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Effects of Projected Climate Change on Quantity and Quality of Soybean Yield under Different Emission Scenarios


Affiliations
1 Department of Biological and Agricultural Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
2 Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO) Karaj, Iran, Islamic Republic of
3 Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
4 Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Iran, Islamic Republic of
5 Department of Land Management, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
6 Institute of Graduate Studies Building, Institute of Ocean and Earth Science (IOES), University of Malaya, 50603 Kuala Lumpur, Malaysia
 

Soybean is one of the most important oilseed crops in the world. Its economic value is based on the concentration of protein and oil produced in the seeds. However, in climate change studies, a crop simulation model like AquaCrop is unable to predict the qualitative yield of crops. Therefore, this study aims to simulate qualitative soybean yield based on regression models between observed dry grain yield (Yd) from 12 treatments as independent variables with their corresponding observed values for oil and protein contents as dependent variables. The P-value (<0.05) and R2 value of the linear regression model showed that oil content was positively regressed with yield, whereas protein content was negatively regressed with yield. On the other hand, predicted values of Yd from the calibrated AquaCrop model over general circulation models based on weighted multi-model ensemble means of five emission scenarios have been used for simulation of soybean oil and protein contents in the future. The results obtained by comparing historical period (1985–2010) to the future period (2020–2039) centred on the 2030s, showed that soybean oil content increased similarly as yield increased in the future period while protein content decreased inversely with yield. Overall, statistical indicators showed that the linear regression model performed well to predict the soybean oil and protein content when AquaCrop model not able to simulate the qualitative yield.

Keywords

Dry Grain Yield, Linear Regression, Oil Contents, Protein Contents, Soybean.
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  • Kumar, V., Rani, A., Solanki, S. and Hussain, S., Influence of growing environment on the biochemical composition and physical characteristics of soybean seed. J. Food Compos. Anal., 2006, 19, 188–195.

  • Song, W. et al., Analyzing the effects of climate factors on soybean protein, oil contents, and composition by extensive and high-density sampling in china. J. Agric. Food Chem., 2016, 64, 4121–4130.

  • Thomas, J., Boote, K., Allen, L., Gallo-Meagher, M. and Davis, J., Elevated temperature and carbon dioxide effects on soybean seed composition and transcript abundance. Crop Sci., 2003, 43, 1548– 1557.

  • Taub, D. R., Miller, B. and Allen, H., Effects of elevated CO2 on the protein concentration of food crops: A meta‐analysis. Glob. Change Biol., 2008, 14, 565–575.

  • Pipolo, A. E., Sinclair, T. R. and Camara, G. M., Effects of temperature on oil and protein concentration in soybean seeds cultured in vitro. Ann. Appl. Biol., 2004, 144, 71–76.

  • Araji, H. A., Wayayok, A., Bavani, A. M., Amiri, E., Abdullah, A. F., Daneshian, J. and Teh, C., Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models. Agric. Water Manage., 2018, 205, 63–71.

  • Raes, D., Steduto, P., Hsiao, T. C. and Fereres, E., Fao, land and water division Rome, Italy, 2012.

  • Stricevic, R., Cosic, M., Djurovic, N., Pejic, B. and Maksimovic, L., Assessment of the fao aquacrop model in the simulation of rainfed and supplementally irrigated maize, sugar beet and sunflower. Agric. Water Manage., 2011, 98, 1615–1621.

  • Iqbal, M. A. et al., Evaluation of the fao aquacrop model for winter wheat on the north china plain under deficit irrigation from field experiment to regional yield simulation. Agric. Water Manage., 2014, 135, 61–72.

  • Araya, A., Habtu, S., Hadgu, K. M., Kebede, A. and Dejene, T., Test of aquacrop model in simulating biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agric. Water Manage., 2010, 97, 1838–1846.

  • Mustafa, S. M. T., Vanuytrecht, E. and Huysmans, M., Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh. Agric. Water Manage., 2017, 191, 124–137.

  • Chung, J. et al., The seed protein, oil, and yield qtl on soybean linkage group i. Crop Sci., 2003, 43, 1053–1067.

  • Dornbos Jr, D. and Mullen, R., Soybean seed protein and oil contents and fatty acid composition adjustments by drought and temperature. J. Am. Oil Chem. Soc., 1992, 69, 228–231.

  • Piper, E. L. and Boote, K. I., Temperature and cultivar effects on soybean seed oil and protein concentrations. J. Am. Oil Chem. Soc., 1999, 76, 1233–1241.

  • Howell, R. W. and Cartter, J. L., Physiological factors affecting composition of soybeans: Ii. Response of oil and other constituents of soybeans to temperature under controlled conditions 1. Agron. J., 1958, 50, 664–667.

  • Divsalar, M., Study the effect of drought stress on oil percent, protein percent and fatty acids composition of soybean grain. J. Plant Ecophysiol., 2017, 8, 44–55.

  • DaMatta, F. M., Grandis, A., Arenque, B. C. and Buckeridge, M. S., Impacts of climate changes on crop physiology and food quality. Food Res. Int., 2010, 43, 1814–1823.

  • Gibson, L. and Mullen, R., Soybean seed composition under high day and night growth temperatures. J. Am. Oil Chem. Soc., 1996, 73, 733–737.

  • Wolf, R., Cavins, J., Kleiman, R. and Black, L., Effect of temperature on soybean seed constituents: oil, protein, moisture, fatty acids, amino acids and sugars. J. Am. Oil Chem. Soc., 1982, 59, 230–232.


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  • Effects of Projected Climate Change on Quantity and Quality of Soybean Yield under Different Emission Scenarios

Abstract Views: 333  |  PDF Views: 121

Authors

Hamidreza Ahmadzadeh Araji
Department of Biological and Agricultural Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
Aimrun Wayayok
Department of Biological and Agricultural Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
Jahanfar Daneshian
Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO) Karaj, Iran, Islamic Republic of
Majid Mirzaei
Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
Ali Reza Massah Bavani
Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Iran, Islamic Republic of
C. B. S. Teh
Department of Land Management, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
Ahmad Fikri Abdullah
Department of Biological and Agricultural Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia
Parisa Ahmadi
Institute of Graduate Studies Building, Institute of Ocean and Earth Science (IOES), University of Malaya, 50603 Kuala Lumpur, Malaysia

Abstract


Soybean is one of the most important oilseed crops in the world. Its economic value is based on the concentration of protein and oil produced in the seeds. However, in climate change studies, a crop simulation model like AquaCrop is unable to predict the qualitative yield of crops. Therefore, this study aims to simulate qualitative soybean yield based on regression models between observed dry grain yield (Yd) from 12 treatments as independent variables with their corresponding observed values for oil and protein contents as dependent variables. The P-value (<0.05) and R2 value of the linear regression model showed that oil content was positively regressed with yield, whereas protein content was negatively regressed with yield. On the other hand, predicted values of Yd from the calibrated AquaCrop model over general circulation models based on weighted multi-model ensemble means of five emission scenarios have been used for simulation of soybean oil and protein contents in the future. The results obtained by comparing historical period (1985–2010) to the future period (2020–2039) centred on the 2030s, showed that soybean oil content increased similarly as yield increased in the future period while protein content decreased inversely with yield. Overall, statistical indicators showed that the linear regression model performed well to predict the soybean oil and protein content when AquaCrop model not able to simulate the qualitative yield.

Keywords


Dry Grain Yield, Linear Regression, Oil Contents, Protein Contents, Soybean.

References





DOI: https://doi.org/10.18520/cs%2Fv118%2Fi1%2F103-107