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Unraveling diversity in wheat competitive ability traits can improve integrated weed management

  • Mariateresa Lazzaro
  • Paolo BàrberiEmail author
  • Matteo Dell’Acqua
  • Mario Enrico Pè
  • Margherita Limonta
  • Delfina Barabaschi
  • Luigi Cattivelli
  • Paolo Laino
  • Patrizia Vaccino
Research Article
  • 67 Downloads
Part of the following topical collections:
  1. Pest control

Abstract

Weed pressure can be high in organic and low-input farming and reduce yield and produce quality. In these systems, integrated weed management includes different agronomic practices but rarely focuses on the use of more competitive cultivars, which would reduce reliance on direct weed control methods and their detrimental effects on soil and the environment. We characterized 160 common wheat (Triticum aestivum L.) accessions cultivated in Italy since the nineteenth century for four traits linked to competitive ability against weeds (above-ground biomass before stem elongation, tillering index, plant height, and flag leaf morphology) and for two production-related traits (grain yield and thousand-kernel weight). This approach aimed to identify the most suitable combinations of competitiveness and production traits, which often show trade-offs, and led to the identification of eight accessions with reduced grain yield to plant height trade-off. We genotyped the collection with SNP markers, revealing high molecular diversity and highlighting a trend of polymorphism loss passing from heritage to modern germplasm, with the presence of unique polymorphisms in both groups. These results underline the importance of studying both heritage and elite germplasm when focusing on traits that are not targeted by formal breeding, such as the competitive ability against weeds. Marker-trait associations (MTAs) with false discovery rates (FDR) < 5% were detected for all traits studied, while MTAs with FDR < 1% were detected for plant height, biomass, grain yield, and thousand-kernel weight. We identified MTAs confirming associations already reported in the literature as well as MTAs pinpointing new genomic regions that may disclose new breeding perspectives in common wheat. This study, for the first time, shows the high potential of interdisciplinary research bridging advanced genetic studies with agroecological approaches for selecting more competitive common wheat germplasm as additional tool in more sustainable integrated weed management systems.

Keywords

Crop-weed interaction Weed control Landraces Low-input breeding Organic breeding Genome-wide association Marker-trait associations Quantitative trait loci Triticum aestivum

