|
|
|
|
|
| Determination of soybean yield gap and potential production in Iran using modeling approach and GIS |
| Alireza NEHBANDANI1, Afshin SOLTANI1, Ali RAHEMI-KARIZAKI2, Amir DADRASI3, Faranak NOURBAKHSH4 |
1 Department of Plant Production, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan 4918943464, Iran
2 Department of Plant Production, Gonbad Kavoos University, Gonbad Kavoos 4971799151, Iran
3 Department of Agronomy, Agricultural Science, Vali-e-Asr University of Rafsanjan, Kerman 7718897111, Iran
4 SWEP Analytical Laboratories, Melbourne, Victoria 3173, Australia |
|
|
|
|
Abstract Increasing crop production is necessary to maintain food security for the growing global population. Reducing the gap between actual and potential yield is one of the important ways to increase yield per unit area. Potential yield and the yield gap of soybean were determined for Golestan Province, Iran, using Soybean Simulation Model (SSM-iCrop2) and Geographical Information System (GIS). Information from 24 weather stations and soil data of the region were used. Yield gap and production gap were calculated at county and province levels. The average actual yield of soybean in this province was 2.28 t ha–1 while the province’s potential yield was 4.73 t ha–1, so the yield gap was estimated 2.44 t ha–1. Thus, there is a great potential for increasing soybean yield in Golestan, which is possible through improving crop management of soybean in farmers’ fields. The average water productivity of soybean was estimated to be 0.81 kg m–3. Spatial distribution of water productivity in soybean farms showed that the highest and the lowest water productivities (0.99 and 0.44 kg m–3) were in western and eastern regions of the province, respectively, in accordance to vapour pressure deficit. It was concluded that soybean production in the province could increase by 66% (from 109 970 to 182 170 tons) if 80% of the current yield gap could be removed.
|
|
Received: 05 August 2019
Accepted:
|
|
Corresponding Authors:
Amir Dadrasi, E-mail: V.dadrasi@gmail.com
|
Cite this article:
Alireza NEHBANDANI, Afshin SOLTANI, Ali RAHEMI-KARIZAKI, Amir DADRASI, Faranak NOURBAKHSH.
2021.
Determination of soybean yield gap and potential production in Iran using modeling approach and GIS. Journal of Integrative Agriculture, 20(2): 395-407.
|
| Abbate P E, Dardanelli J L, Cantarero M G, Maturano M, Melchiori J M, Suero E E. 2004. Climatic and water availability effects on water-use efficiency in wheat. Crop Science, 44, 474–483. Allen R G, Pereira L S, Raes D, Smith M. 1998. Guidelines for Computing Crop Water Requirements-Fao Irrigation and Drainage Paper 56. FAO-Food and Agriculture Organisation of the United Nations, Rome. Bhatia V S, Singh P, Wani S P, Chauhan G S, Rao A V R K, Mishra A K, Srinivas K. 2008. Analysis of potential yields and yield gaps of rainfed soybean in India using CROPGRO-Soybean model. Agricultural and Forest Meteorology, 148, 1252–1265. Egli D B, Hatfield J L. 2014. Yield gaps and yield relationships in central US soybean production systems. Agronomy Journal, 106, 560–566. FAO (Food and Agriculture Organization). 2013. Online statistical database: Trade. FAOSTAT. [2018-01- 11]. http://www.fao.org/faostat/en/#data/TP Faraji A, Raeise S. 2018. Technical instruction: Disturbance complication of podging in soybean. Agricultural Research Education and Extention Organization, Golestan. pp. 1–6. Garbulsky M F, Peñuelas J, Papale D, Ardö J, Goulden M L, Kiely G, Richardson A D, Rotenberg E, Veenendaal E M, Filella I. 2010. Patterns and controls of the variability of radiation use efficiency and primary productivity across terrestrial ecosystems. Global Ecology and Biogeography, 19, 253–267. Grassini P, Bussel L G J, Van Wart J, Van Wolf J, Claessens L, Yang H, Boogaard H, Groot H, De Ittersum M K, Van Cassman K G. 2015. How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Research, 177, 49–63. Hagan P S, West G. 2006. Interpolation methods for curve construction. Applied Mathematical Finance, 13, 89–129. Hatfield J L, Prueger J H. 2015. Temperature extremes: Effect on plant growth and development. Weather and Climate Extremes, 10, 4–10. IOEIA (Iranian Oilseed Extraction Industry Association). 