Analysis of G × E Interaction for Selection of Stable Wheat Genotypes for Grain Yield and Yield Traits in Northern Bangladesh — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Analysis of G × E Interaction for Selection of Stable Wheat Genotypes for Grain Yield and Yield Traits in Northern Bangladesh
Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
,
College of Resources, Sichuan Agricultural University, Chengdu, China
,
College of Resources, Sichuan Agricultural University, Chengdu, China
,
College of Resources, Sichuan Agricultural University, Chengdu, China
In the present study carried out, twelve wheat ( Triticum aestivium L.) genotypes were evaluated for eight morphological traits at six different environments in northern part of Bangladesh, namely Panchaghar (E1), Thakurgaon (E2), Nilphamari (E3), Lalmonirhat (E4), Dinajpur (E5), and Rangpur (E6) during Rabi season 2020 to 2021, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variability was observed among the genotypes for the following traits viz. , plant height (cm), spike length (cm), number of tillers per plant, number of spikelets per spike, spike weight per plant, grains weight per spike (g), thousand seed weight (g) and grain yield (t/ha). Correlation analysis showed that the trait thousand seed weight was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (58.34%). GGE biplot showed E6 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., BARI Gom 32 for E6, BARI Gom 30 for (E2 and E4) and BARI Gom 26 for E1 were particular environment and the genotypes viz., BARI Gom 21, BARI Gom 23, and BARI Gom 30 were highly suitable for all the six environments. The genotypes with minimum genotype stability index (GSI) viz., BARI Gom 21 (17), BARI Gom 23 (22), and BARI Gom 30 (25) were observed with wide adaptation and high yields across all the six environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/prebreeding materials in future wheat breeding programs.
KeywordsGGEAMMIGSIG ×E InteractionWheatYield
Siddiqui, K.A. (2007) Green Biotechnology at the Crossroads of Nanobiotechnology, Globalization, Poverty Alleviation and Food Sovereignty. Indian Journal of Crop Sci ence , 2, 1-4.
Shiferaw, B., Smale, M., Braun, H., Duveiller, E., Reynolds, M. and Muricho, G. (2013) Crops That Feed the World 10. Past Successes and Future Challenges to the Role Played by Wheat in Global Food Security. Food Security , 5, 291-317. https://doi.org/10.1007/s12571-013-0263-y
Shewry, P.R. and Hey, S.J. (2015) The Contribution of Wheat to Human Diet and Health. Food and Energy Security , 4, 178-202. https://doi.org/10.1002/fes3.64
Listman, M. and Ordóñez, R. (2019) Ten Things You Should Know about Maize and Wheat. CIMMYT.
Curtis, B.C., Rajaram, S. and Gómez Macpherson, H. (2002) Wheat in the World. Bread Wheat: Improvement and Production. FAO (Food and Agriculture Organization of the United Nations) and Plant Production and Protection.
Tilman, D. and Clark, M. (2015) Food, Agriculture & the Environment: Can We Feed the World & Save the Earth? Daedalus , 144, 8-23. https://doi.org/10.1162/daed_a_00350
Asseng, S., Cammarano, D., Basso, B., Chung, U., Alderman, P.D., Sonder, K., et al . (2016) Hot Spots of Wheat Yield Decline with Rising Temperatures. Global Change Biology , 23, 2464-2472. https://doi.org/10.1111/gcb.13530
Xu, H., Twine, T.E. and Girvetz, E. (2016) Climate Change and Maize Yield in Iowa. PLOS ONE , 11, e0156083. https://doi.org/10.1371/journal.pone.0156083
Ganesh Kumar, A., Prasad Sanjay, K. and Pullabhotla Hemant, K. (2012) Supply and Demand for Cereals in Bangladesh: 2010-2030 (IFPRI Discussion Paper No. 1186). International Food Policy Research Institute.
