Heritability of individual fiber medullation in Peruvian alpacas

doi:10.1016/j.smallrumres.2018.04.007

Small Ruminant Research

Volume 165, August 2018, Pages 93-100

https://doi.org/10.1016/j.smallrumres.2018.04.007 Get rights and content

Highlights

•
Heritability for fiber medullation in alpaca was of moderate magnitude.
•
Selection against prickling would be indicated using medullation as criterion.
•
Continuous model for fiber medullation was better than threshold model.
•
Removing prickling will impact the income of alpaca producers.

Abstract

The aim of this research was to estimate for the first time the heritability and genetic relationship between medullation and fiber diameter in each fiber by itself. A total of 21,600 fibers from 36 samples from white fleeces, 600 fibers each sample, from males between 0.4 and 10.4 years old from Pacomarca experimental farm (Inca Group, Puno, Peru) were tested using projection microscope (PM). The individual fiber diameter (FD) and the category of medullation (CM) was recorded in each fiber. CM of each fiber was assigned to one of the five categories established in the literature. The percentage of medullated fiber ranged from 12.33% to 91.67% per sample. The correlation between OFDA 100 ^® medullation percentage and PM measurements was 0.79. The statistical model used for estimation of genetic parameters for CM and FD included the age as a linear and quadratic covariate as systematic effect, and the additive genetic and the permanent environmental as random effects. The pedigree that served to predict genetic values was very robust and strong, allowing obtaining reliable and significant parameters. Univariate and bivariate models were used to estimate heritability for CM and DF, as well as its genetic correlation. Different models considering CM as continuous or categorical trait were tested. The highest heritability estimate for CM was 0.36 ± 0.13 obtained using a bivariate continuous model. Using the same model, the heritability estimate for FD was 0.35 ± 0.15 and the genetic correlation between CM and FD was 0.93 ± 0.12. These results implied that selection against medullated fiber is feasible while at the same time reducing the FD in alpacas. Since measurement of CM per fiber sample was time-consuming, PM measured by OFDA 100 ^® would be useful as an indicator to reduce the number of medullated fiber in alpaca fleeces.

Introduction

Alpaca fiber quality is worldwide considered among the best for the textile industry. However its price is still far from other fine animal fibers like cashmere. The main argued reason is the prickle factor associated to alpaca fiber. Big efforts have been made in order to remove this particular issue. Thus, prickling has been linked to fiber diameter, particularly to fibers thicker than 30 μm, and consequently comfort factor has been defined as the percentage of fibers lower than that value (McGregor, 1997; Frank et al., 2006), as an interesting trait to work with. In order to remove prickle factor, selection has been carried out based on the reduction of fiber diameter as selection criterion in Pacomarca experimental farm (Gutiérrez et al., 2011), and a fast reduction has been achieved (Gutiérrez et al., 2014), but prickle factor has not completely been removed. The medullated fiber and type of medullation has alternatively been blamed as responsible for prickle factor (Frank et al., 2014; Frank et al., 2017; McGregor, 1997). They called them objectionable fiber, appearing to have opacity greater than 94% and a diameter greater than 25 μm (IWTO, 1998). If selection objective in fiber has been traditionally the thinness of the fiber and prickle factor still remains, an alternative would be to move the selection criterion from fiber diameter to fiber medullation to reduce prickle factor. A strong genetic relationship between medullation and thickness seems to exist but it would have to be studied individually in each fiber; working with global parameters as mean fiber diameter and medullation percentage might hide information. Before implementing selection based on medullation, that relationship would have to be firstly carefully studied as it would imply important changes, and the first step is to know how heritable individual medullation would be, as well as the genetic relationship between diameter and medullation within each fiber. Such genetic parameters have never been previously estimated in alpacas. Thus, the objective of this study was to estimate genetic parameters of individual fiber medullation in alpacas, as well as to explore its relationship with fineness in each fiber itself, and the possible ways to model the medullation classification to predict breeding values useful in selection of animals.

Section snippets

Material and Methods

A total of 21,600 fibers from 36 samples of white fleeces, 600 fibers each sample, from white Huacaya males between 0.4 and 10.4 years old from Pacomarca experimental farm (Inca Group, Puno, Peru) were analyzed. The fiber samples were prepared and analyzed according to IWTO-8-2011 (IWTO, 2011) procedure at the Universidad Nacional Agraria La Molina (Lima, Perú).

