Roots phenotyping in maize aiming drought tolerance: A review
DOI:
https://doi.org/10.33448/rsd-v10i8.17265Keywords:
Root system; Phenopytic selection; Zea mays.Abstract
It is known that plants have acquired and adapted tolerance mechanisms, such as: more extensive root system and greater root/shoot ratio, changes in stomatal frequency behavior, thicker leaf cuticle, changes in leaf angle, accumulation of metabolites, osmotic adjustment and resistance to cell dehydration. These adaptive modifications can be specific to each genotype, and involve several mechanisms that can be efficient in water use. Thus, the objective of the present work was to show that root phenotyping techniques have been shown to be the most efficient driving tools of selection for drought tolerance in corn. For this, works from the SciELO database, Google Scholar, academic articles and published books were used, relevant to the topic in question. And based on these studies, it was possible to understand that the acquisition of water and nutrients by the root system and its capacity to exploit the soil, form the basis for plant development, being a response factor for the beginning of development, and determinant for the grains yield. Furthermore, with root phenotyping there are selection advantages through one more criterion, other than field phenotyping. Thus, it is possible to admit a saving of time and financial investment, in addition to the development of technology with the validation of root phenotyping.
References
Azevedo, C. F., Resende, M. D. V., Silva, F. F., Viana, J. M. S., Valente, M. S. F., Resende, J. R. M. F. R. & Muñoz, P. (2015). Ridge, Lasso and Bayesian aditive dominance genomic models. BMC Genet, 16, 1 - 13.
Bellian, J. A., Kerans, C., & Jennette, D. C. (2005). Digital outcrop models: applications of terrestrial scanning lidar technology in stratigraphic modeling. Journal of sedimentary research, 75 (2), 166 - 176.
Berger, B., Parent, B. & Tester, M. (2010). High-throughput shoot imaging to study drought responses. Journal of experimental botany, 61 (13), 3519 - 3528.
Blum, A. (2009). Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Field Crops Research, 112, 119 - 123.
Bruce, W. B., Edmeades, G. O. & Barker, T. C. (2002). Molecular and physiological approaches to maize improvement for drought tolerance. Journal of experimental botany, 53 (366), 13 - 25.
Bouma, T. J., Nielsen, K. L. & Koutstaal, B. A. S. (2000). Sample preparation and scanning protocol for computerised analysis of root length and diameter. Plant and Soil, 218 (1), 185 - 196.
Burton, A. L. & Lynch, J. P. (2010). Phenotypic Evaluation and Genetic Basis of Anatomical and Architectural Traits in the Genus Zea. Tese de doutorado. The Pennsylvania State University, Pennsylvania, United States of America.
CONAB - Companhia Nacional de Abastecimento. 8º Boletim de Monitoramento Agrícola. Cultivos de verão (2ª safra) 2018/2019, cultivos de inverno (Safra 2019). Acessado em 01 junho de 2021, em https://www.conab.gov.br/info-agro/safras/graos
Cortes, D. F. M., Catarina, R. S., Barros, G. B. D. A., Arêdes, F. A. S., Silveira, S. F. D., Ferreguetti, G. A., Ramos, H. C. C., Viana, A. P. & Pereira, M. G. (2017). Model assisted phenotyping by digital images in papaya breeding program. Scientia Agricola, 74 (4), 294 - 302.
Dias, K. O. G., Gezan, S. A., Guimarães, C. T., Nazarian, A., Silva, L. C., Parentoni, S. N., Guimarães, P. E. O., Anoni, C. O., Pádua, J. M. V., Pinto, M. O., Noda, R. W., Ribeiro, C. A. G., Magalhães, J. V., Garcia, A. A. F., Souza, J. C., Guimarães, L. J. M. & Pastina, M. M. (2018). Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials. Heredity, 121, 24 - 37.
Dhondt, S., Wuyts, N. & Inzé, D. Cell to whole-plant phenotyping: the best is yet to come. (2013). Trends in Plant Science, 18 (8), 428 - 439.
Durães, F. O. M., Santos, M. X., Gama E. E. G., Magalhães, P. C., Albuquerque, P. E. P. & Guimarães, C. T. Fenotipagem Associada à Tolerância a Seca em Milho para Uso em Melhoramento, Estudos Genômicos e Seleção Assistida por Marcadores. Acessado em 05 de junho de 2021, em https://www.infoteca.cnptia.embrapa.br/infoteca/bitstream/doc/487708/1/Circ39.pdf
Esser, H. G., Carminati, A., Vontobel, P., Lehmann, E. H., & Oswald, S. E. (2010). Neutron radiography and tomography of water distribution in the root zone. Journal of Plant Nutrition and Soil Science, 173 (5), 757 - 764.
Filho, O. M. & Neto, H. V. (1999). Processamento de Imagens Digital de Imagens. Editora Brasport.
Fort, F., Jouany, C. & Cruz, P. (2012). Root and leaf functional trait relations in Poaceae species: implications of differing resource acquisition strategies. Journal of Plant Ecology, 2, 1 - 9.
