Modeling chickpea yield of rain-fed in dormant seeding using general circulation models in west and north western of Iran

Document Type : scientific research article

Authors

1 Corresponding Author, Associate Prof., Dept. of Plant Production, Faculty of Agriculture, Higher Education Complex of Saravan, Iran

2 Department of Agricultural Science, Technical and Vocational University (TVU), Tehran, Iran

Abstract

Background and objectives: According to global warming and climate change, investigating and assessing the efficiency of adaptation strategies are necessary for achieving agricultural sustainable development under future climate conditions. Change in sowing date and dormant seeding for crops can be considered as a suitable strategy to adapt with changing climate conditions. Under dormant seeding management (DSM), the seeds remain ungerminated in the soil, and germinate and emerge with the onset of warming thanks to climate change exploiting late-winter rainfalls, and consequently decreasing frost risk stress at seedling stage and increasing water use efficiency. The main objective of the current study was to investigate the effect of sowing dates especially dormant seeding on rainfed chickpea seed yield in Kermanshah (West) and Tabriz (Northwest) climatic conditions.
Materials and Methods: In the current study, three general circulation models (MPI-ESM-LR, MPI-ESM-MR and NorESM1) were used under two emission scenarios (RCP4.5 and RCP8.5) for the future of 2039–2069 in Kermanshah and Tabriz regions. GCM outputs were downscale by AgMIP methodology. The SSM-Chickpea model was employed to simulate the growth and development of chickpea (Soltani and Sinclair, 2011). Five sowing dates including 21 December (DSM), 6 March, 21 March, 4 April and 21 April were considered as an adaptation strategy to possible impacts of climate change. Study traits included leaf area index, number of days to maturity, mean temperature over the growing season, cumulative rainfall, evapotranspiration, biological yield, and grain yield.
Results and discussion: The results of model validation showed that the model was able to predict the grain yield reasonably well (R2=0.92 and RMSE=14%). Overall, averaged grain yield at all sowing dates in Tabriz was 131% more than Kermanshah in the baseline. High grain yield in Tabriz compared with Kermanshah can be attributed to more leaf area index and length of growing season. Averaged grain yield in dormant seeding was 13.51, 22.30, 31.94 and 46.86% higher compared to 6 March, 21 March, 4 April and 21 April, respectively in both locations at the baseline. On average (GCMs, emission scenarios and locations), dormant seeding had the highest grain yield (24.93%) than other sowing dates in future climate change conditions compared to baseline. The reasons of superiority of dormant seeding of chickpea compared to other sowing dates was due to coinciding of crop growth period with rainfall (Hajjarpoor et al., 2016), reduction in negative effects of high temperatures on grain yield especially during grain filling (Hajarpour et al., 2013), increasing transpiration efficiency due to lower temperatures over the growing season (Soltani et al., 2006) and escaping terminal drought stress at end of growing season. Averaged grain yield (locations, sowing dates and GCMs) under RCP4.5 and RCP8.5 scenarios increased by 8.97 and 14.12% compared to baseline. Increasing grain yield was due to the positive effects of boosting the carbon dioxide concentration on the photosynthesis rate of chickpea as a C3 plant under changing climate (Meghdadi et al., 2014).

