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RESEARCH ARTICLE

Biplot analysis for multi-environment trials of maize (Zea mays L.) hybrids in Iran

Saeed Safari Dolatabad A E , Rajab Choukan C , Eslam Majidi Hervan B and Hamid Dehghani D
+ Author Affiliations
- Author Affiliations

A Faculty of Agriculture, Roudhen Branch, Islamic Azad University (IAU), Tehran, Iran.

B Department of Plant Breeding, Sciences and Research Branch, Islamic Azad University (IAU), Tehran, Iran.

C Seed and Plant Improvement Institute, Karaj, Iran.

D Faculty of Agriculture, The University of Tarbiat Modares, Tehran, Iran.

E Corresponding author. Email: saied582000@yahoo.com

Crop and Pasture Science 61(9) 700-707 https://doi.org/10.1071/CP09325
Submitted: 14 November 2009  Accepted: 8 July 2010   Published: 9 September 2010

Abstract

Adapted maize (Zea mays L.) hybrids should be identified and chosen based on multi-environment trials analysing several traits. The objectives of this study were to identify mega-environments and suitable adapted maize hybrids based on both mean grain yield and grain yield stability and were to evaluate the 14 maize hybrids based on several desirable traits. Biplot analysis determined one mega-environment and two sectors that consist of one location in each sector for maize in Iran. The mega-environment included Kerman (KRM), Kermanshah (KSH), Moghan (MGN), Dezfol A (DZF A), Karaj (KRJ), Darab (DRB), Dezfol B (DZF B), Shiraz B (SHZ B), and Esfahan (ESF), where hybrid OSSK 602 was the best performing hybrid. The first sector included Khoramabad (KHM) where BC 678 was the best hybrid, and the second sector included Shiraz A (SHZ A) where ZP 599 was the hybrid with the highest performance. OSSK 602 was the best hybrid among all of the studied hybrids followed by ZP 677 and ZP 684. The genotype × trait biplot indicated that ZP 677 and OSSK 602 had greater thousand-kernel weight and grain number, whereas ZP 684 had longer day to maturity and larger cob diameter. KSC 700, KSC 704, and BC 678 had higher ear height and more days to tasseling than other hybrids. The genotype × trait biplot graphically displayed the interrelationships among traits and it was used in identifying hybrids that are good for some particular traits.

Additional keywords: genotype × environment, GGE biplot, GT biplot, grain yield, yield stability.


Acknowledgments

We would like to thank Dr B. Sorkhi, Assistant Professor, Seed and Plant Improvement Institute, Karaj, Iran for his technical assistance, for performing the GGE biplot analysis and for his suggestions. The authors would also like to thank Eng. Moeini, maize research officer for his kind assistance in recording data.


References


Allard RW, Bradshaw AD (1964) Implication of genotype × environmental interaction in applied plant breeding. Crop Science 4, 503–506.
Crossref | GoogleScholarGoogle Scholar | open url image1

Arshad M, Bakhsh A, Haqqani AM, Bashir M (2003) Genotype-environment interaction for grain yield in chickpea (Cicer arietinum L.). Pakistan Journal of Botany 35, 181–186. open url image1

Cirilo AG, Dardanelli J, Balzarini M, Andrade FH, Cantarero M, Luque S, Pedrol HM (2009) Morpho-physiological traits associated with maize crop adaptations to environments differing in nitrogen availability. Field Crops Research 113, 116–124.
Crossref | GoogleScholarGoogle Scholar | open url image1

Comstock RE , Moll PH (1963) Genotype-environment interaction. In ‘Symposium on Statistical Genetics and Plant Breeding’. NAS-NRC Publication 982. (Eds WD Hanson, HF Robinson) pp. 164–196. (National Academy of Science, National Research Council: Washington, DC)

Dehghani H, Ebadi A, Yousefi A (2006) Biplot analysis of genotype by environment interaction for barley yield in Iran. Agronomy Journal 98, 388–393.
Crossref | GoogleScholarGoogle Scholar | open url image1

Dehghani H, Sabaghnia N, Moghaddam M (2009) Interpretation of genotype-by-environment interaction for late maize hybrids’ grain yield using a biplot method. Turkish Journal of Agricultural and Forestry 33, 139–148. open url image1

Ebdon JS, Gauch HG (2002) Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: I. Interpretation of genotype × environment interaction. Crop Science 42, 489–496.
Crossref | GoogleScholarGoogle Scholar | open url image1

Fan XM, Kang MS, Zhang HY, Tan J, Xu C (2007) Yield stability of maize hybrids evaluated in multi-environment trials in Yunnan, China. Agronomy Journal 99, 220–228.
Crossref | GoogleScholarGoogle Scholar | open url image1

