CASHMERE GOAT BREEDING IN SCOTLAND
S.C. Bishop1 and A.J.F. Russel2
(Roslin Institute, Roslin, Midlothian EH25 9PS, Scotland1 and Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB15 8QH, Scotland2)
The Scottish cashmere goat industry derives from importations of kids, semen and embryos from Siberia, New Zealand, Tasmania and Iceland from 1986 to 1988. These strains were then intercrossed and crossed with native feral goats to form the base population of Scottish cashmere goats. These goats are farmed at the MLURI’s Sourhope Research Station, which acts as the nucleus for subsequent breeding, and also on commercial farms. These farms are known collectively as Cashmere Breeders Limited (CBL). At its peak, CBL comprised 18 farms and currently, it has 9 farms.
Selection for improved productivity commenced prior to the matings that produced the 1992-born cohort of kids. Selection was practised in the herd at Sourhope which formed the nucleus, supplying bucks to the other CBL member farms. The nucleus herd was initially split into three lines, (i) a line selected for improved cashmere production (the Value line), (ii) a line selected for decreased fibre diameter (the Fine line) and (iii) an unselected control line. One year later, a line selected for helminth resistance (following natural parasite challenge) was initiated. There were 190, 95, 70 and 95 does allocated to the Value, Fine, Control and Helminth lines, respectively. Selection decisions in the Value and Fine lines were based on 10-cm2 patch samples of cashmere taken on 5-month old kids. For each kid, fibre diameter (average and variation within the sample) was measured and total annual cashmere production was estimated, from the weight of cashmere in the sample and the live weight of the kid. The Value line selection criterion was a selection index designed to increase the total value of cashmere produced, derived using published genetic parameter values for fibre diameter and cashmere weight. Relative economic weights for these traits were estimated from 1991 world cashmere prices. This index was predicted to increase cashmere weight, with a small increase in fibre diameter.
Each year, the best five yearling bucks in the Value line and the best four in the Fine line were used for breeding in their respective lines. Additionally, four bucks were selected at random from the Control line for use within this line. Having reserved the top ranking bucks for use in the nucleus, all bucks in the nucleus were then ranked on the ‘fibre value’ selection index. Bucks with index values above the population mean, along with the top ranking bucks from the previous year, were then presented for use in the CBL herds. CBL farmers chose their bucks from those currently available at the nucleus, as well as those used previously on other farms.
Both the Value line and the Fine line responded strongly to selection. In the Value line, there has been an increase in estimated cashmere weight, compared to the Control line, of 16.1g/year (7.3%/year), with no change in fibre diameter. The diameter of the Fine line has decreased by –0.19m/year (1.25%/year),but this has been accompanied by a large and undesirable decrease in cashmere weight.
Breeding goals for these goats have recently been re-examined. The Control and Fine lines, which no longer have commercial value, have been discontinued whilst the Value line has been expanded to include the highest ranking does from the now-defunct Fine and Control lines. This should allow continued rapid genetic progress whilst avoiding inbreeding. It also gives the opportunity to increase the proportion of goats bearing white cashmere. Finally, the genetic control of the date-of-onset of fibre shedding is being quantified, with the eventual aim of also including this as a selection goal.
This paper describes the current status of cashmere goat breeding in Scotland. Briefly summarised will be the structure and background of the cashmere goat breeding industry, the current selection goals and protocols, the genetic progress that has been achieved to date, and some consideration of future plans.
The Scottish cashmere goat industry derives from importations of kids, semen and embryos from cashmere-bearing strains of goats from Siberia, New Zealand, Tasmania and Iceland, from 1986 to 1988. A full description of these importations and the rationale for targeting each strain is given by Bishop and Russel (1994). These strains were then intercrossed and crossed with native feral goats, which also bore small quantities of high quality cashmere. The resulting population of two- and three-way crosses formed the base population of Scottish cashmere goats, used for subsequent breeding.
The Scottish cashmere goat industry has the classical pyramid breeding structure. Selection for productivity is performed at the MLURI’s Sourhope Research Station, which acts as a nucleus for the entire industry. Superior sires are then passed onto a group of commercial farms which, together with MLURI’s Sourhope Research Station, are known collectively as Cashmere Breeders Limited (CBL). At its peak, CBL comprised 18 farms and, currently, it has 9 farms. The commercial farms within CBL effectively act as multipliers. Goats from the CBL farms are then disseminated to the wider cashmere goat industry.
Selection Objectives and Protocols
Selection for improved productivity of cashmere commenced prior to the matings that produced the 1992-born cohort of kids at Sourhope. The original selection goals were designed with two objectives: (i) to produce genetically superior goats for CBL farmers and for the wider industry and (ii) to provide the industry with future options, should the industry requirements for cashmere change. Specifically for the latter, it was envisaged that the industry may become more discriminating with regard to high quality (fine) cashmere. To meet these objectives, three lines were created from the base population: (i) a line selected for increased value of fibre (the Value line), (ii) a line selected for decreased fibre diameter (the Fine line) and (iii) and an unselected Control line.
The Value line selection criterion was a selection index designed to increase the total value of fibre produced. The selection index combined measurements of the estimated annual production of cashmere and fibre diameter, both measured on 5-month old kids. Heritabilities and genetic correlations, used in the derivation of this index, were taken from previously published values, largely Australian studies. The relative economic values for the two traits were estimated from 1991 world cashmere prices. The actual index equation is given below. The expectation of the selection responses produced by selection on this index, prior to the commencement of selection, was that there would be a large increase in the weight of cashmere accompanied by a small increase in fibre diameter.
