Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
Shopping Cart: ( empty )
You are here: Home > Journals > CP > AR07281
RESEARCH ARTICLE
Contents Vol 59(6)

Genotype × environment interaction for wheat yield in different drought stress conditions and agronomic traits suitable for selection

Dejan Dodig A , Miroslav Zoric B , Desimir Knezevic B , Stephen R. King C and Gordana Surlan-Momirovic B D
+ Author Affiliations
- Author Affiliations

A Maize Research Institute, ‘Zemun Polje’, Slobodana Bajica 1, 11185 Belgrade-Zemun, Serbia.

B Institute of Field Crop Science, Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11080 Belgrade-Zemun, Serbia.

C Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-2133, USA.

D Corresponding author. Email: surlang@agrifaculty.bg.ac.yu

Australian Journal of Agricultural Research 59(6) 536-545 https://doi.org/10.1071/AR07281
Submitted: 26 July 2007  Accepted: 18 February 2008   Published: 10 June 2008

Abstract

Wheat cultivars grown in south-eastern Europe are exposed to variable rainfed environments. Climate change predictions indicate that the frequency of dry years will likely increase in the future. This study examined relationships among agronomic traits and some drought indices with grain yield as influenced by genotype and environment. In a 4-year experiment, 100 cultivars and landraces of bread wheat (Triticum aestivum L.) from different countries were tested under 3 watering regimes: fully irrigated, rainfed, and in a rain-out plot shelter. Three selection indices, mean productivity (MP), tolerance (TOL), and stress susceptibility index (SSI), were calculated based on grain yield in irrigated and drought-stressed conditions. The additive main effects and multiplicative interaction (AMMI) models were used to study the genotype × environment effects. Average yield reduction due to drought in the sheltered plots was 37.5%. High-yielding genotypes in each treatment showed high values of MP and high rank for SSI and, particularly, TOL. Conversely, low-yielding genotypes in each treatment had low values of MP and high drought tolerance according to SSI and TOL (i.e. low ranks). MP values were noted as being particularly well suited for predicting performance in this experiment. Total biomass and early vigour were found to be the most important agronomic traits for selecting high-yielding genotypes in a range of stress and non-stress conditions.

Additional keywords: multivariate analysis, yield stability.


Acknowledgments

We are grateful to Dr A. Navabi (University of Alberta, Canada) for critical reading of the manuscript and to Dr S. A. Quarrie (University of Newcastle, UK) for his valuble comments and constructive suggestions on the manuscript. DD thanks Dr S. Dencic (Institute of Field and Vegetable Crops, Serbia) for providing some of the wheat genotypes used in this study.


References


Blum A (1988) ‘Plant breeding for stress environments.’ (CRC Press: Boca Raton, FL)

Blum A (1996) Crop responses to drought and the interpretation of adaptation. Plant Growth Regulation 20, 135–148.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Borojevic S (1981) ‘Principles and methods of plant breeding.’ (Elsevier: Amsterdam)

Dodig D (2005) Evaluation of wheat genotypes for tolerance to drought. PhD Thesis, Belgrade University, Belgrade, Serbia [in Serbian].

Dragovic S , Stanojevic D , Aleksic V , Karagic Đ (1997) The intensity of drought in eastern Serbia and its effects on crop production. In ‘Proceedings of International Symposium: Drought and Plant Production’. (Eds S Jevtic, S Pekic) pp. 71–81. (ARI Serbia: Belgrade)

Evans LT (1998) ‘Feeding the ten billion: plants and population growth.’ (Cambridge University Press: Cambridge)

Fischer RA, Maurer R (1978) Drought resistance in spring wheat cultivars: I. Grain yield responses. Australian Journal of Agricultural Research 29, 897–912.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Gabriel KR (1971) The biplot—graphical display of matrices with applications to principal component analysis. Biometrika 58, 453–467.
| Crossref | GoogleScholarGoogle Scholar | open url image1

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

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

Hohls T (2001) Conditions under which selection for mean productivity, tolerance to environmental stress, or stability should be used to improve yield across a range of contrasting environments. Euphytica 120, 235–245.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Islam TM, Sedgley RH (1981) Evidence for a ‘uniculm effect’ in spring wheat (Triticum aestivum L.) in a Mediterranean environment. Euphytica 30, 277–284.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Jackson P, Robertson M, Cooper M, Hammer G (1996) The role of physiological understanding in plant breeding: from a breeding perspective. Field Crops Research 49, 11–39.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Kang MS (1993) Simultaneous selection for yield and stability in crop performance trials: consequences for growers. Agronomy Journal 85, 754–757. open url image1

