Soybean Yield in Future Climate Scenarios under Low Irrigation Conditions: Case Study: Pars Aabad of Moghan Plain, Iran

Document Type : Original Article

Authors

1 Unit of Agroecology, Department of Agronomy, College of Agriculture, University of Zabol, Zabol, Iran

2 Meshkin-shahr College of Agriculture, University of Mohaghegh Ardabili, Meshkin-shahr, Ardabil, Iran

3 Department of Agronomy and Plant Breeding, Campus of Agriculture and Natural Resources, Razi University, Kermanshah, Iran

Abstract

Using the AquaCrop model, this research simulated the grains and biological yields of soybean cultivars (M9, Zan and Williams) under different irrigation treatments and future climatic conditions. To this end, whether data of the LARS-WG model were used as input data related to 1970-2010 period in Pars­abad of Moghan Plain using AOGCM of HadCM3 based on scenarios of AR4 (A1B, A2 and B1) and NCAR based on scenarios of AR5 (RCP2.6 and RCP 8.5) to study periods of 2011-2030 and 2046-2065. Results showed, compared to the historical period, the statistical periods of 2011-2030 and 2046-2065 would show increases in average monthly minimum temperatures for all scenarios. These periods would also reveal decreases in average monthly maximum temperatures as well as average monthly precipitations for scenarios of RCP8.5, A2, A1B, RCP2.6, and B1, as well as scenarios of B1, RCP2.6, RCP8.5, A2, and A1B, respectively. According to the findings of RMSE and NMRSE, the AquaCrop was a good model for performance evaluation and simulation. The values of grain and biological yield would increase more for A1B and RCP8.5 than for the other scenarios during future periods. These findings indicate that soybean is an acceptable plant for the future climate of Pars­abad of Moghan. In conditions of sufficient water and deficient water, Williams and Zan, respectively, exhibited lesser growth reduction and higher grain and biological yields than M9.

Graphical Abstract

Soybean Yield in Future Climate Scenarios under Low Irrigation Conditions: Case Study: Pars Aabad of Moghan Plain, Iran

Highlights

  • There will be climate change in Moghan in all the scenarios of AR4 and AR5.
  • In the future of Moghan, rainfall will decrease and temperature and CO2 will increase.
  • AquaCrop model has good potential for predicting soybean yield in future climate of Moghan.
  • Soybean is suitable for the present and future climate of Moghan.

