Theoretical and Applied Genetics

, Volume 125, Issue 1, pp 71–90 | Cite as

Quantitative trait loci for water-use efficiency in barley (Hordeum vulgare L.) measured by carbon isotope discrimination under rain-fed conditions on the Canadian Prairies

Original Paper

Abstract

Barley (Hordeum vulgare L.) yield is commonly limited by low rainfall and high temperature during the growing season on the Canadian Prairies. Empirical knowledge suggests that carbon isotope discrimination (Δ13C), through its negative relationship with water-use efficiency (WUE), is a good index for selecting stable yielding crops in some rain-fed environments. Identification of quantitative trait loci (QTL) and linked markers for Δ13C will enhance its use efficiency in breeding programs. In the present study, two barley populations (W89001002003 × I60049 or W × I, six-row type, and Merit × H93174006 or M × H, two-row type), containing 200 and 127 recombinant inbred lines (RILs), were phenotyped for leaf Δ13C and agronomic traits under rain-fed environments in Alberta, Canada. A transgressive segregation pattern for leaf Δ13C was observed among RILs. The broad-sense heritability (H2) of leaf Δ13C was 0.8, and there was no significant interaction between genotype and environment for leaf Δ13C in the W × I RILs. A total of 12 QTL for leaf Δ13C were detected in the W × I RILs and 5 QTL in the M × H RILs. For the W × I RILs, a major QTL located on chromosome 3H near marker Bmag606 (9.3, 9.4 and 10.7 cM interval) was identified. This major QTL overlapped with several agronomic traits, with W89001002003 alleles favoring lower leaf Δ13C, increased plant height, and reduced leaf area index, grain yield, harvest index and days to maturity at this locus or loci. This major QTL and its associated marker, when validated, maybe useful in breeding programs aimed at improving WUE and yield stability of barley on the Canadian Prairies.

References

  1. AgroClimatic Information Service (ACIS) (2009) http://www1.agric.gov.ab.ca/$department/deptdocs.nsf/all/cl12944. Agriculture and Rural Development, Government of Alberta
  2. Anyia AO, Slaski JJ, Nyachiro JM, Archambault DJ, Juskiw P (2007) Relationship of carbon isotope discrimination to water use efficiency and productivity of barley under field and greenhouse conditions. J Agron Crop Sci 193:313–323CrossRefGoogle Scholar
  3. Anyia AO, Slaski JJ, Capo-Chichi L, Chen J, Chang SX (2008) Physiological traits contributing to water productivity and yield stability of barley on the Canadian Prairies. In: The 5th International Crop Science Congress, Jeju Island, South Korea. April 13–18Google Scholar
  4. Araus JL, Amaro T, Casadesús J, Asbati A, Nachit MM (1998) Relationships between ash content, carbon isotope discrimination and yield in durum wheat. Aust J Plant Physiol 25:835–842CrossRefGoogle Scholar
  5. Araus JL, Villegas D, Aparicio N, García del Moral LF, El Hani S, Rharrabti Y, Ferrio JP, Royo C (2003) Environmental factors determining carbon isotope discrimination and yield in durum wheat under Mediterranean conditions. Crop Sci 43:170–180CrossRefGoogle Scholar
  6. Baum M, Von Korff M, Guo P, Lakew B, Hamwieh A, Lababidi S, Udupa SM, Sayed H, Choumane W, Grando S, Ceccarelli S (2007) Molecular approaches and breeding strategies for drought tolerance in barley. In: Varshney R, Tuberosa R (eds) Genomics-assisted crop improvement, vol 2: genomics applications in crops. Springer, Dordrecht, pp 51–79Google Scholar
  7. Bloch D, Hoffmann CM, Märländer B (2006) Impact of water supply on photosynthesis, water use and carbon isotope discrimination of sugar beet genotypes. Eur J Agron 24:218–225CrossRefGoogle Scholar
