Clear effects on root system architecture of winter wheat cultivars (Triticum aestivum L.) from cultivation environment and practices.
Triticum aestivum
Precrop effect
Root growth
Root system architecture
Wheat yield
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
15 05 2024
15 05 2024
Historique:
received:
14
02
2024
accepted:
09
05
2024
medline:
16
5
2024
pubmed:
16
5
2024
entrez:
15
5
2024
Statut:
epublish
Résumé
Roots play a pivotal role in the adaption of a plant to its environment, with different root traits adapting the plant to different stresses. The environment affects the Root System Architecture (RSA), but the genetic factors determine to what extent, and whether stress brought about by extreme environmental conditions is detrimental to a specific crop. This study aimed to identify differences in winter wheat RSA caused by cultivation region and practice, in the form of preceding crop (precrop), and to identify if modern cultivars used in Sweden differ in their reaction to these environments. This was undertaken using high-throughput phenotyping to assess the RSA. Clear differences in the RSA were observed between the Swedish cultivation regions, precrop treatments, and interaction of these conditions with each other and the genetics. Julius showed a large difference between cultivars, with 9.3-17.1% fewer and 12-20% narrower seminal roots. Standardized yield decreased when grown after wheat, 23% less compared to oilseed rape (OSR), and when grown in the Southern region, 14% less than the Central region. Additionally, correlations were shown between the root number, angle, and grain yield, with different root types being correlated depending on the precrop. Cultivars on the Swedish market show differences that can be adapted to the region-precrop combinations. The differences in precrop effect on RSA between regions show global implications and a need for further assessment. Correlations between RSA and yield, based on root-type × precrop, indicate different needs of the RSA depending on the management practices and show the potential for improving crop yield through targeting genotypic and environmental conditions in a holistic manner. Understanding this RSA variance, and the mechanisms of conditional response, will allow targeted cultivar breeding for specific environments, increasing plant health and food security.
Identifiants
pubmed: 38750060
doi: 10.1038/s41598-024-61765-1
pii: 10.1038/s41598-024-61765-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
11099Subventions
Organisme : Sweden SLU Grogrund
ID : HeRo - Healthy Roots: Development of tools for the selection of robust cultivars in Swedish plant breeding, with focus on the root system
Organisme : Sweden SLU Grogrund
ID : HeRo - Healthy Roots: Development of tools for the selection of robust cultivars in Swedish plant breeding, with focus on the root system
Organisme : Sweden SLU Grogrund
ID : HeRo - Healthy Roots: Development of tools for the selection of robust cultivars in Swedish plant breeding, with focus on the root system
Organisme : Sweden SLU Grogrund
ID : HeRo - Healthy Roots: Development of tools for the selection of robust cultivars in Swedish plant breeding, with focus on the root system
Informations de copyright
© 2024. The Author(s).
Références
Troedsson, T. & Wiberg, M. The Royal Academy of Agricultural and Forest (Stockholm, 1986).
Semenov, M. A., Stratonovitch, P., Alghabari, F. & Gooding, M. J. Adapting wheat in Europe for climate change. J. Cereal Sci. 59, 245–256. https://doi.org/10.1016/j.jcs.2014.01.006 (2014).
doi: 10.1016/j.jcs.2014.01.006
pubmed: 24882934
pmcid: 4026126
Reynolds, M. et al. Achieving yield gains in wheat. Plant Cell Environ. 35, 1799–1823. https://doi.org/10.1111/j.1365-3040.2012.02588.x (2012).
doi: 10.1111/j.1365-3040.2012.02588.x
pubmed: 22860982
Kanbar, A., Toorchi, M. & Shashidhar, H. E. Relationship between root and yield morphological characters in rainfed low land rice (Oryza sativa L.). Cereal Res. Commun. 37, 261–268 (2009).
doi: 10.1556/CRC.37.2009.2.14
Iqbal, S. et al. Root morphological adjustments of crops to improve nutrient use efficiency in limited environments. Commun. Soil Sci. Plant Anal. 51, 2452–2465. https://doi.org/10.1080/00103624.2020.1836199 (2020).
doi: 10.1080/00103624.2020.1836199
Ando, K., Grumet, R., Terpstra, K. & Kelly, J. Manipulation of plant architecture to enhance crop disease control. CABI Rev. 2007, 8 (2007).
Manske, G. & Vlek, P. L. G. In Plant Roots: The Hidden Half 382–398 (Marcel Dekker, 2002).
