Effects of sample homogenizing on the performance of an automated strongylid egg counting system

Martin K. Nielsen, Daniel Doran, Paul Slusarewicz

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Fecal egg counts are essential monitoring tools in veterinary parasite control. In recent years, several groups have developed automated egg counting systems based on image analysis and deep learning algorithms. Work in our laboratory demonstrated that an automated system performed with significantly better precision than traditional egg counting techniques. However, while the counting process is no longer operator dependent, the pre-analytical homogenization steps still are. This study aimed at evaluating the influence of sample homogenization on diagnostic performance on an automated equine strongylid egg counting system. Samples were collected from 12 horses and assigned to three egg count categories (four samples per category): Low (0–500 eggs per gram (EPG)), Moderate (501–1000 EPG), and High (1001–2000 EPG). Within each category, all samples were divided into four portions and each was analyzed with the automated system using the following four homogenizing procedures using a homogenizing device supplied with the system: 1) pressing the plunger five times and pouring directly into the counting chamber, 2) pressing the plunger five times and shaking the bottle prior to pouring, 3) pressing the plunger ten times with direct pouring, and 4) pressing the plunger ten times with shaking the bottle before pouring. There were no differences in precision expressed as coefficient of variation between these four procedures but shaking of the bottle prior to pouring was significantly associated with higher counts (p = 0.0068). These results demonstrate that the homogenization process can affect the diagnostic performance of an automated egg counting system and suggest that more efforts should be invested in standardizing and optimizing homogenization procedures.

Original languageEnglish
Article number109623
JournalVeterinary Parasitology
StatePublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.


  • Accuracy
  • Count
  • Fecal
  • Horse
  • Precision
  • Strongyle

ASJC Scopus subject areas

  • Parasitology
  • General Veterinary


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