  8. Bonsal BR, Zhang X, Hogg WD (1999) Canadian Prairie growing season precipitation variability and associated atmospheric circulation. Clim Res 11:191–208CrossRefGoogle Scholar
  9. Canadian International Grains Institute (CIGI) (2004) Canada: crop production, consumption and exports. In: Agriculture and Agri-Food Canada Market Analysis Division (ed) Grains and oilseed textbook, 5th edn.Google Scholar
  10. Cattivelli L, Rizza F, Badeck F-W, Mazzucotelli E, Mastrangelo AM, Francia E, Marè C, Tondelli A, Stanca AM (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. Field Crops Res 105:1–14CrossRefGoogle Scholar
  11. Chaabane R, Felah ME, Salah HB, Naceur MBB, Abdelly C, Ramla D, Nada A, Saker M (2009) Molecular characterization of Tunisian barley (Hordeum vulgare L.) genotypes using microsatellites (SSRs) markers. Eur J Sci Res 36:6–15Google Scholar
  12. Chakravartia AK (1972) The June–July precipitation pattern in the Prairie Provinces of Canada. J Geogr 71:155–160CrossRefGoogle Scholar
  13. Chen J, Chang SX, Anyia AO (2011) The physiology and stability of leaf carbon isotope discrimination as a measure of water-use efficiency in barley on the Canadian Prairies. J Agron Crop Sci 197:1–11CrossRefGoogle Scholar
  14. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971PubMedGoogle Scholar
  15. Condon AG, Richards RA (1992) Broad sense heritability and genotype × environment interaction for carbon isotope discrimination in field-grown wheat. Aust J Agric Res 43:921–934CrossRefGoogle Scholar
  16. Condon AG, Richards RA, Farquhar GD (1987) Carbon isotope discrimination is positively correlated with grain yield and dry matter production in field-grown wheat. Crop Sci 27:996–1001CrossRefGoogle Scholar
  17. Condon A, Richards R, Farquhar G (1992) The effect of variation in soil water availability, vapour pressure deficit and nitrogen nutrition on carbon isotope discrimination in wheat. Aust J Agric Res 43:935–947CrossRefGoogle Scholar
  18. Condon AG, Richards RA, Farquhar GD (1993) Relationships between carbon isotope discrimination, water use efficiency and transpiration efficiency for dryland wheat. Aust J Agric Res 44:1693–1711CrossRefGoogle Scholar
  19. Condon AG, Richards RA, Rebetzke GJ, Farquhar GD (2002) Improving intrinsic water-use efficiency and crop yield. Crop Sci 42:122–131PubMedCrossRefGoogle Scholar
  20. Craufurd PQ, Austin RB, Acevedo E, Hall MA (1991) Carbon isotope discrimination and grain-yield in barley. Field Crops Res 27:301–313CrossRefGoogle Scholar
  21. Dale RF, Coelho DT, Gallo KP (1980) Prediction of daily green leaf area index for corn. Agron J 72:999–1005CrossRefGoogle Scholar
  22. Diab AA, Teulat-Merah B, This D, Ozturk NZ, Benscher D, Sorrells ME (2004) Identification of drought-inducible genes and differentially expressed sequence tags in barley. Theor Appl Genet 109:1417–1425PubMedCrossRefGoogle Scholar
  23. Ehdaie B, Waines JG (1994) Genetic analysis of carbon isotope discrimination and agronomic characters in a bread wheat cross. Theor Appl Genet 88:1023–1028CrossRefGoogle Scholar
  24. Ehleringer JR (1990) Correlations between carbon isotope discrimination and leaf conductance to water vapor in common beans. Plant Physiol 93:1422–1425PubMedCrossRefGoogle Scholar
  25. Ellis RP, Forster BP, Waugh R, Bonar N, Handley LL, Robinson D, Gordon DC, Powell W (1997) Mapping physiological traits in barley. New Phytol 137:149–157CrossRefGoogle Scholar
  26. Ellis RP, Forster BP, Gordon DC, Handley LL, Keith RP, Lawrence P, Meyer R, Powell W, Robinson D, Scrimgeour CM, Young G, Thomas WTB (2002) Phenotype/genotype associations for yield and salt tolerance in a barley mapping population segregating for two dwarfing genes. J Exp Bot 53:1163–1176PubMedCrossRefGoogle Scholar
