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Vol. 18 No. 2 (2024)
Horticultural Excellence: Innovations in Quality, Technology, and Sustainability

Fruits section

Genotype-by-environment interaction of Solanum quitoense (Lam.) using the AMMI model

https://doi.org/10.17584/rcch.2024v18i2.17442

Published 2024-05-01

  • Liz Katherine Lagos-Santander
    • ,
  • David Esteban Duarte-Alvarado
    • ,
  • Túlio César Lagos-Burbano

Liz Katherine Lagos-Santander
Universidad de Nariño, San Juan de Pasto (Colombia)

David Esteban Duarte-Alvarado
Universidad de Nariño, San Juan de Pasto (Colombia)

Túlio César Lagos-Burbano
Universidad de Nariño, San Juan de Pasto (Colombia)

Lulo plant in production. Photo: D.E. Duarte-Alvarado

Abstract

The basis for genetic improvement for the cultivation of lulo (Solanum quitoense Lam.) in Colombia is limited. Research related to genotype-by-environment interaction (GEI) and stability in agronomic traits is scarce. To identify outstanding genotypes, GEI and the stability of fruit weight (FW), ascorbic acid (AA), and yield of 10 half-sib families (HSF) were evaluated. At the locations of San Pedro de Cartago, Arboleda, Tangua and La Union of the department of Nariño (Colombia), four trials were established under the randomised complete block design with four repetitions. To analyse GEI, the additive main effects and multiplicative interaction (AMMI) model and some AMMI stability parameters were used. In yield, the HSF7 and the control presented specific adaptation for Tangua, with 12.82 and 13.41 t ha-1, respectively and FW greater than 100 g. In Arboleda, HSF29 obtained the highest yield (16.14 t ha-1) with an FW of 100.53 g. HSF4, HSF28 and HSF49 reached yields above 9.0 t ha-1 and a FW greater than 100 g; therefore, they are recommended for any of the environments evaluated given their stability. HSF25 in AA and HSF29 in yield presented specific adaptation in Arboleda. Stable families across environments and with good yield were HSF4, HSF28, and HSF49, HSF4 and HSF28 showed higher values in two of the three traits, and HSF49 was outstanding in all three variables. These families can be used in plant breeding programmes as parents or distributed to farmers as improved varieties.