All measurements taken for the purposes of selection and monitoring selection responses were performed on 5-month old kids. In Scotland, this is mid-September and corresponds to approximately 2.5 months of cashmere growth. At the time of measurement, all kids were weighed, a 10-cm2 mid-side patch sample of fibre was collected and fibre colour was observed. On the patch fibre sample the following measurements were made: total fibre weight, weight of cashmere in the sample, average fibre diameter, the standard deviation of fibre diameter, fibre length, the proportion of medullated fibres and the proportion of fibres greater than 27m in diameter.
From these 5-month measurements the estimated annual cashmere production (EAP) was calculated as follows: EAP = 53.6 x (live weight)0.703 x (patch cashmere weight)/0.4. The (53.6 x (live weight)0.703) component relates the patch area to the total cashmere-producing surface area of the goat and the divisor (0.4) reflects the assumption that 5-month kids have grown 40% of their total annual weight of cashmere. This assumption affects the absolute estimated quantity of cashmere, but it does not affect the relative ranking of animals.
The selection index for the Value line, after scaling to simplify, was 2.6 x EAPs – Diameters. The subscript ‘s’ indicates that the trait was corrected for known environmental influences, then scaled to have a mean of zero and a standard deviation of 1.0. The selection index describes the expected performance of progeny of animals. It does not summarise the phenotype of animals. To summarise the actual performance of animals and provide a means of comparing the different selection lines, the so-called ‘Cashmere Production Index’ (CPI) was derived. The formula used was CPI = EAP x (1-0.2 x (Diameter – mean Diameter)). The regression coefficient 0.2 describes the increase in the value of cashmere as fibre diameter decreases, and it was also calculated from 1991 world cashmere prices. The CPI may be thought of as the expected actual value of cashmere produced by a goat, taking into account the fibre diameter.
The three selection lines, the Value, Fine and Control lines, remained intact until the autumn of 1997, when the population structure was redefined, as described below. These three lines comprised 190, 95 and 70 does, respectively. The number of bucks used each year was five for the Value line, four for the Fine line and four for the Control line. These bucks were ranked and selected within lines and used for mating in the nucleus at 1.5 years of age. Mating was practised to minimise inbreeding.
The commercial CBL farms were given access to the best quality bucks available, after meeting the requirements of the nucleus herd. All male kids in the nucleus were ranked on the Value line selection index. The following categories of bucks were then presented, along with their breeding values, to CBL members for selection: 1. bucks with index values above the population mean, but not required in the nucleus 2. top ranking bucks from the previous year which had been used in the nucleus 3. bucks used on another farm in a previous year 4. any other desirable buck (e.g. having exceptionally fine white fibre).
Selection Responses and Genetic Parameters
After some variation between years (essentially replicate) in the first two years of selection, the Value line has shown a rapid response in estimated annual cashmere weight, compared to the Control line. This response comprised a large change in the weight of cashmere in the patch sample but no change in 5-month live weight. There is no change in average fibre diameter in the Value line, compared to the Control line. These responses differ slightly from expectation insofar, as the expected deleterious increase in fibre diameter has not occurred.
The Fine line has shown a steady improvement in fibre diameter, but again, there is considerable between-year (replicate) variation in the difference between the Fine and Control lines. The improvements in fibre diameter in the Fine line have, however, been outweighed by the large decreases in estimated cashmere production. The decrease in EAP is consistent and it demonstrates that selection merely for reduced fibre diameter is not a desirable policy.
Annual selection responses were estimated by regressing the difference between the selection and Control lines on the year of selection. The annual response, in estimated cashmere production in the Value line, was 16.1g/year, or 7.3% per year. This is considerably greater than commonly observed rates of genetic gain of 1-2% per year, reflecting both the high heritability of cashmere traits (see below) and also the considerable genetic variability in the crossbred base population. The annual response in the cashmere production index was 5.7%/year. The annual response in the Fine line was -0.19m/year, or 1.25% per year. This value is more typical of rates of response usually observed in domestic livestock.
Genetic parameters, i.e. heritabilities, genetic and phenotypic correlations, were estimated using data collected in the nucleus from 1987 to 1993. A detailed description of these results is given by Bishop and Russel (1996). Genetic parameters are usually calculated for a variety of reasons: e.g. to give insight into the biology of the trait, to indicate how successful selection is likely to be, or to enable multi-trait selection indices and/or BLUP to be developed. Heritabilities for fibre traits and live weight were as follows:
|Fibre length||Live weight|
The heritabilities for cashmere weight in the patch sample and estimated cashmere weight were calculated on log-transformed data. Maternal effects were negligible for the fibre traits but strong for live weight. The values observed for the fibre traits are all extremely high, especially when compared to heritabilities typically observed for traits measured on domestic livestock. However, these values are not atypical of published heritabilities for cashmere traits. Moreover, they are borne out by the strong selection responses subsequently observed in the nucleus.
In terms of the relationships between traits, fibre diameter, weight and length were all strongly correlated, both phenotypically and genetically. The fibre traits and live weight tended to be uncorrelated. Regression of cashmere weight on fibre diameter showed cashmere weight to be proportional to diameter2.7. This power relationship helps to explain the disproportionate decrease in cashmere weight when selecting to reduce fibre diameter.
Future breeding and research in the cashmere goats in Scotland will be directed towards (i) continuing to breed genetically superior cashmere goats and (ii) expanding our breeding goals.
The nucleus at Sourhope was restructured in 1997. The Fine and Control lines were discontinued as the former was considered unlikely to be economically viable and the latter no longer scientifically necessary. All does in the nucleus were then ranked on their selection index breeding value, and the Value line was expanded to include the best of the now-available does. This expanding of the Value line should allow continued, or even more, rapid genetic progress, whilst avoiding potential inbreeding problems. A group of does was also used in special matings, in an attempt to increase the proportion of goats bearing white cashmere, as white cashmere commands a higher price in the market. The current genetic research effort is focused on studying the patterns of fibre shedding in the goats. Delaying and synchronising the moulting of cashmere in the spring would be a major advantage to cashmere producers, as it would ease the harvesting (by combing) of cashmere, reduce fibre losses and, in some environments, reduce housing costs.