Khan, M. A., Gemenet, D. C. & Villordon, A. Root system architecture and abiotic stress tolerance: Current knowledge in root and tuber crops. Front. Plant Sci. https://doi.org/10.3389/fpls.2016.01584 (2016).
doi: 10.3389/fpls.2016.01584
pubmed: 28144244
pmcid: 5183611
Ober, E. S. et al. Wheat root systems as a breeding target for climate resilience. Theor. Appl. Genet. 134, 1645–1662. https://doi.org/10.1007/s00122-021-03819-w (2021).
doi: 10.1007/s00122-021-03819-w
pubmed: 33900415
pmcid: 8206059
Osmont, K. S., Sibout, R. & Hardtke, C. S. Hidden branches: Developments in root system architecture. Ann. Rev. Plant Biol. 58, 93–113. https://doi.org/10.1146/annurev.arplant.58.032806.104006 (2007).
doi: 10.1146/annurev.arplant.58.032806.104006
McGrail, R. K. & McNear, D. H. Two centuries of breeding has altered root system architecture of winter wheat. Rhizosphere 19, 100411. https://doi.org/10.1016/j.rhisph.2021.100411 (2021).
doi: 10.1016/j.rhisph.2021.100411
Zhu, Y. H., Weiner, J., Yu, M. X. & Li, F. M. Evolutionary agroecology: Trends in root architecture during wheat breeding. Evolut. Appl. 12, 733–743. https://doi.org/10.1111/eva.12749 (2019).
doi: 10.1111/eva.12749
Pariyar, S. R. et al. Variation in root system architecture among the founder parents of two 8-way magic wheat populations for selection in breeding. Agronomy 11, 2452 (2021).
doi: 10.3390/agronomy11122452
Xie, Q., Fernando, K. M. C., Mayes, S. & Sparkes, D. L. Identifying seedling root architectural traits associated with yield and yield components in wheat. Ann. Bot. 119, 1115–1129. https://doi.org/10.1093/aob/mcx001 (2017).
doi: 10.1093/aob/mcx001
pubmed: 28200109
pmcid: 5604548
Zhang, X. et al. Multivariate analyses of root phenotype and dynamic transcriptome underscore valuable root traits and water-deficit responsive gene networks in maize. Plant Direct 3, e00130. https://doi.org/10.1002/pld3.130 (2019).
doi: 10.1002/pld3.130
Alahmad, S. et al. A major root architecture QTL responding to water limitation in durum wheat. Front. Plant Sci. https://doi.org/10.3389/fpls.2019.00436 (2019).
doi: 10.3389/fpls.2019.00436
pubmed: 31024600
pmcid: 6468307
Omori, F. & Mano, Y. QTL mapping of root angle in F
doi: 10.3117/plantroot.1.57
de la Cruz Jiménez, J. et al. Root length is proxy for high-throughput screening of waterlogging tolerance in Urochloa spp. grasses. Funct. Plant Biol. 48, 411–421. https://doi.org/10.1071/FP20200 (2021).
doi: 10.1071/FP20200
pubmed: 33287947
Perkins, A. C. & Lynch, J. P. Increased seminal root number associated with domestication improves nitrogen and phosphorus acquisition in maize seedlings. Ann. Bot. 128, 453–468. https://doi.org/10.1093/aob/mcab074 (2021).
doi: 10.1093/aob/mcab074
pubmed: 34120166
pmcid: 8414917
Liu, Z. et al. Enhanced crown root number and length confers potential for yield improvement and fertilizer reduction in nitrogen-efficient maize cultivars. Field Crops Res. 241, 107562. https://doi.org/10.1016/j.fcr.2019.107562 (2019).
doi: 10.1016/j.fcr.2019.107562
Liu, H., Colombi, T., Jäck, O., Westerbergh, A. & Weih, M. Linking wheat nitrogen use to root traits: Shallow and thin embryonic roots enhance uptake but reduce conversion efficiency of nitrogen. Field Crops Res. 285, 108603. https://doi.org/10.1016/j.fcr.2022.108603 (2022).
doi: 10.1016/j.fcr.2022.108603
Schneider, H. M., Yang, J. T., Brown, K. M. & Lynch, J. P. Nodal root diameter and node number in maize (Zea mays L.) interact to influence plant growth under nitrogen stress. Plant Direct 5, e00310. https://doi.org/10.1002/pld3.310 (2021).