Each individual fiber was considered as one record. Note that this consideration provides 600 records per sample, and the resulting

Results

Variance components estimates for medulla category using several different models combining univariate or bivariate models with fiber diameter, threshold or continuous linear models, and different grouping of medulla categories are shown in Table 2, jointly with the respective standard deviations of their marginal posterior distributions. Heritability estimates for medulla trait ranged from 0.23 to 0.36 in linear models, and from 0.11 to 0.15 in threshold models. All the heritability estimates

Discussion

Over the last years, research on alpaca breeding has been carried out at Pacomarca experimental farm. Some findings have led to some changes in the selection objective (Gutiérrez et al., 2014). Even though initially the textile value was the goal for Pacomarca (Morante et al., 2009), it was shown that the selection response for the goal would be higher if the criterion would focus on the mean fiber diameter of a staple (Gutiérrez et al., 2009). In addition, the selection objective was decided

Conclusion

The heritability of the individual fiber medullation under a continuous linear model was found to be moderate, suggesting that medullation can be used as a selection criterion to decrease the effect of the prickle factor, as itself or maybe combined with fiber diameter. Among all the possible models and grouping ways essayed, grouping jointly all type of medullated fibers will be the trait to use in breeding programs, but the great cost of work under projection microscope suggests rather using

Conflict of interest

None.

Acknowledgment

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References (37)

D. Allain et al.
Genetic and non-genetic variability of OFDA medullated fiber contents and other fleece traits in the French Angora goats
Small Rumin. Res.
(2006)
M. Antonini et al.
Relationship between age and postnatal skin follicular development in three types of South American domestic camelids
Livest. Prod. Sci.
(2004)
I. Cervantes et al.
Genetic parameters and relationships between fiber and type traits in two breeds of Peruvian alpacas
Small Rumin. Res.
(2010)
A. Cruz et al.
Estimation of genetic parameters for reproductive traits in alpacas
Anim. Reprod. Sci.
(2015)
A. Cruz et al.
Effect of the gestation and lactation on fiber diameter and its variability in Peruvian alpacas
Livest. Sci.
(2017)
A. Cruz et al.
Genetic parameters estimation for preweaning traits and their relationship with reproductive, productive and morphological traits in alpaca
Animal
(2017)
E.N. Frank et al.
Phenotypic and genetic description of fiber traits in South American domestic camelids (llamas and alpacas)
Small Rumin. Res.
(2006)
E.N. Frank et al.
Genetic parameters for fleece weight and fiber attributes in Argentinean Llamas reared outside the Altiplano
Small Rumin. Res.
(2011)
F. Goyache et al.
Genetic analysis of calf survival at different preweaning ages in beef cattle
Livest. Prod. Sci.
(2003)
J.P. Gutiérrez et al.
Genetic analysis of six production traits in Peruvian alpacas
Livest. Sci.
(2009)

J.P. Gutiérrez et al.

Weighting fiber and morphological traits in a genetic index for an alpaca breeding program

Animal

(2014)

C.J. Lupton et al.

Medullation in mohair

Small Rumin. Res.

(1991)

B.A. McGregor et al.

The relationship of the incidence of medullated fibers to the dimensional properties of mohair over the lifetime of Angora goats

Small Rumin. Res.

(2013)

B.A. McGregor

Production attributes and relative value of alpaca fleeces in southern Australia and implications for industry development

Small Rumin. Res.

(2006)

M.M. Paredes et al.

Association of microsatellite markers with fiber diameter trait in Peruvian alpacas (Vicugna pacos)

Livest. Sci.

(2014)

J.I. Weller et al.

Models for genetic analysis of dystocia and calf mortality

J. Dairy Sci.

(1989)

J.L. Altarriba et al.

Bayesian inference of variance components for litter size in Rasa Aragonesa sheep

J. Anim. Sci.

(1998)

I. Cervantes et al.

Genetic relationships among calving ease, gestation length, and calf survival to weaning in the Asturiana de los Valles beef cattle breed

J. Anim. Sci.

(2010)

Cited by (25)

