Hostname: page-component-6766d58669-rxg44 Total loading time: 0 Render date: 2026-05-16T08:29:24.930Z Has data issue: false hasContentIssue false
  • English
  • Français

Taxonomic resolution of fleabane species (Conyza spp.) based on morphological and molecular markers and their dispersion across soybean-cropping macroregions and seasons in Brazil

Published online by Cambridge University Press:  29 January 2024

Augusto Kalsing Open the ORCID record for Augusto Kalsing [Opens in a new window] ,
Felipe A. Nunes Open the ORCID record for Felipe A. Nunes [Opens in a new window] ,
Guilherme A. Gotardi Open the ORCID record for Guilherme A. Gotardi [Opens in a new window] ,
Jaqueline B. Campos Open the ORCID record for Jaqueline B. Campos [Opens in a new window] ,
Angelo A. Schneider Open the ORCID record for Angelo A. Schneider [Opens in a new window] ,
Leandro Tropaldi Open the ORCID record for Leandro Tropaldi [Opens in a new window] ,
Edivaldo D. Velini Open the ORCID record for Edivaldo D. Velini [Opens in a new window] ,
Aldo Merotto Jr Open the ORCID record for Aldo Merotto Jr [Opens in a new window]  and
Caio A. Carbonari Open the ORCID record for Caio A. Carbonari [Opens in a new window]
Augusto Kalsing*
Affiliation:
Graduate Student, Postgraduate Group of Crop Protection, São Paulo State University, Botucatu, SP, Brazil; current: Researcher, Corteva Agriscience, Crop Protection Discovery and Development, Mogi Mirim, SP, Brazil
Felipe A. Nunes
Affiliation:
Researcher, Corteva Agriscience, Crop Protection Discovery and Development, Mogi Mirim, SP, Brazil
Guilherme A. Gotardi
Affiliation:
Researcher, Corteva Agriscience, Crop Protection Discovery and Development, Mogi Mirim, SP, Brazil
Jaqueline B. Campos
Affiliation:
Researcher, Corteva Agriscience, Crop Protection Discovery and Development, Mogi Mirim, SP, Brazil
Angelo A. Schneider
Affiliation:
Professor, Biological Sciences Department, Pampa Federal University, São Gabriel, RS, Brazil
Leandro Tropaldi
Affiliation:
Professor, Agricultural and Technological Sciences Department, São Paulo State University, Dracena, SP, Brazil
Edivaldo D. Velini
Affiliation:
Professor, Crop Protection Department, São Paulo State University, Botucatu, SP, Brazil
Aldo Merotto Jr
Affiliation:
Professor, Crop Science Department, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
Caio A. Carbonari
Affiliation:
Professor, Crop Protection Department, São Paulo State University, Botucatu, SP, Brazil
*
Corresponding author: Augusto Kalsing; Email: augusto.kalsing@corteva.com
Get access Rights & Permissions [Opens in a new window]

Abstract

The Conyza genus includes nearly 150 species, comprising closely related weedy species. Proper identification of Conyza spp. is essential to develop effective strategies for their management. The overlap of traits, species varieties, and the putative occurrence of hybridization hampers the identification of Conyza spp. and its management in agricultural and natural environments. Herein, we assessed five DNA barcodes and 32 morphological traits to classify Conyza spp. and survey their dispersion in soybean fields [Glycine max (L.) Merr.] in Brazil in 2019, 2020, and 2021. The Conyza accessions included two species, hairy fleabane [Conyza bonariensis (L.) Cronquist) and Sumatran fleabane [Conyza sumatrensis (Retz.) E. Walker], and each species comprised two varieties. The ITS and rps16-trnQ gene regions showed the ability to distinguish between the two Conyza species, while the matK, rbcL, and trnF-trnF gene regions were not polymorphic. Out of 32 morphological traits, phyllary color, involucre shape, capitulescence type, and inflorescence type were the most polymorphic and even reliable for taxonomic purposes. The combination of ITS or ITS+rps16-trnQ regions and the four morphological markers was able to discriminate 91% of the plants, except those of C. bonariensis var. angustifolia. These results support the taxonomic resolution between C. bonariensis and C. sumatrensis and are useful for other Conyza spp. and other closely related weedy species worldwide. Conyza sumatrensis was detected in 94% of soybean fields across macroregions and seasons in Brazil, while C. bonariensis was sparsely dispersed, mainly in the southern macroregion (MRS 1).

