Ability of alleles of PPD1 and VRN1 genes to predict flowering time in diverse Australian wheat (Triticum aestivum) cultivars in controlled environments
Maxwell T. Bloomfield
A D , James R. Hunt A , Ben Trevaskis B , Kerrie Ramm B and Jessica Hyles B C
+ Author Affiliations
- Author Affiliations
A AgriBio Centre for Agribiosciences, La Trobe University, 5 Ring Road, Bundoora, Vic. 3083, Australia.
B CSIRO Agriculture and Food, GPO Box 1700, Canberra, ACT 2601, Australia.
C The Plant Breeding Institute, University of Sydney, 107 Cobbitty Road, Cobbitty, NSW 2570, Australia.
D Corresponding author. Email: M.Bloomfield@latrobe.edu.au
Crop and Pasture Science 69(11) 1061-1075 https://doi.org/10.1071/CP18102
Submitted: 27 March 2018 Accepted: 28 September 2018 Published: 12 November 2018
Abstract
Flowering time of wheat (Triticum aestivum L.) is a critical determinant of grain yield. Frost, drought and heat stresses from either overly early or overly late flowering can inflict significant yield penalties. The ability to predict time of flowering from different sowing dates for diverse cultivars across environments in Australia is important for maintaining yield as autumn rainfall events become less reliable. However, currently there are no models that can accurately do this when new cultivars are released. Two major Photoperiod1 and three Vernalisation1 development genes, with alleles identified by molecular markers, are known to be important in regulating phasic development and therefore time to anthesis, in response to the environmental factors of temperature and photoperiod. Allelic information from molecular markers has been used to parameterise models that could predict flowering time, but it is uncertain how much variation in flowering time can be explained by different alleles of the five major genes.
This experiment used 13 elite commercial cultivars of wheat, selected for their variation in phenology and in turn allelic variation at the major development genes, and 13 near-isogenic lines (NILs) with matching multi-locus genotypes for the major development genes, to quantify how much response in time to flowering could be explained by alleles of the major genes. Genotypes were grown in four controlled environments at constant temperature of 22°C with factorial photoperiod (long or short day) and vernalisation (±) treatments applied. NILs were able to explain a large proportion of the variation of thermal time to flowering in elite cultivars in the long-day environment with no vernalisation (97%), a moderate amount in the short-day environment with no vernalisation (62%), and less in the short-day (51%) and long-day (47%) environments with vernalisation. Photoperiod was found to accelerate development, as observed in a reduction in phyllochron, thermal time to heading, thermal time to flowering, and decreased final leaf numbers. Vernalisation response was not as great, and rates of development in most genotypes were not significantly increased. The results indicate that the alleles of the five major development genes alone cannot explain enough variation in flowering time to be used to parameterise gene-based models that will be accurate in simulating flowering time under field conditions. Further understanding of the genetics of wheat development, particularly photoperiod response, is required before a model with genetically based parameter estimates can be deployed to assist growers to make sowing-time decisions for new cultivars.
Additional keywords: crop management, genetically-derived parameters, optimal flowering time.
References
ABARES (2017) Australian crop report: September 2017 No. 183. Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, ACT. Available at: http://data.daff.gov.au/data/warehouse/aucrpd9abcc003/aucrpd9aba_20170912_yGQh0/AustCropRrt20170912_CropData_v1.0.0.xlsx (accessed 1 October).Allard V, Veisz O, Kõszegi B, Rousset M, Le Gouis J, Martre P (2012) The quantitative response of wheat vernalization to environmental variables indicates that vernalization is not a response to cold temperature. Journal of Experimental Botany 63, 847–857.
| The quantitative response of wheat vernalization to environmental variables indicates that vernalization is not a response to cold temperature.Crossref | GoogleScholarGoogle Scholar |
Baker JT, Pinter PJ, Reginato RJ, Kanemasu ET (1986) Effects of temperature on leaf appearance in spring and winter wheat cultivars. Agronomy Journal 78, 605–613.