Future options, which may enable us to better meet our aims of breeding genetically superior cashmere goats, include improved selection strategies and broader breeding goals. In terms of improved selection strategies, options that may be considered include multiple-trait BLUP for better estimating breeding values and techniques to better select and design matings, e.g. linear programming and mate selection or even selection based on long term expected contributions. Broader breeding goals may include delayed fibre shedding (as described above), an extended growing season, fibre colour and other quality attributes, and resistance to nematode parasites.
All staff at MLURI’s Sourhope Research Station are thanked for their time and effort in managing the goats and collecting the data. Appreciation is extended to John Barker for managing the goat database, Hilary Redden for supervising the fibre analyses and Margaret Merchant and Ian Wright for continued input into the cashmere research. Funding from the Scottish Office Agriculture, Environment and Fisheries Department, the Scottish Development Agency and the European Community is gratefully acknowledged.
Bishop, S.C. and Russel, A.J.F. (1994). Cashmere production from feral and imported cashmere goat kids. Animal Production, 58:135-144.
Bishop, S.C. and Russel, A.J.F. (1996). The inheritance of fibre traits in a crossbred population of cashmere goats. Animal Science, 63: 429-436.
Line means for Estimated Annual cashmere Production (EAP), fibre diameter, Cashmere Production Index (CPI) and the selection responses:
Line Means for EAP (g) Line Means for diameter (microns)
Value line Fine line Control line Value line Fine line Control line
Line Means for CPI Selection responses
Value line Fine line Control line CPI response EAP response Diameter reponse
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ORGANISATION OF FRENCH ANGORA RABBIT GENETIC SELECTION
H. de Rochambeau1, D. Allain2 and R. G. Thébault3
SAGA, INRA Toulouse, BP37, 31326 Auzeville, France1, INRA Toulouse, SAGA, BP 27, 31326 Castanet-Tolosan, France2 and INRA Magneraud Phanères, Génétique Animale, BP 52, 17700 Surgères, France3
French Angora rabbit production has been in crisis for several years. The number of producers has dramatically decreased. However, work done in the 1980s enabled the precise description of an efficient selection scheme for Angora rabbits. This paper describes the use of performance and other data for genetic and technical improvements. For all species, the use of performance data has technical and economical objectives. The data collected consist in the identification and pedigree of the animal, reproductive performance and fibre production. The animals need to be identified and birth records collected. Tattoos are the reference method for rabbit identification. Where once paper copies allowed information transfer between the farm and the organisation which manages the data, today, computers enable a much faster means of information transfer. The collected data are used to establish a technical evaluation of the breeding farm. The analysis of fibre production enables the farmer to identify his weak and strong points by comparing his results with those of other farms. The additive genetic value of each producer can be then estimated. The use of "BLUP animal models" gives precise estimations of the genetic value of young animals. It is therefore possible to lower the traditional selection age. When the next generation reproducers are chosen, their age, index and potentialities are taken into account. The choice of males is important; their pedigree must be perfectly known. Therefore they are relatively old. For replacement females, the pedigree of the animals is not so important. These evaluations are made from the breeder's collected data. They are completed by a checking organised by the "Pedigree Book". This checking introduces our expert's view and allows the breeder to know exactly the potentiality of his animals within the breed. A collective genetic scheme is more efficient, hence the breeders must work together. Artificial insemination is now well known for the rabbit. On the farm, the utilisation of several males from other farms increases the index precision and allows comparisons between farms. It would be therefore useful to create a breeding centre for young males, which could be used later for artificial insemination. Experiences in other species shows what could be done for Angora rabbit.
Angora rabbit production in France
The Angora rabbit was introduced into France in 1723 from England or Turkey. Genetic selection began in the 1930's, but mainly since 1956-57. A herd book was created at that time, the "Angora Rabbit Book of France". In it, a French Angora rabbit type appeared, with a special fibre quality due to the breed (selection effect) and the harvest process (plucking and later defleecing). By 1988, there were about 250 000 angora rabbits, more than 2000 breeders and a production of fibre of 200 tonnes, exported as a raw material. In 1997, there were only 13 000 rabbits left, 100-120 breeders and a production of 12 tonnes for manufactured clothes.
Herd book "Angora Rabbit Book of France"
Created in 1956, the Herd Book is run by a breeders' organisation, the "Syndicat National Angora Qualité". The improvement of rabbit is done by mass selection. The breeders send a birth registration form for each litter and the animals are individually identified at weaning (provisional number). The animals are graded prior to their fourth harvest by a qualified judge and receive a final official number (ear tag). The breakdown of the total of 100 marks in the grading scheme is as follows: · 20 for body conformation (according to the official standard for body development, ears, head and legs) · 40 for fibre quantity · 40 for fleece quality, of which 15 marks are for homogeneity (bristly fleece rate), 15 marks are for tautness (intensity of bristly character) and 10 marks are for structure. On farm, data are registered on card for each animal, on which the harvest dates, weight of the harvested fibre (by categories) and fibre length are recorded.
Within the French breed, the harvested fibre is sorted and distinguished as 5 classes, according to quality: · Class 1: clean, unfelted, long and bristly fibre, from the back, the sides and the rump of the rabbit. · Class 2: clean, unfelted, long and wooly fibre, from the breast and the belly of the animal. · Class 3: clean, unfelted, short (<6 cm) fibre, from the legs of the rabbit. · Class 4: clean and felted fibre, from the neck and the tail of the animal. · Class 5: dirty fibre, from the underbelly of the rabbit.