  27. Environment Canada (2009) http://www.climate.weatheroffice.gc.ca. National Climate Data and Information Archive
  28. FAOSTAT (2008) Food and Agricultural Organization (FAO). http://faostat.fao.org/site/291/default.aspx
  29. Farquhar GD, Richards RA (1984) Isotopic composition of plant carbon correlates with water-use efficiency of wheat genotypes. Aust J Plant Physiol 11:539–552CrossRefGoogle Scholar
  30. Farquhar GD, O’Leary MH, Berry JA (1982) On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Aust J Plant Physiol 9:121–137CrossRefGoogle Scholar
  31. Farquhar GD, Ehleringer JR, Hubick KT (1989) Carbon isotope discrimination and photosynthesis. Annu Rev Plant Physiol Plant Mol Biol 40:503–537CrossRefGoogle Scholar
  32. Flint-Garcia SA, Jampatong C, Darrah LL, Mcmullen MD (2003) Quantitative trait locus analysis of stalk strength in four maize populations. Crop Sci 43:13–22CrossRefGoogle Scholar
  33. Forster BP, Ellis RP, Moir J, Talamè V, Sanguineti MC, Tuberosa R, This D, Teulat-Merah B, Ahmed I, Mariy SAEE, Bahri H, El Ouahabi M, Zoumarou-Wallis N, El-Fellah M, Salem MB (2004) Genotype and phenotype associations with drought tolerance in barley tested in North Africa. Ann Appl Biol 144:157–168CrossRefGoogle Scholar
  34. Hall AE, Mutters RG, Hubick KT, Farquhar GD (1990) Genotypic differences in carbon isotope discrimination by cowpea under wet and dry field conditions. Crop Sci 30:300–305CrossRefGoogle Scholar
  35. Handley LL, Nevo E, Raven JA, Carrasco RM, Scrimgeour CM, Pakniyat H, Forster BP (1994) Chromosome 4 controls potential water use efficiency (13C) in barley. J Exp Bot 45:1661–1663CrossRefGoogle Scholar
  36. Hanson CH, Robinson HF, Comstock RE (1956) Biometrical studies of yield in segregating populations of Korean Lespedeza. Agron J 48:268–272CrossRefGoogle Scholar
  37. Hausmann NJ, Juenger TE, Sen S, Stowe K, Dawson TE, Simms EL (2005) Quantitative trait loci affecting δ13C and response to differential water availability in Arabidopsis thaliana. Evolution 59:81–96PubMedGoogle Scholar
  38. Hubick KT, Shorter R, Farquhar GD (1988) Heritability and genotype × environment interactions of carbon isotope discrimination and transpiration efficiency in peanut (Arachis hypogaea L.). Aust J Plant Physiol 15:799–813CrossRefGoogle Scholar
  39. IPCC (2007) Climate change 2007: impacts, adaptation and vulnerability: contribution of Working Group II to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University PressGoogle Scholar
  40. Ivlev AA, Voronin VI (2007) The mechanism of carbon isotope fractionation in photosynthesis and carbon dioxide component of the greenhouse effect. Biol Bull Russ Acad Sci 34:603–609CrossRefGoogle Scholar
  41. Jiang QZ, Roche D, Hole DJ (2006) Carbon isotope discrimination of two-rowed and six-rowed barley genotypes under irrigated and non-irrigated field conditions. Can J Plant Sci 86:433–441CrossRefGoogle Scholar
  42. Johnson DA, Rumbaugh MD (1995) Genetic variation and inheritance characteristics for carbon isotope discrimination in Alfalfa. J Range Manage 48:126–131CrossRefGoogle Scholar
  43. Juenger TE, McKay JK, Hausmann N, Keurentjes JJB, Sen S, Stowe KA, Dawson TE, Simms EL, Richards JH (2005) Identification and characterization of QTL underlying whole-plant physiology in Arabidopsis thaliana: δ13C, stomatal conductance and transpiration efficiency. Plant Cell Environ 28:697–708CrossRefGoogle Scholar
  44. Karakousis A, Gustafson JP, Chalmers KJ, Barr AR, Langridge P (2003) A consensus map of barley integrating SSR, RFLP, and AFLP markers. Aust J Agric Res 54:1173–1185CrossRefGoogle Scholar