| Effects of temperature on leaf appearance in spring and winter wheat cultivars.Crossref | GoogleScholarGoogle Scholar |
Basford KE, Cooper M (1998) Genotype × environment interactions and some considerations of their implications for wheat breeding in Australia. Australian Journal of Agricultural Research 49, 153–174.
| Genotype × environment interactions and some considerations of their implications for wheat breeding in Australia.Crossref | GoogleScholarGoogle Scholar |
Beales J, Turner A, Griffiths S, Snape JW, Laurie DA (2007) A pseudo-response regulator is misexpressed in the photoperiod insensitive Ppd-D1a mutant of wheat (Triticum aestivum L.). Theoretical and Applied Genetics 115, 721–733.
| A pseudo-response regulator is misexpressed in the photoperiod insensitive Ppd-D1a mutant of wheat (Triticum aestivum L.).Crossref | GoogleScholarGoogle Scholar |
Brooking IR, Jamieson PD (2002) Temperature and photoperiod response of vernalization in near-isogenic lines of wheat. Field Crops Research 79, 21–38.
| Temperature and photoperiod response of vernalization in near-isogenic lines of wheat.Crossref | GoogleScholarGoogle Scholar |
Brown HE, Jamieson PD, Brooking IR, Moot DJ, Huth NI (2013) Integration of molecular and physiological models to explain time of anthesis in wheat. Annals of Botany 112, 1683–1703.
| Integration of molecular and physiological models to explain time of anthesis in wheat.Crossref | GoogleScholarGoogle Scholar |
Brown HE, Huth NI, Holzworth DP, Teixeira EI, Zyskowski RF, Hargreaves JNG, Moot DJ (2014) Plant Modelling Framework: software for building and running crop models on the APSIM platform. Environmental Modelling & Software 62, 385–398.
| Plant Modelling Framework: software for building and running crop models on the APSIM platform.Crossref | GoogleScholarGoogle Scholar |
Brown H, Huth N, Holzworth D (2018) Crop model improvement in APSIM: using wheat as a case study. European Journal of Agronomy
| Crop model improvement in APSIM: using wheat as a case study.Crossref | GoogleScholarGoogle Scholar |
Cai W, Cowan T (2013) Southeast Australia autumn rainfall reduction: a climate-change-induced poleward shift of ocean–atmosphere circulation. Journal of Climate 26, 189–205.
| Southeast Australia autumn rainfall reduction: a climate-change-induced poleward shift of ocean–atmosphere circulation.Crossref | GoogleScholarGoogle Scholar |
Cai W, Cowan T, Thatcher M (2012) Rainfall reductions over Southern Hemisphere semi-arid regions: the role of subtropical dry zone expansion. Scientific Reports 2, 702
| Rainfall reductions over Southern Hemisphere semi-arid regions: the role of subtropical dry zone expansion.Crossref | GoogleScholarGoogle Scholar |
Cane K, Eagles HA, Laurie DA, Trevaskis B, Vallance N, Eastwood RF, Gororo NN, Kuchel H, Martin PJ (2013) Ppd-B1 and Ppd-D1 and their effects in southern Australian wheat. Crop & Pasture Science 64, 100–114.
| Ppd-B1 and Ppd-D1 and their effects in southern Australian wheat.Crossref | GoogleScholarGoogle Scholar |
Cao W, Moss DN (1989) Daylength effect on leaf emergence and phyllochron in wheat and barley. Crop Science 29, 1021–1025.
| Daylength effect on leaf emergence and phyllochron in wheat and barley.Crossref | GoogleScholarGoogle Scholar |
Chen Y, Carver BF, Wang S, Zhang F, Yan L (2009) Genetic loci associated with stem elongation and winter dormancy release in wheat. Theoretical and Applied Genetics 118, 881–889.
