Investigation on genotype-by-environment interaction and stable maize (Zea mays L.) hybrids across soil moisture conditions

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Research Articles | Published:

Print ISSN : 0970-4078.
Online ISSN : 2229-4473.
Website:www.vegetosindia.org
Pub Email: contact@vegetosindia.org
Doi: 10.1007/s42535-021-00312-z
First Page: 951
Last Page: 958
Views: 1890


Keywords: Drought, Waterlogging, Genotype-by-environment interaction, Stability, AMMI analysis


Abstract


Maize production and productivity are challenged by multiple and co-occurring stresses that impact crop growth, development and consequently the yields. Maize crop is often exposed to a combination of drought and waterlogging stresses during the same or alternative growing seasons, therefore it became a major challenge to select promising cultivars that fit across varied soil moisture conditions. In this context, the present experiment was carried out to evaluate 75 maize hybrids under six environments with a combination of cropping season, location and soil moisture condition. The objective of the present investigation is to carry out simultaneous selection of ideal maize hybrids with better yield potential and stable across soil moisture regimes through additive main effects and multiplicative interaction (AMMI) analysis. The analysis of variance for mean grain yield across test environments showed significant variation for genotype-by-environment interaction (GEI), along with genotypes and environments that ensured stability analysis. Five maize hybrids viz., ZH161303, ZH161478, ZH161330, ZH161047 and ZH161068 were found promising hybrids with high stability and productivity across the soil moisture regimes including low, excess and optimal soil moisture environments.


Drought, Waterlogging, Genotype-by-environment interaction, Stability, AMMI analysis


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References


Abakemal D, Shimelis H, Derera J (2016) Genotype-by-environment interaction and yield stability of quality protein maize hybrids developed from tropical-highland adapted inbred lines. Euphytica 209(3):757–769. https://doi.org/10.1007/s10681-016-1673-7


Abiko T, Kotula L, Shiono K, Malik AI, Colmer TD, Nakazono M (2012) Enhanced formation of aerenchyma and induction of a barrier to radial oxygen loss in adventitious roots of Zea nic-raguensis contribute to its waterlogging tolerance as compared with maize (Zea mays ssp. mays). Plant Cell Environ 35(9):1618–1630. https://doi.org/10.1111/j.1365-3040.2012.02513.x


Agahi K, Ahmadi J, Oghan HA, Fotokian MH, Orang SF (2020) Analysis of genotype × environment interaction for seed yield in spring oilseed rape using the AMMI model. Crop Breed Appl Biotechnol. https://doi.org/10.1590/1984-70332020v20n1a2


Akter A, Hasan MJ, Kulsum MU, Rahman MH, Paul AK, Lipi LF, Akter S (2015) Genotype× environment interaction and yield stability analysis in hybrid rice (Oryza sativa L.) by AMMI biplot. Bangladesh Rice J 19(2):83–90. https://doi.org/10.3329/brj.v19i2.28168


Alwala S, Kwolek T, McPherson M, Pellow J, Meyer D (2010) A comprehensive comparison between Eberhart and Russell joint regression and GGE biplot analyses to identify stable and high yielding maize hybrids. Field Crops Res 119(2–3):225–230. https://doi.org/10.1016/j.fcr.2010.07.010


ASTM (2001) Annual Book of ASTM Standards. In: American Society for Testing and Materials, 100 Barr Harbor Drive. ASTM, West Conshohocken


Badu-Apraku B, Oyekunle M, Obeng-Antwi K, Osuman AS, Ado SG, Coulibay N, Yallou CG, Abdulai M, Boakyewaa GA, Didjeira A (2012) Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis. J Agric Sci 150:473–483. https://doi.org/10.1017/S0021859611000761


Clarke JM, DePauw RM, Townley-Smith TF (1992) Evaluation of methods for quantification of drought tolerance in wheat. Crop Sci 32(3):723–728. https://doi.org/10.2135/cropsci1992.0011183X003200030029x


de Oliveira JP, Moreira WN Jr, Duarte JB, Chaves LJ, Pinheiro JB (2003) Genotype-environment interaction in maize hybrids: an application of the AMMI model. Crop Breed Appl Biotechnol. https://doi.org/10.12702/1984-7033.v03n03a02


Ebdon JS, Gauch HG Jr (2002) Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: I. Interpretation of genotype × environment interaction. Crop Sci 42(2):489–496. https://doi.org/10.2135/cropsci2002.4890


Ertiro BT, Beyene Y, Das B, Mugo S, Olsen M, Oikeh S et al (2017) Combining ability and testcross performance of drought tolerant maize inbred lines under stress and non-stress environments in Kenya. Plant Breed 136:197–205. https://doi.org/10.1111/pbr.12464


Farshadfar E, Sutka J (2003) Locating QTLs controlling adaptation in wheat using AMMI model. Cereal Res Commun 31:249–256. https://doi.org/10.1007/BF03543351


Gauch HG, Zobel RW (1996) AMMI analysis of yield trials. In: Kang MS, Gauch HG (eds) Genotype-by-environment interaction. CRC Press, Boca Raton, pp 85–122


Haruna A, Adu GB, Buah SS, Kanton RA, Kudzo AI, Seidu AM, Kwadwo OA (2017) Analysis of genotype by environment interaction for grain yield of intermediate maturing drought tolerant top-cross maize hybrids under rain-fed conditions. Cogent Food Agric 3(1):1333243. https://doi.org/10.1080/23311932.2017.1333243


Hongyu K, García-Peña M, de Araújo LB, dos Santos Dias CT (2014) Statistical analysis of yield trials by AMMI analysis of genotype × environment interaction. Biomet Lett 51(2):89–102. https://doi.org/10.2478/bile-2014-0007