Keywords

Adaptability, Environments, Lulo, Yield, Fruit weight, Ascorbic acid

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References

  1. Al-Naggar, A.M.M., M.M. Shafik, and R.Y.M. Musa. 2020. AMMI and GGE biplot analyses for yield stability of nineteen maize genotypes under different nitrogen and irrigation levels. Plant Arch. 20(2), 4431-4443.
  2. Alejos, G., P. Monasterio, and R. Rea. 2006. Análisis de la interacción genotipo-ambiente para rendimiento de maíz en la región maicera del estado Yaracuy, Venezuela. Agron. Trop. 56(3), 369-384.
  3. Álvarez, D., L. Casanova, K. Córdoba, and O. Osorio. 2016. Evaluación de poscosecha y calidad fisicoquímica de genotipos de lulo (Solanum quitoense Lam.) tolerantes a Meloidogyne sp. Vitae 23(Supl. 1), 785-789.
  4. Ardila, G.H., G. Fischer, and J.C. García. 2015. La poda de tallos y racimos florales afecta la producción de frutos de lulo (Solanum quitoense var. Septentrionale). Rev. Colomb. Cienc. Hortic. 9(1), 24-37. Doi: https://doi.org/10.17584/rcch.2015v9i1.3743
  5. Bastidas, J.I. and J.A. Cuaspud. 2018. Comportamiento agronómico de diez familias de medios hermanos de lulo (Solanum quitoense Lam.). Undergraduate thesis. Universidad de Nariño, San Juan de Pasto, Colombia.
  6. Cadersa, Y., D. Santchurn, J. Govinden, S. Saumtally, and Y. Parmessur. 2022. Genotype-by-environment interaction for marketable tuber yield in advanced potato clones using AMMI and GGE methods. Afr. Crop Sci. J. 30(3), 331-346. Doi: https://doi.org/10.4314/acsj.v30i3.5
  7. Ceballos, N. 2012. Evaluación agronómica, molecular e interacción genotipo-ambiente de introducciones de tomate tipo cereza. PhD thesis. Facultad de Ciencias Agropecuarias, Universidad de Caldas, Manizales, Colombia.
  8. Ceballos-Aguirre, N., F.A. Vallejo-Cabrera, and Y. Morillo-Coronado. 2021. Genotype-environment interaction for production characteristics in cherry tomato (Solanum spp.). Rev. Colomb. Cienc. Hortic. 15(2), e12608. Doi: https://doi.org/10.17584/rcch.2021v15i2.12608
  9. De Oliveira, E.J., J.P.X. Freitas, and O.N. Jesus. 2014. AMMI analysis of the adaptability and yield stability of yellow passion fruit varieties. Sci. Agric. 71(2), 139-145. Doi: https://doi.org/10.1590/S0103-90162014000200008
  10. De Oliveira, L.A., C.P. Silva, J.J. Nuvunga, A.Q. Silva, and M. Balestre. 2015. Credible intervals for scores in the AMMI with random effects for genotype. Crop Sci. 55(2), 465-476. Doi: https://doi.org/10.2135/cropsci2014.05.0369
  11. Díaz, A.E. and H.L. Brochero. 2012. Parasitoides asociados al perforador del fruto de las solanáceas Neoleucinodes elegantalis (Lepidoptera: Crambidae) en Colombia. Rev. Colomb. Entomol. 38(1), 50-57. Doi: https://doi.org/10.25100/socolen.v38i1.8917
  12. Farshadfar, E. 2008. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pak. J. Biol. Sci. 11(14), 1791-1796. Doi: https://doi.org/10.3923/pjbs.2008.1791.1796
  13. Farshadfar, E., N. Mahmodi, and A. Yaghotipoor. 2011. AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Aust. J. Crop Sci. 5(13), 1837-1844.
  14. Fonseca, M.C., J.A. Rodríguez, A.O. Herrera, and G. Fischer. 2013. Caracterización fisicoquímica del fruto de cuque (Solanum vestissimum Dunal) durante la maduración. Rev. Colomb. Cienc. Hortic. 6(1), 31-40. Doi: https://doi.org/10.17584/rcch.2012v6i1.1276
  15. Gauch Jr., H.G., H.-P. Piepho, and P. Annicchiarico. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Sci. 48(3), 866-889. Doi: https://doi.org/10.2135/cropsci2007.09.0513
  16. Gauch Jr., H.G. and R.W. Zobel. 1996. AMMI analysis of yields trials. pp. 85-122. In: Kangs, M.S. and H.G. Gauch Jr. (eds.). Genotype by environment interaction. CRC Press, Boca Raton, FL. Doi: https://doi.org/10.1201/9780367802226
  17. González, D.I., L.E. Ordoñez, P. Vanegas, and H.D. Vásquez. 2014. Cambios en las propiedades fisicoquímicas de frutos de lulo (Solanum quitoense Lam.) cosechados en tres grados de madurez. Acta Agron. 63(1), 11-17. Doi: https://doi.org/10.15446/acag.v63n1.31717
  18. Gordón-Mendoza, R., J. Franco-Barrera, J.I. Nuñez-Cano, A.E. Sáez-Cigarruista, F. Ramos-Manzané, J.E. Jaén-Villarreal, and F.M. Vicente-García. 2020. Evaluación y selección de variedades de maíz para sistemas de agricultura familiar de panamá, 2017-2019. Cienc. Agropec. (31), 99-126.
  19. Icontec, Instituto Colombiano de Normas Técnicas y Certificación. 2002. NTC5093. Frutas frescas. Lulo de Castilla. Especificaciones. Bogota.
  20. Kizilgeci, F., O. Albayrak, M. Yildirim, and C. Akinci. 2019. Stability evaluation of bread wheat genotypes under varying environments by AMMI model. Fresenius Environ. Bull. 28(9), 6865-6872.
