• Title/Summary/Keyword: Model validation

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Modification of an Ecosystem Model for Carrying Capacity of Shellfish System -I . Validation and Sensitivity Analysis- (패류양식해역 환경용량 산정 모델 구축 -I . 모델 검정 및 민감도 분석-)

  • Lee Won Chan;Kim Hyung Chul;Choi Woo Jeung;Lee Pil Yong;Koo Jun Ho;Park Chung Kil
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.35 no.4
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    • pp.386-394
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    • 2002

  • Carrying capacity model focused on interactions between the filter-feeder growth and their environments is presented, and differences among existing various carrying capacity models are reviewed. For carrying capacity modeling of shellfish system, we constructed a new numerical model coupled oyster growth model with an ecosystem model (EUTRP2). Physical and biological processes such as water transport and mixing, primary production, feeding and growth of the cultivated oyster, Crassostrea gigas and benthic-pelagic exchange were included in the model, Simulated results for validation showed that the more phytoplankton biomass decreased, the more oyster meat weight and nutrients increased, suggesting a powerful tool for reasonable management of shellfish aquaculture. The model was sensitive to parameters controlling the primary production. Among the ecosystem compartments, the oyster growth is highly influenced by small changes in the physiological parameters of phytoplankton and oyster. This sensitivity analysis indicated the importance of experimental data on biological parameters for calibration of the model.

  • https://doi.org/10.5657/kfas.2002.35.4.386 인용 PDF KSCI

Predictive Modeling of the Growth and Survival of Listeria monocytogenes Using a Response Surface Model

  • Jin, Sung-Sik;Jin, Yong-Guo;Yoon, Ki-Sun;Woo, Gun-Jo;Hwang, In-Gyun;Bahk, Gyung-Jin;Oh, Deog-Hwan
    • Food Science and Biotechnology
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    • v.15 no.5
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    • pp.715-720
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    • 2006

  • This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

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