Fritsche-Neto, R. & Borém, A. (2011). Melhoramento de plantas para condições de estresses abióticos. Editora UFV, Brasil.
Fritsche-Neto, R. & Borém, A. (2015). Fenômica. Como a Fenotipagem de Próxima Geração Está Revolucionando o Melhoramento de Plantas. Editora UFV.
Guimarães, P. H. (2017). Método para fenotipagem de raiz e mapeamento associativo para tolerância à deficiência hídrica em arroz. Tese de Doutorado, Universidade Federal de Goiás, Goiânia, Brasil.
Han, C. & Young, S. L. (2014). "Root Growth of Two Perennial Grass Types and Musk Thistle (Carduus nutans) in Temperate Grasslands of North America". Invasive Plant Science and Management, 7 (3), 387 - 397.
Hao, Y., Chen, Z., Wang, Y., Bland, D., Buck, J., Brown-Guedira, G. & Johnson, J. (2011). Characterization of a major QTL for adult plant resistance to stripe rust in US soft red winter wheat. Theoretical and applied genetics, 123 (8), 1401 - 1411.
Hodge, R., Brasington, J., & Richards, K. (2009). Analysing laser‐scanned digital terrain models of gravel bed surfaces: linking morphology to sediment transport processes and hydraulics. Sedimentology, 56 (7), 2024 - 2043.
Hund, A., Trachsel, S. & Stamp, P. (2009). Growth of axile and lateral roots of maize: I development of a phenotying platform. Plant and Soil, 325 (1), 335 - 349.
Jorge, L. A. de C. & Silva, D. J. C. B. (2010). Safira: Manual de utilização. Editora Embrapa Instrumentação-Livro científico.
Kamoshita A., Deshmukh, V. & Amezquita N. (2019). User manual for liner core sampler and WinRhizo for root analysis. SATREPS, Colombia.
Krchov, L. M., Gordillo, G. A. & Bernardo, R. (2015). Multienvironment validation of the effectiveness of phenotypic and genomewide selection within biparental maize populations. Crop Science, 55 (3), 1068-1075.
Liu, G., Frescher, G. T., Pan, X., Cornelissen, J. H. C., Li, Y. & Dong, M. (2010). Coordinated variation in leaf and root traits across multiple spatial scales in Chinese semi-arid and arid ecosystems. New Phytologist, 188, 543 - 553.
Lynch, J. P. (2015). Root phenes that reduce the metabolic costs of soil exploration: opportunities for 21st century agriculture. Plant, Cell and Environment, 38, 1775 - 1784.
Magalhães, P. C., Souza, T. C. & Cantão, F. R. O. (2011). Early evaluation of root morphology of maize genotypes under phosphorus deficiency. Plant, Soil and Environment, 57 (3), 135 - 138.
Magalhães, P.C. & Durães, F.O.M. (2006). Fisiologia da produção de milho. Embrapa Milho e Sorgo. Acessado em 09 de junho de 2021, em https://www.infoteca.cnptia.embrapa.br/bitstream/doc/490408/1/Circ76.pdf
Magalhães, P.C., Lavinsky, A. O., Ávila, R. G., Alves, J. C., Melo, M. D., Junior, C. C. G. & Melo, H. F. (2014). Caracterização radicular e dos componentes de produtividade em quatro genótipos de milho cultivados sob déficit hídrico. Boletim de pesquisa e desenvolvimento. 111. Sete Lagoas: Embrapa Milho e Sorgo. Acessado em 10 de junho de 2021, em https://ainfo.cnptia.embrapa.br/digital/bitstream/item/122152/1/bol-111.pdf
Mairhofer, S., Zappala, S., Tracy, S., Sturrock, C., Bennett, M. J., Mooney, S. J., & Pridmore, T. P. (2013). Recovering complete plant root system architectures from soil via X-ray μ-computed tomography. Plant methods, 9 (1), 1 - 7.
Mairhofer, S., Zappala, S., Tracy, S. R., Sturrock, C., Bennett, M., Mooney, S. J. & Pridmore, T. (2012). RooTrak: automated recovery of three-dimensional plant root architecture in soil from X-ray microcomputed tomography images using visual tracking. Plant physiology, 158 (2), 561 - 569.
Mano Y., Omori F., Takamizo T., Kindiger B., Bird R.M., Loaisiga C.H. & Takahashi H. (2007). QTL mapping of root aerenchyma formation in seedlings of a maize x rare teosinte ‘Zeanicaraguensis’ cross. Plant and Soil, 295, 103 - 113.
Messmer, R., Y. Fracheboud, & M. Bänziger. (2009). Drought stress and tropical maize: QTL-by environment interactions and stability of QTLs across environments for yield components and secondary traits. Theory Appl Genetic. 119, 913 - 930.
Moraes, M. T. (2017). Modelagem do crescimento radicular de milho e soja sujeito a estresses hídrico e mecânico em latossolo. Tese de Doutorado, Universidade Federal do Rio Grande do Sul, Faculdade de Agronomia. Porto Alegre, Brasil.
