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RESEARCH ARTICLE

Genetic improvement of triticale for irrigated systems in south-eastern Australia: a study of genotype and genotype × environment interactions

Andrew Milgate A E , Ben Ovenden B , Dante Adorada A , Chris Lisle C , John Lacy B D and Neil Coombes A
+ Author Affiliations
- Author Affiliations

A NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Pine Gully Road, Wagga Wagga, NSW 2650, Australia.

B NSW Department of Primary Industries, Yanco Agricultural Institute, Trunk Road 80, Yanco, NSW 2703, Australia.

C School of Computing & Mathematics, Charles Sturt University, Locked Bag 588, Wagga Wagga, NSW 2678, Australia.

D Current address: John Lacy Consulting, PO Box 63, Finley, NSW 2713, Australia.

E Corresponding author. Email: andrew.milgate@dpi.nsw.gov.au

Crop and Pasture Science 66(8) 782-792 https://doi.org/10.1071/CP14357
Submitted: 17 December 2014  Accepted: 17 April 2015   Published: 31 July 2015

Abstract

Research into winter cereal breeding in Australia has focused primarily on studying the effects of rainfed environments. These studies typically show large genotype × environment (GE) interactions, and the complexity of these interactions acts as an impediment to the efficient selection of improved varieties. Wheat has been studied extensively; however, there are no published studies on the GE interactions of triticale in Australia under irrigated production systems. We conducted trials on 101 triticale genotypes at two locations over 4 years under intensive irrigated management practices and measured the yield potential, GE interactions, heritability and estimated genetic gain of yield, lodging resistance and several other traits important for breeding triticale. We found that high yield potential exceeding 10 t ha–1 exists in the Australian germplasm tested and that, in these irrigated trials, genotype accounted for a high proportion of the variability in all measured traits. All genetic parameters such as heritability and estimated genetic gain were high compared with rainfed studies. Breeding of triticale with improved yield and lodging resistance for irrigated environments is achievable and can be pursued with confidence in breeding programs.

Additional keywords: triticale, irrigation, yield, lodging, genotype × environment.


References

Akaike H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716–723.
A new look at the statistical model identification.Crossref | GoogleScholarGoogle Scholar |

Alheit KV, Busemeyer L, Liu WX, Maurer HP, Gowda M, Hahn V, Weissmann S, Ruckelshausen A, Reif JC, Wurschum T (2014) Multiple-line cross QTL mapping for biomass yield and plant height in triticale (x Triticosecale Wittmack). Theoretical and Applied Genetics 127, 251–260.
Multiple-line cross QTL mapping for biomass yield and plant height in triticale (x Triticosecale Wittmack).Crossref | GoogleScholarGoogle Scholar | 24173688PubMed |

Bassu S, Asseng S, Richards R (2011) Yield benefits of triticale traits for wheat under current and future climates. Field Crops Research 124, 14–24.
Yield benefits of triticale traits for wheat under current and future climates.Crossref | GoogleScholarGoogle Scholar |

Beauchet R, Berberi V, Corcos PO, Guimont-Montpetit G, Dion Y, Eudes F, Lavoie JM (2013) Fermentation of C6 carbohydrates from triticale straw hemicellulosic fraction as pretreatment for xylose purification. Industrial Crops and Products 51, 463–469.
Fermentation of C6 carbohydrates from triticale straw hemicellulosic fraction as pretreatment for xylose purification.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvVagsL%2FN&md5=a346db83c336c8f9e8a26c0a35796650CAS |

Biberdžić M, Jelić M, Deletić N, Barać S, Stojković S (2012) Effects of agroclimatic conditions at trial locations and fertilization on grain yield of triticale. Research Journal of Agricultural Science 44, 3–8.

Botwright Acuña T, Dean G, Riffkin P (2011) Constraints to achieving high potential yield of wheat in a temperate, high-rainfall environment in south-eastern Australia. Crop & Pasture Science 62, 125–136.
Constraints to achieving high potential yield of wheat in a temperate, high-rainfall environment in south-eastern Australia.Crossref | GoogleScholarGoogle Scholar |

Butler D, Cullis B, Gilmour A, Gogel B (2009) ‘ASReml-R reference manual.’ (Queensland Department of Primary Industries and Fisheries: Brisbane, Qld)

Chapman SC (2008) Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials. Euphytica 161, 195–208.
Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials.Crossref | GoogleScholarGoogle Scholar |

Coombes NE (2002) ‘The reactive tabu search for efficient correlated experimental designs.’ (John Moores University: Liverpool, UK)

Cooper M, Messina CD, Podlich D, Totir LR, Baumgarten A, Hausmann NJ, Wright D, Graham G (2014) Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction. Crop & Pasture Science 65, 311–336.
Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXotVKnsbk%3D&md5=f1c7fa3d58a49739707b52fd5f0e25ecCAS |

Cornish E (1950) The influence of rainfall on the yield of wheat in South Australia. Australian Journal of Biological Sciences 3, 178–218.