Fleece characteristics measurements:
The Angora fleece is heterogeneous. Over the body, there are 5 different grades, whose quality criteria are based on the bristly or woolly aspect, length, the degree of felting and the cleanliness. Inside the lock, there are three fibre types, in which quality criteria are linked with the fibre dimensions and the fleece composition.
The fleece measurements made on the farm are the total fleece weight of each different grades and the length of each fibre type (bristle, downs). In the laboratory, the measurements are from the fleece samples, and they concern the diameter of each fibre type (bristle, awns, downs) by the OFDA method, and the content of each fibre type (bristle rate), using the INRA Cross Section method.
Breeding programme for Angora wool production
The breeding programme was orientated towards the effect of non-genetic factors on the quantitative and qualitative traits. The effects of the sex, birth season, body weight, harvest rank, harvest season, time interval between two harvests, breeder and the year on the total fibre production were quantified. The homogeneity and the structure of the fibre were taken into consideration. The results of this programme were as follows:
Genetic improvement of the French Angora Rabbit
One proposal is to have a collective programme, with a recording system for data collection and data transfer. It would allow both technical and genetic improvement, through selection on the farm and a collective genetic improvement programme. The latter could be done by creating genetic links between farms. The proposal would be to tattoo all the rabbits just after the first harvest and to score all the rabbits before the fourth harvest. On the whole population, the date of harvest, the total fibre weight and reproduction data would be collected. On the top selected population, it would be useful to collect data concerning the homogeneity, tautness and structure of the fleece (as an objective measurement of quality). Finally, connections between farms could be improved by setting up a performance testing farm and developing artificial insemination.
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A GENETIC DATABASE FOR PERFORMANCE PARAMETER RECORDING IN DANISH ANGORA GOATS
Annette Holmenlund, Marie E. Kielsgaard and Joern Pedersen
Danish Agricultural Advisory Centre, Udkaersvej 15, Skejby, 8200 Aarhus-N, Denmark
The Danish goat registration system is a database storing data on pedigree, reproduction, growth rates, mohair yields, mohair quality and health. The database is based on an unambiguous identification system for individuals and on the farmers' own recordings of breeding and production data. The data stored in the database is used as documentation of pedigree, to estimate breeding indices and to produce management information for farmers. The Goat Registration System has been developed since 1991 and today 188 Angora herds are in the system, including 19 Swedish herds. The Nordic Angora goat population consists of many small herds. This is one of the reasons why we have developed a genetic indexation system over the past years, enabling us to compare animals from different herds and to find the best bucks and does in the Nordic countries. This will ensure the best possible basis for breeding progress and thus a profitable mohair production. How can we then incorporate more information about mohair quality into the goat registration system? This is one of the main questions to be dealt with in the next two years. We have defined two pre-conditions. Firstly, we would rather accept many quality figures and thus a higher degree of unreliability on the figures than vice-versa and, secondly, the method should be cheap, simple and user-friendly, in order to get full breeder support.
Since 1991, the Danish Angora goat breeders have reported their pedigree, breeding and production data to a computer-based goat registration programme, which stores all pedigree data on live animals and embryos imported since 1987. The purpose of goat registration programme is to develop a profitable mohair production, both through breeding and production, through the development of breeding values and management lists to the farmers.
One hundred and eighty-eight Angora herds, together with nineteen Swedish herds, are using the goat registration programme. In 1997, one hundred and thirty-three herds sent data about the births of 1400 kids from 1000 does. The breeding is characterised by many small herds with an average of 7.5 kidding per herd (1997).
The Angora goat population consists mainly of animals of the Australasian type imported from New Zealand. They are at present being upgraded using Angora of the Texas and South African types, imported in 1992 and 1993 from Australia and New-Zealand, respectively. The aim is to maintain the quality of the breeding work; it is achieved through the participation of the majority of the goat registration programme herds, which permits the data collection to continue.
The goat registration programme is being currently developed and the latest initiatives are the development of linear classification, breeding values (Pedersen, 1994) and "Herd Prints".
The goat registration system is based on an unambiguous nine-digit eartag number, which follows the animal from birth to death. It also includes the goat owners' own records of matings (inclusive of the buck's ID), kiddings (kidding ease, mortality, birth weight and ID of the kid), the kid's live weights at 2 and 4 months, all fleece weights, disease records, purchase, sale and deaths. Furthermore classification results and mohair test results are recorded.
All records are always linked to the unambiguous eartag number of the animal and to the date of the event, e.g. date of kidding and date of shearing.
From the goat registration system, the herd owner obtains:
The purpose of Herd Prints is that the lists can be adapted to the day-to-day needs of the individual farmer and they can replace some paper work.
Mohair yield and quality
Mohair production consists of two parameters, yield (quantity) and quality. The Angora herds report the fleece weights of every shearing which takes place twice a year - the first one being at the age of 5-7 months. A total of 8700 fleece weights is recorded in the database.
The quality of the mohair is measured objectively through a mohair test and subjectively through a classification scheme. The mohair test is analysed at the National Research Centre, Foulum and includes fibre diameter, standard deviation of the fibre diameter, percentage kemp, medullation and per-cent roundness. A total of 375 mohair samples has been analysed since it started.
The linear classification results are divided into a figure for body and legs, and a figure evaluating the mohair quality (fibre fineness, kemp and medullation, lustre, lanolin, style, character and cover). One hundred and fifty-seven animals were classified in 21 herds in 1995, when linear classification was introduced. In 1996, one hundred and seventy-five and, in 1997, ninety-four animals were linear classified.