  21. Lagos, T.C. 2020. El cultivo de lulo en Colombia. pp. 11-25. In: Lagos, T.C. (ed.), Mejoramiento genético de lulo Solanum quitoense Lam. Universidad de Nariño, San Juan de Pasto, Colombia.
  22. Lagos, L.K. 2023. Selección e interacción genotipo por ambiente de familias de medios hermanos de lulo Solanum quitoense Lam. PhD thesis. Universidad Nacional de Colombia. Universidad Nacional de Colombia, Palmira, Colombia.
  23. Lagos, T., J. Apraez, L. Lagos, and D. Duarte. 2015. Comportamiento de 50 familias de medios hermanos de Solanum quitoense Lam. bajo selección recurrente. Temas Agrar. 20(2), 19-29. Doi: https://doi.org/10.21897/rta.v20i2.755
  24. Lagos-Santander, L.K., T.C. Lagos-Burbano, D.E. Duarte-Alvarado, H. Criollo-Escobar, and N.F. Angulo-Ramos. 2019. Evaluación del rendimiento y calidad del fruto de parentales e híbridos de lulo de Castilla. Rev. U.D.C.A Act. Div. Cient. 22(2), e1344. Doi: https://doi.org/10.31910/rudca.v22.n2.2019.1344
  25. Liu, Q., L. Huang, C. Fu, T. Zhang, W. Ding, and C. Yang. 2022. Genotype–environment interaction of crocin in Gardenia jasminoides by AMMI and GGE biplot analysis. Food Sci. Nutr. 10(11), 4080-4087. Doi: https://doi.org/10.1002/fsn3.3003
  26. Mandel, J. 1971. A new analysis of variance model for non-additive data. Technometrics 13(1), 1-18. Doi: https://doi.org/10.1080/00401706.1971.10488751
  27. Matarazzo, P.H.M., D.L. Siqueira, L.C.C. Salomao, D.F.P. Silva, and P.R. Cecon. 2013. Desenvolvimento dos frutos de lulo (Solanum quitoense Lam), em Viçosa-MG. Rev. Bras. Frutic. 35(1), 131-142. Doi: https://doi.org/10.1590/S0100-29452013000100016
  28. Mejia-Salazar, J.R., C.H. Galeano-Mendoza, E. Burbano-Erazo, F.A. Vallejo-Cabrera, and M. Arango. 2020. Interacción genotipo por ambiente de nueve variedades de algodón para los Valles Interandinos en Colombia. Agron. Mesoam. 31(1), 31-42. Doi: https://doi.org/10.15517/am.v31i1.37178
  29. Mekonnen, Z. and H. Mohammed. 2009. Study on genotype x environment interaction of yield in sesame (Sesamum indicum L.). J. Phytol. 1(4), 199-205.
  30. Muñoz, J.A., L.F. Rodríguez, and L.T. Bermúdez. 2013. Análisis de competitividad del sistema de producción de lulo (Solanum quitoense Lam.) en tres municipios de Nariño. Rev. Colomb. Cienc. Hortic. 7(2), 173-185. http://www.scielo.org.co/pdf/rcch/v7n2/v7n2a04.pdf
  31. Nafisah, Z., Satoto, J. Ali, and S. Priatna. 2020. Genotype by environment interaction for grain yield of salt tolerance rice genotypes in coastal saline area. J. Penelit. Pertanian Tanaman Pangan 4(1), 9-16.
  32. Poudel, P.P., K. Dhakal, R. Darai, R. Sah, S. Subedi, and S. Mishra. 2023. Yield stability and genotype x environment interaction of lentil. Nepal. J. Agric. Sci. 24, 103-124.
  33. Purchase, J.L., H. Hesta, and C.S. van Deventer. 2000. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South Afr. J. Plant Soil 17(3), 101-107. Doi: https://doi.org/10.1080/02571862.2000.10634878
  34. Rodríguez-González, R.E., J.F. Ponce-Medina, E.O. Rueda-Puente, L. Avendaño-Reyes, J.J. Paz, J. Santillano-Cazares, and M. Cruz-Villegas. 2011. Interacción genotipo - ambiente para la estabilidad de rendimiento en trigo en la región de Mexicali, B.C., México. Trop. Subtrop. Agroecosyst. 14(2), 543-558.
  35. Santacruz-Benavides, A.V., W.L. Delgado-Gualmatán, T.C. Lagos-Burbano, and D.-E. Duarte-Alvarado. 2021. Genotype-environment interaction and guata potato yield (Solanum tuberosum L.) in the Department of Nariño (Colombia). Rev. Colomb. Cienc. Hortic. 15(3), e12872. https://doi.org/10.17584/rcch.2021v15i3.12872
  36. Sharifi, P., H. Aminpanah, R. Erfani, A. Mohaddesi, and A. Abbasian. 2017. Evaluation of genotype × environment interaction in rice based on AMMI model in Iran. Rice Sci. 24(3), 173-180. Doi: https://doi.org/10.1016/j.rsci.2017.02.001
  37. Szareski, V.J., I.R. Carvalho, K. Kehl, A.M. Levien, M. Nardino, G.H. Demari, F. Lautenchleger, V.Q. Souza, T. Pedó, and T.Z. Aumonde. 2017. Univariate, multivariate techniques and mixed models applied to the adaptability and stability of wheat in the Rio Grande do Sul State. Genet. Mol. Res. 16(3), gmr16039735. Doi: https://doi.org/10.4238/gmr16039735
  38. Yan, W., L.A. Hunt, Q. Sheng, and Z. Szlavnics. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40(3), 597-605. Doi: https://doi.org/10.2135/cropsci2000.403597x
  39. Zobel, R.W., M.J. Wright, and H.G. Gauch Jr. 1988. Statistical analysis of a yield trial. Agron. J. 80(3), 388-393. Doi: http://dx.doi.org/10.2134/agronj1988.00021962008000030002x

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