Path analysis in soybean subjected to nitrogen sources and application rates inoculated with Bradyrhizobium japonicum in soils with different fertility levels

Authors

DOI:

https://doi.org/10.33448/rsd-v9i7.3813

Keywords:

Direct and indirect effect; Productivity; Protein content.

Abstract

The cultivation of soybeans is of global socioeconomic importance, therefore, studies are needed to increase its productive performance. Thus, this study aimed to evaluate the effect of agronomic traits due to the application of nitrogen sources and rates associated with inoculation with Bradyrhizobium japonicum on the protein content and grain yield of soybean. A randomized block design was used, in a 2 × 2 × 5 factorial scheme: two locations (UFMS 1 and UFMS 2), two sources of nitrogen fertilizer [urea (45% N) and ammonium sulfate(21% N)] and five nitrogen rates (0, 50, 100, 150 and 200 kg ha–1), with four replications. At the R3 stage, plant height, leaf chlorophyll content, leaf area and shoot dry matter were evaluated. At stage R8, first pod height, pods number per plant, grain number per pod, mass of thousand grains, grain yield and crude protein content were measured. The results show that in the experiment conducted in the UFMS 1 area, the leaf area and the mass of thousand grains were the agronomic traits that have the greatest positive direct effect on grain yield and protein content, respectively. In the UFMS 2 area, the mass of a thousand grains and the total dry mass were the agronomic traits that have the greatest direct positive effect on grain yield and protein content, respectively.

References

Afshar, R.K., Lin, R., Mohammed, Y.A. & Chen, C. (2018). Agronomic effects of urease and nitrification inhibitors on ammonia volatilization and nitrogen utilization in a dryland farming system: field and laboratory investigation. Journal of Cleaner Production, 172(91): 4130-9.

Ahammed, G. J., Xu, W., Liu, A. & Chen, S. (2018). COMT1 silencing aggravates heat stress-induced reduction in photosynthesis by decreasing chlorophyll content, photosystem II activity, and electron transport efficiency in tomato. Frontiers in Plant Science, 9, 998.

Ahmed, M., Weijia, Y.U., Lei, M. Raza S. & Zhou (2018). Mitigation of ammonia volatilization with application of urease and nitrification inhibitors from summer maize at the Loess Plateau. Plant, Soil and Environment, 64(4), 164-172.

Alcântara Neto, F., Gravina, G.A., Monteiro, M.M.S., Morais, F.B., Petter, F.A. & Albuquerque, J.A.A. (2011). Análise de trilha do rendimento de grãos de soja na microrregião do Alto Médio Gurguéia. Comunicata Scientiae, 2(2): 107-112.

Bonato, E.R., Bertagnolli, P.F., Lange, C. & Rubin, S.D.A.L. (2000). Teor de óleo e de proteína em genótipos de soja desenvolvidos após 1990. Pesquisa Agropecuária Brasileira, 35(12), 2391-2398.

Borrás, L., Slafer, G.A. & Otegui, M.E. (2004). Seed dry weight response to source–sink manipulations in wheat, maize and soybean: a quantitative reappraisal. Field Crops Research, 86(2-3): 131-146.

BRASIL. Ministério da Agricultura, Pecuária e Abastecimento. Regras para análise de sementes. Brasília, DF: MAPA/ACS, 2009. 399p.

Chae, H.S., Noh, H.J., Song, W.S. & Cho, H.H. (2018). Efficiency and effectiveness of vitamin C-substrate organo-mineral straight fertilizer in lettuce (Lactuca sativa L.). Chemical and Biological Technologies in Agriculture, 5, 4.

Chebotarev, N.T., Yudin, A.A., Konkin, P.I. & Oblizov, A.V. (2017). Efficiency of using organic and mineral fertilizers in fodder crop rotation on northern soddy podzols. Russian Agricultural Sciences, 43(2): 162-166.

Conab. Companhia Nacional de abastecimento. (2019). Acompanhamento de safra brasileira de grãos, safra 2018/19, 6(11) – Décimo primeiro levantamento, Brasília. Acesso em: 07 dez. 2019 em: <http://www.conab.gov.br>

Conab. Companhia Nacional de abastecimento. (2020). Acompanhamento de safra brasileira de grãos, safra 2019/20, 7(4) – Quarto levantamento, Brasília. Acesso em: 10 jan. 2020 em: <http://www.conab.gov.br>

Croft, H., Chen, J.M., Luo, X., Bartlett, P., Chen, B. & Staebler, R.M. (2017). Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global change biology, 23(9), 3513-3524.

Cruz, C.D. & Regazzi, A.J. (1997). Modelos biométricos aplicados ao melhoramento genético. Viçosa: UFV, 390 p.

Detmann, E., Queiroz, A.C. & Cabral, L.S. (2012). Avaliação do nitrogênio total (proteína bruta) pelo método de Kjeldahl. In: Detmann, E., Souza, MA, Valadares Filho, S. C.,

Berchielli, T.T., Cabral, L.S., Ladeira, M.M., Souza, M.A., Queiroz, A.C., Saliba, E.O.S., Pina, D.S. & Azevedo, J.A.G. (Eds.). Métodos para análise de alimentos - INCT - Ciência Animal. Visconde do Rio Branco: Suprema, 1, cap. 4, p. 51-68.

Egamberdieva, D., Jabborova, D., Wirth, S.J., Alam, P., Alyemeni, M.N. & Ahmad, P. (2018). Interactive effects of nutrients and Bradyrhizobium japonicum on the growth and root architecture of soybean (Glycine max L.). Frontiers in microbiology, 9, 1000.

