Variability in measurement of Pithomyces chartarum spore counts

Abstract

AIMS To examine the agreement between spore counts of Pithomyces chartarum measured in a single aliquot of wash water with counts from multiple aliquots from the same 60 g pasture sample, and between spore counts measured in an individual 60 g pasture sample with counts from three 60 g pasture samples selected from the same 200 g paddock sample. MATERIALS AND METHODS Four Waikato dairy farms were visited once weekly from early January to late May 2013. One paddock, with 40 sampling sites, was selected per farm. At each visit, ∼200 g of pasture was collected per site. Spore counting was undertaken using a standard method, except that three separate 60 g pasture samples per 200 g paddock sample was counted; and for each 60 g pasture sample, spores were counted in 10 aliquots of wash water. The relationship between the results of a single aliquot and 6-10 aliquots of wash water from the same 60 g grass sample were assessed by calculating 95% prediction intervals. Limits of agreement analysis was used to assess the agreement between counts from one, two or three aliquots per 60 g pasture sample compared with 10 aliquots, and between counts from one and three 60 g pasture samples from the same 200 g paddock sample. RESULTS Comparing spore counts from individual aliquots with multiple aliquots resulted in large prediction intervals and 95% limits of agreement, which increased with increasing spore count. For an individual aliquot count of 2 spores, the 95% prediction interval for the count from 10 aliquots was 3-49 spores, and for an individual count of 10 spores the 95% prediction interval was 28-222 spores. Increasing the number of aliquots counted improved agreement. For a total count of 10 spores measured in 10 aliquots, the 95% limits of agreement, based on a single aliquot, were 2-50 spores, and for three aliquots were 5-20 spores. The agreement in spore counts measured in one compared with three 60 g pasture samples was moderate and also decreased with increasing spore count; the 95% limits of agreement were 4-14.5 for a mean spore count of 10. CONCLUSIONS AND CLINICAL RELEVANCE Measuring the spore counts of three aliquots of wash water per 60 g grass sample improved repeatability, and should be used as the standard technique, particularly when determining whether to start or finish facial eczema control programmes.

Predicting facial eczema risks in a changing New Zealand climate

“…A first step towards improving the model would be to delve more deeply into its results to understand why some years were outliers in linear relationships between annual exposure to spores and climatic suitability. Many factors could reduce the fit between model predictions and spore counts such as: suboptimal model specifications; incomplete knowledge of P. chartarum including its interactions with pasture management (Lancashire and Keogh 1968;Lima et al 2012;Smith et al 1963); errors inherent in summarising climate data, model results and spore counts; errors in spore count measurements (Cuttance et al 2017); and variation between VCSN climate data and the real climate (Cichota et al 2008;Tait et al 2012;Mason et al 2017). Other next stage work could include running the model using daily data rather than weekly means, analysing the sensitivity of its predictions to ranges of variable values, and making predictions using future climate data from General Circulation Models additional to HADGEM2.…”

Biomarker identification and development of aptamers for the diagnosis of sub-clinical facial eczema

“…This management protocol may be assisted by spore counting to establish the density of Pithomyces chartarum spores in pasture. However, the high degree of variability between pastures, and the low correlation between spore counts and associated numbers of animals with clinical cases of facial eczema, means this method only provides an approximate indication (Cuttance et al, 2017).…”