Simulating Grain Yield and Water Use Efficiency in Dominant Maize Cultivars under Water Limited a Climate Change Conditions

Document Type : Scientific - Research

Authors

• Neda Sharifi Haddad ¹
• Reza Deihim Fard ²
• Omid Nouri ²
• Sajad Rahimi Moghaddam ³

¹ Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University G.C., Tehran, Iran

² Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran.

³ Department of Agronomy and Plants Breeding, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.

10.22067/jag.v13i1.80923

Abstract

Introduction
Today, rapid population growth and economic development have increased demand for food, and climate change has affected food security worldwide. Climate change processes, including increasing the atmospheric carbon dioxide concentration, rising temperature, and fluctuation of precipitation, could directly affect agricultural products. Climate change also causes drought, which indirectly influences agricultural systems as water is the most important for grain yield and its quality. Arid and semi-arid regions are limited in terms of water resources and they are the most fragile regions faced with drought caused by climate change. Khuzestan province is one of the hot and arid regions in Iran which its agricultural crops (especially maize) are very sensitive to climate change. Irrigation schedules and various cultivars can be considered as the adaptation strategies according to the climate change conditions. In agricultural ecosystems, water consumption should be reduced, and grain yield should be increased as much as possible. Optimizing water consumption by improving water use efficiency (WUE) is essential for achieving agricultural sustainability in arid and semi-arid regions. Accordingly, modelling approach has been considered as a time-saving and low-cost way to study the effects of climate change and different treatments. The current study was conducted to investigate the effects of different irrigation management practices on maize grain yield and WUE under climate change conditions in order to optimize water consumption and WUE by using modeling approach.
Material and Methods
The current study was carried out in several locations of Khuzestan province, including Dezful, Izeh, Bostan, and Ahwaz. The long-term climatic data of the studied locations were collected from the Iran Meteorological Organization. These data included minimum and maximum temperatures (°C), rainfall (mm), and solar radiation (MJ m^-2) from 1980 to 2010. Angstrom equation was used for calculating the radiation based on sunshine hours. The climatic data were modified using WeatherMan software embedded in the DSSAT package. The future climate of Khuzestan province (2040-2070) was predicted by the MIROC5 general circulation model under the RCP4.5 climate scenario and using AgMIP methodology. According to the previous studies, the MIROC5 climatic model showed the highest accuracy in predicting the future climatic data of Khuzestan province. Two adaptation strategies, including cultivar and irrigation regime, were considered to mitigate the negative effects of climate change. The cultivars consisted of SC704 (late-maturity) and SC206 (mid-maturity), which had the highest area under cultivation in Khuzestan province. Irrigation regimes included three levels: 12-time irrigation (as farmers’ common practice), 10–time irrigation, and 14-time irrigation per growing season.
Results and Discussion
The results of the current study indicated that climate change had negative effects on maize grain yield as well as positive effects on average temperature during the growing season, evapotranspiration, and corn water use efficiency across the whole province. The results showed that the average grain yield and corn WUE in Khuzestan province in 2050 under the RCP4.5 scenario was -2% and -5.7%, respectively, compared to the baseline. In addition, mean temperature during the growing season and evaporation and transpiration increased by +12.6% and + 0.9% compared to the baseline. The results also showed that with the application of an optimal amount of irrigation regime (10-time irrigation), an increase in WUE and decrease in evapotranspiration were observed, which resulted in acceptable grain yield. Results also portrayed that applying the optimal irrigation level (10-time) along with a late maturity cultivar (SC704) showed the best performance in terms of grain yield (9433.9 kgha^-1) and WUE (19.57 kgha^-1 mm^-1) in the province Khuzestan.
Conclusion
The results illustrated that by 2050, the average grain yield and WUE were reduced compared to the baseline period. However, the mean temperature and evapotranspiration over the growing season were increased. Totally, the results of the current study revealed that an optimal irrigation level 10 and suitable cultivar SC704 could mitigate the negative impacts of climate change on maize in the agroecosystems of Khuzestan province.