Egli, D.B. (2011). Time and the productivity of agronomic crops and cropping systems. Agronomy journal, 103(3), 743-750.

Gregersen, P.L., Culetic, A., Boschian, L. & Krupinska, K. (2013). Plant senescence and crop productivity. Plant molecular biology, 82(6), 603-622.

Hoogerheide, E.S.S., Vencovsky, R., Farias, F.J.C., Freire, E.C. & Arantes, E.M. (2007). Correlações e análise de trilha de caracteres tecnológicos e a produtividade de fibra de algodão. Pesquisa Agropecuária Brasileira, 42(10), 1401-1405.

Leggett, M., Diaz-Zorita, M., Koivunen, M., Bowman, R., Pesek, R., Stevenson, C. & Leister, T. (2017). Soybean response to inoculation with Bradyrhizobium japonicum in the United States and Argentina. Agronomy journal, 109(3), 1031-1038.

Lopes, A.C.D.A., Vello, N.A., Pandini, F., Rocha, M.D.M. & Tsutsumi, C.Y. (2002). Variabilidade e correlações entre caracteres em cruzamentos de soja. Scientia Agrícola, 59(2), 341-348.

Mahapatra, S.K., Dash, A. & Pradhan, J. (2020). Application of Path Analysis in Agricultural Research. Biotica Research Today, 2(2), 18-20.

Martins, M.R., Sant’Anna, S.A.C., Zaman, M., Santos, R.C., Monteiro, R.C., Alves, B.J.R., Jantalia, C.P., Boddey, R.M. & Urquiaga, S. (2017). Strategies for the use of urease and nitrification inhibitors with urea: Impact on N2O and NH3 emissions, fertilizer-15N recovery and maize yield in a tropical soil. Agriculture, Ecosystems & Environment, 247, 54-62.

Meena, R.S., Vijayakumar, V., Yadav, G.S. & Mitran, T. (2018). Response and interaction of Bradyrhizobium japonicum and arbuscular mycorrhizal fungi in the soybean rhizosphere. Plant Growth Regulation, 84(2), 207-223.

Montgomery, D.C., Peck, E.A. & Vining, G.G. (2006). Introduction to linear regression analysis. New York: John Wiley & Sons, 640 p.

Nogueira, A.P.O., Sediyama, T., Sousa, L.B., Hamawaki, O.T., Cruz, C.D., Pereira, D.G. & Matsuo, É. (2012). Análise de trilha e correlações entre caracteres em soja cultivada em duas épocas de semeadura. Bioscience Journal, 28(6), 877-888.

Pereira, A.S., Shitsuka, D.M., Parreira, F.J. & Shitsuka, R. (2018). Metodologia da pesquisa

científica. [e-book]. Santa Maria. Ed. UAB/NTE/UFSM. Consultado el 02/05/20, em:

https://repositorio.ufsm.br/bitstream/handle/1/15824/Lic_Computacao_MetodologiaPesquisa-Cientifica.pdf?sequence=1.

Rigon, J.P.G., Capuani, S., Brito Neto, J.F.D., Rosa, G.M.D., Wastowski, A.D. & Rigon, C.A.G. (2012). Dissimilaridade genética e análise de trilha de cultivares de soja avaliada por meio de descritores quantitativos. Revista Ceres, 59(2), 233-240.

Santos, H.P.D., Fontaneli, R.S., Pires, J., Lampert, E.A., Vargas, A.M. & Verdi, A.C. (2014). Rendimento de grãos e características agronômicas de soja em função de sistemas de rotação de culturas. Bragantia, 73(3), 263-273.

Shiri-Janagard, M., Raei, Y., Gasemi-Golezani, G. & Aliasgarzad, N. (2012). Influence of Bradyrhizobium japonicum and phosphate solubilizing bacteria on soybean yield at different levels of nitrogen and phosphorus. International journal of Agronomy and Plant Production, 3(11): 544-549.

Sonah, H., O'Donoughue, L., Cober, E., Rajcan, I. & Belzile, F. (2015). Identification of loci governing eight agronomic traits using a GBS‐GWAS approach and validation by QTL mapping in soya bean. Plant biotechnology journal, 13(2): 211-221.

Thomas, A.L. & Costa, J.A. (2010). Desenvolvimento da planta de soja e o potencial de rendimento de grãos. In: Thomas, AL, Costa, JA. (Ed.). Soja: manejo para alta produtividade de grãos. Porto Alegre: Evangraf, p.13-33.

Wright, S. (1921). Correlation and causation. J. of Agricultural Research, 20(7): 557-585.

Zuffo, A.M., Zuffo Jr., J.M., Fonseca, W.L., Zambiazzi, E.V., Oliveira, A.M., Guilherme, S.R., Mendes, A.E.S., Godinho, S.H.M., Ribeiro, F.O. & Pinto, A.R.S. (2017). Path Analysis in Soybean Cultivars Grown under Foliar Spraying and Furrow Inoculation with Azospirillum brasilense. Journal of Agricultural Science, 9(10): 137-144.

Published

07/05/2020

How to Cite

ZUFFO, A. M.; AGUILERA, J. G.; RATKE, R. F.; STEINER, F.; OLIVEIRA, A. M. de; FONSECA, W. L. Path analysis in soybean subjected to nitrogen sources and application rates inoculated with Bradyrhizobium japonicum in soils with different fertility levels. Research, Society and Development, [S. l.], v. 9, n. 7, p. e203973813, 2020. DOI: 10.33448/rsd-v9i7.3813. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/3813. Acesso em: 18 nov. 2024.

Issue

Section

Agrarian and Biological Sciences