2015. Trade data. [2018-03-01]. http://www.oilepa.com/ Irmak S, Specht J E, Odhiambo L O, Rees J M, Cassman K G. 2014. Soybean yield, evapotranspiration, water productivity, and soil water extraction response to subsurface drip irrigation and fertigation. Transactions of the American Society of Agricultural and Biological Engineers, 57, 729–748. Kazemi H, Bourkheili S H, Kamkar B, Soltani A, Gharanjic K, Nazari N M. 2016. Estimation of greenhouse gas (GHG) emission and energy use efficiency (EUE) analysis in rainfed canola production (case study: Golestan Province, Iran). Energy, 116, 694–700. Koo J, Dimes J. 2013. HC27 generic soil profile database. In: Harvard Dataverse. ver. 4. International Food Policy Research Institute, Washington, D.C. Koocheki A, Nassiri M, Alimoradi L, Ghorbani R. 2009. Effect of cropping systems and crop rotations on weeds. Agronomy for Sustainable Development, 29, 401–408. Lindquist J L, Arkebauer T J, Walters D T, Cassman K G, Dobermann A. 2005. Maize radiation use efficiency under optimal growth conditions. Agronomy Journal, 97, 72–78. MAJ (Ministry of Agriculture Jihad). 2016. Statistics Database. [2016-11-01]. http://www.maj.ir/ MAJ (Ministry of Agriculture Jihad). 2018. Statistics Database. [2018-02-01]. http://www.maj.ir/ Merlos F A, Monzon J P, Mercau J L, Taboada M, Andrade F H, Hall A J, Jobbagy E, Cassman K G, Grassini P. 2015. Potential for crop production increase in Argentina through closure of existing yield gaps. Field Crops Research, 184, 145–154. Nehbandani A. 2018. Yield gap analysis of soybean in Iran. Ph D thesis, Gorgan University of Agricultural Sciences and Natural Resources, Iran. Rodriguez D, Sadras V O. 2007. The limit to wheat water-use efficiency in eastern Australia. I. Gradients in the radiation environment and atmospheric demand. Australian Journal of Agricultural Research, 58, 287–302. Sadok W, Sinclair T R. 2009. Genetic variability of transpiration response to vapor pressure deficit among soybean (Glycine max [L.] Merr.) genotypes selected from a recombinant inbred line population. Field Crops Research, 113, 156–160. Sinclair T R. 2006. A reminder of the limitations in using Beer’s law to estimate daily radiation interception by vegetation. Crop Science, 46, 2343–2347. Singh P, Vijaya D, Chinh N T, Pongkanjana A, Prasad K S, Srinivas K, Wani S P. 2001. Potential productivity and yield gap of selected crops in the rainfed regions of India, Thailand, and Vietnam. Journal of SAT Agricultural Research, 2, 1–34. Soltani A, Alimagham M, Nehbandani A, Torabi B, Zeinali E, Dadrasi A, Zand E, Ghassemi S, Pourshirazi S, Alasti O, Hosseini R S, Zahed M, Arabameri R, Mohammadzadeh Z, Rahbanl S, Kamari H, Fayazi H, Mohammadi S, Keramat S, Vadez V, et al. 2020. Modeling plant production at country level as affected by availability and productivity of land and water. Agricultural Systems, 183, 102859. Soltani A, Ghassemi-Golezani K, Khooie F R, Moghaddam M. 1999. A simple model for chickpea growth and yield. Field Crops Research, 62, 213–224. Soltani A, Maddah V, Sinclair T R. 2013. SSM-Wheat: A simulation model for wheat development, growth and yield. International Journal of Plant Production, 7, 711–740. Soltani A, Sinclair T R. 2011. A simple model for chickpea development, growth and yield. Field Crops Research, 124, 252–260. Tohidi M, Hasheminia M, Mohebi R, Khalili D, Hosseinpanah F, Yazdani B, Nasiri A A, Azizi F, Hadaegh F. 2012. Incidence of chronic kidney disease and its risk factors, results of over 10 year follow up in an Iranian cohort. PLoS ONE, 7, e45304. |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
