Published

2023-08-31

Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield

Efecto de la interacción genotipo por ambiente sobre la germinación, índice de vigor y rendimiento de la semilla de soya (Glycine max (L.) Merrill)

DOI:

https://doi.org/10.15446/agron.colomb.v41n2.108748

Keywords:

environmental adaptation, seed quality, stability, water stress, oilseed crop, viability (en)
adaptación ambiental, calidad de semillas, estabilidad, estrés hídrico, cultivo oleaginoso, viabilidad (es)

Downloads

Authors

  • Rubén-Alfredo Valencia-Ramírez 1Corporación Colombiana de Investigación Agropecuaria AGROSAVIA - Centro de Investigación La Libertad - Villavicencio, Meta - Colombia https://orcid.org/0000-0001-6176-6956
  • Yuli Stephani Tibocha-Ardila 1Corporación Colombiana de Investigación Agropecuaria AGROSAVIA - Centro de Investigación La Libertad - Villavicencio, Meta - Colombia https://orcid.org/0000-0002-5338-5202

The adverse edaphoclimatic conditions in the Orinoquía region affect the soybean crop cycle, deteriorating seed quality. The aim of this study was to investigate the effect of the genotype (G),  the environment (E), and their interaction (GxE) on the yield and seed quality of six soybean varieties (Corpoica Superior 6, Orinoquía 3, Soyica P34, Corpoica Taluma 5, and Agrosavia Primavera 11 of Colombian origin and Barreira of Brazilian origin) in five environments of the Orinoquía Colombia region, two in the second half of 2020 (LIBB: La Libertad and TALB: Taluma) and three in the first half of 2021 (LIBA: La Libertad, TALA: Taluma, and LEONAS), to determine their adaptation domain. Highly significant differences (P<0.01) were observed between G, E, and GxE for germination (GER) and seed yield (SY). A similar situation was shown by the vigor index (VI), although without differences between environments. The GGE biplot for GER, and SY separated environments by year halves. Taluma during the first half was the most discriminating environment for the response variables, useful for genetic breeding programs with a seed quality approach. Only in La Libertad during the second half was GER above 80%. The most stable variety per environment was Soyica P34 in two response variables, and the best with specific adaptation were Corpoica Superior 6 and Orinoquía 3.  These last two reached higher average values in GER (69.6%; 63.1%), VI (13.3; 13.4), and SY (1473 kg ha-1; 1404 kg ha-1).

Las condiciones edafoclimáticas adversas en la Orinoquía afectan el ciclo de cultivo de soya deteriorando la calidad de las semillas. El objetivo de este estudio fue investigar el efecto del genotipo-(G), el ambiente-(A) y su interacción-(GxA) sobre el rendimiento y la calidad de las semillas de seis variedades de soya (Corpoica Superior 6, Orinoquía 3, Soyica P34, Corpoica Taluma 5 y Agrosavia Primavera 11 de origen colombiano, y Barreira de origen brasilero) en cinco ambientes de la Orinoquía, Colombia, dos en el segundo semestre de 2020 (LIBB: La Libertad y TALB: Taluma) y tres en el primer semestre de 2021 (LIBA: La Libertad, TALA: Taluma y LEONAS), para determinar el dominio de adaptación. Se observaron diferencias altamente significativas (P<0.01) entre G, A y GxA para germinación (GER) y rendimiento de semillas (RS). Situación similar mostró el índice de vigor (VI), aunque sin diferencias entre ambientes. El biplot-GGA para GER y RS separó ambientes por semestre. Taluma, durante el primer semestre, fue el ambiente más discriminante para las variables respuesta, útil para programas de mejoramiento genético enfocados en calidad de semillas. Solamente en La Libertad durante el segundo semestre, GER estuvo por encima del 80%. La variedad más estable por ambiente fue Soyica P34 en dos variables respuesta, y las mejores con adaptación específica fueron Corpoica Superior 6 y Orinoquia 3. Estas dos últimas alcanzaron valores promedios más altos de GER (69.6%; 63.1%), VI (13.3; 13.4) y RS (1473 kg ha-1; 1404 kg ha-1).

References

Allard, R. W., & Bradshaw, A. D. (1964). Implications of genotypeenvironmental interactions in applied plant breeding. Crop Science 4(5), 503–508. https://doi.org/10.2135/cropsci1964.0011183X000400050021x DOI: https://doi.org/10.2135/cropsci1964.0011183X000400050021x

Bellaloui, N., Reddy, K. N., Bruns, H. A., Gillen, A. M., Mengistu, A., Zobiole, L. H., Fisher, D. K., Abbas, H. K., Zablotowicz, R. M., & Kremer, R. J. (2011). Soybean seed composition and quality: Interactions of environment, genotype, and management practices.Soybeans: Cultivation, Uses and nutrition. Nova Science Publishers, Inc.