Hossain, T. (2017) Bangladesh Grain and Feed Annual (USDA GAIN Report No. BG7004). U.S. Department of Agriculture Foreign Agricultural Service. https://www.fas.usda.gov/data/bangladesh-grain-and-feed-annual-3
IndexMundi (2019) Bangladesh Wheat Imports by Year. IndexMundi. https://www.indexmundi.com/agriculture/?country=bd&commodity=wheat&graph=imports
FAO (2018) FAOSTAT Data for Wheat Crop in Bangladesh. Food and Agriculture Organization of the United Nations. https://www.fao.org/faostat/en/#data/QC
FAOSTAT (2019) FAOSTAT data for Rice Crop in Bangladesh. Food and Agriculture Organization of the United Nations. http://www.fao.org/faostat/en/#data/QC
BBS (2018) Estimates of Wheat. Bangladesh Bureau of Statistics. http://bbs.portal.gov.bd/sites/default/files/files/bbs.portal.gov.bd/page/16d38ef2_2163_4252_a28b_e65f60dab8a9/wheat2018.pdf
BARC (2019) Crop Suitability Maps and Data. http://cropzoning.barcapps.gov.bd/homes/downloads/1
Tabakovic, M., Secanski, M., Stanisavljevic, R., Mladenovic-Drinic, S., Simic, M., Knezevic, J., et al . (2020) The Impact of Agroecological Factors on Morphological Traits of Maize. Genetika , 52, 1203-1213. https://doi.org/10.2298/gensr2003203t
Popovi’c, V., Jovovi’c, Z., Marjanovi’c-Jeromela, A., Sikora, V., Miki’c, S., Šarčević-Todosijević, L. (2020) Climatic Change and Agricultural Production. Proceedings of the GEA Conference 2021, Podgorica, 27-31 March 2020, 160-166.
Petrovic, S., Dimitrijevic, M., Belic, M., Banjac, B., Boskovic, J., Zecevic, V., et al . (2010) The Variation of Yield Components in Wheat ( Triticum aestivum L.) in Response to Stressful Growing Conditions of Alkaline Soil. Genetika , 42, 545-555. https://doi.org/10.2298/gensr1003545p
Oerke, E., Steiner, U., Dehne, H.W. and Lindenthal, M. (2006) Thermal Imaging of Cucumber Leaves Affected by Downy Mildew and Environmental Conditions. Journal of Experimental Botany , 57, 2121-2132. https://doi.org/10.1093/jxb/erj170
Quarrie, S., Pekic Quarrie, S., Radosevic, R., Rancic, D., Kaminska, A., Barnes, J.D. and Dodig, D. (2006) Dissecting a Wheat QTL for Yield Present in a Range of Environments: From the QTL to Candidate Genes. Journal of Experimental Botany , 57, 2627-2637. https://doi.org/10.1093/jxb/erl026
Ain, Q., Rasheed, A., Anwar, A., Mahmood, T., Imtiaz, M., Mahmood, T., et al . (2015) Genome-wide Association for Grain Yield under Rainfed Conditions in Historical Wheat Cultivars from Pakistan. Frontiers in Plant Science , 6, Article ID: 743. https://doi.org/10.3389/fpls.2015.00743
Foroozanfar, M. and Zeynali, H. (2013) Inheritance of Some Correlated Traits in Bread Wheat Using Generation Mean Analysis. Advanced Crop Science , 3, 436-443.
Ljubičić, N.D., Petrovi, S., Dimitrijevi, M. and Hristov, N. (2016) Gene Actions Involved in the Inheritance of Yield Related Traits in Bread Wheat ( Triticum aestivum L.). Emirates Journal of Food and Agriculture , 28, 477-484. https://doi.org/10.9755/ejfa.2016-02-117
Kang, M.S. (1993) Simultaneous Selection for Yield and Stability in Crop Performance Trials: Consequences for Growers. Agronomy Journal , 85, 754-757. https://doi.org/10.2134/agronj1993.00021962008500030042x
Tariku, S., Lakew, T., Bitew, M. and Asfaw, M. (2013) Genotype by Environment Interaction and Grain Yield Stability Analysis of Rice ( Oryza sativa L.) Genotypes Evaluated in Northwestern Ethiopia. Net Journal of Agricultural Science , 1, 10-16.