ICAR-IIMR (2015) Vision 2050. Indian Institute of Maize Research. Indian Council of Agricultural Research, New Delhi


Kahram A, Khodarahmi M, Mohammadi A, Bihamta M, Ahmadi GH, Ghandi A, Abdi H (2013) Genotype × environment interaction analysis for grain yield of durum wheat new genotypes in the moderate region of Iran using AMMI model. World J Agric Res 9(3):298–304. https://doi.org/10.5829/idosi.wjas.2013.9.3.1735


Kivuva BM, Githiri SM, Yencho GC, Sibiya J (2014) Genotype x environment interaction for storage root yield in sweet potato under managed drought stress conditions. J Agric Sci 6(10):41–56. https://doi.org/10.5539/jas.v6n10pxx


Luan H, Shen H, Pan Y, Guo B, Lv C, Xu R (2018) Elucidating the hypoxic stress response in barley (Hordeum vulgare L.) during waterlogging: a proteomics approach. Sci Rep 8(1):1–13. https://doi.org/10.1038/s41598-018-27726-1


Mafouasson HNA, Gracen V, Yeboah MA, Ntsomboh-Ntsefong G, Tandzi LN, Mutengwa CS (2018) Genotype-by-environment interaction and yield stability of maize single cross hybrids developed from tropical inbred lines. Agronomy 8(5):62. https://doi.org/10.3390/agronomy8050062


Mebratu A, Wegary D, Mohammed W, Teklewold A, Tarekegne A (2019) Genotype × environment interaction of quality protein maize hybrids under contrasting management conditions in Eastern and Southern Africa. Crop Sci 59:1576–1589. https://doi.org/10.2135/cropsci2018.12.0722


Mohammadi R, Armion M, Sadeghzadeh D, Amri A, Nachit M (2013) Analysis of genotype-by-environment interaction for agronomic traits of durum wheat in Iran. Plant Prod Sci 14(1):15–21. https://doi.org/10.1626/pps.14.15


Ndhlela T, Herselman L, Magorokosho C, Setimela P, Mutimaamba C, Labuschagne M (2014) Genotype × environment interaction of maize grain yield using AMMI biplots. Crop Sci 54(5):1992–1999. https://doi.org/10.2135/cropsci2013.07.0448


Oyekunle M, Menkir A, Mani H, Olaoye G, Usman IS, Ado SG et al (2017) Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis. Cereal Res Commun 45(2):336–345. https://doi.org/10.1556/0806.44.2016.054


Pacheco A, Rodríguez F, Alvarado G, Burgueño J (2017) ADEL-R. analysis and design of experiments with R for Windows. Version 2.0", CIMMYT Research Data & Software Repository Network, V3R studio (2020). https://hdl.handle.net/11529/10857


Pour-Aboughadareh A, Yousefian M, Moradkhani H, Poczai P, Siddique KHM (2019) STABILITYSOFT: a new online program to calculate parametric and non- parametric stability statistics for crop traits. Appl Plant Sciences 7:e1211


Purchase JL (1997) Parametric analysis to describe GE interaction and yield stability in winter wheat. Dissertation, University of the Orange Free State


RStudio (2020) Integrated development for R. Rstudio Inc, Bostan


Sah RP, Chakraborty M, Prasad K, Pandit M, Tudu VK, Chakravarty MK, Narayan SC, Rana M, Moharana D (2020) Impact of water deficit stress in maize: phenology and yield components. Sci Rep 10:2944. https://doi.org/10.1038/s41598-020-59689-7


Shabala S (2011) Physiological and cellular aspects of phytotoxicity tolerance in plants: the role of membrane transporters and implications for crop breeding for waterlogging tolerance. New Phytol 190:289–298. https://doi.org/10.1111/j.1469-8137.2010.03575.x


Singamsetti A, Shahi JP, Zaidi PH, Seetharam K, Vinayan MT, Kumar M et al (2021) Genotype × environment interaction and selection of maize (Zea mays L.) hybrids across moisture regimes. Field Crops Res. 270:108224. https://doi.org/10.1016/j.fcr.2021.108224


Yan W, Cornelius PL, Crossa J, Hunt LA (2001) Two types of GGE biplots for analyzing multi-environment trial data. Crop Sci 41:656–663. https://doi.org/10.2135/cropsci2001.413656x


Zaidi PH, Vinayan MT, Seetharam K (2016) Phenotyping for abiotic stress tolerance in maize: waterlogging stress. A field manual. CIMMYT, Hyderabad


Zaman-Allah M, Zaidi PH, Trachsel S, Cairns JE, Vinayan MT, Seetharam K (2016) Phenotyping for abiotic stress tolerance in maize-Drought stress. A field manual. CIMMYT, Mexico


Zobel RW, Wright MG, Gauch HG (1988) Statistical analysis of a yield trial. Agron J 80:388–393. https://doi.org/10.2134/agronj1988.00021962008000030002x

 


Acknowledgements


Institute of Agricultural Sciences, Banaras Hindu University, Varanasi and CIMMYT-Asia, Hyderabad, India are gratefully acknowledged for providing necessary facilities, material, and financial grants to support this experiment. First author is grateful to the Project Coordinator, Climate Resilient Maize for Asia (CRMA), CIMMYT, Hyderabad for constant support and guidance during the preparation of manuscript.


Author Information


Singamsetti Ashok
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India
ashoks.setti10@bhu.ac.in
Shahi J. P.
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India


Zaidi P. H.
The International Maize and Wheat Improvement Center (CIMMYT)-Asia Maize Programme, ICRISAT Campus, Hyderabad, India


Seetharam K.
The International Maize and Wheat Improvement Center (CIMMYT)-Asia Maize Programme, ICRISAT Campus, Hyderabad, India


Madankar Kartik
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India

Kumar Munnesh
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India