Blanche, B., & Myers, G. O. (2006). Identifying discriminating locations for cultivar selection in Louisiana. Crop Science, 46(2), 946–949. https://doi.org/10.2135/cropsci2005.0279 DOI: https://doi.org/10.2135/cropsci2005.0279

Burgueño, J., Crossa, J., & Vargas, M. (2002). SAS Programs for graphing GE and GGE biplots. Biometrics and Statistics Unit, CIMMYT, México D.F.

Carmello, V., Santa, L., & Neto, A. (2016). Rainfall variability and soybean yield in Paraná State, Southern Brazil. International Journal of Agriculture and Environmental Research, 2(1), 86–89.

Crossa, J., Cornelius, P. L., & Yan, W. (2002). Biplots of linear-bilinear models for studying crossover genotype x environment interaction. Crop Science, 42(2), 619–633. https://doi.org/10.2135/cropsci2002.6190 DOI: https://doi.org/10.2135/cropsci2002.6190

Crossa, J., Gauch Jr., H. G., & Zobel, R. W. (1990). Additive main effects and multiplicative interactions analysis of two international maize cultivar trials. Crop Science, 30(3), 493–500. https://doi.org/10.2135/cropsci1990.0011183X003000030003x DOI: https://doi.org/10.2135/cropsci1990.0011183X003000030003x

Egli, D. B., TeKrony, D. M., Heitholt, J. J., & Rupe, J. (2005). Air temperature during seed filling and soybean seed germination and vigor. Crop Science, 45(4), 1329–1335. https://doi.org/10.2135/cropsci2004.0029 DOI: https://doi.org/10.2135/cropsci2004.0029

FAO. (2019). Materiales para capacitación en semillas. Organización de las Naciones Unidas para la Alimentacion y la Agricultura & AfricaSeeds.

Gollob, H. (1968). A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika, 33, 73–115. https://doi.org/10.1007/BF02289676 DOI: https://doi.org/10.1007/BF02289676

González, G., Mendoza, F., Covarrubias., J., Vázquez, N., & Acosta, J. (2008). Rendimiento y calidad de semilla de fríjol en dos épocas de siembra en la región del Bajío. Agricultura Técnica en México, 34(4), 421–430.

Ibáñez M., Cavanagh, M., Bonamico, N., & Renzo, M. (2006). Análisis gráfico mediante biplot del comportamiento de híbridos de maíz. Revista de Investigaciones Agropecuarias, 35(3), 83–93.

ISTA. (2016). Reglas Internacionales para el análisis de las semillas. International Seed Testing Association. https://www.studocu.com/es-mx/document/universidad-autonoma-de-sinaloa/fisiologia-vegetal/ista-rules-2016-spanish/39386727

Kempton, R. A. (1984). The use of biplots in interpreting variety by environment interactions. Journal of Agricultural Science, 103(1), 123–135. https://doi.org/10.1017/S0021859600043392 DOI: https://doi.org/10.1017/S0021859600043392

León Castillo, H., Rincón Sánchez, F., Reyes Valdés, M. H., Sámano Garduño, D., Martínez Zambrano, G., Cavazos Cadena, R., & Figueroa Cárdenas, J. D. (2005). Potencial de rendimiento y estabilidad de combinaciones germoplásmicas formadas entre grupos de maíz. Revista Fitotecnia Mexicana, 28(2), 135–143. DOI: https://doi.org/10.35196/rfm.2005.2.135

Marcos Filho, J. (2015). Seed vigor testing: An overview of the past, present and future perspective. Scientia Agricola, 72(4), 363–374. https://doi.org/10.1590/0103-9016-2015-0007 DOI: https://doi.org/10.1590/0103-9016-2015-0007

Ngalamu, T., Ashraf, M., & Meseka, S. (2013). Soybean (Glycine max L) genotype and environment interaction effect on yieldand other related traits. American Journal of Experimental Agriculture, 3(4), 977–987. DOI: https://doi.org/10.9734/AJEA/2013/5069

Pádua, G. P., França-Neto, J. B., Carvalho, M. L. M., Krzyzanowski, F. C., & Guimarães, R. M. (2009). Incidence of green soybean seeds as a function of environmental stresses during seed maturation. Revista Brasileira de Sementes, 31(3), 150–159. https://doi.org/10.1590/S0101-31222009000300017 DOI: https://doi.org/10.1590/S0101-31222009000300017

Purchase, J. L., Hatting, H., & Van Deventer, C. S. (2000). Genotype x environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil, 17(3), 101–107. https://doi.org/10.1080/02571862.2000.10634878 DOI: https://doi.org/10.1080/02571862.2000.10634878

Ritchie, H., & Roser, M. (2021). Forests and deforestation. Our World in Data.

