Skip to main navigation menu Skip to main content Skip to site footer

Vol. 14 No. 1 (2020)

Vegetable section

Fitting a logistic growth model to yield traits in lettuce cultivars growing in summer

https://doi.org/10.17584/rcch.2020v14i1.8955

Published 2020-01-01

  • Fernanda Carini
    • ,
  • Alberto Cargnelutti Filho
    • ,
  • Jéssica Maronez de Souza
    • ,
  • Rafael Vieira Pezzini
    • ,
  • Cassiane Ubessi
    • ,
  • Márcio André Kreutz

Fernanda Carini
Federal University of Santa Maria, Postgraduate Program in Agronomy, Santa Maria

Alberto Cargnelutti Filho
Federal University of Santa Maria, Department of Crop Science, Santa Maria

Jéssica Maronez de Souza
Federal University of Santa Maria, Postgraduate Program in Agronomy, Santa Maria

Rafael Vieira Pezzini
Federal University of Santa Maria, Postgraduate Program in Agronomy, Santa Maria

Cassiane Ubessi
Federal University of Santa Maria, Postgraduate Program in Agronomy, Santa Maria

Márcio André Kreutz
Federal University of Santa Maria, Graduate Agronomy, Santa Maria

Cultivars lettuce experiment view. Photo: F. Carini

Abstract

The objective of this study was to fit a logistic model to leaf fresh and dry matter and shoot fresh and dry matter in four lettuce cultivars to describe growth in summer. The cultivars Crocantela, Elisa, Rubinela, and Vera were evaluated in the summers of 2017 and 2018 in soil in a protected environment and in a soilless system. Seven days after transplanting, the leaf fresh and dry matter and shoot fresh and dry matter of 8 plants were weighed every 4 days. The model parameters were estimated using R software with the least squares method and iterative process of Gauss-Newton. This study also estimated the confidence intervals of the parameters, verified the assumptions of the models, calculated the goodness-of-fit measures and the critical points, and quantified the parametric and intrinsic nonlinearities. The logistic growth model fit well to the fresh and dry matter in the leaves and shoots in the cultivars Crocantela, Elisa, Rubinela, and Vera and described the growth of lettuce.

