. O. (2001). Agro-ecological zoning and potential yield of single or double cropping of potato in Argentina and Forest Meteorology. 109, 311-320. Available online: www.elsevier.com. https://doi.org/10.1016/S0168-1923(01)00231-3
  4. Dadrasi, A., Torabi, B., Rahimi, A., Soltani, A., & Zeinali, E. (2021). Determination of Potato (Solanum tuberosum) yield gap in Golestan Province. Journal of Agroecology, 12(4), 613-633. (in Persian). https://doi.org/10.22124/CR.2022.20959.1696
  5. Dadrasi, A., Torabi, B., Rahimi, A., Soltani, A., & Zeinali, E. (2022). Modeling Potential production and yield gap of potato using modelling and GIS approaches. Ecological Modeling, 471, 110050. https://doi.org/10.1016/j.ecolmodel.2022.110050
  6. Fisher, J. W., Francis, L. J., & Johnson, P. (2000). Assessing spiritual health via four domains of spiritual well-being: the SH4DI. Pastoral Psychology, 49, 133-145. https://doi.org/1023/A:1004609227002
  7. Food and Agriculture Organization of the United Nations (FAO). (1996). Agro-Ecological Zoning: Guidelines. Food and Agricultural Organization of the United Nations, Rome.
  8. Food and Agriculture Organization of the United Nations (FAO). (1997). Land quality indicators and their use in sustainable agriculture and rural development, FAO, Rome, Italy. 212.
  9. Food and Agriculture Organization of the United Nations (FAO). (2002). World Agriculture: Towards 2015/2030: Summary Report. FAO, Rome, Italy.
  10. Geerts, S., Raes, D., Garcia, M., Del Castillo, C., & Buytaert, W. (2006). Agro-climatic suitability mapping for crop production in the Bolivian Altiplano: a case study for quinoa. Agricultural and Forest Meteorology, 139, 399-412. https://doi.org/10.1016/j.agrformet.2006.08.018
  11. Ghaffari, A. (2008). Agroclimatic zoning of Iran, rainfed crop production areas with particular emphasis to agroecological characterization. Report, Agricultural Extension, Education and Research Organization (AEERO), Dryland Agricultural Research Institute (DARI). ICARDA Technical Report.
  12. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal Climatology, 25, 1965-1978. https://doi.org/10.1002/joc.1276
  13. Khajehpour, M. R. (2006). Industrial plants (second edition). Academic Jihad Publications of Isfahan Industrial Unit.
  14. Koo, J., & Dimes, J. (2013). HC27 Generic Soil Profile Database, http://hdl.handle.net/1902.1/20299, Harvard Dataverse, V2.
  15. Muthuwatta, L., & Chemin, Y. (2003). Vegetation growth zonation of Sirlanka for improved water resources planning. Agricultural Water Management, 58, 123-143.
  16. Nasiri Mahalati, M., & Kokhaki, A. (2009). Agro-ecological zoning of wheat in Khorasan province: estimation of yield potential and gap. Agricultural Researches of Iran, 7, 695-709.
  17. Nehbandani, A. R., Soltani, A., Taghdisi Naghab, R., Dadrasi, A., & Alimagham, S. M. (2020). Assessing HC27 Soil Database for Modeling Plant Production. International Journal of Plant Production. https://doi.org/10.1007/s42106-020-00114-4
  18. Nehbandani, A., Soltani, A., Rahemi-Karizaki, A., Dadrasi, A., & Noubakhsh, F. (2021). Determination of soybean yield gap and potential production in Iran using modeling approach and GIS. Journal of Integrative Agriculture, 20(2), 395-407. https://doi.org/10.1016/S2095-3119(20)63180-X
  19. Norwood, Charles, A. (2000). Dry land Winter Wheat as Affected by Previous Crops, Agronomy Journal.
  20. Ramirez-Villegas, J., & Challinor, A. (2012). Assessing relevant climate data for Agricultural applications. agricultural forest meteorology 161, 26-45. https://doi.org/10.7910/dvn/25626
  21. Rasouli, S. J., & Qaemi, A. R. (2010). Rapeseed cultivation zoning based on temperature and climate needs using GIS in Khorasan provinces. Electronic Journal of Crop Production, 1. https://doi.org/10.22126/ATIC.2022.7903.1056
  22. Sadeghi, A. R., Kamgar-Haghighi, A. A., Sepaskhah, A. R., Khalili, D., & Zand-Parsa, Sh. (2002). Regional classification for dryland agriculture in southern Iran. Journal of Arid Environments, 50, 333-341. https://doi.org/1006/jare.2001.0822
  23. Seppelt, R. (2000). Regionalised optimum control problems for agroecosystem management. Ecological Modelling, 131, 121-132. https://doi.org/10.1016/S0304-3800(00)00270-2
  24. Soltani, A., & Sinclair, T. R. (2012). Modeling Physiology of Crop Development. Growth and Yield, CABI, Wallingford, UK.
  25. Van Lanen, H. A. J., Van DiepenReinds, G. J., De Koning, G. H. J., Bulens, J. D., & Bregt, A. K. (1992). Physical land evaluation methods and GIS to explore the crop growth potential and its effects within the European communities. Agricultural Systems, 39, 307-328. https://doi.org/10.1016/0308-521X(92)90102-T
  26. Williams, C. L., Liebman, M., Edwards, J. W., James, D. E., Singer, J. W., Arritt, R., & Herzmann, D., (2008). Patterns of regional yield stability in association with regional environmental characteristics. Crop Science, 48, 1545-1559. https://doi.org/10.2135/cropsci2006.12.0837
  27. Zolfaqhari, H., & Moradi, F. (2005). Investigation of thermal comfort in Kermanshah province. Geography and Regional Development, 43-89.
Send comment about this article
CAPTCHA Image

Files

History

  • Receive Date: 28 August 2022
  • Revise Date: 26 October 2022
  • Accept Date: 21 December 2022
  • First Publish Date: 21 December 2022

Share

How to cite

Statistics