Keywords

DNA barcodinghairy fleabaneITSmorphologyphylogenyrps16-trnQSumatran fleabanetaxonomy

Information

Type
Research Article
Information
Weed Science , Volume 72 , Issue 2 , March 2024 , pp. 192 - 204
Check for updates
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Weed Science Society of America

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

Associate Editor: William Vencill, University of Georgia

References

Albrecht, AJP, Pereira, VGC, De Souza, CNZ, Zobiole, LHS, Albrecht, LP, Adegas, FS (2020) Multiple resistance of Conyza sumatrensis to three mechanisms of action of herbicides. Acta Sci Agron 42:e42485 CrossRefGoogle Scholar
Alpen, K, Gopurenko, D, Wu, H, Lepschi, BJ, Weston, L (2014) The development of a DNA barcode system for species identification of Conyza spp. (fleabane). Pages 401–404 in 19th Australasian Weeds Conference. Hobart, Australia: Tasmanian Weed SocietyGoogle Scholar
Arif, IA, Bakir, MA, Khan, HA, Al Farhan, AH, Al Homaidan, AA, Bahkali, AH, Sadoon, MA, Shobrak, M (2010) A brief review of molecular techniques to assess plant diversity. Int J Mol Sci 11:2079–2096 CrossRefGoogle ScholarPubMed
Bajwa, AA, Sadia, S, Ali, HH, Jabran, K, Peerzada, AM, Chauhan, BS (2016) Biology and management of two important Conyza weeds: a global review. Environ Sci Pollut Res 23:24694–24710 CrossRefGoogle Scholar
Burgos, NR, Tranel, PJ, Streibig, JC, Davis, VM, Norsworthy, JK, Ritz, C (2013) Review: confirmation of resistance to herbicides and evaluation of resistance levels Weed Sci 61:4–20 CrossRefGoogle Scholar
Chen, X, Zhou, J, Cui, Y, Wang, Y, Duan, B, Yao, H (2018) Identification of Ligularia herbs using the complete chloroplast genome as a super-barcode. Front Pharmacol 9:695 CrossRefGoogle ScholarPubMed
Daniell, H, Lin, CS, Yu, M, Chang, WJ (2016) Chloroplast genomes: diversity, evolution, and applications in genetic engineering. Genome Biol 17:134 CrossRefGoogle Scholar
Da Silva, A, Karam, D, Vargas, L, Adegas, F, Gazziero, D, Ikeda, F, Cavalieri, S, Costa, A, Perina, F (2021) Monitoramento de Plantas Daninhas Resistentes a Glifosato no Brasil. Sete Lagoas, Brazil: Empresa Brasileira de Pesquisa Agropecuária. 21 pGoogle Scholar
De Pinho, CF, Leal, JFL, Dos Santos Souza, A, De Oliveira, GFPB, De Oliveira, C, Langaro, AC, Machado, AFL, Christoffoleti, PJ, Zobiole, LHS (2019) First evidence of multiple resistance of Sumatran fleabane (‘Conyza sumatrensis’ (Retz.) E. Walker) to five-mode-of-action herbicides. Aust J Crop Sci 13:1688–1697 CrossRefGoogle Scholar
Deroo, AC, Eckstein, P, Benaragama, D, Beattie, AD, Willenborg, CJ (2019) Evaluation of Galium species and populations using morphological characters and molecular markers. Weed Res 59:28–38 CrossRefGoogle Scholar
De Ulzurrun, PD, Acedo, MB, Garavano, ME, Gianelli, V, Ispizúa, VN (2018) Morphological characterization of Conyza blakei, Conyza bonariensis var. bonariensis, Conyza sumatrensis var. sumatrensis and Conyza lorentzii in the southeast of Buenos Aires (Argentine). Bol Soc Argent Bot 53:359–373 CrossRefGoogle Scholar