doi: 10.1002/pld3.310
pubmed: 33748655
pmcid: 7963125
Preissel, S., Reckling, M., Schläfke, N. & Zander, P. Magnitude and farm-economic value of grain legume pre-crop benefits in Europe: A review. Field Crops Res. 175, 64–79. https://doi.org/10.1016/j.fcr.2015.01.012 (2015).
doi: 10.1016/j.fcr.2015.01.012
White, R. G. & Kirkegaard, J. A. The distribution and abundance of wheat roots in a dense, structured subsoil–implications for water uptake. Plant Cell Environ. 33, 133–148. https://doi.org/10.1111/j.1365-3040.2009.02059.x (2010).
doi: 10.1111/j.1365-3040.2009.02059.x
pubmed: 19895403
Köpke, U. & Nemecek, T. Ecological services of faba bean. Field Crops Res. 115, 217–233. https://doi.org/10.1016/j.fcr.2009.10.012 (2010).
doi: 10.1016/j.fcr.2009.10.012
Han, E. et al. Can precrops uplift subsoil nutrients to topsoil?. Plant Soil 463, 329–345. https://doi.org/10.1007/s11104-021-04910-3 (2021).
doi: 10.1007/s11104-021-04910-3
Friberg, H., Persson, P., Jensen, D. F. & Bergkvist, G. Preceding crop and tillage system affect winter survival of wheat and the fungal communities on young wheat roots and in soil. FEMS Microbiol. Lett. https://doi.org/10.1093/femsle/fnz189 (2019).
doi: 10.1093/femsle/fnz189
pubmed: 31504475
pmcid: 6759068
Beuters, P., Eichert, T. & Scherer, H. W. Influence of pre-crop and root architecture on the mobilization of non-exchangeable NH
doi: 10.17221/260/2014-pse
Griffiths, M. et al. Optimisation of root traits to provide enhanced ecosystem services in agricultural systems: A focus on cover crops. Plant Cell Environ. 45, 751–770. https://doi.org/10.1111/pce.14247 (2022).
doi: 10.1111/pce.14247
pubmed: 34914117
pmcid: 9306666
Lombardi, M., De Gara, L. & Loreto, F. Determinants of root system architecture for future-ready, stress-resilient crops. Physiol. Plant. 172, 2090–2097. https://doi.org/10.1111/ppl.13439 (2021).
doi: 10.1111/ppl.13439
pubmed: 33905535
pmcid: 8360026
Trachsel, S., Kaeppler, S. M., Brown, K. M. & Lynch, J. P. Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant Soil 341, 75–87. https://doi.org/10.1007/s11104-010-0623-8 (2011).
doi: 10.1007/s11104-010-0623-8
Fradgley, N. et al. Effects of breeding history and crop management on the root architecture of wheat. Plant Soil 452, 587–600. https://doi.org/10.1007/s11104-020-04585-2 (2020).
doi: 10.1007/s11104-020-04585-2
pubmed: 32713967
pmcid: 7371663
Hobson, D. J., Harty, M. A., Langton, D., McDonnell, K. & Tracy, S. R. The establishment of winter wheat root system architecture in field soils: The effect of soil type on root development in a temperate climate. Soil Use Manag. https://doi.org/10.1111/sum.12795 (2022).
doi: 10.1111/sum.12795
pubmed: 37033407
pmcid: 10078784
Koevoets, I. T., Venema, J. H., Elzenga, J. T. M. & Testerink, C. Roots withstanding their environment: Exploiting root system architecture responses to abiotic stress to improve crop tolerance. Front. Plant Sci. https://doi.org/10.3389/fpls.2016.01335 (2016).
doi: 10.3389/fpls.2016.01335
pubmed: 27630659
pmcid: 5005332
Rich, S. M. & Watt, M. Soil conditions and cereal root system architecture: review and considerations for linking darwin and weaver. J. Exp. Bot. 64, 1193–1208. https://doi.org/10.1093/jxb/ert043 (2013).
doi: 10.1093/jxb/ert043
pubmed: 23505309
Wang, Y., Zhang, F. & Marschner, P. Soil pH is the main factor influencing growth and rhizosphere properties of wheat following different pre-crops. Plant Soil 360, 271–286. https://doi.org/10.1007/s11104-012-1236-1 (2012).
doi: 10.1007/s11104-012-1236-1
Bertollo, A. M. et al. Precrops alleviate soil physical limitations for soybean root growth in an Oxisol from Southern Brazil. Soil Tillage Res. 206, 104820. https://doi.org/10.1016/j.still.2020.104820 (2021).
