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将湿筛分析结果浓缩为单个数据:粒径描述方法的比较。

Condensing results of wet sieving analyses into a single data: a comparison of methods for particle size description.

机构信息

Institute of Physiology, Physiological Chemistry and Animal Nutrition, Ludwig-Maximilians-University Munich, Germany.

出版信息

J Anim Physiol Anim Nutr (Berl). 2012 Oct;96(5):783-97. doi: 10.1111/j.1439-0396.2011.01183.x. Epub 2011 Jul 6.

Abstract

Sieve analysis is used in feed analysis, and studies of digestive physiology with various approaches to describe an average value of particle size which can serve to compare different samples. To demonstrate the effects of such different approaches, we compared five particle size indicators to demonstrate advantages and disadvantages of each method, the modulus of fineness (MOF), the discrete mean (dMEAN) and median (dMED), and the continuous mean (cMEAN) and median (cMED), well aware of the fact that a gold standard for this procedure is lacking. Data were obtained from 580 individual faecal samples of different herbivore species by wet sieving over a cascade of nine sieves with mesh sizes ranging from 0.063 to 16 mm. MOF, dMEAN and dMED can be calculated directly from the results of sieve analysis, but cMEAN and cMED require a curve-fitting procedure. Across the whole sample size, dMEAN and cMEAN showed the highest correlation. The correlation between the respective MEAN and MED was higher for d than for c. As expected, MOF deviated most from the other measurements. Simulating different sieve sets resulted in a poor correlation between the results from the different sets in MOF and cMED, but a good correlation in dMEAN and cMEAN, suggesting that these latter measures can also be compared between studies that do not use identical sieve sets. As the calculation of dMEAN is comparatively simpler and less time-consuming than that of cMEAN, we propose the dMEAN as a standard for the description of a mean particle size value obtained from sieve analysis. For practical application, the good correlation of different simulated sieve sets indicates that sets with fewer sieves could be used in large-scale studies to reduce analytical workload.

摘要

筛析法用于饲料分析和各种消化生理研究,以描述可用于比较不同样本的平均粒径值。为了展示这些不同方法的效果,我们比较了五种粒径指标,以展示每种方法的优缺点,即细度模数(MOF)、离散平均值(dMEAN)和中位数(dMED),以及连续平均值(cMEAN)和中位数(cMED),我们深知缺乏该方法的金标准。通过对来自 580 个不同食草动物物种的个体粪便样本进行湿筛,在由网孔尺寸从 0.063 毫米到 16 毫米的九级筛的级联上进行筛选,获得了数据。MOF、dMEAN 和 dMED 可以直接从筛析结果计算得出,但是 cMEAN 和 cMED 需要曲线拟合过程。在整个样本大小范围内,dMEAN 和 cMEAN 显示出最高的相关性。d 比 c 的各自 MEAN 和 MED 之间的相关性更高。正如预期的那样,MOF 与其他测量值的偏差最大。模拟不同的筛网套件导致 MOF 和 cMED 的结果之间的相关性较差,但在 dMEAN 和 cMEAN 之间的相关性较好,这表明这些后一种测量值也可以在不使用相同筛网套件的研究之间进行比较。由于 dMEAN 的计算相对比较简单,并且比 cMEAN 用时更少,因此我们建议将 dMEAN 作为描述通过筛析获得的平均粒径值的标准。在实际应用中,不同模拟筛网套件的良好相关性表明,在大型研究中可以使用较少筛网的套件来减少分析工作量。

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