Fazekas, AJ, Burgess, KS, Kesanakurti, PR, Graham, SW, Newmaster, SG, Husband, BC, Percy, DM, Hajibabaei, M, Barrett, SCH (2008) Multiple multilocus DNA barcodes from the plastid genome discriminate plant species equally well. PLoS ONE 3:e2802 CrossRefGoogle ScholarPubMed
Flora e Funga do Brasil (2023) Jardim Botânico do Rio de Janeiro. http://floradobrasil.jbrj.gov.br. Accessed: July 1, 2023Google Scholar
Gichira, AW, Avoga, S, Li, Z, Hu, G, Wang, Q, Chen, J (2019) Comparative genomics of 11 complete chloroplast genomes of Senecioneae (Asteraceae) species: DNA barcodes and phylogenetics. Bot Stud 60:17 CrossRefGoogle ScholarPubMed
Ginestet, C (2011) ggplot2: elegant graphics for data analysis. J R Stat Soc Ser A Stat Soc 174:245–246 CrossRefGoogle Scholar
Grover, A, Sharma, PC (2016) Development and use of molecular markers: past and presente. Crit Rev Biotechnol 36:290–302.CrossRefGoogle Scholar
Guo, YY, Huang, LQ, Liu, ZJ, Wang, XQ (2016) Promise and challenge of DNA barcoding in Venus slipper (Paphiopedilum). PLoS One 11:e0146880 CrossRefGoogle ScholarPubMed
Hall, TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser 41:95–98 Google Scholar
Han, S, Sebastin, R, Wang, X, Lee, KJ, Cho, GT, Hyun, DY, Chung, JW (2021) Identification of Vicia species native to South Korea using molecular and morphological characteristics. Front Plant Sci 12:608559 CrossRefGoogle ScholarPubMed
Hao, JH, Qiang, S, Liu, QQ, Cao, F (2009) Reproductive traits associated with invasiveness in Conyza sumatrensis . J Syst Evol 47:245–254 CrossRefGoogle Scholar
Heap, I (2022) The International Herbicide-Resistant Weed Database. http://www.weedscience.org. Accessed: July 1, 2023Google Scholar
Hebert, PDN, Cywinska, A, Ball, SL, DeWaard, JR (2003) Biological identifications through DNA barcodes. Proc R Soc London Ser B Biol Sci 270:313–321 CrossRefGoogle ScholarPubMed
Jombart, T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24:1403–1405 CrossRefGoogle Scholar
Kaster, M, Farias, JRB (2012) Regionalização dos Testes de Valor de Cultivo e Uso e da Indicação de Cultivares de Soja-Terceira Aproximação. Embrapa Soja Document 330. Londrina, Brazil: Embrapa Soja. 69 pGoogle Scholar
Kress, WJ, Erickson, DL (2007) A two-locus global DNA barcode for land plants: the coding rbcL gene complements the non-coding trnH-psbA spacer region. PLoS ONE 2:e508 CrossRefGoogle ScholarPubMed
Li, X, Yang, Y, Henry, RJ, Rossetto, M, Wang, Y, Chen, S (2015) Plant DNA barcoding: from gene to genome. Biol Rev 90:157–166 CrossRefGoogle ScholarPubMed
Lucio, FR, Kalsing, A, Adegas, FS, Rossi, CVS, Correia, NM, Gazziero, DLP, Da Silva, AF (2019) Dispersal and frequency of glyphosate-resistant and glyphosate-tolerant weeds in soybean-producing edaphoclimatic microregions in Brazil. Weed Technol 33:217–231 CrossRefGoogle Scholar
Marochio, CA, Bevilaqua, MRR, Takano, HK, Mangolim, CA, Oliveira, RSD, Machado, MDFPS (2017) Genetic admixture in species of Conyza (Asteraceae) as revealed by microsatellite markers. Acta Sci Agron 39:437–445 CrossRefGoogle Scholar