Ludlow MM, Muchow RC (1990) A critical evaluation of traits for improving crop yields in water-limited environments. Advances in Agronomy 43, 107–153. open url image1

Panthuwan G, Fokai S, Cooper M, Rajatasereekul S, O’Toole JC (2002) Yield response of rice genotypes to different types of drought under rainfed lowlands: I. Grain yield and yield components. Field Crops Research 41, 45–54. open url image1

Pheloung PC, Siddique KHM (1991) Contribution of stem dry matter to grain yield in wheat cultivars. Australian Journal of Plant Physiology 18, 53–64. open url image1

Quarrie SA, Stojanovic J, Pekic S (1999) Improving drought resistance in small grained cereals: a case study, progress and prospects. Plant Growth Regulation 29, 1–21.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Reynolds M, Calderini D, Condon A, Vargas M (2007) Association of source/sink traits with yield, biomass and radiation use efficiency among random sister lines from three wheat crosses in a high-yield environment. The Journal of Agricultural Science 145, 3–16.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Rizza F, Badeckb FW, Cattivellia L, Lidestric O, Di Fonzoc N, Stanca AM (2004) Use of a water stress index to identify barley genotypes adapted to rainfed and irrigated conditions. Crop Science 44, 2127–2137. open url image1

Rosielle AA, Hamblin J (1981) Theoretical aspects of selection for yield in stress and non-stress enviroments. Crop Science 21, 943–946. open url image1

Saulescu NN , Ittu G , Balota M , Ittu M , Mustatea P (1998) Breeding wheat for lodging resistance, earliness and tolerance to abiotic stresses. In ‘Wheat: prospects for global improvement’. (Eds HJ Braun et al.) pp. 181–188. (Kluwer Academic Publishers: Dordrecht, The Netherlands)

Sio-Se Mardeh A, Ahmadi A, Poustini K, Mohammadi V (2006) Evaluation of drought resistance indices under various environmental conditions. Field Crops Research 98, 222–229.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Sudaric A, Simic D, Vrataric M (2006) Characterization of genotype by environment interactions in soybean breeding programmes of southeast Europe. Plant Breeding 125, 191–194.
| Crossref | GoogleScholarGoogle Scholar | open url image1

van Eeuwijk FA (1995) Linear and bilinear models for the analysis of multi-environment trials: I. An inventory of models. Euphytica 84, 1–7.
| Crossref | GoogleScholarGoogle Scholar | open url image1

van Ginkel M, Calhoun DS, Gebeyehu S, Miranda A, Tian-you C, Pargas Lara R, Trethowan RM, Sayre K, Crossa J, Rajaram S (1998) Plant traits related to yield of wheat in early, late, or continuous drought conditions. Euphytica 100, 109–121.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Vargas M, Crossa J, van Eeuwijk FA, Ramírez ME, Sayre K (1999) Using partial least squares regression, factorial regression, and AMMI models for interpreting genotype × environment interaction. Crop Science 39, 955–967. open url image1

Vermes L , Szemessy Á (Eds) (2000) ‘Proceedings of the central and eastern European workshop on drought mitigation.’ (RePRINT Studio Ltd.: Budapest, Hungary)

Waggoner PE (1993) Preparing for climate change. In ‘International crop science I’. pp. 239–245. (Crop Science Society of America: Madison, WI)

Whan BR, Carlton GP, Anderson WK (1991) Potential for increasing early vigour and total biomass in spring wheat. I. Identification of genetic improvements. Australian Journal of Agricultural Research 42, 347–361.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Wright GC , Rachaputi NC (2004) Drought and drought resistance. In ‘Encyclopedia of plant and crop science’. (Ed. RM Goodman) pp. 386–390. (Marcel Dekker, Inc.: New York)

Yan W (2002) Singular value partition for biplot analysis of multi-environment trial data. Agronomy Journal 94, 990–996. open url image1

Zobel RW (1990) A powerful statistical model for understanding genotype by environment interaction. In ‘Genotype by environment interaction and plant breeding’. (Ed. MS Kang) pp. 126–140. (Louisiana State University: Baton Rouge, FL)

Zobel RW, Wright MJ, Gauch HG (1988) Statistical analysis of a yield trial. Agronomy Journal 80, 388–393. open url image1