| Genetic loci associated with stem elongation and winter dormancy release in wheat.Crossref | GoogleScholarGoogle Scholar |
Chen A, Li C, Hu W, Lau MY, Lin H, Rockwell NC, Martin SS, Jernstedt JA, Lagarias JC, Dubcovsky J (2014) PHYTOCHROME C plays a major role in the acceleration of wheat flowering under long-day photoperiod. Proceedings of the National Academy of Sciences of the United States of America 111, 10037–10044.
| PHYTOCHROME C plays a major role in the acceleration of wheat flowering under long-day photoperiod.Crossref | GoogleScholarGoogle Scholar |
Comadran J, Kilian B, Russell J, Ramsay L, Stein N, Ganal M, Shaw P, Bayer M, Thomas W, Marshall D, Hedley P, Tondelli A, Pecchioni N, Francia E, Korzun V, Walther A, Waugh R (2012) Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley. Nature Genetics 44, 1388–1392.
| Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley.Crossref | GoogleScholarGoogle Scholar |
Cooper M, Technow F, Messina C, Gho C, Totir LR (2016) Use of crop growth models with whole-genome prediction: Application to a maize multienvironment trial. Crop Science 56, 2141–2156.
| Use of crop growth models with whole-genome prediction: Application to a maize multienvironment trial.Crossref | GoogleScholarGoogle Scholar |
Davidson J, Christian K, Jones D, Bremner P (1985) Responses of wheat to vernalization and photoperiod. Australian Journal of Agricultural Research 36, 347–359.
| Responses of wheat to vernalization and photoperiod.Crossref | GoogleScholarGoogle Scholar |
DeLacy IH, Fox PN, McLaren G, Trethowan R, White JW (2009) A conceptual model for describing processes of crop improvement in database structures. Crop Science 49, 2100–2112.
| A conceptual model for describing processes of crop improvement in database structures.Crossref | GoogleScholarGoogle Scholar |
Díaz A, Zikhali M, Turner AS, Isaac P, Laurie DA (2012) Copy number variation affecting the Photoperiod-B1 and Vernalization-A1 genes is associated with altered flowering time in wheat (Triticum aestivum). PLoS One 7, e33234
| Copy number variation affecting the Photoperiod-B1 and Vernalization-A1 genes is associated with altered flowering time in wheat (Triticum aestivum).Crossref | GoogleScholarGoogle Scholar |
Distelfeld A, Li C, Dubcovsky J (2009) Regulation of flowering in temperate cereals. Current Opinion in Plant Biology 12, 178–184.
| Regulation of flowering in temperate cereals.Crossref | GoogleScholarGoogle Scholar |
Eagles HA, Cane K, Vallance N (2009) The flow of alleles of important photoperiod and vernalisation genes through Australian wheat. Crop & Pasture Science 60, 646–657.
| The flow of alleles of important photoperiod and vernalisation genes through Australian wheat.Crossref | GoogleScholarGoogle Scholar |
Eagles HA, Cane K, Kuchel H, Hollamby GJ, Vallance N, Eastwood RF, Gororo NN, Martin PJ (2010) Photoperiod and vernalization gene effects in southern Australian wheat. Crop & Pasture Science 61, 721–730.
| Photoperiod and vernalization gene effects in southern Australian wheat.Crossref | GoogleScholarGoogle Scholar |
Eagles HA, Cane K, Trevaskis B (2011) Veery wheats carry an allele of Vrn-A1 that has implications for freezing tolerance in winter wheats. Plant Breeding 130, 413–418.
| Veery wheats carry an allele of Vrn-A1 that has implications for freezing tolerance in winter wheats.Crossref | GoogleScholarGoogle Scholar |
Ellis MH, Rebetzke GJ, Azanza F, Richards RA, Spielmeyer W (2005) Molecular mapping of gibberellin-responsive dwarfing genes in bread wheat. Theoretical and Applied Genetics 111, 423–430.
| Molecular mapping of gibberellin-responsive dwarfing genes in bread wheat.Crossref | GoogleScholarGoogle Scholar |
Faure S, Turner AS, Gruszka D, Christodoulou V, Davis SJ, von Korff M, Laurie DA (2012) Mutation at the circadian clock gene EARLY MATURITY 8 adapts domesticated barley (Hordeum vulgare) to short growing seasons. Proceedings of the National Academy of Sciences of the United States of America 109, 8328–8333.