Keywords

• Evapotranspiration
• APSIM model
• Irrigation regime

20.1001.1.20087713.1400.13.1.7.6

---

References

Abbas Torki, T., Mojaddam, M., and Abadouz, G.R., 2011. Study of water stress on morphological characters of corn (Zea mays L.) hybrids in south Khouzestan condition. In First National Conference on Climate Change and its Impact on Agriculture and the Environment, Urmia, Iran, 24 July 2011, p. 1836-1842. (In Persian with English Summary)

Anonymous, 2014. Agricultural statistics. Iranian Ministry of Agriculture Jihad. Department of Planning and Economically. Center of Information and Communication Technology. Iran. p. 158. (In Persian)

Bannayan, M., Crout, N.M.J., and Hoogenboom, G., 2003. Application of the CERES-wheat model for within–season prediction of wheat yield in United Kingdom. Agronomy Journal 95: 114–125.

Bannayan, M., Kobayashi, K., Kim, H.Y., Lieffering, M., Okada, M., and Miura, S., 2005. Modeling the interactive effects of atmospheric CO₂ and N on rice growth and yield. Field Crops Research 93: 237-251.

Boote, K.J., 2011. Crop adaptation to climate change. In: S.S. Yadav, R.J. Redden, J.L. Hatfield, H. Lotze-Campen and A.E. Hall (Eds.). Improving soybean cultivars for adaptation to climate change and climate variability: Wiley-Blackwell Press. p. 370-395.

Dashtbozorgi, A., Alijani, B., Jafarpur, Z., and Shakiba, A., 2015. Simulatiing extreme temperature indicators based on RCP scenarios: the case of Khuzestan Province. Geography and Environmental Hazards 4: 105–123 (In Persian with Englosh Summary)

Dong, B., Shi, L., Shi, C., Qiao, Y., Liu, M., and Zhang, Z., 2011. Grain yield and water use efficiency of two types of winter wheat cultivars under different water regimes. Agricultural Water Management 99: 103-110.

Dupuis, I., and Dumas, C., 1990. Influence of temperature stress on in vitro fertilisation and heat shock protein synthesis in maize (Zea mays L.) reproductive tissues. Plant Physiology 94: 665–670.

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 Journal of Crop Production8(4): 203-224. (In Persian with English Summary)

Huang, J.K., Pray, C., and Rozelle, S., 2002. Enhancing the crops to feed the poor. Nature 48: 678–684.

Igbadun, H.E., Mahoo, H.F., Tarimo, A.K., and Salim, B.A., 2006. Crop water productivity of an irrigated maize crop in Mkoji sub-catchment of the Great Ruaha River Basin. Tanzania. Agricultural Water Management 85: 141-150.

IPCC, 2014. Climate Change: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Core Writing Team, R.K. Pachauri and L.A. Meyer (Eds.)). IPCC. Geneva, Switzerland. p. 151.

Izadi Darbandi, E., 2012. Evolution of drought stress and nitrogen rate on redroot pigweed (Amaranthus retroflexus) and corn (Zea mays) competition. Agronomy Journal(Pajouhesh and Sazandegi) 94: 68-74. (In Persian with English Summary)

Kang, Y., Khan, S., and Ma, X., 2015. Analysing climate change impacts on water productivity of cropping systems in the Murray Darling Basin, Australia. Irrigation and Drainag64: 443-453.

Karandish, F., Kalanaki, M., and Saberali, S.F., 2017. Projected impacts of global warming on cropping calendar and water requirement of maize in a humid climate. Archives of Agronomy and Soil Science 63(1): 1-13.

Kirkegaard, J.A., Lilley, J.M., Howe, G.N., and Graham, J.M., 2007. Impact of subsoil water use on wheat yield. Crop and Pasture Science 58: 303–315.