Islam, M.R., Sarker, M.R.A., Sharma, N., Rahman, M.A., Collard, B.C.Y., Gregorio, G.B., et al . (2016) Assessment of Adaptability of Recently Released Salt Tolerant Rice Varieties in Coastal Regions of South Bangladesh. Field Crops Research , 190, 34-43. https://doi.org/10.1016/j.fcr.2015.09.012
Grüneberg, W.J., Manrique, K., Zhang, D. and Hermann, M. (2005) Genotype × Environment Interactions for a Diverse Set of Sweetpotato Clones Evaluated across Varying Ecogeographic Conditions in Peru. Crop Science , 45, 2160-2171. https://doi.org/10.2135/cropsci2003.0533
Sabri, R.S., Rafii, M.Y., Ismail, M.R., Yusuff, O., Chukwu, S.C. and Hasan, N. (2020) Assessment of Agro-Morphologic Performance, Genetic Parameters and Clustering Pattern of Newly Developed Blast Resistant Rice Lines Tested in Four Environments. Agronomy , 10, Article 1098. https://doi.org/10.3390/agronomy10081098
Knežević, D., Zečević, V., Đukić, N., Dodig, D. (2008) Genetic and Phenotypic Vari-ability of Grain Mass Per Spike of Winter Wheat Genotypes ( Triticum aestivum L.). Kragujevac Journal of Science , 30, 131-136. http://rik.mrizp.rs/handle/123456789/207
Kang, M.S. (1997) Using Genotype-by-Environment Interaction for Crop Cultivar Development. Advances in Agronomy , 62, 199-252. https://doi.org/10.1016/s0065-2113(08)60569-6
Gauch Jr., H.G. (1992) Statistical Analysis of Regional Yield Trials: AMMI Analysis of Factorial Designs. Elsevier Science Publishers.
Yan, W. and Kang, M.S. (2002) GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. CRC Press.
Yan, W. and Tinker, N.A. (2006) Biplot Analysis of Multi-Environment Trial Data: Principles and Applications. Canadian Journal of Plant Science , 86, 623-645. https://doi.org/10.4141/p05-169
Zobel, R.W., Wright, M.J. and Gauch, H.G. (1988) Statistical Analysis of a Yield Trial. Agronomy Journal , 80, 388-393. https://doi.org/10.2134/agronj1988.00021962008000030002x
Gauch, H.G. (2006) Statistical Analysis of Yield Trials by AMMI and GGE. Crop Science , 46, 1488-1500. https://doi.org/10.2135/cropsci2005.07-0193
Rodrigues, P.C., Malosetti, M., Gauch, H.G. and van Eeuwijk, F.A. (2014) A Weighted AMMI Algorithm to Study Genotype‐by‐Environment Interaction and QTL‐by‐Environment Interaction. Crop Science , 54, 1555-1570. https://doi.org/10.2135/cropsci2013.07.0462
Popović, V., Ljubičić, N., Kostić, M., Radulović, M., Blagojević, D., Ugrenović, V., et al . (2020) Genotype × Environment Interaction for Wheat Yield Traits Suitable for Selection in Different Seed Priming Conditions. Plants , 9, Article 1804. https://doi.org/10.3390/plants9121804
Spanic, V., Cosic, J., Zdunic, Z. and Drezner, G. (2021) Characterization of Agronomical and Quality Traits of Winter Wheat ( Triticum aestivum L.) for Fusarium Head Blight Pressure in Different Environments. Agronomy , 11, Article 213. https://doi.org/10.3390/agronomy11020213
Ljubičić, N., Popović, V., Ćirić, V., Kostić, M., Ivošević, B., Popović, D., et al . (2021) Multivariate Interaction Analysis of Winter Wheat Grown in Environment of Limited Soil Conditions. Plants , 10, Article 604. https://doi.org/10.3390/plants10030604
Plavšin, I., Gunjača, J., Šimek, R. and Novoselović, D. (2021) Capturing GEI Patterns for Quality Traits in Biparental Wheat Populations. Agronomy , 11, Article 1022. https://doi.org/10.3390/agronomy11061022
ISTA (2015) International Rules for Seed Testing, Vol. 215, Introduction, i-1-6 (10). The International Seed Testing Association.