Development and validation of a smart system for medullation and diameter assessment of alpaca, llama and mohair fibres
2023, Animal
Medullated fibres, due to their higher resistance to bending and pressure, constitute a problem for the textile industry. Thus, having practical instruments to identify them is essential. Therefore, the aim of this research was to develop and validate a novel, swift, automatic system (referred to as S-Fiber Med) for medullation and diameter assessment of animal fibres based on artificial intelligence. The medullation of 88 samples of alpaca, llama and mohair fibres (41, 43 and 4, respectively) was evaluated. Additionally, 269 samples of alpacas were considered for average fibre diameter (AFD) and the results were compared with the Portable Fiber Tester (PFT) and Optical Fibre Diameter Analyser (OFDA) methods (72 and 197 samples, respectively). The preparation of each sample to be analysed followed the procedure described in IWTO-8-2011. Version 5 of “You Only Look Once” and DenseNet models were used to recognise the type of medullation and diameter of the fibres, respectively. Within each image (n = 661 for alpaca), all fibres were labelled (as Non-Medullated, Fragmented Medulla, Uncontinuous Medulla, Continuous Medulla and Strongly Medullated) using the LabelImg tool. Data augmentation technique was applied to obtain 3 966 images. Such data set was divided into 3 576 and 390 images for training and test data, respectively. For mohair samples (n = 321), a similar process was carried out. The data to train the model used to infer the diameter contained 16 446 fibres labelled with his respective AFD. A complementary hardware composed of three subsystems (mechanical, electronic, and optical) was developed for evaluation purposes. T-test, Pearson and Concordance correlation, Bland-Altman plot and linear regression analyses were used to validate and compare the S-Fiber Med with other methods. Results indicate that there was no significant difference between medullation percentage obtained with the projection microscope and the S-Fiber Med. The Pearson and Concordance correlation analysis shows a strong, high and significant relationship (P-value < 0.001). The AFDs of alpaca and llama fibre samples obtained with the two methods are very similar, because no significant difference was found at the t-test (P-value > 0.172), and they have a strong, high and significant relationship between them, given the high Pearson correlation value (r ≥ 0.96 with P-value < 0.001), high Concordance coefficient and bias correction factor. Similar results were found when PFT and OFDA100 were compared with S-Fiber Med. As a conclusion, this new system provides precise, accurate measurements of medullation and AFD in an expeditious fashion (40 seconds/sample).
Genomic selection improves genetic gain for fiber traits in a breeding program for alpacas
2023, Livestock Science
The implementation of genetic improvement programs including genomic information leads to higher genetic and economic gains in animal production. So far, genomic selection in alpacas is still at an early stage and its response for fiber quality traits has not been studied. Therefore, this study aimed to evaluate the genetic gains for fiber diameter (FD) and percentage of medullation (PM) using BLUP (Best Linear Unbiased Prediction) and ssGBLUP (single-step Genomic BLUP) under five selection index scenarios. The ZPLAN+ software was used to simulate for FD and PM annual genetic gain and standardized genetic gain, and also a total standardized genetic gain for a selection index. Input parameters were taken from field data of the Pacomarca Scientific Station in the Highlands of Peru. The respective weights given for FD and PM in the selection indexes were as follows: -1 and 0 (Scenario 1); -0.75 and -0.25 (Scenario 2); -0.5 and -0.5 (Scenario 3); -0.25 and -0.75 (Scenario 4); and 0 and -1 (Scenario 5). Total standardized genetic gain from the alpaca breeding program based on ssGBLUP in scenario 2 was higher compared to other scenarios. In all scenarios the genetic gain using ssGBLUP were higher than those from BLUP. Therefore, the use of genomic breeding values could have a favorable impact on genetic gains for FD and PM in alpacas.
Application of artificial intelligence and digital images analysis to automatically determine the percentage of fiber medullation in alpaca fleece samples
2022, Small Ruminant Research
Citation Excerpt :
In white animal fibers, the main cause of opacity is medullation (hollow fibers). It is thus unlikely to detect medullae of small diameter in thin fibers (Reid et al., 2007), and probably in other types of animal fibers such as alpaca (Pinares et al., 2018; Torres, 2020), Angora rabbit (Rafat et al., 2007), or Brushtail possum fibers (Reid et al., 2007), because they have different properties of wool. Alpaca fibers have higher %MedFib, the scales are thinner and the shape and structure are different compared to wool (McGregor and Quispe, 2018).
The aim of this research is to develop and validate two computer programs based on artificial intelligence (AI) and digital image analysis (DIA) in order to determine the incidence of medullation in white alpaca fibers. Two data sets were analyzed: 76 samples of Huacaya alpaca fibers obtained from Huancavelica, Peru, and 200 samples of white alpacas of two genotypes (Huacaya, n =100; Suri, n = 100), obtained from Arequipa, Peru. The preparation of each sample followed the procedure described in IWTO-8-2011. The Pytorch framework was used to generate several training models based on the You Only Look at Once (YOLO) architecture. Circa 4000 pictures of fibers were taken and 661 of them were selected as representative. Using the LabelImg software, the fibers present in each representative picture (approximately 10 fibers/picture) were labeled as one of these two classes: either medullated or non-medullated. Subsequently, the data augmentation technique was applied to expand the data set to 3966 photographs. Thus, 90 of them were used as initial