Investigating the Growth of Bacteria using Double Sigmoid Model with Reparameterization
https://doi.org/10.56225/ijgoia.v2i4.239
Keywords:
Growth curve, Bacterial growth, Pseudomonas putida, Double Sigmoid ModelAbstract
The growth of an organism can be modeled using a growth curve. However, bacteria's growth pattern differs from other organisms. Bacterial growth is divided into four phases: lag, logarithmic, stationary, and death. The experts re-parameterized the growth curve to match the growth phase of the bacteria. Bacterial growth patterns generally do not show a single sigmoid pattern but form two curves. Therefore, the double sigmoid model is more suitable. This study modeled the growth of the Pseudomonas putida bacteria by observing the optical density of the medium. Model parameters are estimated using the Non-Linear Least Square (NLS) method with the Gauss-Newton algorithm. The modeling results show that the double sigmoid model fits the growth curve of Pseudomonas putida better than the single sigmoid model. The Double Logistic model outperforms all models with the highest adjusted R2 and the smallest RMSE, AIC, and BIC values.
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References
Anderson, A. (2014). Business Statistics for Dummies. John Wiley & Sons.
Burnham, K. P., & Anderson, D. R. (2004). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.). Springer.
Chong, E. K. P., & Zak, S. H. (2013). An Introduction to Optimization (4th ed.). Wiley.
de Sousa, J. E. R., Façanha, D. A. E., Bermejo, L. A., Ferreira, J., Paiva, R. D. M., Nunes, S. F., & do Socorro Medeiros de Souza, M. (2021). Evaluation of non-linear models for growth curve in Brazilian tropical goats. Tropical Animal Health and Production, 53(198), 1–14. https://doi.org/10.1007/s11250-021-02598-2
Lai, W. H., Kek, S. L., & Tay, K. G. (2017). Solving Nonlinear Least Squares Problem Using Gauss-Newton Method. International Journal of Innovative Science, Engineering & Technology, 4(1), 258–262.
Longhi, D. A., Dalcanton, F., De Aragão, G. M. F., Carciofi, B. A. M., & Laurindo, J. B. (2017). Microbial growth models: A general mathematical approach to obtain μmaxand λ parameters from sigmoidal empirical primary models. Brazilian Journal of Chemical Engineering, 34(2), 369–375. https://doi.org/10.1590/0104-6632.20170342s20150533
Madigan, M. T., Bender, K. S., Buckley, D. H., Sattley, W. M., & Stahl, D. A. (2021). Brock Biology of Microorganisms (16th ed.). Pearson.
Njalam’mano, J. B. J., & Chirwa, E. M. N. (2019). Determination of Growth Parameters of Butyric Acid-Degrading Bacterium, Achromobacter xylosoxidans, as a Function of Constant Temperatures in Batch System. Chemical Engineering Transactions, 76, 1321–1326. https://doi.org/10.3303/CET1976221
Panik, M. J. (2014). Growth curve modeling: Theory and applications. In Growth Curve Modeling: Theory and Applications. https://doi.org/10.1002/9781118763971
Pla, M.-L., Oltra, S., Esteban, M.-D., Andreu, S., & Palop, A. (2015). Comparison of Primary Models to Predict Microbial Growth by the Plate Count and Absorbance Methods. BioMed Research International, 2015, 1–14. https://doi.org/10.1155/2015/365025
Prayogo, W. P., Suprijatna, E., & Kurnianto, E. (2017). Perbandingan Dua Model Pertumbuhan dalam Analisis Pertumbuhan Itik Magelang di Balai Pembibitan dan Budidaya Ternak Non Ruminansia Banyubiru, Kabupaten Semarang. Jurnal Sain Peternakan Indonesia, 12(3), 239–247.
Priestley, M. B. (1981). Spectral Analysis and Time Series. Academic Press.
Puteri, M. S. M. (2015). Karakterisasi Enzim Organofosfat Hidrolase (OPH) dari Pseudomonas Putida dengan Menggunakan Substrat Dimetoat. Universitas Brawijaya.
Siregar, R. W., Tulus, & Ramli, M. (2018). Analysis Local Convergence of Gauss-Newton Method. IOP Conference Series: Materials Science and Engineering, 300, 1–6. https://doi.org/10.1088/1757-899X/300/1/012044
Tjørve, K. M. C., & Tjørve, E. (2017). The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family. PLoS ONE, 12(6), 1–17. https://doi.org/10.1371/journal.pone.0178691
Vázquez, J. A., Lorenzo, J. M., Fuciños, P., & Franco, D. (2012). Evaluation of non-linear equations to model different animal growths with mono and bisigmoid profiles. Journal of Theoretical Biology, 314, 95–105. https://doi.org/10.1016/j.jtbi.2012.08.027
Wiradarya, T. R., Putra, W. P. B., Harahap, A. E., & Alwi. (2020). The growth curve of body weight in Kacang goats managed by smallholders at Tambang District of Indonesia. International Journal of Agriculture, Environment and Food Sciences, 4(3), 334–339. https://doi.org/10.31015/jaefs.2020.3.12
Zhang, J. X. J., & Hoshino, K. (2019). Optical transducers: Optical molecular sensing and spectroscopy. In Molecular Sensors and Nanodevices (pp. 231–309). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-814862-4.00005-3
Zwietering, M. H., Jongenburger, I., Rombouts, F. M., & van ’t Riet, K. (1990). Modeling of the bacterial growth curve. Applied and Environmental Microbiology, 56(6), 1875–1881.
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