Notes

Funding information

The authors acknowledge the Italian Ministry of Agriculture for partially funding this research in the framework of the Project RGV-FAO (DM 11746, 10/04/17) and the International PhD program in Agrobiodiversity of Scuola Superiore Sant’Anna for providing the scholarship to the first author.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Ahlgren S (2004) Environmental impact of chemical and mechanical weed control in agriculture: a comparing study using life cycle assessment (LCA) methodology. SIK rapport Nr 719 2004. The Sdewish Institute for Food and Biotechnology, Gothenburg, SwedenGoogle Scholar
  2. Andrew IKS, Storkey J, Sparkes DL (2015) A review of the potential for competitive cereal cultivars as a tool in integrated weed management. Weed Res 55:239–248.  https://doi.org/10.1111/wre.12137 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Austin RB, Ford MA, Morgan CL (1989) Genetic improvement in the yield of winter wheat: a further evaluation. J Agric Sci 112:295–301.  https://doi.org/10.1017/S0021859600085749 CrossRefGoogle Scholar
  4. Barabaschi D, Tondelli A, Desiderio F, Volante A, Vaccino P, Valè G, Cattivelli L (2016) Next generation breeding. Plant Sci 242:3–13.  https://doi.org/10.1016/j.plantsci.2015.07.010 CrossRefPubMedGoogle Scholar
  5. Bàrberi P (2002) Weed management in organic agriculture: are we addressing the right issues? Weed Res 42:177–193.  https://doi.org/10.1046/j.1365-3180.2002.00277.x CrossRefGoogle Scholar
  6. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57:289–300Google Scholar
  7. Cui F, Fan X, Zhao C, Zhang W, Chen M, Ji J, Li J (2014) A novel genetic map of wheat: utility for mapping QTL for yield under different nitrogen treatments. BMC Genet 15:57.  https://doi.org/10.1186/1471-2156-15-57 CrossRefPubMedPubMedCentralGoogle Scholar
  8. Fan X, Cui F, Zhao C, Zhang W, Yang L, Zhao X, Han J, Su Q, Ji J, Zhao Z, Tong Y, Li J (2015) QTLs for flag leaf size and their influence on yield-related traits in wheat (Triticum aestivum L.). Mol Breed 35:24.  https://doi.org/10.1007/s11032-015-0205-9 CrossRefGoogle Scholar
  9. Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Alibert L, Orford S, Wingen L, Snape J (2012) Meta-QTL analysis of the genetic control of crop height in elite European winter wheat germplasm. Mol Breed 29:159–171.  https://doi.org/10.1007/s11032-010-9534-x CrossRefGoogle Scholar
  10. Hoad SP, Bertholdsson N-Ø, Neuhoff D, Köpke U (2012) Approaches to breed for improved weed suppression in organically grown cereals. In: Lammerts van Bueren ET, Myers JR (eds) Organic crop breeding. Wiley-Blackwell, Chichester, pp 61–76Google Scholar
  11. Khaliq I, Irshad A, Ahsan M (2008) Awns and flag leaf contribution towards grain yield in spring wheat (Triticum aestivum L.). Cereal Res Commun 36:65–76.  https://doi.org/10.1556/CRC.36.2008.1.7 CrossRefGoogle Scholar
  12. Kidane YG, Hailemariam BN, Mengistu DK, Fadda C, Pè ME, Dell'Acqua M (2017) Genome-wide association study of Septoria tritici blotch resistance in Ethiopian durum wheat landraces. Front Plant Sci 8:1586.  https://doi.org/10.3389/fpls.2017.01586 CrossRefPubMedPubMedCentralGoogle Scholar
  13. Kuraparthy V, Sood S, Dhaliwal HS, Chhuneja P, Gill BS (2006) Identification and mapping of a tiller inhibition gene (tin3) in wheat. Theor Appl Genet 114:285–294.  https://doi.org/10.1007/s00122-006-0431-y CrossRefPubMedGoogle Scholar
  14. Laino P, Limonta M, Gerna D, Vaccino P (2015) Morpho-physiolological and qualitative traits of a bread wheat collection spanning a century of breeding in Italy. Biodivers Data J 3:e4760.  https://doi.org/10.3897/BDJ.3.e4760 CrossRefGoogle Scholar
  15. Li WL, Nelson JC, Chu CY et al (2002) Chromosomal locations and genetic relationships of tiller and spike characters in wheat. Euphytica 125:357–366.  https://doi.org/10.1023/A:1016069809977
  16. Lopes MS, El-Basyoni I, Baenziger PS et al (2015) Exploiting genetic diversity from landraces in wheat breeding for adaptation to climate change. J Exp Bot 66:3477–3486.  https://doi.org/10.1093/jxb/erv122 CrossRefPubMedGoogle Scholar
  17. Mengistu DK, Kidane YG, Catellani M, Frascaroli E, Fadda C, Pè ME, Dell'Acqua M (2016) High-density molecular characterization and association mapping in Ethiopian durum wheat landraces reveals high diversity and potential for wheat breeding. Plant Biotechnol J 14:1800–1812.  https://doi.org/10.1111/pbi.12538 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Murphy KM, Dawson JC, Jones SS (2008) Relationship among phenotypic growth traits, yield and weed suppression in spring wheat landraces and modern cultivars. Field Crop Res 105:107–115.  https://doi.org/10.1016/j.fcr.2007.08.004 CrossRefGoogle Scholar
