Abstract

To identify fleece and animal growth characteristics that are associated with cashmere production, the magnitude and direction of factors affecting cashmere production using fleece and live body weight measurements available to the cashmere producer were modelled. Data was collected from 11 Australian commercial cashmere farms. Following log transformation of clean cashmere weight, the best general linear model for predicting clean cashmere weight included: farm, mean fibre diameter, fibre diameter standard deviation, cashmere fibre curvature and fibre curvature standard deviation, cashmere staple length, clean washing yield, live body weight, live body weight change, and interactions between these parameters. The best general linear model did not include variables for age and sex cohorts. The variance accounted for was 67.6%. The residual standard deviation was 0.115. A majority of the variation regarding clean cashmere production (58%) was related to farm, staple length and mean fibre diameter. To obtain an understanding of how the responses of clean cashmere weight to fleece and growth measurements varied with farm, regression coefficients in the general linear model were modelled as possibly correlated random effects, using REML mixed model analysis. On a typical farm, greater clean cashmere weight was associated with longer staple length, greater mean fibre diameter, greater fibre diameter standard deviation, greater fibre curvature, greater fibre curvature standard deviation and greater live body weight. Farms recorded responses varying from negative to positive for washing yield and live body weight change. It was concluded that fleece characteristics and animal growth (but not age and sex) are primary determinants of cashmere production. However, the way these characteristics affect cashmere production varies from farm to farm.

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