| Mutation at the circadian clock gene EARLY MATURITY 8 adapts domesticated barley (Hordeum vulgare) to short growing seasons.Crossref | GoogleScholarGoogle Scholar |
Fletcher A, Lawes R, Weeks C (2016) Crop area increases drive earlier and dry sowing in Western Australia: implications for farming systems. Crop & Pasture Science 67, 1268–1280.
| Crop area increases drive earlier and dry sowing in Western Australia: implications for farming systems.Crossref | GoogleScholarGoogle Scholar |
Flohr BM, Hunt JR, Kirkegaard JA, Evans JR (2017a) Water and temperature stress define the optimal flowering period for wheat in south-eastern Australia. Field Crops Research 209, 108–119.
| Water and temperature stress define the optimal flowering period for wheat in south-eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Flohr BM, Hunt JR, Kirkegaard JA, Evans JR (2017b) Winter is coming: the potential for a fast winter wheat to stabilise flowering and maximise yield in southern and Western Australia. In ‘Doing more with less. Proceedings 18th Australian Agronomy Conference’. 24–28 September 2017, Ballarat, Vic. (Australian Society of Agronomy) Available at: http://www.agronomyconference.com/2017/15_ASA2017_Flohr_Bonnie_Final.pdf (accessed 6 October 2017)
Friend DJC, Helson VA, Fisher JE (1962) Leaf growth in Marquis wheat, as regulated by temperature, light intensity, and daylength. Canadian Journal of Botany 40, 1299–1311.
| Leaf growth in Marquis wheat, as regulated by temperature, light intensity, and daylength.Crossref | GoogleScholarGoogle Scholar |
Fu D, Szűcs P, Yan L, Helguera M, Skinner JS, von Zitzewitz J, Hayes PM, Dubcovsky J (2005) Large deletions within the first intron in VRN-1 are associated with spring growth habit in barley and wheat. Molecular Genetics and Genomics 273, 54–65.
| Large deletions within the first intron in VRN-1 are associated with spring growth habit in barley and wheat.Crossref | GoogleScholarGoogle Scholar |
Gallagher JN (1979) Field studies of cereal leaf growth I. Initiation and expansion in relation to temperature and ontogeny. Journal of Experimental Botany 30, 625–636.
| Field studies of cereal leaf growth I. Initiation and expansion in relation to temperature and ontogeny.Crossref | GoogleScholarGoogle Scholar |
Gawroński P, Ariyadasa R, Himmelbach A, Poursarebani N, Kilian B, Stein N, Steuernagel B, Hensel G, Kumlehn J, Sehgal SK, Gill BS, Gould P, Hall A, Schnurbusch T (2014) A distorted circadian clock causes early flowering and temperature-dependent variation in spike development in the Eps-3Am mutant of einkorn wheat. Genetics 196, 1253–1261.
| A distorted circadian clock causes early flowering and temperature-dependent variation in spike development in the Eps-3Am mutant of einkorn wheat.Crossref | GoogleScholarGoogle Scholar |
Gomez D, Vanzetti L, Helguera M, Lombardo L, Fraschina J, Miralles DJ (2014) Effect of Vrn-1, Ppd-1 genes and earliness per se on heading time in Argentinean bread wheat cultivars. Field Crops Research 158, 73–81.
| Effect of Vrn-1, Ppd-1 genes and earliness per se on heading time in Argentinean bread wheat cultivars.Crossref | GoogleScholarGoogle Scholar |
González FG, Slafer GA, Miralles DJ (2002) Vernalization and photoperiod responses in wheat pre-flowering reproductive phases. Field Crops Research 74, 183–195.
| Vernalization and photoperiod responses in wheat pre-flowering reproductive phases.Crossref | GoogleScholarGoogle Scholar |
Harris FAJ, Eagles HA, Virgona JM, Martin PJ, Condon JR, Angus JF (2017) Effect of VRN1 and PPD1 genes on anthesis date and wheat growth. Crop & Pasture Science 68, 195–201.