As both mohair yield and fibre fineness are important economic production parameters, it is important that as many data as possible are collected on these two parameters. It would be a major progress if more data on mohair quality was available in the database.
Indices in Angora breeding
The traits are divided into 5 main categories:
Animal's own traits:
Kemp and medullation:
Besides the five main indices and the three sub-indices describing mohair quality, a total breeding index is estimated, the S-index, combining all the indices. Like sheep and beef cattle breeding, Angora goat breeding is characterised by a very limited number of artificial inseminations. Therefore the male breeding animals have only a small number of progeny, often born in one herd. Hence, it is very difficult to estimate breeding values which can be compared, from one herd to another and for animals born in different years. In connection with sale or exchange of breeding stock -and perhaps insemination- some relationships will be established in other herds. By using the Animal Model, it is thus possible to estimate fairly reliable breeding values.
The Animal Model estimates breeding values, making allowance for the heritabilities of the traits and the known relationships. At the same time, a correction is made for systematic environmental impacts. These corrections allow a comparison between the results collected in different environmental conditions (e.g. herds) and for different categories of animal (e.g. sex and age).
Table 1 shows the average indices of all Angora goats born during the past 6 years. When comparing the results of the different years, the breeding progress achieved can be estimated. According to Table 1, Angora breeding activities have been based on the evaluation of the mohair. Progress has also been achieved in the field of production and fineness, due to the positive correlation between mohair evaluation and mohair quality.
Table 1. Average of indices for birth year and breeding process per year (1990-1997)
* calculated by means of regression analysis
|1990||1992||1994||1996||1997||Average change per year*|
|Number of animals||651||1824||1584||1408||1387||-|
|Kemp & medullation||99.8||99.7||101.9||103.6||104.0||0.8|
The purpose of estimating the S-index is to increase the total breeding progress in the years to come. It should be possible to greatly improve production figures and fineness while, at the same time, maintaining or moderately improving mothering traits and liveability.
Do we do enough recording?
Jørn Pedersen (pers. comm.) has analysed the number of information recorded on the registered goats. Thirteen thousand two hundred and forty-seven Angora goats have been registered in the Danish Angora database. Eight percent are born in foreign countries and 12 per cent are not registered from birth. The remaining 79 per cent corresponds to 10,488 animals. The following records have been reported, expressed as a percentage of the 10,488 animals in the Danish Breeding database:
Table 2. Registration of traits in Goat Registration Scheme of Angora goats:
Trait recorded Percent records
Kidding ease 86%
Birth weight 80%
Live weight at 2 months 52%
Live weight at 4 months 18%
Mohair yields 1st year 44%
Mohair yields 2nd year 27%
Mohair yields, other years 13%
Objective fibre test 3.1%
Linear classification 4.1%
Original scoring system 4.5%
Table 3. Changes in percentage record collected between 1991 and 1997
Year of birth
Traits recorded 1991 1992 1993 1994 1995 1996 1997
% Fibre test 5.1 3.9 2.0 3.0 3.5 4.8 % -
Original classification system 18.6 11.9 3.9 - - - -
% Linear classification* 0.4 1.4 3.3 9.8 7.2 5.5 -
% Mohair yields 1st year 52 59 44 45 45 50 11
% Mohair yields 2nd year 37 37 27 28 29 26 -
% Mohair yields, other years 23 19 16 18 9 - -
*Only the linear classification system has been used since 1995.
The number of linear classifications and mohair tests have declined over the past years, resulting in very little progress in mohair fineness. The breeders require to make more fibre tests, used on the majority of the best progeny, especially if a cheaper method is available.
Pedersen, J. (1994). Genetic evaluation of Danish Angora goats. In : J.P. Laker & S.C. Bishop (editors). Genetic improvement of Fine Fibre Producing Animals. European Fine Fibre Network No.1.pp89.
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THE GENETIC IMPROVEMENT OF THE ANGORA GOAT IN FRANCE
Daniel Allain1 and André Billant2
INRA, Génétique Animale, Station d’Amélioration Génétique des Animaux, 31326 Castanet Tolosan, France1 and Caprigène France, Section Angora, Agropole, Mignaloux Beauvoir, 87000 Poitiers, France2
The French mohair industry has been developing since 1978. Today, about 8000 pure-bred Angora goats are raised, on about 180 different farms, and produce annually 30 t of mohair. The entire French production is collected, graded and processed under the control of farmer's co-operatives, to produce finished products such as hand-knitted shawls or pure mohair blankets, and marketed directly to consumers by the farmers themselves. A niche market for French mohair has been developed and producers control all the steps from farm to final consumer. French producers are all gathered in different farmers organisations, in order to control the genetic improvement of Angora goats (Caprigène Angora) as well as production (Association Nationale des Eleveurs de Chèvre Angora) and marketing (SICA-Mohair and France Mohair) of mohair produced in France under a common label «Le Mohair des Fermes de France ». A National Selection scheme has been developed with breeders, in order to improve on a national and common basis both quantity and quality of mohair produced by Angora goats. As a breeding objective, an ideal 18-month Angora goat will produce a high clean fleece weight with an average fibre diameter lower than 30µ, without kemp and medullated fibres. Other breeding attributes, including reproductive rate and ability to utilise low-value feed, will be maintained at a reasonable level. This selection scheme is based on an open nucleus population of 1500 breeding does on 50 farms with an on-farm performance recording system, a national genetic database and a buck-testing station. The objectives are to estimate annually breeding value on a common national basis, to help farmers on selection decisions by regular information exchanges between the farmers and the genetic database, and to create and disseminate genetic progress, inside both the open selected nucleus and the whole French Angora goat population. The following institutes and organisations are involved in this genetic improvement programme: a breeder organisation, « Caprigène France section angora », a textile laboratory « Institut Textile de France -Sud » for fibre measurements, « Institut de l’Elevage » the French Breeding Institute for genetic database management and INRA, a Research Institute for breeding value estimation and general purpose of the selection scheme.