Salmerόn, M., Purcell, L. C., Vories, E. D., & Shannon, G. (2017). Simulation of genotype by-environment interactions on irrigated soybean yields in the U.S. Midsouth. Agricultural Systems, 150, 120–129. https://doi.org/10.1016/j.agsy.2016.10.008 DOI: https://doi.org/10.1016/j.agsy.2016.10.008

Sanchez, M. F. R., & Pinchinat, A. M. (1974). Bean seed quality in Costa Rica (Phaseolus vulgaris). Turrialba, 24(1), 72–75.

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611. https://doi.org/10.2307/2333709 DOI: https://doi.org/10.1093/biomet/52.3-4.591

Valencia, R. A., & Ligarreto, G. A. (2010). Mejoramiento genético de la soya (Glycine max [L.] Merril) para su cultivo en la altillanura colombiana: una visión conceptual prospectiva. Agronomía Colombiana, 28(2), 155–163. https://revistas.unal.edu.co/index.php/agrocol/article/view/18018

Valencia-Ramírez, R. A., & Ligarreto-Moreno, G. A. (2012). Phenotypic correlation and path analysis for yield in soybean (Glycine max (L.) Merril). Acta Agronómica, 61(4), 322–332.

Vargas Hernández, M., & Crossa, J. (2000). El análisis AMMI y la gráfica del biplot en SAS. CIMMYT. https://repository.cimmyt. org/xmlui/bitstream/handle/10883/3489/73248.pdf

Yan, W., Hunt, L. A., Sheng, Q., & Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science, 40(3), 597–605. https://doi.org/10.2135/cropsci2000.403597x DOI: https://doi.org/10.2135/cropsci2000.403597x

Yan, W., & Kang, M. S. (2003). GGE Biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press. https://doi.org/10.1201/9781420040371 DOI: https://doi.org/10.1201/9781420040371

Yan, W., & Rajcan, I. (2002). Biplot analysis of test sites and traitrelations of soybean in Ontario. Crop Science, 42(1), 11–20. https://doi.org/10.2135/cropsci2002.0011 DOI: https://doi.org/10.2135/cropsci2002.1100

How to Cite

APA

Valencia-Ramírez, R.-A. and Tibocha-Ardila, Y. S. (2023). Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield. Agronomía Colombiana, 41(2), e108748. https://doi.org/10.15446/agron.colomb.v41n2.108748

ACM

[1]
Valencia-Ramírez, R.-A. and Tibocha-Ardila, Y.S. 2023. Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield. Agronomía Colombiana. 41, 2 (May 2023), e108748. DOI:https://doi.org/10.15446/agron.colomb.v41n2.108748.

ACS

(1)
Valencia-Ramírez, R.-A.; Tibocha-Ardila, Y. S. Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield. Agron. Colomb. 2023, 41, e108748.

ABNT

VALENCIA-RAMÍREZ, R.-A.; TIBOCHA-ARDILA, Y. S. Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield. Agronomía Colombiana, [S. l.], v. 41, n. 2, p. e108748, 2023. DOI: 10.15446/agron.colomb.v41n2.108748. Disponível em: https://revistas.unal.edu.co/index.php/agrocol/article/view/108748. Acesso em: 10 mar. 2025.

Chicago

Valencia-Ramírez, Rubén-Alfredo, and Yuli Stephani Tibocha-Ardila. 2023. “Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield”. Agronomía Colombiana 41 (2):e108748. https://doi.org/10.15446/agron.colomb.v41n2.108748.

Harvard

Valencia-Ramírez, R.-A. and Tibocha-Ardila, Y. S. (2023) “Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield”, Agronomía Colombiana, 41(2), p. e108748. doi: 10.15446/agron.colomb.v41n2.108748.

IEEE

[1]
R.-A. Valencia-Ramírez and Y. S. Tibocha-Ardila, “Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield”, Agron. Colomb., vol. 41, no. 2, p. e108748, May 2023.

MLA

Valencia-Ramírez, R.-A., and Y. S. Tibocha-Ardila. “Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield”. Agronomía Colombiana, vol. 41, no. 2, May 2023, p. e108748, doi:10.15446/agron.colomb.v41n2.108748.

Turabian

Valencia-Ramírez, Rubén-Alfredo, and Yuli Stephani Tibocha-Ardila. “Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield”. Agronomía Colombiana 41, no. 2 (May 1, 2023): e108748. Accessed March 10, 2025. https://revistas.unal.edu.co/index.php/agrocol/article/view/108748.

Vancouver

1.
Valencia-Ramírez R-A, Tibocha-Ardila YS. Effect of genotype-environment interaction on soybean (Glycine max (L.) Merrill) germination, vigor index, and seed yield. Agron. Colomb. [Internet]. 2023 May 1 [cited 2025 Mar. 10];41(2):e108748. Available from: https://revistas.unal.edu.co/index.php/agrocol/article/view/108748

Download Citation

CrossRef Cited-by

CrossRef citations0

Dimensions

PlumX

Article abstract page views

466

Downloads