Cullis BR, Smith AB, Coombes NE (2006) On the design of early generation variety trials with correlated data. Journal of Agricultural, Biological & Environmental Statistics 11, 381–393.
On the design of early generation variety trials with correlated data.Crossref | GoogleScholarGoogle Scholar |

Cullis BR, Smith AB, Beeck CP, Cowling WA (2010) Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis. Genome 53, 1002–1016.
Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3cbmvFKgsw%3D%3D&md5=94d3c86b584a5819d12fe2ba1e18d984CAS | 21076516PubMed |

Dodig D, Zoric M, Knezevic D, King SR, Surlan-Momirovic G (2008) Genotype × environment interaction for wheat yield in different drought stress conditions and agronomic traits suitable for selection. Australian Journal of Agricultural Research 59, 536–545.
Genotype × environment interaction for wheat yield in different drought stress conditions and agronomic traits suitable for selection.Crossref | GoogleScholarGoogle Scholar |

Dogan R, Kacar O, Coplu N, Azkan N (2009) Characteristics of new breeding lines of triticale. African Journal of Agricultural Research 4, 133–138.

Dogan R, Kacar O, Goksu E, Azkan N (2011) Evaluation of triticale genotypes in terms of yield stability for the southern Marmara region. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 39, 249–253.

Estrada-Campuzano G, Slafer GA, Miralles DJ (2012) Differences in yield, biomass and their components between triticale and wheat grown under contrasting water and nitrogen environments. Field Crops Research 128, 167–179.
Differences in yield, biomass and their components between triticale and wheat grown under contrasting water and nitrogen environments.Crossref | GoogleScholarGoogle Scholar |

Falconer DS, Mackay TFC (1996) ‘Introduction to quantitative genetics.’ 4th edn (Longmann Group Ltd: Harlow, UK)

Farshadfar E, Mohammadi R, Aghaee M, Vaisi Z (2012) GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. Australian Journal of Crop Science 6, 1074–1079.

Fufa H, Baenziger OS, Beecher BS, Graybosch RA, Eskridge KM, Nelson LA (2005) Genetic improvement trends in agronomic performances and end-use quality characteristics among hard red winter wheat cultivars in Nebraska. Euphytica 144, 187–198.
Genetic improvement trends in agronomic performances and end-use quality characteristics among hard red winter wheat cultivars in Nebraska.Crossref | GoogleScholarGoogle Scholar |

Gilmour AR, Cullis BR, Verbyla AP (1997) Accounting for natural and extraneous variation in the analysis of field experiments. Journal of Agricultural, Biological & Environmental Statistics 2, 269–293.
Accounting for natural and extraneous variation in the analysis of field experiments.Crossref | GoogleScholarGoogle Scholar |

Goodchild N, Boyd W (1975) Regional and temporal variations in wheat yield in Western Australia and their implications in plant breeding. Australian Journal of Agricultural Research 26, 209–217.
Regional and temporal variations in wheat yield in Western Australia and their implications in plant breeding.Crossref | GoogleScholarGoogle Scholar |

Gowda M, Hahn V, Reif JC, Longin CFH, Alheit K, Maurer HP (2011) Potential for simultaneous improvement of grain and biomass yield in Central European winter triticale germplasm. Field Crops Research 121, 153–157.
Potential for simultaneous improvement of grain and biomass yield in Central European winter triticale germplasm.Crossref | GoogleScholarGoogle Scholar |

Gowda M, Zhao YS, Maurer HP, Weissmann EA, Wuerschum T, Reif JC (2013) Best linear unbiased prediction of triticale hybrid performance. Euphytica 191, 223–230.
Best linear unbiased prediction of triticale hybrid performance.Crossref | GoogleScholarGoogle Scholar |