The French mohair industry:
The French mohair industry has been developing since 1978. Today, there is around 8000 pure-bred goats, in about 180 farms. Thirty tonnes of mohair are produced each year. The mohair is graded and processed by farmers co-operatives. The final product is sold directly to the consumers.
Producers belong to regional associations. The genetic improvement of mohair is controlled via Caprigène France Section Angora; the mohair production, through the French Association of Angora Goat Breeders (ANECA). The marketing of the fibre is made by Processor Associations (Sica Mohair and France Mohair). The final product is sold under a common label "Le Mohair des Fermes de France".
The French selection scheme:
A National Selection scheme has been developed with breeders, to improve the quantity and quality of the mohair fibre. The breeding objectives for mohair are to have an 18-month old Angora goat producing a high clean fleece weight, with an average fibre diameter lower than 30 microns, free of kemp and medullated fibres. This scheme is based on an open nucleus population, which consist in 1500 breeding females, on 50 farms (a system of on-farm performance recording is implemented), a national database system and a buck-testing station. The objective is to estimate annually the breeding value of the animals on a common national basis, to help farmers taking selection decisions and to create, and disseminate, genetic progress.
Recording system and measurements:
The on-farm performance recording system: On the farm, the farmer records the animal identification, its pedigree and the reproduction data. Every 6 month, he shears and weighs the greasy fleece of the animal. A scoring committee visits the farm and undertakes an animal scoring and fleece assessment on all animals between 15-18 months of age. A fleece sampling is also done. The textile laboratory then measures fleece and fibre characteristics.
Measurements of fleece characteristics:
Objective measurements are done both on the farm and in the laboratory. On the farm, the staple length at the animal shoulder and the greasy fleece weight are measured. In the laboratory, the clean mohair yield is measured (using the ITF-INRA method), as well as the mean fibre diameter and fibre distribution (using the OFDA method). The fleece quality is assessed by looking at its uniformity over the body and at the lock type. Four zones over the body are considered. The kemp is also scored (from 1 to 5) on 5 zones over the body. Finally, the body cover is assessed, using a score from 1 to 10.
The Buck-Testing Station:
A buck-testing station was created in 1995. Thirty bucks, aged one year, are admitted in February. They need one month's adaptation. They require a 5-month testing period from March to August. A fleece assessment is done before and after the testing period. The following characteristics are considered: · greasy and clean fleece weight · mean fibre diameter and fibre diameter distribution · kemp score and fleece homogeneity · style and character, body cover and staple length The culling rate is 20%, with the best males being kept. A genetic assessment is reached, before dissemination of the animals.
The genetic database structure:
The database was created in 1988. It allows regular information exchanges (paper lists, diskettes) between the database and the farm, the laboratory or the scoring committee. This database is an aid to farmers through the data analyses, the annual technical reports, the selection decisions and the breeding value estimations. The database structure contains the following information :
As an illustration, Table 1 and Table 2 show the kind of information that can be extracted from the database.
Table 1- French Mohair production traits-mean performance data
mean fibre diameter (microns)
CV fibre diameter (%)
kemp score (max. of 25)
lock type (max. of 7)
staple length (cm)
body cover score (max. of 10)
fleece weight (kg)
Table 2- Genetic parameters of different fleece trait, heritability and genetic correlations are above the diagonal
|mean fibre diameter (MFD)
CV fibre diameter (CVFD)
kemp score (KS)
fleece homogeneity (FH)
lock type (LT)
staple length (SL)
body cover (BC)
fleece weight (FW)
New requirements for the French Angora goat breeding scheme
New requirements concern both fibre measurements and the genetic database.
The kemp and medullated fibre rate are needed. The new OFDA version could be used to provide such information. It would be useful to know the mean fibre diameter, the fibre distribution and medullation over the body, to assess better the fleece homogeneity. The problem might be the fleece sampling cost per animal. Finally, the age of the animal should be recorded at fibre measurement.
The idea is to develop a relational database and to improve the data flow exchange. To achieve the latter, an automation of data collection and the use of modern telecommunication (videotex, Internet) would be useful.
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CASHMERE : Design of a common database for recording traits
by Dr Clara Diaz, Spain (Rapporteur)
Members of workshop session: Dr Margaret Merchant (UK), Dr Stephen Bishop (UK), Dr John Milne (UK), Dr K. Ho Phan (Germany), Ms Sigrid Lammer (Germany), Prof. Raffaele Celi (Italy), Dr Lars Olav Eik (Norway), Dr Tormod Ådnøy (Norway).
The aims of this workshop were to consider the implications for quality and quantity traits identified in workshop 1. On the basis of the latter, measurements of fibre traits and other traits were finalised. The framework of a common database was discussed, as well as its management.
It was decided to design four tables, including the three main types of traits. The last table will be for additional information concerning the animal itself. The three types of traits will be the fibre traits (quality, quantity and other quality traits), the reproduction traits (for the kid and the dam) and the general purpose traits, such as meat production. The additional table will mainly concern the pedigree of the animal.
1-Fibre traits table.
This will contain information on the quality of the fibre, the quantity of the fibre and other traits.
