**3. Quantitative selection and genetic improvement**

Genetic improvement of small stock in South Africa can largely be attributed to the research performed over many decades in official research and prestige flocks. The results from the research flocks set the trends for selection and breeding programs, while the prestige flocks confirmed the value of applying a scientific approach to the farming community [14]. Performance recording was introduced for small stock, including goats, as early as 1956 by the Department of Agricultural and Technical services. Since then, production systems and environments have evolved and new selection tools became available for additional measure‐ ments, e.g., for fiber traits [15]. Advancements in the statistical methodologies for genetic evaluations made estimated breeding value possible for the breeds where sufficient animal and pedigree recording has been performed [14].

The genetic improvement of goats has been slow and less spectacular compared to sheep and other livestock species in South Africa. Of the goat breeds, most of the genetic improvement took place in the Angora goat due to the high economic value of mohair and South Africa being one of the largest producers of mohair in the world [16]. The poor participation in the National Small Stock Improvement Scheme (NSIS) by the meat and dairy goat breeders lim‐ its the potential genetic improvement, as limited phenotypic and pedigree recording occurs. Several factors play a role in the relative poor participation of SA goat breeders in animal recording, including difficulties in recording on large extensive farming units, multi‐sire prac‐ tices presenting challenges for accurate parentage verifications and the cost of using modern technology for measuring traits of economic importance. Beef remains the primary choice for meat consumption by the consumer, and goats have often been neglected in the creation of new markets and products. All these factors may play a role in decision making by farm‐ ers when it comes to the costs involved in official animal recording and genetic evaluations. Furthermore, the unimproved veld goat is largely uncharacterized and has not been subjected to artificial selection or improvement strategies. It presents opportunities to utilize these goat types for improvement of the broader goat population due to their unique adaptive traits, but at the same time poses a danger if the selection strategies are not well formulated and implemented. Care must be taken that the uniqueness of genetic resources is conserved while implementing genetic progress.

#### **3.1. Angora goats**

The most significant genetic improvement in the South African Angora goat population took place over the past four decades. Although the National Small Stock Information Scheme was established in the 1950s, the uptake by Angora goat breeders was slow. A pilot study for animal recording in Angora goats was only implemented in 1983 [17]. The participation of Angora breeders in this scheme was voluntary and has remained poor over the past few decades. A lack of complete data for South African Angora breeders [18], combined with chal‐ lenges regarding parentage verification, currently limits the application of breeding values.

of 149% with a weaning weight of 29 kg at 120 days. The SA Boer goat has also been found to be early maturing with a high incidence of multiple births. Approximately 56.5% twins, 33.2% triplets and 2.4% quadruplets born were reported in a study on the influence of age on the reproductive performance of the improved Boer goat [8]. The high fecundity poses some obvious advantage under optimal feeding conditions, but could also result in increased kid mortality when reared under extensive conditions, especially with kids born as triplets and quadruplets. Some genetic progress is evident in growth traits as can be seen in the increase in 100‐day weights based on performance of tested goats corrected for age and birth status from 1998 (25.3 kg for males to 22.3 kg for females) to 1996 (26.9 kg for males and 23.4 kg for

**Table 2.** Heritability estimated for fiber quality traits in SA Angora goats obtained from OFDA measurements.

0.14 ± 0.08\*\*

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Despite the availability of animal recording for small stock, the participation remains poor with only 38% registered Boer goat, 41% Kalahari Red and 67% Savanna goat breeders taking part in the Logix recording system for small stock [24]. Only one indigenous goat veld goat breeder takes part in recording out of 14 registered breeders. **Figure 6** highlights the poor

The poor participation in animal recording of meat goats limits the potential for estimation of genetic parameters for traits of economic importance. In **Table 3**, available heritability esti‐ mates are presented for reproductive and growth traits. The available records for postwean‐ ing weights in South African Boer goat were insufficient for estimation of heritability [13]. A heritability value of 0.45 was reported for yearling weights in Australian Boer goats [25]. Selection progress for preweaning weights is likely to be slow due to low heritability esti‐ mates, whereas postweaning growth tends to exhibit higher heritability as seen in most farm animal species. The challenge for genetic improvement in the SA meat goat breeds lies in obtaining more and accurate recording for larger numbers of registered animals. This will enable genetic evaluations for breeding value estimation that can be applied by individual goat breeders in their herds as well as improvement of the national flock. A number of stud‐ ies have highlighted the meat characteristics of South African Boer goat [28], but no genetic

females) [8].

the staple (µm)

\*\* Visser et al. [22].

\*

participation of meat goat breeders in the NSIS.

**Trait** *h***<sup>2</sup>**

Standard deviation of fiber diameter along the length of

Snyman and Olivier [21, 24]; Visser et al. [22].

Fleece weight (kg) 0.19 ± 0.04–0.24 ± 0.03\* Fiber diameter (µm) 0.26 ± 0.05–0.45 ± 0.03\*

Coefficient of variation of fiber diameter (µm) 0.37 ± 0.10\*\* Standard deviation of fiber diameter 0.32 ± 0.11\*\* Comfort factor (%) 0.63 ± 0.11\*\* Spinning effective fineness 0.61 ± 0.10\*\*

parameters are available for selection for improved carcass traits.

