ORIGINAL ARTICLE
Understanding nutrient competition between Echinochloa spp. and Oryza sativa L.
1
Department of Crop Protection, Federal University of Santa Maria, Santa Maria, Brazil
2
Department of Soil Science, Federal University of Pelotas, Pelotas, Brazil
3
Department of Crop Production, Federal University of Santa Maria, Santa Maria, Brazil
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
Submission date: 2020-03-04
Acceptance date: 2020-04-29
Online publication date: 2020-08-18
Corresponding author
André da Rosa Ulguim
Department of Crop Protection, Federal University of Santa Maria, Roraima Ave, 97105-900, Santa Maria, Brazil
Department of Crop Protection, Federal University of Santa Maria, Roraima Ave, 97105-900, Santa Maria, Brazil
Journal of Plant Protection Research 2020;60(3):296-310
KEYWORDS
TOPICS
ABSTRACT
Weed competition in southern Brazil is one of the main limiting factors for Oryza sativa L. (flooded rice) yield. Echinochloa spp. (barnyardgrass) occurs at a high frequency. Although the potential for weed interference in this cereal is well known, there is little information available about the impact of nutrient competition on rice. Thus, this study aimed to evaluate the relationship between the increase of the barnyardgrass population and the development and nutrition of flooded rice plants at different stages of development. The treatments consisted of growing populations of barnyardgrass competing with the crop from stage V4, which were: 0, 1, 6, 13, 100 and 200 plants · m−2. The experimental design was randomized blocks with two replications, and the experimental units were plots 1.53 m wide by 5 m long. Plant biomass, nutrient uptake and loss of productivity were determined with three replications. An increase in the barnyardgrass population reduced the dry mass of rice leaves and stems, regardless of the evaluation period and the vegetative or reproductive period. Barnyardgrass plants had a significant impact on the reduced grain yield of
a flooded rice crop, mainly due to high nutrient competitiveness, especially N in the vegetative period and K in the reproductive period. Barnyardgrass caused a loss of yield by
unit · m−2 of 1.13%. The competition for N between rice and barnyardgrass plants was higher in the vegetative period, while for K, Ca and Mg the highest competition occurred in the reproductive period.
CONFLICT OF INTEREST
The authors have declared that no conflict of interests exist.
REFERENCES (31)
1.
Afifi A., Swanton C. 2012. Early physiological mechanisms of weed competition. Weed Science 60 (4): 542–551. DOI: https://doi.org/10.1614/WS-D-1....
2.
Agostinetto D., Galon L., Moraes P., Rigoli R., Tironi S., Panozzo L. 2008. Relative competitivity between flooded rice cultivars and Echinochloa spp. Planta Daninha 26 (4): 757−766. DOI: http://dx.doi.org/10.1590/S010....
3.
Agostinetto D., Galon L., Moraes P., Tironi S., Dal Magro T., Vignolo G. 2007. Barnyardgrass (Echinochloa spp.) interference in flooded rice (Oryza sativa) in function of irrigation timing. Planta Daninha 25 (4): 689−696. DOI: http://dx.doi.org/10.1590/S010....
4.
Agostinetto D., Galon L., Silva J., Tironi S., Andres A. 2010. Interference and economic weed threshold (Ewt) of barnyardgrass on rice as a function of crop plant arrangement. Planta Daninha 28 (n.spe): 993–1003. DOI: http://dx.doi.org/10.1590/S010....
5.
Burgos N., Norman R., Gealy D., Black H. 2006. Competitive N uptake between rice and weedy rice. Field Crops Research 99 (2−3): 96−105. DOI: https://doi.org/10.1016/j.fcr.....
6.
Cathcart R., Swanton C. 2004. Nitrogen and green foxtail (Setaria viridis) competition effects on corn growth and development. Weed Science 52 (6): 1039−1049. DOI: https://doi.org/10.1614/WS-03-....
7.
Chauhan B. 2012. Weed ecology and weed management strategies for dry-seeded rice in Asia. Weed Technology 26 (1): 1–13. DOI: https://doi.org/10.1614/WT-D-1....
8.
Chauhan B., Abugho S. 2013. Effects of water regime, nitrogen fertilization, and rice plant density on growth and reproduction of lowland weed Echinochloa crus-galli. Crop Protection 54: 142–147. DOI: http://dx.doi.org/10.1016/j.cr....
9.
Chauhan B.S., Johnson D.E. 2010. Responses of rice flatsedge (Cyperus iria) and barnyardgrass (Echinochloa crus-gali) to rice interference. Weed Science 58 (3): 204–208. DOI: https://doi.org/10.1614/WS-D-0....
10.
Chauhan B.J., Johnson D.E. 2011. Relative importance of shoot and root competition in dry-seeded rice growing with Junglerice (Echinochloa colona) and Ludwigia (Ludwigia hyssopifolia). Weed Science 58 (3): 295–299. DOI: https://doi.org/10.1614/WS-D-0....
11.
Che S., Zhao B., Li Y., Yuan L., Lin Z., Hu S., Shen B. 2016. Nutrient uptake requirements with increasing grain yield for rice in China. Journal of Integrative Agriculture 15 (4): 907−917. DOI: https://doi.org/10.1016/S2095-....
12.
Chu C., Weiner J., Maestre F., Wang Y., Morris C., Xiao S., Yuan J.L., Du G.Z., Wang G. 2010. Effects of positive interactions, size symmetry of competition and abiotic stress on self-thinning in simulated plant populations. Annals of Botany 106 (4): 647−652. DOI: https://doi.org/10.1093/aob/mc....
13.
Counce P., Keisling T., Mitchell A. 2000. A uniform, objective, and adaptive system for expressing rice development. Crop Science 40 (2): 436−443. DOI: 10.2135/cropsci2000.402436x.