1-1- Quality fibre traits:
The following parameters were chosen for recording:
1-2- Quantity fibre traits:
The parameters to be recorded are:
1-3- Other traits:
The following information will be contained:
2-Reproduction traits table:
The following traits will be recorded for each dam:
1. Kidding rate
2. Fertility records (include if the animal has had a failed pregnancy, an abortion or was not mated)
3-Meat traits table:
The following data will be recorded:
This will mainly concern the pedigree of the animal and the following information will be recorded:
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MOHAIR : Design of a common database for recording traits.
by Dr Daniel Allain, France (Rapporteur)
Members of workshop session: Mrs Jill King (UK), Mrs Helen Swallow (UK), Mr Christian Julia (France), Mr André Billant (France), Mr Marco Dumont (France), Ms Annette Holmenlund (Denmark), Mr Christian Aabo (Denmark), Mr João Pedro Varzéa Rodrigues (Portugal).
The aims of this workshop were to consider the implications for quality and quantity traits identified at the previous workshop. Some selection goals were discussed there and a way of standardisation for recording was drafted. Following these decisions taken in Spain, proposals about fibre tests and fleece assessment were presented and a database structure was drafted.
1- Summary of previous discussions:
1-1-Selection goals and selection criteria for Angora goats:
At the previous workshop, it was agreed that it would be desirable for the fleece weight of the animal to be increased, the mean fibre diameter to be decreased, kemp and medullated fibres to be avoided and the variability of the fibre diameter to be reduced. The following selection criteria were agreed upon:
1-2-Standardisation of performance recording system for mohair production:
Some measurements were agreed previously. These concerned:
Concerning fleece sampling and the fibre testing, some further decisions and testing were necessary. It was proposed to proceed to fleece testing at three locations for the bucks (shoulder, midside and britch) and on one location for the does. The fibre test would be done on a clean fleece weight and the OFDA methodology would be used to measure the mean fibre diameter, the fibre distribution and the medullation rate.
2-Proposed programme of fibre test and fleece assessment:
The above programme was decided upon, resolving the questions that have been raised at the last workshop but on which agreement had not been reached.
2-1-Proposed programme of fibre testing (implementation in Summer 1998)
2-2-Proposed programme of fleece assessment:
A round trial test will be carried out at the French buck testing station, in which French, Danish and British experts will participate. The following criteria for scoring will be:
The fleece assessment test was carried out before the final group discussions about the database structure.
3-Draft database structure
It was decided that the database for Angora goats would consist of five tables. They will concern:
For each animal, the following identification components will be:
3-1-Animal identification table:
Inside this table, the data recorded will be:
3-2-Fleece weight table:
Concerning the fleece weight, the following information will be recorded:
3-3-Fibre test table:
The data recorded in this table will be:
3-4-Fleece assessment table:
The information found inside this table will be:
The following data will be recorded in this table:
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ANGORA RABBIT: Design of a common database and recording card
by Dr René-Gérard Thébault, France (Rapporteur)
Members of workshop session: Mrs Brigitte Richard (France), Mr Denis Leduc (France), Ms Anne Katrine Jensen (Norway), Ms Marianne Nilsen (Norway), Dr Liisa Nurminen (Finland), Mrs Arja Simola (Finland).
At the last workshop, the Angora rabbit group felt the necessity to agree upon the design of a common animal registration method. A unified fleece classification system was required, a standard method of taking fibre samples was needed and the most appropriate time of sampling had to be identified. France, Finland and Norway were involved in this approach. Hence, the three Angora strains considered were the Finnish strain, the Norwegian strain and the French strain. After some discussions, and taking into account the different backgrounds of each country involved, agreement was reached on an unified recording card, a classification for raw Angora fibre and sampling methods. Concerning selection criteria, a common strategy cannot be agreed upon yet, as each country wants to produce a special, typical Angora fibre quality, according to the final product sold within the country. Database framework will follow these first steps.
1-Recording card for Angora wool production data and reproduction data
1-1-Fibre production traits:
1-1-1- Heading of the card (general information)
1-1-2-Fleece data (recorded at each harvest)
2-Common classification for raw Angora wool:
3-Sampling methods for determining fineness and bristle rate in angora wool
The time of sampling was agreed to be at the fifth and the seventh harvest (animal aged more than fourteen months, and at two opposite seasons). The patch sample will be on the back, on the highest part of the body when the animal is standing; ideally, at the middle distance between ears and tail. The patch sample will be taken by shaving (using a razor blade) an area of 1 cm2. The sample will be then put in a little paper or cellophane bag carefully and clearly identified (animal number and harvest date). The fineness and bristle rate will be measured by OFDA methodology. The strength of the fibre will be measured using other textile fibre methods.
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FINE WOOL : Design of a common database and common recorded traits
by Dr Angus Russel, UK (Rapporteur)
Members of workshop session: Ms Almudena Moreno (Spain), Dr Luis Pinto de Andrade (Portugal), Mr Fergus Wood (UK), Ms Claire Souchet (UK), Prof. Dr Peter Horst (Germany), Mr Hervé Tripard (France), Mr Joseph Rémillon (France), Mr Damien Theurkauff (France), Mr Francis Personne (France), Dr Marja-Leena Puntila (Finland).
Before discussing the parameters to be included in selection indices and databases, it was important to consider some basic points relating to fine wool production.
The range of measurements to be made and recorded is dependent on the selection objectives and it is essential that these aims are clearly defined. Selection objectives vary from country to country.
In France, where there are a number of different Merino breeds, all of which have the potential to produce fine wool, it is considered that the first priority is to improve milk production to achieve better lamb growth rates. Wool quality is not adequately rewarded under the current marketing system and until such time, as it pays to produce fine wool, breeders are content to maintain present quality levels and concentrate on traits, such as lamb growth rate, which will bring a more immediate improvement in returns.
In Germany it is likely that Saxon Merino genes exist in a number of the native breeds. The first priority there is to identify those breeds and individuals within breeds which are superior in terms of wool characteristics and to create a genepool from which selection for fine wool can be made.