McClintock, D, Marshall, JB (1998) On Conyza sumatrensis (Retz.) E. Walker and certain hybrids in the genus. Watsonia 17:172–173 Google Scholar
Mendes, RR, Takano, HK, Netto, AG, Picoli, GJ Jr, Cavenaghi, AL, Silva, VF, Nicolai, M, Christoffoleti, PJ, Oliveira, RS Jr, De Melo, MS (2021) Monitoring glyphosate-and chlorimuron-resistant Conyza spp. populations in Brazil. An Acad Bras Cienc 93:e20190425 CrossRefGoogle ScholarPubMed
Ochoa, MC, Catan, A, Targa, MG, Fraño, A, Caro, R, Chaila, S (2023) Morphoanatomic characterization of Gomphrena perennis and Gomphrena pulchella leaves. Adv Weed Sci 41:e020202203.CrossRefGoogle Scholar
Park, HS, Lee, WK, Lee, SC, Lee, HO, Joh, HJ, Park, JY, Kim, S, Song, K, Yang, TJ (2021) Inheritance of chloroplast and mitochondrial genomes in cucumber revealed by four reciprocal F1 hybrid combinations. Sci Rep 11:2506 CrossRefGoogle ScholarPubMed
Piasecki, C, Mazon, A, Agostinetto, D, Vargas, L (2019) Glyphosate resistance affect the physiological quality of Conyza bonariensis seeds. Planta Daninha 37:e019213902 CrossRefGoogle Scholar
Pruski, JF, Sancho, G (2006) Conyza sumatrensis var. leiotheca (Compositae: Astereae), a new combination for a common neotropical weed. Novon 16:96–101 CrossRefGoogle Scholar
Rozas, J, Ferrer-Mata, A, Sánchez-DelBarrio, JC, Guirao-Rico, S, Librado, P, Ramos-Onsins, SE, Sánchez-Gracia, A (2017) DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol 34:3299–3302 CrossRefGoogle ScholarPubMed
Sancho, G (2014) Tribu astereae. Pages 38–246 in Zuloaga F, Belgrano M, Anton A, eds. Flora Vascular de La República Argentina. Volume 7(1), Dicotyledoneae Asteraceae (Anthemideae a Gnaphalieae). Buenos Aires, AR: Instituto de Botánica DarwinionCrossRefGoogle Scholar
Santos, G, Oliveira, RS Jr, Constantin, J, Francischini, AC, Machado, MFPS, Mangolin, CA, Nakajima, JN (2014) Conyza sumatrensis: a new weed species resistant to glyphosate in the Americas. Weed Biol Manag 14:106–114 CrossRefGoogle Scholar
Sela, I, Ashkenazy, H, Katoh, K, Pupko, T (2015) GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters. Nucleic Acids Res 43:W7–W14 CrossRefGoogle ScholarPubMed
Shaik, RS, Lepschi, BJ, Gopurenko, D, Urwin, NA, Burrows, GE, Weston, LA (2016) An integrative morphological and molecular approach to identification of three Australian cucurbitaceous invasive weeds: Citrullus colocynthis, C. lanatus and Cucumis myriocarpus . Aust Syst Bot 29:247–264 CrossRefGoogle Scholar
Simeone, MC, Piredda, R, Papini, A, Vessella, F, Schirone, B (2013) Application of plastid and nuclear markers to DNA barcoding of Euro-Mediterranean oaks (Quercus, Fagaceae): problems, prospects and phylogenetic implications. Bot J Linn Soc 172:478–499 CrossRefGoogle Scholar
Starr, JR, Naczi, RFC, Chouinard, BN (2009) Plant DNA barcodes and species resolution in sedges (Carex, Cyperaceae). Mol Ecol Resour 9:151–163 CrossRefGoogle ScholarPubMed