Haun JR (1973) Visual quantification of wheat development. Agronomy Journal 65, 116–119.
| Visual quantification of wheat development.Crossref | GoogleScholarGoogle Scholar |
He C, Holme J, Anthony J (2014) SNP genotyping: the KASP assay. In ‘Crop breeding: methods and protocols’. (Eds D Fleury, R Whitford) pp. 75–86. (Springer: New York)
Hochman Z, van Rees H, Carberry PS, Hunt JR, McCown RL, Gartmann A, Holzworth D, van Rees S, Dalgliesh NP, Long W, Peake AS, Poulton PL, McClelland T (2009) Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate. Crop & Pasture Science 60, 1057–1070.
| Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate.Crossref | GoogleScholarGoogle Scholar |
Hochman Z, Gobbett DL, Horan H (2017) Climate trends account for stalled wheat yields in Australia since 1990. Global Change Biology 23, 2071–2081.
| Climate trends account for stalled wheat yields in Australia since 1990.Crossref | GoogleScholarGoogle Scholar |
Holzworth DP, Huth NI, deVoil PG, Zurcher EJ, Herrmann NI, McLean G, Chenu K, van Oosterom EJ, Snow V, Murphy C, Moore AD, Brown H, Whish JPM, Verrall S, Fainges J, Bell LW, Peake AS, Poulton PL, Hochman Z, Thorburn PJ, Gaydon DS, Dalgliesh NP, Rodriguez D, Cox H, Chapman S, Doherty A, Teixeira E, Sharp J, Cichota R, Vogeler I, Li FY, Wang E, Hammer GL, Robertson MJ, Dimes JP, Whitbread AM, Hunt J, van Rees H, McClelland T, Carberry PS, Hargreaves JNG, MacLeod N, McDonald C, Harsdorf J, Wedgwood S, Keating BA (2014) APSIM—evolution towards a new generation of agricultural systems simulation. Environmental Modelling & Software 62, 327–350.
| APSIM—evolution towards a new generation of agricultural systems simulation.Crossref | GoogleScholarGoogle Scholar |
Holzworth D, Huth NI, Fainges J, Brown H, Zurcher E, Cichota R, Verrall S, Herrmann NI, Zheng B, Snow V (2018) APSIM Next Generation: overcoming challenges in modernising a farming systems model. Environmental Modelling & Software 103, 43–51.
| APSIM Next Generation: overcoming challenges in modernising a farming systems model.Crossref | GoogleScholarGoogle Scholar |
Hoogendoorn J (1985) A reciprocal F1 monosomic analysis of the genetic control of time of ear emergence, number of leaves and number of spikelets in wheat (Triticum aestivum L.). Euphytica 34, 545–558.
| A reciprocal F1 monosomic analysis of the genetic control of time of ear emergence, number of leaves and number of spikelets in wheat (Triticum aestivum L.).Crossref | GoogleScholarGoogle Scholar |
IWGSC (2018) Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361, eaar7191
Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. European Journal of Agronomy 18, 235–265.
| The DSSAT cropping system model.Crossref | GoogleScholarGoogle Scholar |
Kamran A, Iqbal M, Spaner D (2014) Flowering time in wheat (Triticum aestivum L.): a key factor for global adaptability. Euphytica 197, 1–26.
| Flowering time in wheat (Triticum aestivum L.): a key factor for global adaptability.Crossref | GoogleScholarGoogle Scholar |
Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18, 267–288.
| An overview of APSIM, a model designed for farming systems simulation.Crossref | GoogleScholarGoogle Scholar |
Levy J, Peterson ML (1972) Responses of spring wheats to vernalization and photoperiod. Crop Science 12, 487–490.
| Responses of spring wheats to vernalization and photoperiod.Crossref | GoogleScholarGoogle Scholar |
Li C, Distelfeld A, Comis A, Dubcovsky J (2011) Wheat flowering repressor VRN2 and promoter CO2 compete for interactions with NUCLEAR FACTOR-Y complexes. The Plant Journal 67, 763–773.