Similarly, in Spain, where there is no organised current production of fine wool, it is believed that a number of fine wool strains exist in a number of native breeds. There is a need to conduct a national audit of the wool characteristics of these breeds to identify superior stock, from which fine wool strains could be developed.
In Portugal there is a small population of white-faced Merinos, which are known to produce high quality fine wool. There is also some local expertise in the subjective assessment of wool quality. The main priority is considered to be the objective measurement of wool characteristics in this population, to enable the initiation of a scientifically based breeding programme designed to improve wool quality further.
The main breeding objective in Finland is to improve the wool quality of the Finnsheep without prejudicing other production characteristics, and in particular the prolificacy for which this breed is noted.
There are three distinct, but complementary, fine wool initiatives in the UK, each based on recently established and still very small populations. In each of these, the principal objective is the improvement of wool quality.
1-2-Wool Marketing Infrastructure
European wool merchants and textile processors import large lots of wool which have been rigorously graded and meet rigid specifications. They, perhaps understandably, are reluctant to buy small batches of locally grown wools, which are of variable quality and often heavily contaminated with vegetable matter, polypropylene and non-scourable marking fluids. If European-grown wool is to realise its true value (i.e. the price of Australasian wools of comparable quality), it must be offered in substantial volumes, which are graded into uniform, well-presented lots, free from all forms of contamination. These stringent requirements will be best met by the formation of a European Wool Marketing infrastructure which is responsible for grading and marketing, and which adequately rewards a high standard of presentation of quality fine wool.
Breeding programmes must rely on objective measurements of those characteristics which determine value, and not on subjective assessments, such as the Bradford count. The Optical Fibre Diameter Analyser (OFDA) is strongly recommended as the method of choice for measurements of fibre diameter as, unlike the widely used air-flow technique, it provides reliable estimates of both mean and variance.
2-Genetic implications for quality and quantity traits
Mean fibre diameter and fleece weight are positively correlated, i.e. there is a negative association between wool quantity and quality. This relationship has a physical basis because, without changes in fibre length and follicle density, weight must vary as diameter2.
The relationship between wool value and fibre diameter is such that, in the many breeds with mean fibre diameters greater than 25 microns, selection for reduced fibre diameter will generally lead to a lower monetary return. This arises because the value lost through the reduction in fleece weight will generally be greater than the increase in value resulting from the improvement in quality. In these breeds, returns from wool are more likely to be increased by selection for heavier fleece weights than by selection for lower fibre diameter.
In fine wool breeds, with a mean fibre diameter of less than about 20mm, however, the situation is very different; the value of each unit reduction in fibre diameter is likely to be greater than that attaching to the inevitably lower fleece weight. In these cases, net returns will increase as fibre diameter (and fleece weight) are reduced. The nature of the relationship between wool value and fibre diameter is such that each unit reduction in mean fibre diameter results in a greater increase in net return.
It is, of course, possible to select for a reduction in mean fibre diameter without any change in clean wool weight. Such a strategy is, however, likely to lead to slower progress towards the objective of increased wool value per animal.
2-2-Wool and Non-wool Quantitative Traits
It appears that, across the many Merino breeds and strains, there is a negative relationship between mean fibre diameter and live weight, prolificacy and milk production potential. It is considered that, although there is probably a genetic basis for this association between wool and non-wool production traits, there is no reason why selection for, say, milk production and wool quality should not be successful in achieving improvements in both characteristics simultaneously, although progress might be slow.
Until such time, as quality wool production is adequately rewarded in Europe, there will be a role for dual purpose breeds. In the immediate future milk production, prolificacy and lamb growth rate are likely to have greater effects on per animal returns than fleece weight or wool quality. This should not, however, obscure the longer-term objective of improving wool quality, and breeding programmes designed to improve both wool and non-wool traits should be encouraged.
The strategy of combining wool and non-wool production traits through a cross-breeding system also merits consideration. An example of this is seen in the use of a fine-wooled Merino sire (the Lomond) on Shetland ewes in the UK, where finished lambs are traditionally produced from cross-bred ewes. In this system, the cross-bred ewe (combining the wool quality of its sire with the milk production and prolificacy of its dam) is in turn mated to a terminal sire, such as the Suffolk or Texel, to produce finished lambs. This system has lead to significant improvements in the wool quality and value of both the cross-bred ewe and the finished lamb.
3-Measurements used in Selection Indices
The number of parameters included in a selection index must be kept to a minimum if a reasonable rate of progress is to be achieved. For this reason two categories of measurements are considered: basic measurements, which are likely to feature in the majority of breeding programmes, and optional measurements, which will have application in special situations.
4-Information for inclusion in databases
The principal items of information required for inclusion in databases include:
4-2-Production data :
In most systems it is necessary to screen, at least the juvenile males, prior to the age at which young stock are normally slaughtered for meat. It is also important to be able to estimate adult production from the samples collected from these juveniles. For these reasons, the database must include information which will allow relationships between juvenile and adult production measurements to be calculated. It is not practicable to recommend a standard age at which samples from juveniles should be collected, as age at slaughter varies widely between countries. It is, therefore, important that the date and live weight at the time of juvenile sampling and the date of the measurements of adult production parameters are recorded.
Wool traits, such as fleece weight, fibre diameter and fibre length, are influenced to a major extent by nutrition. It is known, however, that within individuals the ratio of fibre length to fibre diameter (L:D) remains constant under different nutritional regimes. This ratio can be used to compare the production potential of individuals maintained in different nutritional environments, and it is there important that these parameters are included in the database. Clean wool weight (W) is a function of fibre length x fibre diameter2 and thus the ratio L:D can also be expressed as W:D3 .
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