validation data, while the reaming 3876 pictures (containing a total of 23,964 labeled fibers) were used as training data. Matlab was used to develop the DIA-based software. More specifically, algorithms of pre-processing, segmentation, smoothing, skeletonization and Hough transform were implemented to detect medullated and non-medullated fibers. Correlation and linear regression analyses were used to evaluate the models. The medullation percentage results show that there is no statistically significant difference between the AI-based method and the projection microscope method (p-value = 0.668 and 0.672 for the t-student and Wilcoxon tests, respectively). Moreover, the correlation of each of the developed computer methods with the projection microscope method is very strong (r = 0.99 and 0.97). This confirms the software ability to perform the recognition of fibers with and without medullation. Similar results (p-value = 0.357) were obtained when comparing the projection microscope method and DIA-based software method. Finally, using the proposed framework, the average time required to analyze a sample was 19.44 s. As a result, this software allows the implementation of practical, precise, and efficient methodologies to determine the incidence of medullation of alpaca fibers.
Colorimetry analysis of coat color and its relationship with fiber traits in alpacas
2021, Animal
Citation Excerpt :
The variance components were estimated using a restricted maximum likelihood procedure under a multitrait animal model, in which three values were taken from the three-dimensional space and the linear coefficients of the two principal components retained. These have been correlated with the FD and SD described by Gutiérrez et al. (2009) and the percentage of medullation as described by Cruz et al. (2019) and Pinares et al. (2018). The fixed effects included in the model for colorimetry traits were as follows: sex (2 levels) coat color (9 levels), year of recording as contemporary group (2 levels) and age as linear and quadratic covariate.
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.
Mohair, cashmere and other animal hair fibres
2020, Handbook of Natural Fibres: Second Edition
Although luxury animal fibres, excluding silk, represent far less than 0.1% of global fibre production of 100 million tons (10 x 10¹⁰ kg), they play a very significant role in the luxury, high-value-added end of the market, notably the apparel market, being renowned for their special and mostly unique features, notably comfort and softness. This chapter covers the production, properties, processing and end-uses of the various luxury animal fibres, with the exclusion of silk, with the main focus on the down (undercoat) fibres of those animals with two fibre coats.
Genetic (co)variance across age of fiber diameter and standard deviation in Huacaya alpacas, estimated by repeatability, multi-trait and random regression models
2020, Livestock Science
Citation Excerpt :
This result is consistent with those published by Cruz et al. (2017)a, 2019), Gutiérrez et al. (2011), 2014) and Morante et al. (2009) in Pacomarca's own herd as well as in other regions of Peru (Roque and Ormachea, 2018) and in Australia (McGregor and Butler, 2004). The similar results of the Pacomarca program had already been indicated by Cervantes et al. (2010), Cruz et al. (2017a, 2019), Gutiérrez et al. (2009), 2011), Morante et al. (2009) and Pinares et al. (2018) and the current study with the largest number of observations corroborates the same type of favorable response for the quality of the Huacaya alpaca fiber in the period between 2003 and 2017. In terms of genetic parameters, the estimates of heritability between 0.263 and 0.368 for FD and SD respectively according to the RM model (Table 2), were within the range of publications available that has been compiled in Table 10 with heritabilities between 0.24 and 0.73.
A total of 14,378 records of fiber diameter (FD) and its standard deviation (SD) from Huacaya alpaca recorded between 2001 and 2017 at Pacomarca genetic center were used in this study. These records were analyzed by a repeatability (RM), multitrait (MT) and random regression (RRM) models. The heritability (h²) estimates were 0.263 and 0.368 for FD and SD respectively under a RM model; these ranged from 0.653 to 0.742 for FD and 0.627 to 0.764 for SD under MT and from 0.561 to 0.614 for FD and 0.556 to 0.702 for SD under RRM. The MT and RRM show a pattern of increase in variances and heritability as age increases for SD and till 6 years of age for FD, while the genetic correlation (rg) decrease for both traits between 1 and 5 years of ages. The breeding value for the three models show a linear relationship for FD and SD across age at shearing, meaning that any of these models can be used in the selection process. The results of this study shows that during this period of time a highly favorable selection response was obtained for fiber quality in Huacaya alpaca using RM, however the use of the RRM approach can offer more valuable information, particularly in the persistence of the genetic merit of the animals at 5 years respect to 1 years old at shearing. More research is needed on the use and relationship between persistence and others economical traits in alpaca.

View all citing articles on Scopus

View full text

Heritability of individual fiber medullation in Peruvian alpacas

Highlights

Abstract

Introduction

Section snippets

Material and Methods

Results

Discussion

Conclusion

Conflict of interest

Acknowledgment

Small Rumin. Res.

Livest. Prod. Sci.

Small Rumin. Res.

Anim. Reprod. Sci.

Livest. Sci.

Animal

Small Rumin. Res.

Small Rumin. Res.

Livest. Prod. Sci.

Livest. Sci.

Animal

Small Rumin. Res.

Small Rumin. Res.

Small Rumin. Res.

Livest. Sci.

J. Dairy Sci.

Bayesian inference of variance components for litter size in Rasa Aragonesa sheep

J. Anim. Sci.

Genetic relationships among calving ease, gestation length, and calf survival to weaning in the Asturiana de los Valles beef cattle breed

J. Anim. Sci.