Amare, A., Mekbib, F., Tadesse, W. and Tesfaye, K. (2020) Genotype X Environment Interaction and Stability of Drought Tolerant Bread Wheat ( Triticum aestivum L.) Genotypes in Ethiopia. International Journal of Research Studies in Agricultural Sciences , 6, 26-35.
RStudio (2014) RStudio: Integrated Development Environment for R (Computer Software v0.98.1074). http://www.rstudio.org/
Yan, W., Kang, M.S., Ma, B., Woods, S. and Cornelius, P.L. (2007) GGE Biplot vs. AMMI Analysis of Genotype‐by‐Environment Data. Crop Science , 47, 643-653. https://doi.org/10.2135/cropsci2006.06.0374
Yan, W., Hunt, L.A., Sheng, Q. and Szlavnics, Z. (2000) Cultivar Evaluation and Mega‐Environment Investigation Based on the GGE Biplot. Crop Science , 40, 597-605. https://doi.org/10.2135/cropsci2000.403597x
Purchase, J.L., Hatting, H. and van Deventer, C.S. (2000) Genotype × Environment Interaction of Winter Wheat ( Triticum aestivum L.) in South Africa: II. Stability Analysis of Yield Performance. South African Journal of Plant and Soil , 17, 101-107. https://doi.org/10.1080/02571862.2000.10634878
Farshadfar, E. and Sutka, J. (2003) Locating QTLs Controlling Adaptation in Wheat Using AMMI Model. Cereal Research Communications , 31, 249-256. https://doi.org/10.1007/bf03543351
Angela, P., Mateo, V., Gregorio, A., Francisco, R., Jose, C. and Juan, B. (2015) GEA-R (Genotype × Environment Analysis with R for Windows) Version 4.1, hdl:11529/ 10203, CIMMYT Research Data and Software Repository Network, V16; GEA-R_v4.1_BASE_setup.exe.
Dehghani, H., Ebadi, A. and Yousefi, A. (2006) Biplot Analysis of Genotype by Environment Interaction for Barley Yield in Iran. Agronomy Journal , 98, 388-393. https://doi.org/10.2134/agronj2004.0310
Kaya, Y. and Akcura, M. (2014) Effects of Genotype and Environment on Grain Yield and Quality Traits in Bread Wheat ( T. aestivum L.). Food Science and Technology (Campinas) , 34, 386-393. https://doi.org/10.1590/fst.2014.0041
Nehe, A.S., Misra, S., Murchie, E.H., Chinnathambi, K. and Foulkes, M.J. (2018) Genetic Variation in N-Use Efficiency and Associated Traits in Indian Wheat Cultivars. Field Crops Research , 225, 152-162. https://doi.org/10.1016/j.fcr.2018.06.002
Taghouti, M., Gaboun, F., Nsarellah, N., Rhrib, R., El-Haila, M., Kamar, M., Ab-bad-Andaloussi, M. and Udupa, S.M. (2010) Genotype × Environment Interaction for Quality Traits in Durum Wheat Cultivars Adapted to Different Environments. African Journal of Biotechnology , 9, 3054-3062.
Win, K., Win, K., Min, T., Htwe, N. and Shwe, T. (2018) Genotype by Environment Interaction and Stability Analysis of Seed Yield, Agronomic Characters in Mungbean ( Vigna radiata L. Wilczek) Genotypes. International Journal of Advanced Research , 6, 926-934. https://doi.org/10.21474/ijar01/6750
Kilic, H. (2014) Additive Main Effects and Multiplicative Interactions (AMMI) Analysis of Grain Yield in Barley Genotypes across Environments. Tarım Bilimleri Dergisi , 20, 337-344. https://doi.org/10.15832/tbd.44431