Keywords

Main Subjects

References

Aghighi Shahverdi1 M., Abassi Shahmersi F., Mamivand B. 2015. Evaluation of morphological traits, yield and yield components of soybean genotypes (Glycine max L.) in Parsabad Moghan region. Plant Ecophysiology 7 (24): 237-250.
Ahmadzadeh Araji H., Wayayok A., Massah Bavani A., Amiri E., Fikri Abdullah A., Daneshian J., Tef C.B.S. 2018. Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models. Agricultural Water Management 205: 63-71. https://doi.org/10.1016/j.agwat.2018.04.023
Alison L.K., Richard G.J., Nicholas S.R. 2004. RCM rainfall for UK flood frequency estimation. II. Climate change results. Journal of Hydro-Environment Research 318: 163-172. https://doi.org/10.1016/j.jhydrol.2005.06.013
Allen R.G. 1996. Assessing integrity of weather data for reference evapotranspiration estimation. Journal of Irrigation and Drainage Engineering 122 (2): 97-106. https://doi.org/10.1061/(ASCE)0733-9437(1996)122:2(97)
Amiri Z., Asgharipour M.R., Campbell D.E., Azizi K., Kakolvand E., Moghadam E.H. 2021. Conservation agriculture, a selective model based on emergy analysis for sustainable production of shallot as a medicinal-industrial plant. Journal of Cleaner Production 292: 126000. https://doi.org/10.1016/j.jclepro.2021.126000
Araya A., Keesstra S., Stroosnijder L. 2010. Simulating yield response to water of Teff (Eragrostis tef) with FAO's AquaCrop model. Field Crops Research 116: 196-204. https://doi.org/10.1016/j.fcr.2009.12.010
Asgharipour M.R., Mosapour, H. 2016. A foliar application silicon enhances drought tolerance in fennel. The Journal of Animal & Plant Sciences 26(4): 1056-1062.
Bao Y., Hoogenboom G., Mcclendon R., Urich P. 2015. Soybean production in 2025 and 2050 in the southeastern USA based on the SimCLIM and the CSM‑Cropgro‑soybean models. Climate Research 63: 73-89.
https://doi.org/10.3354/cr01281
Blum A. 1988. Plant breeding for stress environments. CRC Press. Boca Raton. FLPP., pp. 38-78.
Brevedan R.E., Egli D.B. 2003. Short periods of water stress during seed filling, leaf senescence, and yield of soybean. Crop Sciences 43: 2083-2088.
https://doi.org/10.2135/cropsci2003.2083
Doorenbos J., Kassam A.H. 1979. Yield response to water. Irrigation and Drainage, Paper No. 33. FAO, Rome, Italy, 193pp.
Doorenbos J., Oruitt W.O. 1977. Crop water requirements. FAO Irrigation and Drainage Paper. 24: 20-50.
Droogers, P., Kite, G. 2001. Simulation modeling at different scales to evaluate the productivity of water. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 26(11-12): 877-880. https://doi.org/10.1016/S1464-1909(01)00100-9
Garcia-Vila M., Fereres E., Mateos L., Orgaz F., Steduto P. 2009. Deficit irrigation optimization of cotton with aquacrop. Journal of Agrobiology 101: 477-487. https://doi.org/10.2134/agronj2008.0179s
Geerts S., Raes D., Garcia M., Miranda R., Cusicanqui J.A., Taboada C., Mendoza J., Huanca R., Maman I.A., Condori O., Mamani J., Morales B., Osco V., Steduto P. 2009. Simulating yield response to water of quinoa (Chenopodium quinoa Willd.) with FAO-AquaCrop. Journal of Agrobiology 101: 499-508. https://doi.org/10.2134/agronj2008.0137s
Ghorbani K., Zakerinia M., Hezarjaribi A. 2014. The effect of climate change on water requirement of soybean in Gorgan. Journal of Agricultural Meteorology 2 (1): 60-72.
Giménez L., Paredes P., Pereira L.S. 2017. Water Use and Yield of Soybean under Various Irrigation Regimes and Severe Water Stress. Application of AquaCrop and SIMDualKc Models. Journal of Water Supply 9: 1-18.
https://doi.org/10.3390/w9060393
Guo D., Zhao R., Xing X., Ma X. 2019. Global sensitivity and uncertainty analysis of the AquaCrop model for maize under different irrigation and fertilizer management conditions. Archives of Agronomy and Soil Science 64 (2): 1-19. https://doi.org/10.1080/03650340.2019.1657845
Haverkort A.J., Verhagen A. 2019. Climate change and its repercussions for the potato supply chain. Journal of Potato Research 51: 223-237.
https://doi.org/10.1007/s11540-008-9107-0