| Wheat flowering repressor VRN2 and promoter CO2 compete for interactions with NUCLEAR FACTOR-Y complexes.Crossref | GoogleScholarGoogle Scholar |
Messina CD, Technow F, Tang T, Totir R, Gho C, Cooper M (2018) Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP). European Journal of Agronomy
| Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP).Crossref | GoogleScholarGoogle Scholar |
Mosaad MG, Ortiz-Ferrara G, Mahalakshmi V, Fischer RA (1995) Phyllochron response to vernalization and photoperiod in spring wheat. Crop Science 35, 168–171.
| Phyllochron response to vernalization and photoperiod in spring wheat.Crossref | GoogleScholarGoogle Scholar |
Nishida H, Ishihara D, Ishii M, Kaneko T, Kawahigashi H, Akashi Y, Saisho D, Tanaka K, Handa H, Takeda K, Kato K (2013) Phytochrome C is a key factor controlling long-day flowering in barley. Plant Physiology 163, 804–814.
| Phytochrome C is a key factor controlling long-day flowering in barley.Crossref | GoogleScholarGoogle Scholar |
Onogi A, Watanabe M, Mochizuki T, Hayashi T, Nakagawa H, Hasegawa T, Iwata H (2016) Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates. Theoretical and Applied Genetics 129, 805–817.
| Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.Crossref | GoogleScholarGoogle Scholar |
Penrose LDJ, Martin RH, Landers CF (1991) Measurement of response to vernalization in Australian wheats with winter habit. Euphytica 57, 9–17.
Pook MJ, McIntosh PC, Meyers GA (2006) The synoptic decomposition of cool-season rainfall in the southeastern Australian cropping region. Journal of Applied Meteorology and Climatology 45, 1156–1170.
| The synoptic decomposition of cool-season rainfall in the southeastern Australian cropping region.Crossref | GoogleScholarGoogle Scholar |
Porter JR, Gawith M (1999) Temperatures and the growth and development of wheat: a review. European Journal of Agronomy 10, 23–36.
| Temperatures and the growth and development of wheat: a review.Crossref | GoogleScholarGoogle Scholar |
Pugsley AT (1963) The inheritance of a vernalization response in Australian spring wheats. Australian Journal of Agricultural Research 14, 622–627.
| The inheritance of a vernalization response in Australian spring wheats.Crossref | GoogleScholarGoogle Scholar |
Pugsley AT (1965) Inheritance of a correlated day-length response in spring wheat. Nature 207, 108–108.
| Inheritance of a correlated day-length response in spring wheat.Crossref | GoogleScholarGoogle Scholar |
Pugsley AT (1966) The photoperiodic sensitivity of some spring wheats with special reference to the variety Thatcher. Australian Journal of Agricultural Research 17, 591–599.
| The photoperiodic sensitivity of some spring wheats with special reference to the variety Thatcher.Crossref | GoogleScholarGoogle Scholar |
Pugsley AT (1971) A genetic analysis of the spring-winter habit of growth in wheat. Australian Journal of Agricultural Research 22, 21–31.
| A genetic analysis of the spring-winter habit of growth in wheat.Crossref | GoogleScholarGoogle Scholar |
Pugsley AT (1983) The impact of plant physiology on Australian wheat breeding. Euphytica 32, 743–748.
| The impact of plant physiology on Australian wheat breeding.Crossref | GoogleScholarGoogle Scholar |
Santra DK, Santra M, Allan RE, Campbell KG, Kidwell KK (2009) Genetic and molecular characterization of vernalization genes Vrn-A1, Vrn-B1, and Vrn-D1 in spring wheat germplasm from the Pacific Northwest region of the U.S.A. Plant Breeding 128, 576–584.
| Genetic and molecular characterization of vernalization genes Vrn-A1, Vrn-B1, and Vrn-D1 in spring wheat germplasm from the Pacific Northwest region of the U.S.A.Crossref | GoogleScholarGoogle Scholar |
Scarth R, Law CN (1984) The control of the day-length response in wheat by the group 2 chromosomes. Zeitschrift für Pflanzenzüchtung 92, 140–150.
