Test for the presence of autocorrelation in the modified Gompertz model used in fitting of Burkholderia sp. strain Neni-11 growth on acrylamide

A. Shukor, M. Yunus
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Abstract

The growth of microorganism on substrates, whether toxic or not usually exhibits sigmoidal pattern. This sigmoidal growth pattern can be modelled using primary models such as Logistic, modified Gompertz, Richards, Schnute, Baranyi-Roberts, Von Bertalanffy, Buchanan three-phase and Huang. Previously, the modified Gompertz model was chosen to model the growth of Burkholderia sp. strain Neni-11 on acrylamide, which shows a sigmoidal curve. The modified Gompertz model relies on the ordinary least squares method, which in turn relies heavily on several important assumptions, which include that the data does not show autocorrelation. In this work we perform statistical diagnosis test to test for the presence of autocorrelation using the Durbin-Watson test and found that the model was adequate and robust as no autocorrelation of the data was found.
修正Gompertz模型拟合伯克霍尔德氏菌菌株Neni-11在丙烯酰胺上生长的自相关性检验
微生物在基质上的生长,无论是否有毒,通常呈s型模式。这种s型增长模式可以使用诸如Logistic、改进的Gompertz、Richards、Schnute、Baranyi-Roberts、Von Bertalanffy、Buchanan三相和Huang等主要模型来建模。在此之前,我们选择改良的Gompertz模型来模拟伯克霍尔德氏菌菌株Neni-11在丙烯酰胺上的生长,结果显示为s型曲线。修正后的Gompertz模型依赖于普通最小二乘法,而普通最小二乘法又严重依赖于几个重要的假设,其中包括数据不显示自相关。在这项工作中,我们使用Durbin-Watson测试进行统计诊断测试,以测试自相关的存在,并发现该模型是足够的和稳健的,因为没有发现数据的自相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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