Tabacchi, M, Mantegazza, R, Spada, A, Ferrero, A (2006) Morphological traits and molecular markers for classification of Echinochloa species from Italian rice fields. Weed Sci 54:1086–1093 CrossRefGoogle Scholar
Taberlet, P, Gielly, L, Pautou, G, Bouvet, J (1991) Universal primers for amplification of three non-coding regions of chloroplast DNA. Plant Mol Biol 17:1105–1109 CrossRefGoogle ScholarPubMed
Thébaud, C, Abbott, RJ (1995) Characterization of invasive Conyza species (Asteraceae) in Europe: quantitative trait and isozyme analysis. Am J Bot 82:360–368 CrossRefGoogle Scholar
[TICA] The International Composite Alliance (2023) Global Compositae Database. https://www.compositae.org. Accessed: July 1, 2023Google Scholar
Untergasser, A, Cutcutache, I, Koressaar, T, Ye, J, Faircloth, BC, Remm, M, Rozen, SG (2012) Primer3—new capabilities and interfaces. Nucleic Acids Res 40:e115 CrossRefGoogle ScholarPubMed
[USDA] U.S. Department of Agriculture (2022) Foreign Agricultural Service. https://fas.usda.gov. Accessed: October 30, 2022Google Scholar
Van Velzen, R, Weitschek, E, Felici, G, Bakker, FT (2012) DNA barcoding of recently diverged species: relative performance of matching methods. PLoS ONE 7:e30490 CrossRefGoogle ScholarPubMed
Vidal, R, Kalsing, A, Goulart, I, Lamego, F, Christoffoleti, P (2007) Impact of temperature, light and seed depth on emergence and germination of Conyza bonariensis e Conyza canadensis resistant to glyphosate. Planta Daninha 25:309–315 CrossRefGoogle Scholar
Wang, A, Wu, H, Zhu, X, Lin, J (2018) Species identification of Conyza bonariensis assisted by chloroplast genome sequencing. Front Genet 9:374 CrossRefGoogle ScholarPubMed
Wilgenbusch, JC, Swofford, D (2003) Inferring evolutionary trees with PAUP. Curr Protoc Bioinformatics 6.4.1–6.4.28, 10.1002/0471250953.bi0604s00CrossRefGoogle Scholar
Yang, B, Zhang, Z, Yang, CQ, Wang, Y, Orr, MC, Wang, H, Zhang, AB (2022) Identification of species by combining molecular and morphological data using convolutional neural networks. Syst Biol 71:690–705 CrossRefGoogle ScholarPubMed
Yang, CQ, Lv, Q, Zhang, AB (2020) Sixteen years of DNA barcoding in China: what has been done? What can be done? Front Ecol Evol 8:e00057 CrossRefGoogle Scholar
Zelaya, IA, Owen, MDK, Van Gessel, MJ (2007) Transfer of glyphosate resistance: evidence of hybridization in Conyza (Asteraceae). Am J Bot 94:660–673 CrossRefGoogle ScholarPubMed
Supplementary material: File

Kalsing et al. supplementary material 1

Kalsing et al. supplementary material
Download Kalsing et al. supplementary material 1(File)
File 12.1 KB
Supplementary material: File

Kalsing et al. supplementary material 2

Kalsing et al. supplementary material
Download Kalsing et al. supplementary material 2(File)
File 23.1 KB
Supplementary material: File

Kalsing et al. supplementary material 3

Kalsing et al. supplementary material
Download Kalsing et al. supplementary material 3(File)
File 34.4 KB
Supplementary material: File

Kalsing et al. supplementary material 4

Kalsing et al. supplementary material
Download Kalsing et al. supplementary material 4(File)
File 437 KB