Goyal A, Beres BL, Randhawa HS, Navabi A, Salmon DF, Eudes F (2011) Yield stability analysis of broadly adaptive triticale germplasm in southern and central Alberta, Canada, for industrial end-use suitability. Canadian Journal of Plant Science 91, 125–135.
Yield stability analysis of broadly adaptive triticale germplasm in southern and central Alberta, Canada, for industrial end-use suitability.Crossref | GoogleScholarGoogle Scholar |

Graybosch RA, Peterson CJ (2012) Specific adaptation and genetic progress for grain yield in Great Plains hard winter wheats from 1987 to 2010. Crop Science 52, 631–643.
Specific adaptation and genetic progress for grain yield in Great Plains hard winter wheats from 1987 to 2010.Crossref | GoogleScholarGoogle Scholar |

Hou X, Jia Z, Han Q, Li R, Wang W, Li Y (2011) Effects of rotational tillage practices on soil water characteristics and crop yields in semi-arid areas of north-west China. Soil Research 49, 625–632.
Effects of rotational tillage practices on soil water characteristics and crop yields in semi-arid areas of north-west China.Crossref | GoogleScholarGoogle Scholar |

Hristov N, Mladenov N, Djuric V, Kondic-spika A, Marjanovic-jeromela A, Simic D (2010) Genotype by environment interactions in wheat quality breeding programs in southeast Europe. Euphytica 174, 315–324.
Genotype by environment interactions in wheat quality breeding programs in southeast Europe.Crossref | GoogleScholarGoogle Scholar |

Karimizadeh R, Mohammadi M, Sabaghnia N, Shefazadeh MK, Pouralhossini J (2012) Univariate stability analysis methods for determining genotype × environment interaction of durum wheat grain yield. African Journal of Biotechnology 11, 2563–2573.

Krenzer EG, Thompson JD, Carver BF (1992) Partitioning of genotype × environment interactions of winter wheat forage yield. Crop Science 32, 1143–1147.
Partitioning of genotype × environment interactions of winter wheat forage yield.Crossref | GoogleScholarGoogle Scholar |

Lacy J (2011) Cropcheck: Farmer benchmarking participatory model to improve productivity. Agricultural Systems 104, 562–571.
Cropcheck: Farmer benchmarking participatory model to improve productivity.Crossref | GoogleScholarGoogle Scholar |

McGoverin CM, Snyders F, Muller N, Botes W, Fox G, Manley M (2011) A review of triticale uses and the effect of growth environment on grain quality. Journal of the Science of Food and Agriculture 91, 1155–1165.
A review of triticale uses and the effect of growth environment on grain quality.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXkt12hu7w%3D&md5=d5631c412ebbd42eb6995576f65c6ba0CAS | 21433010PubMed |

Mohammadi R, Amri A, Haghparast R, Sadeghzadeh D, Armion M, Ahmadi MM (2009) Pattern analysis of genotype-by-environment interaction for grain yield in durum wheat. The Journal of Agricultural Science 147, 537–545.
Pattern analysis of genotype-by-environment interaction for grain yield in durum wheat.Crossref | GoogleScholarGoogle Scholar |

Mohammadi R, Haghparast R, Amri A, Ceccarelli S (2010a) Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials. Crop & Pasture Science 61, 92–101.
Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials.Crossref | GoogleScholarGoogle Scholar |

Mohammadi R, Roustaii M, Haghparast R, Roohi E, Solimani K, Ahmadi MM, Abedi GR, Amri A (2010b) Genotype × environment interactions for grain yield in rainfed winter wheat multi-environment trials in Iran. Agronomy Journal 102, 1500–1510.
Genotype × environment interactions for grain yield in rainfed winter wheat multi-environment trials in Iran.Crossref | GoogleScholarGoogle Scholar |

Moreno-Gonzalez J, Crossa J (1998) Combining genotype, environment and attribute variables in regression models for predicting the cell-means of multi-environment cultivar trials. Theoretical and Applied Genetics 96, 803–811.
Combining genotype, environment and attribute variables in regression models for predicting the cell-means of multi-environment cultivar trials.Crossref | GoogleScholarGoogle Scholar |

Motzo R, Giunta F, Deidda M (2001) Factors affecting the genotype x environment interaction in spring triticale grown in a Mediterranean environment. Euphytica 121, 317–324.
Factors affecting the genotype x environment interaction in spring triticale grown in a Mediterranean environment.Crossref | GoogleScholarGoogle Scholar |