In 1988, a research flock was established with the aim of breeding fine‐hair producing Angora goats, without sacrificing body weight [14, 19]. Selection indices were made available to the breeders with emphasis on fiber diameter, fleece weight and body weight in varying ratios [20, 21]. This selection strategy resulted in a significant improvement of the fiber diameter and the general fitness of the Angora goat population [19].

The development of Optical Fiber Diameter Analyzer (OFDA) technology was important for obtaining accurate measurements for the full fiber profile. It has been implemented since 1992 in routine fleece measurement in South Africa by a number of breeders [22]. The quality traits associated with the full diameter profile (including coefficient of variation of fiber diameter, comfort factor and spinning fineness) hold potential for inclusion in the breeds' selection indices. In **Table 2**, a summary is provided of available heritability estimates for fiber quality traits in SA Angora goats [15].

Unfavorable genetic correlations between fiber diameter and fleece weight remain a challenge [22], and higher participation in recording and genetic evaluations will be required for further genetic improvement.

#### **3.2. Meat goats**

Most of the available research on meat goats was performed on the SA Boer goat, focusing on phenotypic characteristics [10] and production traits [8, 10]. Average reproductive perfor‐ mances for the Boer goat are reported [10] based on records obtained over a 20‐year period, included a kidding rate (kids born/does mated) of 189%, fecundity of 210% and a weaning rate


recording, including difficulties in recording on large extensive farming units, multi‐sire prac‐ tices presenting challenges for accurate parentage verifications and the cost of using modern technology for measuring traits of economic importance. Beef remains the primary choice for meat consumption by the consumer, and goats have often been neglected in the creation of new markets and products. All these factors may play a role in decision making by farm‐ ers when it comes to the costs involved in official animal recording and genetic evaluations. Furthermore, the unimproved veld goat is largely uncharacterized and has not been subjected to artificial selection or improvement strategies. It presents opportunities to utilize these goat types for improvement of the broader goat population due to their unique adaptive traits, but at the same time poses a danger if the selection strategies are not well formulated and implemented. Care must be taken that the uniqueness of genetic resources is conserved while

The most significant genetic improvement in the South African Angora goat population took place over the past four decades. Although the National Small Stock Information Scheme was established in the 1950s, the uptake by Angora goat breeders was slow. A pilot study for animal recording in Angora goats was only implemented in 1983 [17]. The participation of Angora breeders in this scheme was voluntary and has remained poor over the past few decades. A lack of complete data for South African Angora breeders [18], combined with chal‐ lenges regarding parentage verification, currently limits the application of breeding values.

In 1988, a research flock was established with the aim of breeding fine‐hair producing Angora goats, without sacrificing body weight [14, 19]. Selection indices were made available to the breeders with emphasis on fiber diameter, fleece weight and body weight in varying ratios [20, 21]. This selection strategy resulted in a significant improvement of the fiber diameter and

The development of Optical Fiber Diameter Analyzer (OFDA) technology was important for obtaining accurate measurements for the full fiber profile. It has been implemented since 1992 in routine fleece measurement in South Africa by a number of breeders [22]. The quality traits associated with the full diameter profile (including coefficient of variation of fiber diameter, comfort factor and spinning fineness) hold potential for inclusion in the breeds' selection indices. In **Table 2**, a summary is provided of available heritability estimates for fiber quality

Unfavorable genetic correlations between fiber diameter and fleece weight remain a challenge [22], and higher participation in recording and genetic evaluations will be required for further

Most of the available research on meat goats was performed on the SA Boer goat, focusing on phenotypic characteristics [10] and production traits [8, 10]. Average reproductive perfor‐ mances for the Boer goat are reported [10] based on records obtained over a 20‐year period, included a kidding rate (kids born/does mated) of 189%, fecundity of 210% and a weaning rate

implementing genetic progress.

traits in SA Angora goats [15].

genetic improvement.

**3.2. Meat goats**

the general fitness of the Angora goat population [19].

**3.1. Angora goats**

26 Goat Science

**Table 2.** Heritability estimated for fiber quality traits in SA Angora goats obtained from OFDA measurements.

of 149% with a weaning weight of 29 kg at 120 days. The SA Boer goat has also been found to be early maturing with a high incidence of multiple births. Approximately 56.5% twins, 33.2% triplets and 2.4% quadruplets born were reported in a study on the influence of age on the reproductive performance of the improved Boer goat [8]. The high fecundity poses some obvious advantage under optimal feeding conditions, but could also result in increased kid mortality when reared under extensive conditions, especially with kids born as triplets and quadruplets. Some genetic progress is evident in growth traits as can be seen in the increase in 100‐day weights based on performance of tested goats corrected for age and birth status from 1998 (25.3 kg for males to 22.3 kg for females) to 1996 (26.9 kg for males and 23.4 kg for females) [8].

Despite the availability of animal recording for small stock, the participation remains poor with only 38% registered Boer goat, 41% Kalahari Red and 67% Savanna goat breeders taking part in the Logix recording system for small stock [24]. Only one indigenous goat veld goat breeder takes part in recording out of 14 registered breeders. **Figure 6** highlights the poor participation of meat goat breeders in the NSIS.