Shaw LM, Turner AS, Laurie DA (2012) The impact of photoperiod insensitive Ppd-1a mutations on the photoperiod pathway across the three genomes of hexaploid wheat (Triticum aestivum). The Plant Journal 71, 71–84.
| The impact of photoperiod insensitive Ppd-1a mutations on the photoperiod pathway across the three genomes of hexaploid wheat (Triticum aestivum).Crossref | GoogleScholarGoogle Scholar |
Shcherban AB, Efremova TT, Salina EA (2012) Identification of a new Vrn-B1 allele using two near-isogenic wheat lines with difference in heading time. Molecular Breeding 29, 675–685.
| Identification of a new Vrn-B1 allele using two near-isogenic wheat lines with difference in heading time.Crossref | GoogleScholarGoogle Scholar |
Slafer GA, Rawson HM (1994a) Does temperature affect final numbers of primordia in wheat? Field Crops Research 39, 111–117.
| Does temperature affect final numbers of primordia in wheat?Crossref | GoogleScholarGoogle Scholar |
Slafer GA, Rawson HM (1994b) Sensitivity of wheat phasic development to major environmental factors: a re-examination of some assumptions made by physiologists and modellers. Functional Plant Biology 21, 393–426.
Slafer GA, Rawson HM (1995a) Intrinsic earliness and basic development rate assessed for their response to temperature in wheat. Euphytica 83, 175–183.
| Intrinsic earliness and basic development rate assessed for their response to temperature in wheat.Crossref | GoogleScholarGoogle Scholar |
Slafer GA, Rawson HM (1995b) Photoperiod × temperature interactions in contrasting wheat genotypes: Time to heading and final leaf number. Field Crops Research 44, 73–83.
| Photoperiod × temperature interactions in contrasting wheat genotypes: Time to heading and final leaf number.Crossref | GoogleScholarGoogle Scholar |
Slafer GA, Rawson HM (1995c) Rates and cardinal temperatures for processes of development in wheat: effects of temperature and thermal amplitude. Functional Plant Biology 22, 913–926.
Slafer GA, Rawson HM (1997) Phyllochron in wheat as affected by photoperiod under two temperature regimes. Functional Plant Biology 24, 151–158.
Slafer GA, Abeledo LG, Miralles DJ, Gonzalez FG, Whitechurch EMZ Bedö, L Láng (Eds) (2001) Photoperiod sensitivity during stem elongation as an avenue to raise potential yield in wheat. In ‘Wheat in a global environment. Proceedings 6th International Wheat Conference’. 5–9 June 2000, Budapest. (Springer: Dordrecht, The Netherlands) Available at:
Slafer GA, Kantolic AG, Appendino ML, Tranquilli G, Miralles DJ, Savin R (2014) Genetic and environmental effects on crop development determining adaptation and yield. In ‘Crop physiology’. 2nd edn (Ed. DF Calderini) pp. 285–319. (Academic Press: San Diego, CA, USA)
Stapper M, Fischer R (1990) Genotype, sowing date and plant spacing influence on high-yielding irrigated wheat in southern New South Wales. I. Phasic development, canopy growth and spike production. Australian Journal of Agricultural Research 41, 997–1019.
| Genotype, sowing date and plant spacing influence on high-yielding irrigated wheat in southern New South Wales. I. Phasic development, canopy growth and spike production.Crossref | GoogleScholarGoogle Scholar |
Steinfort U, Trevaskis B, Fukai S, Bell KL, Dreccer MF (2017) Vernalisation and photoperiod sensitivity in wheat: impact on canopy development and yield components. Field Crops Research 201, 108–121.