doi: 10.1016/j.still.2020.104820
Perkons, U. et al. Root-length densities of various annual crops following crops with contrasting root systems. Soil Tillage Res. 137, 50–57. https://doi.org/10.1016/j.still.2013.11.005 (2014).
doi: 10.1016/j.still.2013.11.005
Roy, J. et al. Legacy effects of pre-crop plant functional group on fungal root symbionts of barley. Ecol. Appl. 31, e02378. https://doi.org/10.1002/eap.2378 (2021).
doi: 10.1002/eap.2378
pubmed: 33988274
Vilich, V. Crop rotation with pure stands and mixtures of barley and wheat to control stem and root rot diseases. Crop Protect. 12, 373–379. https://doi.org/10.1016/0261-2194(93)90081-S (1993).
doi: 10.1016/0261-2194(93)90081-S
Lynch, J. Root architecture and plant productivity. Plant Physiol. 109, 7–13. https://doi.org/10.1104/pp.109.1.7 (1995).
doi: 10.1104/pp.109.1.7
pubmed: 12228579
pmcid: 157559
Nguyen, V. L. & Stangoulis, J. Variation in root system architecture and morphology of two wheat genotypes is a predictor of their tolerance to phosphorus deficiency. Acta Physiol. Plant. 41, 109. https://doi.org/10.1007/s11738-019-2891-0 (2019).
doi: 10.1007/s11738-019-2891-0
Loades, K. W., Bengough, A. G., Bransby, M. F. & Hallett, P. D. Biomechanics of nodal, seminal and lateral roots of barley: Effects of diameter, waterlogging and mechanical impedance. Plant Soil 370, 407–418. https://doi.org/10.1007/s11104-013-1643-y (2013).
doi: 10.1007/s11104-013-1643-y
Volkmar, K. M. Water stressed nodal roots of wheat: Effects on leaf growth. Funct. Plant Biol. 24, 49–56. https://doi.org/10.1071/PP96063 (1997).
doi: 10.1071/PP96063
Smith, M. E. et al. Increasing crop rotational diversity can enhance cereal yields. Commun. Earth Environ. 4, 89. https://doi.org/10.1038/s43247-023-00746-0 (2023).
doi: 10.1038/s43247-023-00746-0
Xu, F. et al. Genome-wide association study on seminal and nodal roots of wheat under different growth environments. Front. Plant Sci. https://doi.org/10.3389/fpls.2020.602399 (2021).
doi: 10.3389/fpls.2020.602399
pubmed: 35211127
pmcid: 8750863
Středa, T., Dostál, V., Horáková, V. & Chloupek, O. Effective use of water by wheat varieties with different root system sizes in rain-fed experiments in central Europe. Agric. Water Manage. 104, 203–209. https://doi.org/10.1016/j.agwat.2011.12.018 (2012).
doi: 10.1016/j.agwat.2011.12.018
Izumi, Y., Yoshida, T. & Iijima, M. Effects of subsoiling to the non-tilled field of wheat-soybean rotation on the root system development, water uptake, and yield. Plant Prod. Sci. 12, 327–335. https://doi.org/10.1626/pps.12.327 (2009).
doi: 10.1626/pps.12.327
van der Bom, F. J. T. et al. Root angle, phosphorus, and water: Interactions and effects on durum wheat genotype performance in drought-prone environments. Plant Soil https://doi.org/10.1007/s11104-023-05966-z (2023).
doi: 10.1007/s11104-023-05966-z
Kirschner, G. K. et al. Genetic regulation of the root angle in cereals. Trends Plant Sci. https://doi.org/10.1016/j.tplants.2024.01.008 (2024).
doi: 10.1016/j.tplants.2024.01.008
pubmed: 38402016
Si, Z., Delhaize, E., Hendriks, P.-W. & Li, X. Differences in root morphologies of contrasting wheat (Triticum aestivum) genotypes are robust of a drought treatment. Plants 12, 275. https://doi.org/10.3390/plants12020275 (2023).
doi: 10.3390/plants12020275
pubmed: 36678988
pmcid: 9863919
Zhao, J. et al. Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers. Nat. Commun. 13, 4926. https://doi.org/10.1038/s41467-022-32464-0 (2022).
doi: 10.1038/s41467-022-32464-0
pubmed: 35995796
pmcid: 9395539
Rebetzke, G. J. et al. Genotypic variation and covariation in wheat seedling seminal root architecture and grain yield under field conditions. Theor. Appl. Genet. https://doi.org/10.1007/s00122-022-04183-z (2022).
