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Optimising the number of isolates to be used to estimate growth parameters of mycotoxigenic species

机译：优化用于估计致毒毒素物种生长参数的分离株数量

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摘要

The aim of the present work was to mathematically assess the minimum number of isolates that would lead to equivalent growth parameters estimates to those obtained with a high number of strains. The datasets from two previous works on 30 Aspergillus carbonarius isolates and 62 Penicillium expansion isolates were used for this purpose. First, the datasets were used to produce a global estimation of growth parameters μ (growth rate, mm/d) and A (time to visible growth, d) under the different experimental conditions, providing also a 95% confidence interval. Second, a computational algorithm was developed in order to obtain an estimation of the growth parameters that one would obtain using a lower number of isolates and/or replicates, using a bootstrap procedure with 5000 simulations. The result of this algorithm was the probability that the obtained estimation falls in the 95% confidence interval previously produced using all sample isolates. Third, the algorithm was intensively applied to obtain these probabilities for all possible combinations of isolates and replicates. Finally, these results were used to determine the minimum number of isolates and replicates needed to obtain a reasonable estimation, i.e. inside the confidence interval, with a probability of 0.8, 0.9 and 0.95. The results revealed that increasing the number of isolates may be more effective than increasing the number of replicates, in terms of increasing the probability. In particular, 12-17 isolates of A carbonarius led to the same growth parameters as the total 30 (p = 0.05) or 9 isolates with p = 0.20; by contrast, 25-30 isolates of P. expansum led to the same growth parameters as the total 62 (p = 0.05) or 18-21 isolates with p = 0.20. As far as we know, this is the first study that provides a systematic evaluation of the number of isolates and replicates needed when designing an experiment involving mycotoxigenic moulds responses to environmental factors, and may serve to support decision making in this kind of studies or other similar ones.
机译：本工作的目的是在数学上评估分离株的最小数量，该分离株将导致与使用大量菌株获得的菌株等效的生长参数估计值。为此，使用了之前针对30株碳曲霉分离株和62株青霉菌扩展株进行的两次研究获得的数据集。首先，在不同的实验条件下，使用数据集对生长参数μ（生长速率，mm / d）和A（可见生长时间，d）进行全局估计，还提供了95％的置信区间。其次，开发了一种计算算法，以便通过使用具有5000个模拟的自举程序来获得对使用较少数量的分离物和/或复制品可获得的生长参数的估计。该算法的结果是获得的估计值落在先前使用所有样本分离物产生的95％置信区间内的概率。第三，该算法被广泛应用，以获取分离物和复制品所有可能组合的这些概率。最后，这些结果用于确定获得合理估计所需的最小分离数和重复数，即在置信区间内，概率为0.8、0.9和0.95。结果表明，就增加可能性而言，增加分离株的数量可能比增加重复数量的方法更为有效。特别是，12-17个A碳菌的分离株导致了与总30个（p = 0.05）或9个分离株（p = 0.20）相同的生长参数。相比之下，25.-30个扩张假单胞菌导致的生长参数与62个总体（p = 0.05）或18-21个分离菌（p = 0.20）相同。据我们所知，这是第一项研究，当设计涉及致毒素的霉菌对环境因素的反应的实验时，它提供了系统评估所需要的分离物和复制品数量的信息，并可能有助于支持此类研究或其他方面的决策类似的。

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  • 来源
    《Food microbiology》 |2012年第2期|p.235-242|共8页
  • 作者

    Daiana Garcia; Joan Vails; Antonio J. Ramos; Vicente Sanchis; Sonia Marin;

  • 作者单位

    Food Technology Department, Lleida University, XaRTA-UTPV, Agrotecnio Center, Rovira Rome 191, 25198 Lleida, Spain;

    Biostatistics Unit, Biomedical Research Institute of Lleida (IRBUEIDA), Rovira Roure 80, 25198 Lleida, Spain;

    Food Technology Department, Lleida University, XaRTA-UTPV, Agrotecnio Center, Rovira Rome 191, 25198 Lleida, Spain;

    Food Technology Department, Lleida University, XaRTA-UTPV, Agrotecnio Center, Rovira Rome 191, 25198 Lleida, Spain;

    Food Technology Department, Lleida University, XaRTA-UTPV, Agrotecnio Center, Rovira Rome 191, 25198 Lleida, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    growth parameters; estimation; replication; intraspecies variability; mycotoxin;

    机译：生长参数;估计;复制;种内变异性;霉菌毒素;

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