Colorimetry analysis of coat color and its relationship with fiber traits in alpacas

Abstract

Addressing the improvement of the textile characteristics is currently required in natural color production of alpaca fiber. This study analyses the possibility of implementing a genetic improvement program aiming to reduce the fiber diameter and the percentage of medullation in natural colors under the incomplete definition of the natural colors of alpaca fiber. The study considers color determination analysis in three separate steps. The first step aimed at finding the values of lightness (L*), red/green axis (a*), yellow/blue axis (b*) of three-dimensional space of color and chroma (C*ab), tone (h*ab) and color difference (ΔE) with mathematical models for the description of the coat color. The second analysis is aimed at estimating genetic parameters of color traits and their correlation with fiber traits (fiber diameter, standard deviations and percentage of medullation – PM). The third step was to determine the potential selection criteria of breeding animals based on the parameters provided by a three-dimensional space values regarding the coat color assignment in alpacas. The colorimetric data were taken using a Chroma meter device analyzing 3 008 records from Huacaya type alpacas, collected between 2018 and 2019. In the first objective of the study, the color traits were subjected to a principal component analysis. The analysis of variance components and the estimation of genetic parameters were carried out using a restricted maximum likelihood procedure. The discriminant analysis was used for the correct assignment of the coat color. The principal component analysis results showed that the L*, a*, b*, h*ab and ΔE values can be grouped into two Principal Components (PC) to describe the color, where the L* value is mainly distributed in PC2, b* is distributed in PC1, while a* is distributed in both components. The heritabilities found were 0.144, 0.128, 0.151, 0.104 and 0.152 for L*, a*, b*, PC1 and PC2. The relevant genetic correlations were between L*-PM (−0.557) and b*-PM (−0.622). The discriminant analysis showed a high percentage of correct assignment in white (99.15%) and black (99.19%) coat colors for Huacaya type alpacas, while for the intermediate colors, the accuracy was lower. The three analyses showed that there is no pure natural color, but a range of color variation. It is better to use the values of the three-dimensional space and within them, the values of L* and b* are potential selection criteria to be included in a genetic improvement program.