Keywords

Main Subjects

References

1.Eyni-Nargeseh, H., Deihimfard, R., Soufizadeh, S., Haghighat, M. and Nouri, O. 2016. Predicting the impacts of climate change on irrigated wheat yield in Fars province using APSIM model. Electronic J. Crop Prod. 8: 4. 203-224. (In Persian with English abstract)
2.Rahimi-Moghaddam, S., Kambouzia, J. and Deihimfard, R. 2018. Adaptation strategies to lessen negative impact of climate change on grain maize under hot climatic conditions: A model-based assessment. Agric. For. Meteorol. 254: 1-14.
3.Zeinali Mobarakeh, Z., Deihimfard, R. and Kambouzia, J. 2018. Modelling the Impacts of Climate Change on Irrigated Wheat Yield under Water Limited Conditions in Khorasan Razavi Province. J. Agric. Sci. Sustain. Prod. 28: 3. 155-169. (In Persian with English abstract)
4.Asseng, S., Ewert, F., Martre, P., Rotter, R.P., Lobell, D.B., Cammarano, D., Kimbal, B.A., Ottman, M.J., Wall, W., White, J.W., Reynolds, M.P., Alderman, P.D., Prasad, P.V.V., Aggarwal, 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., Hunt, L.A., Izaurralde, R.D., Jabloun, M., Jounes, C.D., Kersebaum, K.C., Koehler, A.K., Muller, C., Naresh Kumar, S., Nendel. C., Leary, C.O., Olesen, J.E., Palosuo, T., Priesack, E., Eyshi Rezaei, E., Ruane., A.C., Semenov, M.A., Shcherbak, I., Stocke, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Thorburn, P.J., Waha, K., Wang, E., Wallach, D., Woll, J., Zhao, Z. and Zhu, Y. 2015. Rising temperatures reduce global wheat production. Nat. Clim. Chang. 5: 143-147.
5.Wang, B., Liu, D.L., Asseng, S., Macadam, I. and Yu, Q. 2015. Impact of climate change on wheat flowering time in eastern Australia. Agric. For. Meteorol. 209-210: 11-21.
6.Manschadi, A.M., Soufizadeh, S. and Deihimfard, R. 2010. The role and importance of simulation modeling in improving crop production in Iran. Key paper in the 11th Iranian Crop Science Congress, pp. 234-247.
7.Tingem, M. and Rivington, M. 2009. Adaptation for crop agriculture to climate change in Cameroon: Turning on the heat. Mitig. and Adapt. Strateg. Glob. Chang. 14: 153-168.
8.Luo, Q., Bellotti, W., Williams, M. and Wang, E. 2009. Adaptation to climate change of wheat growing in South Australia: Analysis of management and breeding strategies. Agric. Ecosyst. Environ. 129: 261-267.
9.White, J.W., Hoogenboom, G., Kimball, B.A. and Wall, G.W. 2011. Methodologies for simulating impacts of climate change on crop production. Field Crops Res. 124: 357-368.
10.Soltani, A. and Sinclair, T.R. 2012. Optimizing chickpea phenology to available water under current and future climates. Eur. J. Agron. 38: 22-31.
11.Singh, P., Nedumaran, S., Boote, K.J., Gaur, P.M., Srinivas, K. and Bantilan, M.C.S. 2014. Climate change impacts and potential benefits of drought and heat tolerance in chickpea in South Asia and East Africa. Eur. J. Agron. 52: 123-137.
12.Mohammed, A., Tana, T., Singh, P., Molla, A. and Seid, A. 2017. Identifying best crop management practices for chickpea (Cicer arietinum L.) in Northeastern Ethiopia under climate change condition. Agric. Water Manage. 194: 68-77.
13.Eyni-Nargeseh, H., Rahimi-Moghaddam, S., Deihimfard, R. and Mokhtassi-Bidgoli, A. 2017. Evaluation of yield and crop water requirement in response to change of planting date under climate change conditions in Kermanshah province. J. Agric. Sci. Sustain. Prod. 27: 3. 172-186. (In Persian with English abstract)
14.Hajjarpoor, A., Meghdadi, N., Soltani, A. and Kamkar, B. 2016. Assessment of the adaptation strategies in rainfed chickpea in response to future climate change in Zanjan province. J. Agroecol. 8: 2. 169-181. (In Persian with English Abstract)
15.MAJ [Ministry of Agriculture Jihad]. 2020. Agricultural statistics, 2019-2020, volume 1. Available at: http:// www.maj.ir/Portal/Home/.
16.Zyaie, S.M., Nezami, A., Valizadeh, J. and Jafari, M. 2012. Evaluation of possible autumn sowing of lentil in Saravan condition. Agron. J. (Pajouhesh Sazandegi). 104: 55-62. (In Persian with English abstract)
17.Amiri, S.R. and Deihimfard, R. 2018. Can the dormant seeding of rainfed lentil improve productivity and water use efficiency in arid and semi-arid conditions? Field Crops Res. 227: 67-78.
18.Hoogenboom, G., Jones, J.W., Porter, C.H., Wilkens, P.W., Boote, K.J., Batchelor, W.D., Hunt, L.A. and Tsuji G.Y. (Eds). 2003. Decision Support System for Agrotechnology Transfer Version 4.0. Vol. 1: Overview. University of Hawaii, Honolulu, HI.