The poor participation in animal recording of meat goats limits the potential for estimation of genetic parameters for traits of economic importance. In **Table 3**, available heritability esti‐ mates are presented for reproductive and growth traits. The available records for postwean‐ ing weights in South African Boer goat were insufficient for estimation of heritability [13]. A heritability value of 0.45 was reported for yearling weights in Australian Boer goats [25].

Selection progress for preweaning weights is likely to be slow due to low heritability esti‐ mates, whereas postweaning growth tends to exhibit higher heritability as seen in most farm animal species. The challenge for genetic improvement in the SA meat goat breeds lies in obtaining more and accurate recording for larger numbers of registered animals. This will enable genetic evaluations for breeding value estimation that can be applied by individual goat breeders in their herds as well as improvement of the national flock. A number of stud‐ ies have highlighted the meat characteristics of South African Boer goat [28], but no genetic parameters are available for selection for improved carcass traits.

**4. Molecular research and genetic improvement**

number of studies performed on the SA Angora goat.

would result in faster genetic progress.

**4.1. Angora goats**

Since the advent of molecular genetics, research on goats has entered a new era, also influencing the South African goat populations. The first research on South African goats was performed using microsatellite markers in the early 2000s and mainly involved genetic diversity and char‐ acterization studies. Genetic characterization assists in the conservation of unique character‐ istics of indigenous populations, whereas genetic diversity has a direct influence on genetic progress, selection strategies and the control of inbreeding levels. The identification of quan‐ titative trait loci (QTL) explaining significant fractions of the genetic variance in economically important traits could lead to increased accuracy of estimated breeding values (EBVs) with a corresponding faster rate of genetic improvement. A few QTL identification studies were performed on Angora goats, but the limited amount of variation explained by these fragments restricted the application of the results in terms of marker‐assisted selection (MAS). Some effort has gone into sequencing genes of economic importance and estimating their population fre‐ quencies as well as identifying novel variants in the local populations. The first caprine single nucleotide polymorphism (SNP) chip became commercially available in 2012, and since then (as with almost all other livestock species) SNP markers have become the marker of choice.

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Without a doubt, the Angora goat breed is the South African goat breed on which most molec‐ ular research has been performed. The SA Angora goat served as the model breed for improv‐ ing the goat linkage map in 2010, using 94 microsatellite markers [30]. Both the accuracy and the coverage of the map were improved by adding markers, correcting previously reported order alignments and decreasing map distances. This linkage map formed the basis for a

Angora goats in South Africa are primarily farmed extensively and are subjected to group mating and over‐mating. This limits accurate parentage recording and has a negative effect on the accuracy of estimated breeding value estimation and selection progress. A DNA par‐ entage verification panel was created, using 14 microsatellite markers with a combined prob‐ ability of exclusion of 99.7% [31]. The impact of DNA‐based parentage verification on EBV accuracies and ranking of sires were evaluated a few years later [32]. It was shown that correct allocation of parentage had a significant effect on EBV estimation and ranking of sires, espe‐ cially for growth traits. DNA‐based parentage verification enhanced selection accuracy and

Phenotypic recording and EBV selection on mohair and growth traits were relatively success‐ ful during the 1980–1990s. However, intense selection pressure for increased mohair quality and yield resulted in small, unthrifty goats with high mortality rates. QTL identification stud‐ ies were performed to identify chromosomal segments associated with product and qual‐ ity traits of mohair [33] as well as preweaning growth [34]. Eighteen QTL for mohair traits (including fleece weight, fiber diameter, coefficient of variation of fiber diameter, comfort factor, spinning fineness and variation along the length of the fiber) were identified on 13 chromosomes [15]. In the study focusing on preweaning growth traits, four chromosomal regions of interest with an influence on birth weight were identified on CHI 4, 8, 18 and 27

**Figure 6.** Participation of meat goat breeders in the National Small Stock Improvement Scheme [24].


**Table 3.** Heritability estimates for preweaning weights of Boer goats.

#### **3.3. Dairy goats**

The South African dairy population is small in comparison with the other goat breeds and small stock. There are currently 45 registered herds representing 16,561 animals [24], and the remaining animals are used in commercial milk operations. Of the 45 herds, 16 herds (approximately 1217 goats) participate in official recording. Although participation in offi‐ cial animal recording is limited, the opportunity is available to record milk yield, milk composition and linear traits for selection and improvement. Heritability estimates have been reported for the SA Saanen for milk yield (0.23), butter fat yield (0.22) and protein yield (0.20). Protein and butterfat percentages had a heritability of 0.44 and 0.21, respec‐ tively [29].

Despite this relatively small population size, a niche market is served with the produc‐ tion of fresh milk and specialty cheeses. Marketing of these products occurs mostly in an informal way, such as by selling directly to consumers via on‐farm sales, or at various mar‐ kets. The renewed interest in organic products and dairy goats in general may result in breeders adopting modern technologies to overcome limitations in parentage recording and thus improved recording in order to perform accurate selection for long‐term genetic improvement.