Neto, A. T., & Latado, R. R. (2007). Indução de mutação: ampliação da variabilidade genética para o melhoramento de ornamentais. Ornamental Horticulture, 13, 2101 - 2110.
Pace, J., N. Lee, H.S., Naik, B., Ganapathy, S. & Lübberstedt, T. (2014). Analysis of maize (Zea mays L.) seedlingroots with the high-throughput image analysis tool ARIA (AutomaticRoot Image Analysis). PLoS One, 9 (9), 108 – 255.
Pedrotti, A., Pauletto, E. A., Crestana, S., Cruvinel, P. E., Vaz, C. M. P., Naime, J. D. M. & Silva, A. M. D. (2003). Tomografia computadorizada aplicada a estudos de um Planossolo. Pesquisa Agropecuária Brasileira., Brasília, 38 (7), 819 - 826.
Pereira, A. S., Shitsuka, D. M., Parreira, F. J., & Shitsuka, R. (2018). Metodologia da pesquisa científica. [free e-book]. Santa Maria/RS. Ed. UAB/NTE/UFSM.
Pierret, A., Gonkhamdee, S., Jourdan, C. & Maeght, J. (2013). "IJ_Rhizo: an open-source software to measure scanned images of root samples", Plant and Soil, 373, 531–539.
Pound, M. P., French, A. P., Atkinson, J. A., Wells, D. M., Bennett, M. J. & Pridmore, T. (2013). RootNav: navigating images of complex root architectures. Plant physiology, 162 (4), 1802 - 1814.
Saengwilai P. (2013) Root traits for efficient nitrogen acquisition and genomewide association study of root anatomical traits in maize (Zea mays L.). Tese de doutorado. The Pennsylvania State University, Pennsylvania, United States of America.
Souza, T. C., Castro, E. M., Magalhães, P. C., Lino, L. O., Alves, E. T. & Albuquerque, P. (2013). Morphophysiology, morphoanatomy, and grain yield under field conditions for two maize hybrids with contrasting response to drought stress. Acta Physiologia e Plantarum, 35, 3201 - 3211.
Souza, T. C., Magalhães, P. C., Castro, E. M. de, Durte, V. P. & Lavisky, A. O. (2016). Corn root morphoanatomy at different development stages and yield under water stress. Pesquisa Agropecuária Brasileira, 51 (4), 330 - 339.
Trachsel, S., Stamp, P. & Hund, A. (2010). Growth of axile and lateral roots of maize: Response to desiccation stress induced by polyethylene glycol 8000. Maydica, 55, 101 - 109.
Tracy, S. R., Black, C. R., Roberts, J. A., MCneill, A., Davidson, R., Tester, M. & Mooney, S. J. (2012). Quantifying the effect of soil compaction on three varieties of wheat (Triticum aestivum L.) using X-ray Micro Computed Tomography (CT). Plant and Soil, 353 (1), 195 - 208.
UK Government, 2011. Foresight project on global food and farming futures: Trends in food demand production. Acessado em 29 de maio de 2021, em https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/288329/11-546-future-of-food-and-farming-report.pdf
USDA. Safra Mundial de Milho. 2015/2016, 11º Levantamento. Acessado em 11 de junho de 2021, em https://www.fiesp.com.br/indices-pesquisas-e-publicacoes/safra-mundial-de-milho-2/attachment/file-20210611193905-boletimmilhojunho2021/
Valadão, F. C. D. A., Weber, O. L. D. S., Valadão Júnior, D. D., Scapinelli, A., Deina, F. R. & Bianchini, A. (2015). Adubação fosfatada e compactação do solo: sistema radicular da soja e do milho e atributos físicos do solo. Revista Brasileira de Ciência do Solo, 39 (1), 243 - 255.
Vencovsky, R. & Ramalho, M. A. P. (2006). Contribuições do melhoramento genético no Brasil. In: PATERNIANI, E. (Ed.). Ciência, agricultura e sociedade (41 – 74). Embrapa Milho e Sorgo, Brasília.
Walter, A., Liebisch, F. & Hund, A. (2015). Plant phenotyping: from bean weighing to image analysis. Plant Methods, 11 (14), 1 - 11.
Yang, P. M., Huang, Q. C., Qin, G. Y., Zhao, S. P. & Zhou, J. G. (2014). Different drought-stress responses in photosynthesis and reactive oxygen metabolism between autotetraploid and diploid rice. Photosynthetica, 52 (2), 193 - 202.
Ziyomo, C. & Bernardo, R. (2013). Drought tolerance in maize-indirect selection through secondary traits versus genome wide selection. Crop Science, 52, 1269 - 1275.
Zuffo, A. M., Aguilera, J. G. & Oliveira, B. R. (2019). Ciência em foco. Editora Pantanal.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Crislene Vieira dos Santos; Flávio Araújo de Moraes; Luciane Gonçalves Torres; Ruane Alice da Silva; Karla Jorge da Silva; Silvino Guimarães Moreira; Cícero Beserra de Menezes; Aluízio Borém
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