14.
Cousens R. 1985. An empirical model relating crop yield to weed and crop density and a statistical comparison with other models. The Journal of Agricultural Science 105 (3): 513−521. DOI: https://doi.org/10.1017/S00218....
15.
Cury J.P., Santos J.B., Silva E.B., Byrro E.C.M., Braga R.R., Carvalho F.P., Valadäo Silva D. 2012. Accumulation and partitioning of dry matter and nutrients in maize cultivars in competition with weed. Planta Dominha 30 (2): 287–296. DOI: https://doi.org/10.1590/S0100-....
16.
Dos Santos H., Jacomine P., Anjos L., Oliveira V., Lumbreras J., Coelho M., Almeida J., Araujo Filho J., Oliveira J., Cunha T. 2018. Sistema brasileiro de classificação de solos [Brazillian system of soil classification]. 5th ed. Embrapa, Brasília, Br. 356 pp. (in Portuguese).
17.
Fleck N., Lamego F., Schaedler C., Ferreira F. 2007. Resposta de cultivares de soja a competição com cultivar simuladora de infestação de plantas concorrentes [Soybean cultivar response to competition with a weed mimicking genotype scientia agraria] 8 (3): 213–218. DOI: http://dx.doi.org/10.5380/rsa.... (in Portuguese).
18.
Galon L., Agostinetto D., Moraes P., Tironi S., Dal Magro T. 2007. Estimativa das perdas de produtividade de grãos em cultivares de arroz (Oryza sativa) pela interferência do capim-arroz (Echinochloa spp.) [Estimation of grain yield loss in rice (Oryza sativa) cultivars due to interference by barnyardgrass (Echinochloa spp.)]. Planta Daninha 25 (4): 697−707. DOI: http://dx.doi.org/10.1590/S010... (in Portuguese).
19.
Genro Junior S., Marcolin E., Anghinoni I. 2010. Efficacy of fertilizer recommendations for different yield expectations of flooded rice. Revista brasileira de ciencia do solo 34 (5): 1667−1675. DOI: http://dx.doi.org/10.1590/S010....
20.
Heap I. 2019. The international survey of herbicide resistant weeds. Available on: www.weedscience.org. [Accessed: 25 February, 2019].
21.
Kuinchtner A., Buriol G. 2001. Clima do Estado do Rio Grande do Sul segundo a classificação climática de Köeppen e Thornthwaite [The climate of the Rio Grande do Sul State according to the Köppen e Thornthwaite systems]. Disciplinarum Scientia 2 (1): 171–182. (in Portuguese).
22.
Mamun M. 2014. Modelling rice-weed competition in direct-seeded rice cultivation. Agricultural Research 3 (4): 346−352. DOI: https://doi.org/10.1007/s40003....
23.
McDonald A., Riha S., DiTommaso A. 2010. Early season height differences as robust predictors of weed growth potential in maize: New avenues for adaptive management? Weed Research 50 (2): 110–119. DOI: https://doi.org/10.1111/j.1365....
24.
Ratkowsky D. 1983. Nonlinear regression modeling: a unified practical approach. 1th ed. Central Books, Dagemham, UK, 276 pp.
25.
Reis A., Nascente A., Almeira R., Chagas Junior A. 2018. Growth and nutrient contents in lowland rice due to phosphorus and potassium fertilization. Pesquisa Agropecuária Tropical 48 (2): 98–108. DOI: http://dx.doi.org/10.1590/1983....
26.
Rezaeieh A., Aminpanah H., Sadeghi S. 2015. Competition between rice (Oryza sativa L.) and barnyardgrass (Echinochloa crus-galli (L.) P. Beauv. as affected by methanol foliar application. Anais da Academia Brasileira de Ciências 87 (2): 879−890. DOI: http://dx.doi.org/10.1590/0001....
27.
Rotilli E., Fidelis R., Dos Santos M., Barros H., Pinto L. 2010. Eficiência do uso e resposta à aplicação de fósforo de cultivares de arroz em solos de terras altas [Use efficiency and response to phosphorus of application rice cultivars in highlands soils]. Bragantia 69 (3): 705–710. DOI: http://dx.doi.org/10.1590/S000... (in Portuguese).
28.
Streck E., Kampf N., Dalmolin R., Klant E., Nascimento P., Schneider P., Giasson E., Pinto L. 2008. Solos do Rio Grande do Sul [Soils of Rio Grande do Sul]. 2th ed. UFRGS: EMATER/RS-ASCAR. Porto Alegre, BR., 222 pp. (in Portuguese).
29.
Technical Meeting of Flooded Rice. 2018. Available on: http://www.sosbai.com.br/dcs/B.... (in Portuguese) Tedesco M., Gianello C., Bissani C., Bohnen H., Volkweiss S. 1995. Análises de solo, plantas e outros materiais [Soil, plant and another materials analisys]. 1th ed. UFRGS, Porto Alegre, Br., 100 pp.
30.
Xiong Q., Tang G., Zhong L., He H., Chen X. 2018. Response to nitrogen deficiency and compensation on physiological characteristics, yield formation, and nitrogen utilization of rice. Frontiers in Plant Sciences 9: 1075. DOI: https://doi.org/10.3389/fpls.2....
31.
Westendorff N., Agostinetto D., Ulguim A., Perboni L., Da Silva B. 2014. Yield loss and economic thresholds of yellow nutsedge in irrigated rice as a function of the onset of flood irrigation. Bragantia 73 (1): 32−38. DOI: http://dx.doi.org/10.1590/brag....
| eISSN: | 1899-007X |
| ISSN: | 1427-4345 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
