首页> 外文期刊>Journal of Animal Physiology and Animal Nutrition >Condensing results of wet sieving analyses into a single data: a comparison of methods for particle size description.
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Condensing results of wet sieving analyses into a single data: a comparison of methods for particle size description.

机译:将湿筛分分析的冷凝结果合并为一个数据:粒径描述方法的比较。

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摘要

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.
机译:筛分分析用于饲料分析,并通过各种方法研究消化生理,以描述粒径平均值,可用于比较不同样品。为了证明这种不同方法的效果,我们比较了五个粒径指标以证明每种方法的优缺点,分别是细度模量(MOF),离散平均值(dMEAN)和中位数(dMED)和连续平均值(cMEAN) )和中位数(cMED),充分意识到这一程序缺乏黄金标准的事实。通过在9个筛网的级联上湿筛,从580个不同草食动物种类的粪便样本中获得数据,筛网尺寸为0.063至16 mm。 MOF,dMEAN和dMED可以直接从筛分分析的结果中计算出来,但是cMEAN和cMED需要曲线拟合程序。在整个样本量中,dMEAN和cMEAN相关性最高。 d的MEAN和MED之间的相关性高于c。不出所料,MOF与其他度量的偏差最大。模拟不同的筛网组会导致MOF和cMED中不同筛网组的结果之间的相关性较差,但dMEAN和cMEAN的相关性很好,这表明也可以在不使用相同筛网组的研究之间比较后一种方法。由于dMEAN的计算比cMEAN相对更简单且耗时更少,因此我们建议使用dMEAN作为描述通过筛分分析获得的平均粒径值的标准。对于实际应用,不同模拟筛网组的良好相关性表明,筛网较少的组可用于大规模研究中,以减少分析工作量。

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