  45. Kondo M, Pablico P, Aragones D, Agbisit R (2004) Genotypic variations in carbon isotope discrimination, transpiration efficiency, and biomass production in rice as affected by soil water conditions and N. Plant Soil 267:165–177CrossRefGoogle Scholar
  46. Lambrides CJ, Chapman SC, Shorter R (2004) Genetic variation for carbon isotope discrimination in sunflower: association with transpiration efficiency and evidence for cytoplasmic inheritance. Crop Sci 44:1642–1653CrossRefGoogle Scholar
  47. Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln SE, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181PubMedCrossRefGoogle Scholar
  48. Laza MR, Kondo M, Ideta O, Barlaan E, Imbe T (2006) Identification of quantitative trait loci for 13C and productivity in irrigated lowland rice. Crop Sci 46:763–773CrossRefGoogle Scholar
  49. Li JZ, Sjakste TG, Röder MS, Ganal MW (2003) Development and genetic mapping of 127 new microsatellite markers in barley. Theor Appl Genet 107:1021–1027PubMedCrossRefGoogle Scholar
  50. Li-Cor (1992) LAI-2000 plant canopy analyzer operating manual. Li-Cor Inc., Lincoln, NE, USAGoogle Scholar
  51. Liu ZW, Biyashev RM, Saghai Maroof MA (1996) Development of simple sequence repeat DNA markers and their integration into a barley linkage map. Theor Appl Genet 93:869–876CrossRefGoogle Scholar
  52. Martin B, Nienhuis J (1989) Restriction fragment length polymorphisms associated with water use efficiency in tomato. Science 243:1725–1728PubMedCrossRefGoogle Scholar
  53. Merah O, Deléens E, Monneveux P (1999) Grain yield, carbon isotope discrimination, mineral and silicon content in durum wheat under different precipitation regimes. Physiol Plant 107:387–394CrossRefGoogle Scholar
  54. Merah O, Monneveux P, Deléens E (2001) Relationships between flag leaf carbon isotope discrimination and several morpho-physiological traits in durum wheat genotypes under Mediterranean conditions. Environ Exp Bot 45:63–71PubMedCrossRefGoogle Scholar
  55. Monneveux P, Reynolds MP, Trethowan R, González-Santoyo H, Peña RJ, Zapata F (2005) Relationship between grain yield and carbon isotope discrimination in bread wheat under four water regimes. Eur J Agron 22:231–242CrossRefGoogle Scholar
  56. Monneveux P, Rekika D, Acevedo E, Merah O (2006) Effect of drought on leaf gas exchange, carbon isotope discrimination, transpiration efficiency and productivity in field grown durum wheat genotypes. Plant Sci 170:867–872CrossRefGoogle Scholar
  57. Morgan JA, LeCain DR, McCaig TN, Quick JS (1993) Gas exchange, carbon isotope discrimination, and productivity in winter wheat. Crop Sci 33:178–186CrossRefGoogle Scholar
  58. Price AH, Cairns JE, Horton P, Jones HG, Griffiths H (2002) Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses. J Exp Bot 53:989–1004PubMedCrossRefGoogle Scholar
  59. Ramsay L, Macaulay M, degli Ivanissevich S, MacLean K, Cardle L, Fuller J, Edwards KJ, Tuvesson S, Morgante M, Massari A, Maestri E, Marmiroli N, Sjakste T, Ganal M, Powell W, Waugh R (2000) A simple sequence repeat-based linkage map of barley. Genetics 156:1997–2005PubMedGoogle Scholar
  60. Rebetzke GJ, Condon AG, Richards RA, Farquhar GD (2002) Selection for reduced carbon isotope discrimination increases aerial biomass and grain yield of rain-fed bread wheat. Crop Sci 42:739–745CrossRefGoogle Scholar
  61. Rebetzke GJ, Condon AG, Richards RA, Farquhar GD (2003) Gene action for leaf conductance in three wheat crosses. Aust J Agric Res 54:381–387CrossRefGoogle Scholar
  62. Rebetzke GJ, Richards RA, Condon AG, Farquhar GD (2006) Inheritance of carbon isotope discrimination in bread wheat (Triticum Aestivum L.). Euphytica 150:97–106CrossRefGoogle Scholar
