Genetic (co)variance across age of fiber diameter and standard deviation in Huacaya alpacas, estimated by repeatability, multi-trait and random regression models
Introduction
The production of alpaca fiber is one of the main sources of income for the high Andean inhabitants of South America Andes. Its profitability is influenced by the quantity and quality of the fleece that each alpaca produces. The alpaca fleece weight is of about 2.2 kg and usually performing steadily from one year of age up to ten years with a maximum of weight around 2.7 kg in the fourth or five year of age. The quality refers to the diameter of the fiber; those of smaller diameters or called fine fibers offer greater opportunities to produce textiles of greater acceptance in the market, competing commercially with fiber of other species such as goats and rabbits (Allain and Renieri, 2010). Fiber diameter usually ranges from 19 to 36 µm (Cruz et al., 2019), but there exists still finer fiber, like the new commercial category called "alpaca sixteen" referring to mean fiber diameter below 17 µm. In addition, for an optimal quality, the fiber diameter must be accompanied by uniformity, and this is assessed by low values of standard deviation. There are many factors that affect the production and quality of alpaca fiber, some directly linked to the fiber itself, such as follicular density and staple length that depends on the interval between shearing and others linked to the seasonality and the number of shearing of each alpaca concomitant with age (Gutiérrez et al., 2011).
The animal selection can be a very important tool taking into account the important genetic variability in several traits of economic importance in alpaca (Cervantes et al., 2010; Cruz et al., 2015, 2017a, 2019; Gutiérrez et al., 2009, 2011; Pinares et al., 2018); so that one of the basic objectives has so far focused on decreasing fiber diameter, with satisfactory results (Cruz et al., 2017a; Gutiérrez et al., 2014; Morante et al., 2009). These authors have applied a repeatability multitrait model (MT) for predicting of the breeding values and the estimation of (co)variance components, which implies assuming the same form of response to the selection throughout the different shearing of the alpaca. However, some evidence indicates that genetic parameters may be different when the number of shearing is treated as independent traits within a multivariate animal model (MT), as indicated by Pun et al. (2011) in alpacas and Wang et al. (2014) in cashmere goats. Comparing among performances of an individual across its productive life allows dealing with properties as plasticity and persistence. Plasticity would be the ability of an animal to change its phenotype when conditions environmental changes, while persistence would refer to the ability of an animal to keep performing across its productive life. A plastic animal would also be more persistent as it would accommodate its performance level across its life.
Many of the traits of economic interest are expressed and recorded repeatedly throughout the life of the animal and are called as Function Value Traits (FVT) cited by de Jong (1990), which can be analyzed by longitudinal models and the study of alpaca fiber diameter can be included as an example of FVT. The practical use of this concept of FVT allows to make more precise descriptions of the trajectory of a trait in terms of the variations of its genetic components throughout the productive age of the animal. Random regression models (RRM) are the statistical procedure that have proven useful for this type of traits (Schaeffer, 2004), in different scenarios of animal production and is currently the method recommended in the analysis and estimation of genetic variance components (Martínez et al., 2011). Under certain conditions the MT and RRM models can produce similar results. However, in practical terms the superiority of RRM in growth traits has been demonstrated (Speidel, 2009) as well as in milk production (Mrode and Coffey, 2008) among others.
The purpose of this paper was to estimate (co)variance components, heritability and genetic correlation of fiber diameter (FD) and its standard deviation (SD) in Alpacas of the Huacaya type estimated by repeatability, multitrait and random regression models along the age at shearing trajectory. The comparison between models would allow making better decisions about the use of these tools during the selection of alpacas.
Section snippets
Data
The data were taken from the Genetic Center of Pacomarca, dedicated to the production of fiber for textile production, located in southern Peru. The fiber samplings were carried out at the time of the shearing of the alpacas, fiber samples of approximately 100 gr were taken mid-side of the animal, which is the most representative area of the fleece and which is best correlated with other body parts (McGregor et al., 2012), these samples were washed and bent in four, sectioning the fiber in
Results
The results of the first fixed effects model showed highly significant differences for the age effects, the least square means evolution of FD and SD is shown in Fig. 1. This representation can be interpreted as the maturity pattern for FD and SD which apparently show the same form, but with some differences. For FD, a first stage was manifested with a sustained increase until 5 years of age (23.96 µm) with increases of 19.61% per year with regard to the mean at first shearing (19.20 µm), after
Discussion
Improving the fiber textile qualities in both fineness and uniformity is the objective in alpaca production. It has been possible to select very fine animals, but age is crucial in increasing the thickness of the fiber and it would be interesting to look for the animals that maintain the fineness throughout the different shearing, the effects of age show a pattern of increase in FD and SD up to 4 years of age, increasing from 19.20 to 23.96 µm in only four years. This increase of 4.76 µm
Conclusion
In conclusion, the use of a transversal RM model used till present time of selection process in Pacomarca herd have provided important results of genetic progress. The MT and RRM models showed the same expected response for both traits. Nevertheless, the RRM provided additional information that might be used to deal with persistence. The breeding program in Pacomarca could use a screening process based in the persistence results for the selection of the parents of the next generation. More
Declaration of Competing Interest
There is no conflict of interest for this paper.
Acknowledgement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author Declaration
We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.
We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.
We confirm that we
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