Ibrahim F.D., Ibrahim P.A., Odine A.I., Jirgi A.J., Usman R.K., Ogaji A., Gbanguba A.U. 2016. Impact of climate change on soybean production in local government area of Niger State. Asian Journal of Agricultural Extension, Economics and Sociology 10 (1): 1-6. https://doi.org/10.9734/AJAEES/2016/21886
IPCC. 2007. Summary for policymakers. Climate change, in physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change, eds.
IPCC. 2014. Report is based on the reports of the three Working Groups of the Intergovernmental Panel on Climate Change (IPCC), including relevant Special Reports.
Jamali S.H., Sadghi L., Sadeghin-Motahhar S.Y. 2011. Identification and distinction of soybean commercial cultivars using morphological and microsatellite markers. Iranian Journal of Crop Sciences 13 (1): 131-145. (In Persian)
Jones J.W., Jagtap S.S., Boote K.J. 2009. Climate change: implications for soybean yield and management in the USA Proc. World Soybean Research Conf. VI.
Jones R.N. 2000. Analyzing the risk of climate change using an irrigation demand model. Climate Research 14: 89-100. https://doi.org/10.3354/cr014089
Khorsand A., Verdinezhad V., Shahidi A. 2014. Evaluation of Aquacrop model for simulation wheat yield, moisture and salinity of soil profiles under water and salinity stress. Journal of Water and Irrigation Management 4 (1): 89-104. (In Persian)
Khoshravesh M., Mostafazadeh-Fard B., Heidarpour M., Kiani A.R. 2013. AquaCrop model simulation under different irrigation water and nitrogen strategies. Water Science & Technology 67 (1): 232-238.
https://doi.org/10.2166/wst.2012.564
Masuda T., Goldsmith P.D. 2009. World soybean production: Area harvested, yield, and long-term projections. International Food and Agribusiness Management Review 12 (4): 143-162.
Mekuria W., Noble A., McCartney M., Hoanh C.T., Douangsavanh S., Langan S. 2016. Soil management for raising crop water productivity in rainfed production systems in Lao PDR. Archives of Agronomy and Soil Science 62 (1): 53-68.
https://doi.org/10.1080/03650340.2015.1037297
Ministry of Agriculture-Jihad. 2016. Agricultural Statistics, Vol. II.
Mitchell T.D. (2003). Pattern Scaling: An examination of accuracy of the technique for describing future climates. Climate Change 60:217-242. https://doi.org/10.1023/A:1026035305597
Mohanty M., Sammi Reddy K., Probert M.E., Dalal R.C., Sinha N.K., Subba Rao A., Menzies N.W. 2016. Efficient nitrogen and water management for the soybean-wheat system of Madhya Pradesh, central India, Assessed Using APSIM Model. Proceedings of the National Academy of Sciences, India Section B: Biological Science 86: 217-228. https://doi.org/10.1007/s40011-014-0443-3
Nehbandani A.R., Soltani A. 2016. Simulate the effect of climate change on development, iIrrigation requirements and soybean yield in Gorgan. Journal of Water and Soil Sciences 30: 77-87.
Ohe I., Reiko U., Jyo S., Kuramashi T., Saitoh K., Kuroda T. 2007. Effect of rising temperature on flowering, pod set, dry matter production and seed yield in soybean. Japanese Journal of Crop Science 76 (1): 433-444. https://doi.org/10.1626/jcs.76.433
Raes D., Steduto P., Hsiao T.C., Fereres E. 2012. Reference manual AquaCrop, FAO, Land and Water Division, Rome, Italy.
Rashidian L. 2017. Study of the process of climate change according to data simulation using LARS WG software during 2010-2030: Case study of Semnan Province. International Journal of Marine and Environmental Sciences 11 (9): 848-852.
Ribas-Carbo M., Taylor N.L., Giles L., Busquets S., Finnegan P.M., Day D.A., Lambers H., Medrano H., Berry J.A., Flexas J. 2005. Effects of water stress on respiration in soybean leaves. Plant Physiology 139: 466-473.
https://doi.org/10.1104/pp.105.065565
Rio A.D., Sentelhas P.C., Farias J.R.B., Sibaldelli R.N.R., Ferreira R.C. 2015. Alternative sowing dates as a mitigation measure to reduce climate change impacts on soybean yield in southern Brazil. International Journal of Climatology 36: 3664-3672. https://doi.org/10.1002/joc.4583
Rodríguez Díaz J.A., Weather Head E.K. Knox J.W., Camacho1 E. 2020. Climate change impacts on irrigation water requirements in the Guadalquivir River Basin in Spain. Regional Environmental Change 7: 149-159. https://doi.org/10.1007/s10113-007-0035-3