19.Prescott, J.A. 1940. Evaporation from a water surface in relation to solar radiation. Transactions of the Royal Society of South Australia. 64: 114-118.
20.Ghahreman, N., Babaeian, I. and Tabatabaei, M. 2015. Investigation of uncertainty in the IPCC AR5 precipitation and temperature projections over Iran under RCP scenarios. Our Future under Climate Change. 7th-10th July, Paris, France.
21.Ruane, A.C., Winter, J.M., McDermid, S.P. and Hudson, N.I. 2014. AgMIP Climate Datasets and Scenarios for Integrated Assessment. In: Hillel, D., Rosenzweig, C. (Eds.), Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Phase I Activities (Vol. 3). ICP Series on Climate Change Impacts, Adaptation, and Mitigation. Imperial College Press.
22.Wilby, R.L. and Wigley, T.M.L. 1997. Downscaling general circulation model output: A review of methods and limitations. Prog. Phys. Geogr. 21: 530-548.
23.AgMIP. 2013a. Guide for Running AgMIP Climate Scenario Generation Tools with R in Windows. AgMIP, URL: http://www.agmip.org/wp-content/ uploads/2013/ 10/Guide -for- Running-AgMIP Climate Scenario Generation-with-R-v2.3.pdf.
24.AgMIP. 2013b. The coordinated climate-crop modeling project c3mp: an initiative of the agricultural model inter comparison and improvement project. C3MP Protocols and Procedures. AgMIP, URL: http://research.agmip. org/ download/ attachments/ 1998899/C3MP+Protocols+v2.pdf.
25.Araya, A., Hoogenboom, G., Luedeling, E., Hadgu, K.M., Kisekka, I. and Martorano, L.G. 2015. Assessment of maize growth and yield using crop models under present and future climate in southwestern Ethiopia. Agric. For. Meteorol. 214: 252-265.
26.Wilby, R.L, Charles, S.P, Zorita, E., Timbal, B., Whetton, P. and Mearns, L.O. 2004. Guidelines for use of climate scenarios developed from statistical downscaling methods. In: IPCC Task Group on Data and Scenario Support for Impacts and Climate Analysis.
27.Moss, R.H., Edmonds, J.A., Hibbard, K.A., Manning, M.R., Rose, S.K., van Vuuren, D.P., Carter, T.R., Emori, S., Kainuma, M., Kram, T., Meehl, G.A., Mitchell., J.F.B., Nakicenovic, N., Riahi, K., Smith, S.J., Stouffer, R.J., Thomson, A.M., Weyant, J.P. and Wilbanks, T. 2010. The next generation of scenarios for climate change. Nature. 463: 747-756.
28.Wayne, G.P. 2013. The beginner’s guide to representative concentration pathways. Skeptical Sci., URL: http://www.skepticalscience.com/docs/ RCP Guide.
29.Soltani, A. and Sinclair, T.R. 2011. A simple model for chickpea development, growth and yield. Field Crops Res.
124: 252-260.
30.Amiri, S.R., Deihimfard, R. and Soltani, A. 2016. A single supplementary irrigation can boost chickpea grain yield and water use efficiency in arid and semiarid conditions: a modeling study. Agron. J. 108: 2406-2416.
31.Wallach, D. and Gofnet, B. 1987. Mean squared error of prediction in models for studying economic and agricultural systems. Biometrics. 43: 561-576.
32.Soltani, A. and Faraji, A. 2006. Determine phenology and growth rate of chickpea under rainfed conditions favorable for the dome of Gorgan. J. Food Sci. Technol. 20: 7. 49-57.
33.Meghdadi, N., Soltani, A., Kamkar, B. and Hajarpoor, A. 2015. Simulating the impact of climate change on production of chickpea in Zanjan province. Electronic J. Crop Prod. 7: 4. 1-22. (In Persian with English abstract)
34.Vadez, V., Soltani, A. and Sinclair, T.R. 2013. Crop simulation analysis of phonological adaptation of chickpea to different latitudes of India. Field Crops Res. 146: 1-9.
35.Wang, B., Liu, D.L., Asseng, S., Macadam, I. and Yu, Q. 2015. Impact of climate change on wheat flowering time in eastern Australia. Agric. For. Meteorol. 209-210: 11-21.
36.Deihimfard, R., Eyni-Nargeseh, H. and Farshadi, Sh. 2017. Modeling the effects of climate change on irrigation requirement and water use efficiency of wheat fields of Khuzestan province. J. Water Soil. 31: 4. 1015-1030. (In Persian with English abstract)
37.Hajarpoor, A., Soltani, A., Zeinali, E. and Sayyedi, F. 2014. Potential benefits from adaptation to climate change
in chickpea. J. Agric. Sci. Develop. 3: 230-236.
38.Soltani, A. and Gholipoor, M. 2006. Simulating the impact of climate change on growth, yield and water use of chickpea. J. Agric. Sci. Natur. Res. 13: 69-79. (In Persian with English abstract)
Journal of Plant Production Research
Volume 30, Issue 1
June 2023
Pages 187-208

Files

Share

How to cite

Statistics