Flores F, Moreno MT, Cubero JI (1998) A comparison of univariate and multivariate methods to analyze G × E interaction. Field Crops Research 56, 271–286.
Crossref | GoogleScholarGoogle Scholar | open url image1

Fox PN, Rosielle AA (1982) Reducing the environmental main effects on pattern analysis of plant breeding environments. Euphytica 31, 645–656.
Crossref |
open url image1

Gauch HG (2006) Statistical analysis of yield trials by AMMI and GGE. Crop Science 46, 1488–1500.
Crossref |
open url image1

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

Gauch HG, Zobel RW (1997) Identifying mega-environments and targeting genotypes. Crop Science 37, 311–326.
Crossref | GoogleScholarGoogle Scholar | open url image1

Kang MS (1997) Using genotype-by-environment interaction for crop cultivar development. Advances in Agronomy 62, 199–252.
Crossref | GoogleScholarGoogle Scholar | open url image1

Kang MS (2004) Breeding: genotype by environment interaction. In ‘Encyclopedia of plant and crop science’. (Ed. RM Goodman) pp. 218–221. (Marcel Dekker: New York)

Kang MS, Aggarwal VD, Chirwa RM (2006) Adaptability and stability of bean cultivars as determined via yield stability statistic and GGE biplot analysis. Journal of Crop Improvement 15, 97–120.
Crossref | GoogleScholarGoogle Scholar | open url image1

Lee SJ, Yan W, Ahn JK, Chung IM (2003) Effects of year, site, genotype and their interactions on various soybean isoflavones. Field Crops Research 41, 1–12. open url image1

Lúquez JE, Aguirrezábal LAN, Agüero ME, Pereyra VR (2002) Stability and adaptability of cultivars in non-balanced yield trials: comparison of methods for selecting high oleic sunflower hybrids for grain yield and quality. Journal of Agronomy & Crop Science 188, 225–234.
Crossref | GoogleScholarGoogle Scholar | open url image1

Magari R, Kang MS (1993) Genotype selection via a new yield stability statistic in maize yield trials. Euphytica 70, 105–111.
Crossref | GoogleScholarGoogle Scholar | open url image1

Morris CF, Campbell KG, King GE (2004) Characterization of the end-use quality of soft wheat cultivars from the eastern and western US germplasm ‘pools’. Plant Genetic Resources 2, 59–69.
Crossref | GoogleScholarGoogle Scholar | open url image1

Sabaghnia N, Dehghani H, Sabaghpour SH (2006) Nonparametric methods for interpreting genotype × environment interaction of lentil genotypes. Crop Science 46, 1100–1106.
Crossref | GoogleScholarGoogle Scholar | open url image1

Samonte SOPB, Wilson LT, McClung AM, Medley JC (2005) Targeting cultivars onto rice growing environments using AMMI and SREG GGE biplot analyses. Crop Science 45, 2414–2424.
Crossref | GoogleScholarGoogle Scholar | open url image1

Setimela PS, Vivek B, Banziger M, Crossa J, Maideni F (2007) Evaluation of early to medium maturing open pollinated maize varieties in SADC region using GGE biplot based on the SREG model. Field Crops Research 103, 161–169.
Crossref | GoogleScholarGoogle Scholar | open url image1

Yan W (1999) Methodology of cultivar evaluation based on yield trial data with special reference to winter wheat in Ontario. PhD Dissertation, University of Guelph, Guelph, Ontario, Canada.

Yan W (2001) GGE biplot Windows application for graphical analysis of multienvironment trial data and other types of two-way data. Agronomy Journal 93, 1111–1118.
Crossref | GoogleScholarGoogle Scholar | open url image1

Yan W (2002) Singular value partitioning in biplot analysis of multienvironment trial data. Agronomy Journal 94, 990–996.
Crossref | GoogleScholarGoogle Scholar | open url image1

Yan W, Cornelius PL, Crossa J, Hunt LA (2001) Comparison of two types of GGE biplots for studying genotype by environment interaction. Crop Science 41, 656–663.
Crossref | GoogleScholarGoogle Scholar | open url image1

Yan W, Hunt LA, Sheng Q, Szlavnics Z (2000) Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40, 597–605.
Crossref | GoogleScholarGoogle Scholar | open url image1

Yan W , Kang MS (2003) ‘GGE biplot analysis: a graphical tool for breeders, geneticists, and agronomists.’ (CRC Press: Boca Raton, FL)

Yan W, Rajcan I (2002) Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science 42, 11–20.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Yan W, Tinker NA (2005) An integrated system of biplot analysis for displaying, interpreting, and exploring genotype by environment interactions. Crop Science 45, 1004–1016.
Crossref | GoogleScholarGoogle Scholar | open url image1