  63. Rebetzke GJ, Condon AG, Farquhar GD, Appels R, Richards RA (2008) Quantitative trait loci for carbon isotope discrimination are repeatable across environments and wheat mapping populations. Theor Appl Genet 118:123–137PubMedCrossRefGoogle Scholar
  64. Richards RA (1996) Defining selection criteria to improve yield under drought. Plant Growth Regul 20:157–166CrossRefGoogle Scholar
  65. 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 Sci 42:111–121PubMedCrossRefGoogle Scholar
  66. Röder MS, Plaschke J, König SU, Börner A, Sorrells ME, Tanksley SD, Ganal MW (1995) Abundance, variability and chromosomal location of microsatellites in wheat. Mol Gen Genet 246:327–333PubMedCrossRefGoogle Scholar
  67. Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW (1984) Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci USA 81:8014–8018PubMedCrossRefGoogle Scholar
  68. Saranga Y, Menz M, Jiang C, Wright RJ, Yakir D, Paterson AH (2001) Genomic dissection of genotype × environment interactions conferring adaptation of cotton to arid conditions. Genome Res 11:1988–1995PubMedCrossRefGoogle Scholar
  69. Sayrea KD, Acevedob E, Austinc RB (1995) Carbon isotope discrimination and grain yield for three bread wheat germplasm groups grown at different levels of water stress. Field Crops Res 41:45–54CrossRefGoogle Scholar
  70. Sicher R (1993) Assimilate partitioning within leaves of small grain cereals. In: Abrol YP, Mohanty P, Govindjee (eds) Photosynthesis: photoreactions to plant productivity. Kluwer, Dordrecht, pp 351–360CrossRefGoogle Scholar
  71. Specht JE, Chase K, Macrander M, Graef GL, Chung J, Markwell JP, Germann M, Orf JH, Lark KG (2001) Soybean response to water—a QTL analysis of drought tolerance. Crop Sci 41:493–509CrossRefGoogle Scholar
  72. Stiller WN, Read JJ, Constable GA, Reid PE (2005) Selection for water use efficiency traits in a cotton breeding program: cultivar differences. Crop Sci 45:1107–1113CrossRefGoogle Scholar
  73. Takai T, Fukuta Y, Sugimoto A, Shiraiwa T, Horie T (2006) Mapping of QTLs controlling carbon isotope discrimination in the photosynthetic system using recombinant inbred lines derived from a cross between two different rice (Oryza sativa L.) cultivars. Plant Prod Sci 9:271–280CrossRefGoogle Scholar
  74. Takai T, Ohsumi A, San-oh Y, Laza MRC, Kondo M, Yamamoto T, Yano M (2009) Detection of a quantitative trait locus controlling carbon isotope discrimination and its contribution to stomatal conductance in japonica rice. Theor Appl Genet 118:1401–1410PubMedCrossRefGoogle Scholar
  75. Tanksley SD (1993) Mapping polygenes. Annu Rev Genet 27:205–233PubMedCrossRefGoogle Scholar
  76. Teulat B, Borries C, This D (2001a) New QTLs identified for plant water status, water-soluble carbohydrate and osmotic adjustment in a barley population grown in a growth-chamber under two water regimes. Theor Appl Genet 103:161–170CrossRefGoogle Scholar
  77. Teulat B, Merah O, Souyris I, This D (2001b) QTLs for agronomic traits from a Mediterranean barley progeny grown in several environments. Theor Appl Genet 103:774–787CrossRefGoogle Scholar
  78. Teulat B, Merah O, This D (2001c) Carbon isotope discrimination and productivity in field-grown barley genotypes. J Agron Crop Sci 187:33–39CrossRefGoogle Scholar
  79. Teulat B, Merah O, Sirault X, Borries C, Waugh R, This D (2002) QTLs for grain carbon isotope discrimination in field-grown barley. Theor Appl Genet 106:118–126PubMedGoogle Scholar
  80. Thiel T, Michalek W, Varshney R, Graner A (2003) Exploiting EST databases for the development of cDNA derived microsatellite markers in barley (Hordeum vulgare L.). Theor Appl Genet 106:411–422PubMedGoogle Scholar