Liu, Z., Hubbard, K.G., Lin, X., and Yang, X., 2013. Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China. Global Change Biology 19: 3481-3492.

Maa, L., Ahujaa, L.R., Islamb, A., Trout C.T.J., Saseendrand, S.A., and Malone, R.W., 2017. Modeling yield and biomass responses of maize cultivars to climate change under full and deficit irrigation. Agricultural Water Management 180: 88–98.

Manschadi, A.M., Soufizadeh, S., and Deihimfard, R., 2010. The role and importance of simulation modeling in improving crop production in Iran. In: Proceedings of 11^th Iranian Crop Science Congress, Shahid Beheshti University, Tehran, Iran, 24 July 2010, p. 234-247. (In Persian with English Summary)

Martin de Santa Olalla, F., Dominguez-Padilla, A., and Lopez, R., 2004. Production and quality of the onion crop (Allium cepa) cultivated under controlled deficit irrigation conditions in a semi-arid climate. Agricultural Water Management 68: 77-89.

Medrano, H., Tomás, M., Martorell, S., Flexas, J., Hernández, E., Rosselló, J., Pou, A., J. Escalona, M., and Bota, J., 2015. From leaf to whole-plant water use efficiency (WUE) in complex canopies: limitations of leaf WUE as a selection target. The Crop Journal 3: 220-228.

Meza, F.J., Silva, D., and Vigil, H., 2008. Climate change impacts on irrigated maize in Mediterranean climates: evaluation of double cropping as an emerging adaptation alternative. Agricultural Systems 98: 21–30.

Moradi, R., Koocheki, A., Nassiri Mahallati, M., and Mansoory, H., 2013. Adaptation strategies for maize cultivation under climate change in Iran: Irrigation and planting data management. Mitigation andAdaptation Strategies for Global Change 18: 265-284.

Oktem, A., Simsek, M., and Oktem, G., 2003. Deficit irrigation effects on sweet corn (Zea mays saccharata Sturt) with drip irrigation system in a semi-arid region: I. Water-yield relationship. Agricultural Water Management 61: 63-74.

Rahimi Moghaddam, S., and Azizi, K., 2017. Early sowing date as a strategy for improvement of maize yield and maize physiological and phonological characteristics in climate change conditions at Kermanshah Province. Electronic Journal of Crop Production 10(40): 129-147. (In Persian with English Summary)

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. Agricultural and Forest Meteorology 253: 1-14.

Rahimi-Moghaddam, S., Kambouzia, J., and Deihimfard, R., 2019. Optimal genotype × environment × management as a strategy to increase grain maize productivity and water use efficiency in water-limited environments and rising temperature. Ecological Indicators 107: 105570.

Rahimi-Moghaddam, S., Eyni-Nargeseh, H., Ahmadi, S.A.K., and Azizi, K., 2021. Towards withholding irrigation regimes and drought-resistant genotypes as strategies to increase canola production in drought-prone environments: A modeling approach. Agricultural Water Management 243: 106487.

Sabziparvar, A.A., and Tabari, H., 2010. Regional estimation of reference evapotranspiration in arid and semi-arid regions. Journal of Irrigation and Drainage Engineering 136(10): 724–731.

Seifert, E., 2014. OriginPro 9.1: Scientific data analysis and graphing software—software review. Journal of Chemical Information and Modeling 54: 1552–1552.

Soltani, A., and Hoogenboom, G., 2007. Assessing crop management options with crop simulation models based on generated weather data. Field Crops Research 103: 198- 207.

Wakrim, R., Aganchich, B., Tahi, H., Serraj, R., and Wahbi, S., 2005. Comparative effects of partial root drying (PRD) and regulated deficit irrigation (RDI) on water relations and water use efficiency in common bean (Phaseolus vulgaris L.). Agriculture, Ecosystems and Environment 106: 275-287.