| Vernalisation and photoperiod sensitivity in wheat: impact on canopy development and yield components.Crossref | GoogleScholarGoogle Scholar |
Sukumaran S, Lopes MS, Dreisigacker S, Dixon LE, Zikhali M, Griffiths S, Zheng B, Chapman S, Reynolds MP (2016) Identification of earliness per se flowering time locus in spring wheat through a genome-wide association study. Crop Science 56, 2962–2972.
| Identification of earliness per se flowering time locus in spring wheat through a genome-wide association study.Crossref | GoogleScholarGoogle Scholar |
Syme J (1968) Ear emergence of Australian, Mexican, and European wheats in relation to time of sowing and their response to vernalization and daylength. Australian Journal of Experimental Agriculture 8, 578–581.
| Ear emergence of Australian, Mexican, and European wheats in relation to time of sowing and their response to vernalization and daylength.Crossref | GoogleScholarGoogle Scholar |
Technow F, Messina CD, Totir LR, Cooper M (2015) Integrating crop growth models with whole genome prediction through approximate Bayesian computation. PLoS One 10, e0130855
| Integrating crop growth models with whole genome prediction through approximate Bayesian computation.Crossref | GoogleScholarGoogle Scholar |
Tottman DR, Makepeace RJ, Broad H (1979) An explanation of the decimal code for the growth stages of cereals, with illustrations. Annals of Applied Biology 93, 221–234.
| An explanation of the decimal code for the growth stages of cereals, with illustrations.Crossref | GoogleScholarGoogle Scholar |
Trevaskis B (2010) The central role of the VERNALIZATION1 gene in the vernalization response of cereals. Functional Plant Biology 37, 479–487.
| The central role of the VERNALIZATION1 gene in the vernalization response of cereals.Crossref | GoogleScholarGoogle Scholar |
White JW, Herndl M, Hunt LA, Payne TS, Hoogenboom G (2008) Simulation-based analysis of effects of Vrn and Ppd loci on flowering in wheat. Crop Science 48, 678–687.
| Simulation-based analysis of effects of Vrn and Ppd loci on flowering in wheat.Crossref | GoogleScholarGoogle Scholar |
Yan L, Helguera M, Kato K, Fukuyama S, Sherman J, Dubcovsky J (2004) Allelic variation at the VRN-1 promoter region in polyploid wheat. Theoretical and Applied Genetics 109, 1677–1686.
| Allelic variation at the VRN-1 promoter region in polyploid wheat.Crossref | GoogleScholarGoogle Scholar |
Yin X, van der Linden CG, Struik PC (2018) Bringing genetics and biochemistry to crop modelling, and vice versa. European Journal of Agronomy
| Bringing genetics and biochemistry to crop modelling, and vice versa.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 |
Zhang J, Wang Y, Wu S, Yang J, Liu H, Zhou Y (2012) A single nucleotide polymorphism at the Vrn-D1 promoter region in common wheat is associated with vernalization response. Theoretical and Applied Genetics 125, 1697–1704.
| A single nucleotide polymorphism at the Vrn-D1 promoter region in common wheat is associated with vernalization response.Crossref | GoogleScholarGoogle Scholar |
Zheng B, Biddulph B, Li D, Kuchel H, Chapman S (2013) Quantification of the effects of VRN1 and Ppd-D1 to predict spring wheat (Triticum aestivum) heading time across diverse environments. Journal of Experimental Botany 64, 3747–3761.
| Quantification of the effects of VRN1 and Ppd-D1 to predict spring wheat (Triticum aestivum) heading time across diverse environments.Crossref | GoogleScholarGoogle Scholar |
Zikhali M, Leverington-Waite M, Fish L, Simmonds J, Orford S, Wingen LU, Goram R, Gosman N, Bentley A, Griffiths S (2014) Validation of a 1DL earliness per se (eps) flowering QTL in bread wheat (Triticum aestivum). Molecular Breeding 34, 1023–1033.
| Validation of a 1DL earliness per se (eps) flowering QTL in bread wheat (Triticum aestivum).Crossref | GoogleScholarGoogle Scholar |