doi: 10.1007/s00122-022-04183-z
pubmed: 35925366
Fang, Y. et al. Rotation with oilseed rape as the winter crop enhances rice yield and improves soil indigenous nutrient supply. Soil Tillage Res. 212, 105065. https://doi.org/10.1016/j.still.2021.105065 (2021).
doi: 10.1016/j.still.2021.105065
Materechera, S. A., Alston, A. M., Kirby, J. M. & Dexter, A. R. Influence of root diameter on the penetration of seminal roots into a compacted subsoil. Plant Soil 144, 297–303. https://doi.org/10.1007/BF00012888 (1992).
doi: 10.1007/BF00012888
Arnhold, J., Grunwald, D., Kage, H. & Koch, H.-J. No differences in soil structure under winter wheat grown in different crop rotational positions. Can. J. Soil Sci. 103, 642–649. https://doi.org/10.1139/cjss-2023-0030 (2023).
doi: 10.1139/cjss-2023-0030
Kuhlmann, H. & Barraclough, P. B. Comparison between the seminal and nodal root systems of winter wheat in their activity for N and K uptake. Pflanzenernährung Bodenkunde 150, 24–30. https://doi.org/10.1002/jpln.19871500106 (1987).
doi: 10.1002/jpln.19871500106
White, C. A., Sylvester-Bradley, R. & Berry, P. M. Root length densities of UK wheat and oilseed rape crops with implications for water capture and yield. J. Exp. Bot. 66, 2293–2303. https://doi.org/10.1093/jxb/erv077 (2015).
doi: 10.1093/jxb/erv077
pubmed: 25750427
pmcid: 4986724
Saleem, M., Law, A. D., Sahib, M. R., Pervaiz, Z. H. & Zhang, Q. Impact of root system architecture on rhizosphere and root microbiome. Rhizosphere 6, 47–51. https://doi.org/10.1016/j.rhisph.2018.02.003 (2018).
doi: 10.1016/j.rhisph.2018.02.003
Bedő, Z. & Láng, L. In Alien Introgression in Wheat: Cytogenetics, Molecular Biology, and Genomics 77–101 (Springer, 2015).
doi: 10.1007/978-3-319-23494-6_3
Kahiluoto, H. et al. Decline in climate resilience of European wheat. PNAS 116, 123–128. https://doi.org/10.1073/pnas.1804387115 (2019).
doi: 10.1073/pnas.1804387115
pubmed: 30584094
Reidsma, P., Ewert, F., Lansink, A. O. & Leemans, R. Adaptation to climate change and climate variability in European agriculture: The importance of farm level responses. Eur. J. Agron. 32, 91–102. https://doi.org/10.1016/j.eja.2009.06.003 (2010).
doi: 10.1016/j.eja.2009.06.003
van Duijnen, R., Roy, J., Härdtle, W. & Temperton, V. M. Precrop functional group identity affects yield of winter barley but less so high carbon amendments in a mesocosm experiment. Front. Plant Sci. 9, 912. https://doi.org/10.3389/fpls.2018.00912 (2018).
doi: 10.3389/fpls.2018.00912
pubmed: 30018627
pmcid: 6037990
Boyle, J. GeoRange: Calculating Geographic Range from Occurrence Data (2017).
SLU Fältforsk, Jordbruksverket & Hushållningsällskapen. Lantmet. https://www.ffe.slu.se/lm/LMHome.cfm?LMSUB=0&ADM=0 (2023).
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2013).
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed—Effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).
doi: 10.18637/jss.v067.i01
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmertest package: Tests in linear mixed effects models. J. Stat. Softw. 82, 1–26. https://doi.org/10.1637/jss.v082.i13 (2017).
doi: 10.1637/jss.v082.i13
Halekoh, U. & Højsgaard, S. A Kenward-roger approximation and parametric bootstrap methods for tests in linear mixed models—The R package pbkrtest. J. Stat. Softw. 59, 1–32. https://doi.org/10.18637/jss.v059.i09 (2014).
doi: 10.18637/jss.v059.i09
Lenth, R. V. emmeans: Estimated Marginal Means, aka Least-Squares Means (2022).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).
doi: 10.1007/978-3-319-24277-4
Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots (2023).
Hope, R. M. Rmisc: Ryan Miscellaneous (2013).