  19. Ormoli L, Costa C, Negri S, Perenzin M, Vaccino P (2015) Diversity trends in bread wheat in Italy during the 20th century assessed by traditional and multivariate approaches. Sci Rep 5:1–7.  https://doi.org/10.1038/srep08574 CrossRefGoogle Scholar
  20. Riaz A, Hathorn A, Dinglasan E, Ziems L, Richard C, Singh D, Mitrofanova O, Afanasenko O, Aitken E, Godwin I, Hickey L (2016) Into the vault of the Vavilov wheats: old diversity for new alleles. Genet Resour Crop Evol 64:531–544.  https://doi.org/10.1007/s10722-016-0380-5 CrossRefGoogle Scholar
  21. Rimbert H, Darrier B, Navarro J, Kitt J, Choulet F, Leveugle M, Duarte J, Rivière N, Eversole K, on behalf of The International Wheat Genome Sequencing Consortium, le Gouis J, on behalf The BreedWheat Consortium, Davassi A, Balfourier F, le Paslier MC, Berard A, Brunel D, Feuillet C, Poncet C, Sourdille P, Paux E (2018) High throughput SNP discovery and genotyping in hexaploid wheat. PLoS One 13:e0186329.  https://doi.org/10.1371/journal.pone.0186329 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Roussel V, Leisova L, Exbrayat F, Stehno Z, Balfourier F (2005) SSR allelic diversity changes in 480 European bread wheat varieties released from 1840 to 2000. Theor Appl Genet 111:162–170.  https://doi.org/10.1007/s00122-005-2014-8 CrossRefPubMedGoogle Scholar
  23. Salvi S, Porfiri O, Ceccarelli S (2013) Nazareno Strampelli, the ‘prophet’ of the green revolution. J Agric Sci 151:1–5.  https://doi.org/10.1017/S0021859612000214 CrossRefGoogle Scholar
  24. VanRaden PM (2008) Efficient methods to compute genomic predictions. J Dairy Sci 91:4414–4423.  https://doi.org/10.3168/jds.2007-0980 CrossRefPubMedGoogle Scholar
  25. Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing Consortium, Lillemo M, Mather D, Appels R, Dolferus R, Brown-Guedira G, Korol A, Akhunova AR, Feuillet C, Salse J, Morgante M, Pozniak C, Luo MC, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards KJ, Hayden M, Akhunov E (2014) Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796.  https://doi.org/10.1111/pbi.12183 CrossRefPubMedPubMedCentralGoogle Scholar
  26. Wang Z, Liu Y, Shi H, Mo H, Wu F, Lin Y, Gao S, Wang J, Wei Y, Liu C, Zheng Y (2016) Identification and validation of novel low-tiller number QTL in common wheat. Theor Appl Genet 129:603–612.  https://doi.org/10.1007/s00122-015-2652-4 CrossRefPubMedGoogle Scholar
  27. Winfield MO, Allen AM, Wilkinson PA, Burridge AJ, Barker GLA, Coghill J, Waterfall C, Wingen LU, Griffiths S, Edwards KJ (2018) High-density genotyping of the A.E. Watkins collection of hexaploid landraces identifies a large molecular diversity compared to elite bread wheat. Plant Biotechnol J 16:165–175.  https://doi.org/10.1111/pbi.12757 CrossRefPubMedGoogle Scholar
  28. Yang D, Liu Y, Cheng H, Chang L, Chen J, Chai S, Li M (2016) Genetic dissection of flag leaf morphology in wheat (Triticum aestivum L.) under diverse water regimes. BMC Genet 17:94.  https://doi.org/10.1186/s12863-016-0399-9 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Zanke CD, Ling J, Plieske J et al (2014a) Genetic architecture of main effect QTL for heading date in European winter wheat. Front Plant Sci 5:217.  https://doi.org/10.3389/fpls.2014.00217 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann K, Ganal MW, Röder MS (2014b) Whole genome association mapping of plant height in winter wheat (Triticum aestivum L.). PLoS One 9:e113287.  https://doi.org/10.1371/journal.pone.0113287 CrossRefPubMedPubMedCentralGoogle Scholar
  31. Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann F, Eichhorn A, Polley A, Jaenecke C, Ganal MW, Röder MS (2015) Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping. Front Plant Sci 6:644.  https://doi.org/10.3389/fpls.2015.00644 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  • Mariateresa Lazzaro
    • 1
  • Paolo Bàrberi
    • 1
    Email author return OK on get
  • Matteo Dell’Acqua
    • 1
  • Mario Enrico Pè
    • 1
  • Margherita Limonta
    • 2
  • Delfina Barabaschi
    • 3
  • Luigi Cattivelli
    • 3
  • Paolo Laino
    • 4
  • Patrizia Vaccino
    • 5
  1. 1.Scuola Superiore Sant’AnnaInstitute of Life SciencesPisaItaly
  2. 2.Atlas S.R.L.Sant’Angelo LodigianoItaly
  3. 3.Consiglio per la Ricerca in agricoltura e l’analisi dell’economia AgrariaResearch Centre for Genomics and BioinformaticsFiorenzuola d’ArdaItaly
  4. 4.ICE SpAReggio EmiliaItaly
  5. 5.Consiglio per la ricerca in agricoltura e l’analisi dell’economia agrariaResearch Centre for Cereal and Industrial CropsVercelliItaly

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