Mühleisen J, Reif JC, Maurer HP, Mohring J, Piepho HP (2013) Visual scorings of drought stress intensity as covariates for improved variety trial analysis. Journal of Agronomy & Crop Science 199, 321–330.
Visual scorings of drought stress intensity as covariates for improved variety trial analysis.Crossref | GoogleScholarGoogle Scholar |

Mühleisen J, Piepho HP, Maurer HP, Longin CFH, Reif JC (2014) Yield stability of hybrids versus lines in wheat, barley, and triticale. Theoretical and Applied Genetics 127, 309–316.
Yield stability of hybrids versus lines in wheat, barley, and triticale.Crossref | GoogleScholarGoogle Scholar | 24162154PubMed |

R Development Core Team (2012) ‘R: A language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna)

Rane J, Pannu RK, Sohu VS, Saini RS, Mishra B, Shoran J, Crossa J, Vargas M, Joshi AK (2007) Performance of yield and stability of advanced wheat genotypes under heat stress environments of the Indo-Gangetic plains. Crop Science 47, 1561–1573.
Performance of yield and stability of advanced wheat genotypes under heat stress environments of the Indo-Gangetic plains.Crossref | GoogleScholarGoogle Scholar |

Reynolds MP, Trethowan R, Crossa J, Vargas M, Sayre KD (2002) Physiological factors associated with genotype by environment interaction in wheat. Field Crops Research 75, 139–160.
Physiological factors associated with genotype by environment interaction in wheat.Crossref | GoogleScholarGoogle Scholar |

Richards RA, Rebetzke GJ, Condon AG, van Herwaarden AF (2002) Breeding opportunities for increasing the efficiency of water use and crop yield in temperate cereals. Crop Science 42, 111–121.
Breeding opportunities for increasing the efficiency of water use and crop yield in temperate cereals.Crossref | GoogleScholarGoogle Scholar | 11756261PubMed |

Roozeboom KL, Schapaugh WT, Tuinstra MR, Vanderlip RL, Milliken GA (2008) Testing wheat in variable environments: genotype, environment, interaction effects, and grouping test locations. Crop Science 48, 317–330.
Testing wheat in variable environments: genotype, environment, interaction effects, and grouping test locations.Crossref | GoogleScholarGoogle Scholar |

Santiveri F, Royo C, Romagosa I (2004) Growth and yield responses of spring and winter triticale cultivated under Mediterranean conditions. European Journal of Agronomy 20, 281–292.
Growth and yield responses of spring and winter triticale cultivated under Mediterranean conditions.Crossref | GoogleScholarGoogle Scholar |

Saunders, R (2010) ‘2009 field crop variety evaluation.’ Mallee Sustainable Farming 2009 Research Compendium. pp. 65–72. (Mallee Sustainable Farming Inc.: Mildura, Vic.)

Sissons M, Ovenden B, Adorada D, Milgate A (2014) Durum wheat quality in high-input irrigation systems in south-eastern Australia. Crop & Pasture Science 65, 411–422.
Durum wheat quality in high-input irrigation systems in south-eastern Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXpvV2rtLk%3D&md5=2b5d1b2e807d86bbb5c0935cc0a37fedCAS |

Smith A, Cullis B, Thompson R (2001) Analyzing variety by environment data using mulitplicative mixed models and adjustments for spatial field trend. Biometrics 57, 1138–1147.

Smith AB, Ganesalingam A, Kuchel H, Cullis BR (2015) Factor analytic mixed models for the provision of grower information from national crop variety testing programs. Theoretical and Applied Genetics 128, 55–72.
Factor analytic mixed models for the provision of grower information from national crop variety testing programs.Crossref | GoogleScholarGoogle Scholar | 25326722PubMed |

Sutton B, Dubbelde E (1980) Effects of water deficit on yield of wheat and triticale. Australian Journal of Experimental Agriculture 20, 594–598.
Effects of water deficit on yield of wheat and triticale.Crossref | GoogleScholarGoogle Scholar |

Toohey DE (2006) ‘Irrigated grain crops—a scoping study of southern Murray–Darling basin.’ (Dennis E Toohey and Associates: Albury, NSW)

Trethowan RM, Mahmood T, Ali Z, Oldach K, Garcia AG (2012) Breeding wheat cultivars better adapted to conservation agriculture. Field Crops Research 132, 76–83.
Breeding wheat cultivars better adapted to conservation agriculture.Crossref | GoogleScholarGoogle Scholar |

Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Research 14, 415–421.
A decimal code for the growth stages of cereals.Crossref | GoogleScholarGoogle Scholar |