Rosenzweig C., Parry M.L. 2019. Potential impacts of climate change on world food supply. Nature 367: 133-138. https://doi.org/10.1038/367133a0
Rosielle A., Hamblin J. 1981. Theoretical aspects of selection for yield in stress and nonstress environment. Crop Sciences 21: 943-946. https://doi.org/10.2135/cropsci1981.0011183X002100060033x
Semenov M.A., Barrow E.M. 2002 LARS-WG: A Stochastic Weather Generator for Use in Climate Impact Studies, Version 3.0, User Manual.
Silva V.P.R., Silva R.A., Maciel G.F., Braga C.C., Silva Júnior J.L., Souza C., Almeida R.S.R., Silva M.T., Holanda R.M. 2018. Calibration and validation of the AquaCrop model for the soybean crop grown under different levels of irrigation in the Motopiba region, Brazil. Rural Engineer 48: 1-8.
https://doi.org/10.1590/0103-8478cr20161118
Steduto A., Raes P., Hsiao T., Fereres T.C., Heng E., Izzi L., Hoogeveen J. 2009. AquaCrop: a new model for crop prediction under water deficit conditions. Options Mediterranean 80: 285-292.
Steduto A., Hsiao T.C., Raes D., Fereres E. 2009b. AquaCrop-The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal 101: 426-437. https://doi.org/10.2134/agronj2008.0139s
Stricevic R., Simic A., Kusvuran A., Cosic M. 2017. Assessment of AquaCrop model in the simulation of seed yield and biomass of Italian ryegrass. Archives of Agronomy and Soil Sciences 63 (9):1301-1313. https://doi.org/10.1080/03650340.2016.1275580
Sun Z., Jia S.F., Lv A.F., Yang K.J., Svensson J., Gao Y.C. 2015. Impacts of climate change on growth period and planting boundaries of winter wheat in China under RCP4.5 scenario. Earth System Dynamics Discussion 6: 2181-2210 https://doi.org/10.5194/esdd-6-2181-2015
Tacarindua C.R., Shiraiwa T., Homma K., Kumagai E., Sameshima R. 2013. The effects of increased temperature on crop growth and yield of soybean grown in a temperature gradient chamber. Field Crop Research 154 (1): 74-81. https://doi.org/10.1016/j.fcr.2013.07.021
Travasso M.I., Magrin G., Rodríguez G.R., López G.M. 2009. Potential impacts of climate change on soybean yield in the Argentinean pampas and adaptation measures for future sustainable production. Earth and Environment Science 6: 37-40. https://doi.org/10.1088/1755-1307/6/37/372045
Vara Prasad P., Allen J.L., Boote K. 2005. Crop responses to elevated carbon dioxide and interaction with temperature: grain legumes. Journal of Crop Improvement 13: 113-155. https://doi.org/10.1300/J411v13n01_07
Vatankhah Sadat A. 2009. Feasibility regions cultivation of citrus in Prs Abad Moghan. M.Sc., Thesis. Azad University, Ahar branch, 95 pp.
Voloudakisa D., Karamanosa A., Economoua G., Kalivasb D., Vahamidisa P., Kotoulasa V., Kapsomenakisc J., Zerefosc C. 2014. Prediction of climate change impacts on cotton yield in Greece fewer than eight climatic models using the AquaCrop crop simulation model and discriminate function analysis. Agricultural Water Management 147: 116-128. https://doi.org/10.1016/j.agwat.2014.07.028
Wheeler T.R., Hong T.D., Ellis R.H., Battsm G.R., Morison J.I.L., Hadley P. 1996. The duration and rate of grain growth, and harvest index, of wheat (Triticum aestivum L.) in response to temperature and CO2. Journal of Experimental Botany 47 (5): 623-630. https://doi.org/10.1093/jxb/47.5.623
Wilcox J., Makowski D. 2014. A meta-analysis of the predicted effects of climate change on wheat yield using simulation studies. Field Crop Research 156 (2): 180-190. https://doi.org/10.1016/j.fcr.2013.11.008
Zhang W., Liu W., Xue Q., Chen J., Han X. 2013. Evaluation of the AquaCrop model for simulation yield response of winter wheat to water on the southern Loess Plateau of China. Water Sciences Technology 68 (4): 821-829.
https://doi.org/10.2166/wst.2013.305
Zhang X.C., Nearing M.A. 2005. Impact of climate change on soil erosion, runoff, and wheat productivity in central Oklahoma. Catena 61: 185-195.
https://doi.org/10.1016/j.catena.2005.03.009
Agrotechniques in Industrial Crops
Volume 1, Issue 1
Agrotechniques in Industrial Crops (Agrotech Ind Crops) (Online ISSN: 2783-2945)
March 2021
Pages 36-51

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