  81. This D, Comstock J, Courtois B, Xu Y, Ahmadi N, Vonhof WM, Fleet C, Setter T, McCouch S (2010) Genetic analysis of water use efficiency in rice (Oryza sativa L.) at the leaf level. Rice 3:72–86CrossRefGoogle Scholar
  82. Thorne GN (1965) Photosynthesis of ears and flag leaves of wheat and barley. Ann Bot 29:317–329Google Scholar
  83. Varshney RK, Marcel TC, Ramsay L, Russell J, Röder MS, Stein N, Waugh R, Langridge P, Niks RE, Graner A (2007) A high density barley microsatellite consensus map with 775 SSR loci. Theor Appl Genet 114:1091–1103PubMedCrossRefGoogle Scholar
  84. Virgona JM, Hubick KT, Rawson HM, Farquhar GD, Downes RW (1990) Genotypic variation in transpiration efficiency, carbon-isotope discrimination and carbon allocation during early growth in sunflower. Aust J Plant Physiol 17:207–214CrossRefGoogle Scholar
  85. Voltas J, Romagosa I, Lafarga A, Armesto AP, Sombrero A, Araus JL (1999) Genotype by environment interaction for grain yield and carbon isotope discrimination of barley in Mediterranean Spain. Aust J Agric Res 50:1263–1271CrossRefGoogle Scholar
  86. Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77–78PubMedCrossRefGoogle Scholar
  87. Wang S, Basten CJ, Zeng Z-B (2010) Windows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NCGoogle Scholar
  88. Wassmann R, Jagadish SVK, Heuer S, Ismail A, Redona E, Serraj R, Singh RK, Howell G, Pathak H, Sumfleth K (2009) Chapter 2 Climate change affecting rice production: the physiological and agronomic basis for possible adaptation strategies. Adv Agron 101:59–122CrossRefGoogle Scholar
  89. Wenzl P, Carling J, Kudrna D, Jaccoud D, Huttner E, Kleinhofs A, Kilian A (2004) Diversity Arrays Technology (DArT) for whole-genome profiling of barley. Proc Natl Acad Sci USA 101:9915–9920PubMedCrossRefGoogle Scholar
  90. Wenzl P, Li H, Carling J, Zhou M, Raman H, Paul E, Hearnden P, Maier C, Xia L, Caig V, Ovesná J, Cakir M, Poulsen D, Wang J, Raman R, Smith KP, Muehlbauer GJ, Chalmers KJ, Kleinhofs A, Huttner E, Kilian A (2006) A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits. BMC Genomics 7:206–228PubMedCrossRefGoogle Scholar
  91. White JW (1993) Implications of carbon isotope discrimination studies for breeding common bean under water deficits. In: Ehleringer JR, Hall AE, Farquhar GD (eds) Stable isotopes and plant carbon–water relations. Academic Press, San Diego, pp 387–398Google Scholar
  92. Xu X, Martin B, Comstock JP, Vision TJ, Tauer CG, Zhao B, Pausch RC, Steven K (2008) Fine mapping a QTL for carbon isotope composition in tomato. Theor Appl Genet 117:221–233PubMedCrossRefGoogle Scholar
  93. Xu Y, This D, Pausch RC, Vonhof WM, Coburn JR, Comstock JP, McCouch SR (2009) Leaf-level water use efficiency determined by carbon isotope discrimination in rice seedlings: genetic variation associated with population structure and QTL mapping. Theor Appl Genet 118:1065–1081PubMedCrossRefGoogle Scholar
  94. Xue D, Chen M, Zhou M, Chen S, Mao Y, Zhang G (2008) QTL analysis of flag leaf in barley (Hordeum vulgare L.) for morphological traits and chlorophyll content. J Zhejiang Univ Sci B 9:938–943PubMedCrossRefGoogle Scholar
  95. Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421CrossRefGoogle Scholar
  96. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468PubMedGoogle Scholar

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© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of Renewable Resources, 442 Earth Sciences BuildingUniversity of AlbertaEdmontonCanada
  2. 2.Department of Landscape Studies, College of Architecture and Urban PlanningTongji UniversityShanghaiPeople’s Republic of China
  3. 3.Alberta Innovates-Technology FuturesVegrevilleCanada

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