Keywords

Lactuca sativa, Plant models, Crop modelling, Non-linear models, Vegetable crop

PDF

References

  1. Alvares, C.A., J.L. Stape, P.C. Sentelhas, J.L.M. Gonçalves, and G. Sparovek. 2013. Köppen’s climate classification map for Brazil. Meteorol. Z. 22, 711-728. Doi: https://doi.org/10.1127/0941-2948/2013/0507
  2. Andriolo, J.L. 2017. Olericultura geral. 3a ed. UFSM, Santa Maria, Brazil.
  3. Archontoulis, S.V. and F.E. Miguez. 2015. Nonlinear regression models and applications in agricultural research. Agron. J. 107, 786-798. Doi: https://doi.org/10.2134/agronj2012.0506
  4. Arnold, C.T. 1959. The determination and significance of the base temperature in a linear heat unit system. Proc. Am. Soc Hort Sci. 74, 430-455.
  5. Bates, D.M. and D.G. Watts. 1998. Nonlinear regression analysis and its applications. John Wiley & Sons, New York, NY.
  6. Batista, E.L.S., S. Zolnier, A. Ribeiro, G.B. Lyra, T. G.F. Silva, and D. Boehringer. 2013 Modelagem do crescimento de cultivares de cana-de-açúcar no período de formação da cultura. Rev. Bras. Eng. Agr. Amb. 17, 1080-1087. Doi: https://doi.org/10.1590/S1415-43662013001000009
  7. Bem, C.M., A. Cargnelutti Filho, G. Facco, D.E. Schabarum, D.L. Silveira, , F.M. Simões, and D.B. Uliana. 2017. Growth models for morphological traits of sunn hemp. Semina: Cienc. Agrár. 38, 2933-2944. Doi: https://doi.org/10.5433/1679-0359.2017v38n5p2933
  8. Brunini, O. 1976. Temperatura-base para alface cultivar "white boston", em um sistema de unidades térmicas. Bragantia 35, 213-219. Doi: https://doi.org/10.1590/S0006-87051976000100019
  9. Carini, F., A. Cargenelutti Filho, C.T. Bandeira, I.M.M. Neu, R.V. Pezzini, M. Pacheco, and R.M. Tomasi. 2019. Growth models for lettuce cultivars growing in spring. J. Agric. Sci. 11, 147-159. Doi: https://doi.org/10.5539/jas.v11n6p147
  10. Carranza, C., O. Lanchero, D. Miranda, and B. Chaves. 2009. Análisis del crecimiento de lechuga (Lactuca sativa L.) ‘Batavia’ cultivada en un suelo salino de la Sabana de Bogotá. Agron. Colomb. 27, 41-48.
  11. Diel, M.I., B.G. Sari, D.K. Krysczun, T. Olivoto, M.V.M. Pinheiro, D. Meira, D. Schmidt, and A.D. Lúcio. 2018. Nonlinear regression for description of strawberry (Fragaria x ananassa) production. J. Hortic. Sci. Biotechnol. 94, 259-273. Doi: https://doi.org/10.1080/14620316.2018.1472045
  12. Gilmore, E.C. and J.S. Rogers. 1958. Heat units as a method of measuring maturity in corn. Agron. J. 50, 611-615. Doi: https://doi.org/10.2134/agronj1958.00021962005000100014x
  13. Lúcio, A.D., L.F. Nunes, and F. Rego. 2015. Nonlinear models to describe production of fruit in Cucurbita pepo and Capiscum annuum. Sci. Hortic. 193, 286-293. Doi: https://doi.org/10.1016/j.scienta.2015.07.021
  14. Lúcio, A.D., B.G. Sari, M. Rodrigues, L.M. Bevilaqua, H.M.G. Voss, D. Copetti, and M. Faé. 2016. Nonlinear models for estimating cherry tomato yield. Cienc. Rural 46, 233-241. Doi: https://doi.org/10.1590/0103-8478cr20150067
  15. Lyra, G.B, S. Zolnier, L.C. Costa, G.C. Sediyama and M.A.N. Sediyama. 2003. Modelos de crescimento para alface (Lactuca sativa L.) cultivada em sistema hidropônico sob condições de casa-de-vegetação. Rev. Bras. Agrometeorol. 11, 69-77.
  16. Maynard, D.N. and G. J. Hochmuth. 2007. Knott’s handbook or vegetable growers. 5th ed. John Wiley e Sons, Hoboken, NJ. Doi: https://doi.org/10.1002/9780470121474
  17. Mischan, M.M. and S.Z. Pinho. 2014 Modelos não lineares: funções assintóticas de crescimento. Cultura Acadêmica, Sao Paulo, Brazil.
  18. Muniz, J.A, M. S. Nascimento, and T.J Fernandes. 2017. Nonlinear models for description of cacao fruit growth with assumption violations. Rev. Caatinga 30, 250-257. Doi: https://doi.org/10.1590/1983-21252017v30n128rc
  19. Ntsoane, L.L.M., P. Soundy, J. Jifon, and D. Sivakumar. 2016. Variety-specific responses of lettuce grown under the different coloured shade nets on phytochemical quality after postharvest storage. J. Hortic. Sci. Biotechnol. 91, 520-528. Doi: https://doi.org/10.1080/14620316.2016.1178080
  20. Pereira, A.A., A.R. Morais, M.S. Scalco, and T.J. Fernandes. 2014. Descrição do crescimento vegetativo do cafeeiro cultivar Rubi MG 1192, utilizando modelos de regressão. Coffee Sci. 9, 266-274.
  21. Pereira, A.A., A.R. Morais, M.S. Scalco, and T.J. Fernandes. 2016. Modelagem do diâmetro de copa do cafeeiro podado cultivado em diferentes densidades e regimes hídricos. Coffee Sci. 11, 495-501.
  22. Pôrto, D.R.Q., A.B. Cecílio Filho, A. May, and J.C. Barbosa. 2006. Acúmulo de macronutrientes pela cebola ‘Optima’ estabelecida por semeadura direta. Hortic. Bras. 24, 470-475. Doi: https://doi.org/10.1590/S0102-05362006000400015
  23. Prado, T.K.L., T.V. Savian, and J.A. Muniz. 2013. Ajuste dos modelos Gompertz e Logístico aos dados de crescimento de frutos de coqueiro anão verde. Cienc. Rural 43, 803-809. Doi: https://doi.org/10.1590/S0103-84782013005000044
  24. Puiatti, G.A., P.R. Cecon, M. Nascimento, M. Puiatti, F.L. Finger, A.R., Silva, and A.C.C. Nascimento. 2013. Análise de agrupamento em seleção de modelos de regressão não lineares para descrever o acúmulo de matéria seca em plantas de alho. Rev. Bras. Biom. 31, 337-351.
  25. R Development Core Team. 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
  26. Reis, R.M., P.R. Cecon, M. Puiatti, F.L. Finger, M. Nascimento, F.F. Silva, A.P.S. Carneiro and A.R. Silva. 2014. Modelos de regressão não linear aplicados a grupos de acessos de alho. Hortic. Bras. 32, 178-183. Doi: https://doi.org/10.1590/S0102-05362014000200010
  27. Ribeiro, T.D., T.V. Savian, T.J. Fernandes, and J.A. Muniz. 2018. The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar. Cienc. Rural 48, 1-7. Doi: https://doi.org/10.1590/0103-8478cr20161097
  28. Sala, C.F. and C.P Costa. 2012. Retrospectiva e tendência da alfacicultura brasileira. Hortic. Bras. 30, 187-194. Doi: https://doi.org/10.1590/S0102-05362012000200002
  29. Sari, B.G., A.D. Lúcio, C.S. Santana, and T.V. Savian. 2019. Describing tomato plant production using growth models. Sci. Hortic. 246, 146-154. Doi: https://doi.org/10.1016/j.scienta.2018.10.044
  30. Terra, M.F., J.A. Muniz, and T. V. Savian. 2010. Ajuste dos modelos Logístico e Gompertz aos dados de crescimento de frutos de tamareira-anã (Phoenix roebelenni O’BRIEN). Magistra 22, 1-7.

Downloads

Download data is not yet available.

Most read articles by the same author(s)

Similar Articles

<< < 1 2 3 4 > >> 

You may also start an advanced similarity search for this article.