Description of body measurements (cm) recorded for Boer goats, Kalahari Red and Savanna goats (adapted from Ref. [11]).
\r\n\tSome of them are potential hazards caused by novel (bio)technologies, such as nanoparticles or process-related toxicants. Others are well-known hazards that climate change and new trends in food consumption have now moved under the spotlight. Some are due to the deliberate adulteration of food for economic reasons, that is strongly affecting the global market.
\r\n\tFood scientists are strongly involved in tackling this global challenge, supported by novel technologies and ICT-based tools. On one hand, innovative analytical approaches, mainly based on omics science and big data, may offer a great support for hazard characterization and risk assessment. On the other hand, early warning tools are strongly needed to efficiently support risk management and avoid food losses.
\r\n\tAlthough many contaminants are regulated worldwide and routine control plans ensure the compliance of food before entering our plate, scientists are now focusing their research not only on single compounds, but mainly on a cocktail of toxicants thanks to biomonitoring and imaging techniques. This change in the approach will lead to a new design of risk assessment within few years.
\r\n\tBesides traditional players, like scientists and policy-makers, also agro-food companies are investing efforts and resources in the identification and assessment of emerging risks, to meet consumer’s demand of safer food and prevent misleading communication.
\r\n\tIt is clear that the food safety scenario is rapidly changing, driven by innovation and big data. This book intends to provide the reader with a comprehensive overview on the methodological advances the scientific community has brought about to face emerging risks and new trends.The main emerging risks will be covered, and methodological improvements will be outlined. Strategies in management and communication will be described. New market trends and consumers’ behavior leading to a change in the future scenario, will be discussed.
South Africa contributes almost 50% to the Southern African goat population [1] with approximately 5.62 million animals [2] distributed throughout nine provinces. Approximately 2 million of these animals are found in the Eastern Cape Province, almost 1 million in Limpopo Province and just over 700,000 in KwaZulu‐Natal Province. The remaining provinces share the remaining 1.8 million animals. The Angora goat population of approximately 640,000 goats is the major contributor to the income generated in the formal goat sector, by supplying more than 50% of the global mohair clip. The commercial meat goat industry, consisting of the Boer, Savannah and the Kalahari Red breeds makes up 1.3 million goats, with commercial dairy goats being the smallest sector, with approximately 4000 registered dairy goats. The majority (approximately 63%) of South African goats consist of unimproved indigenous veld goats in the noncommercialized agricultural sector and are kept under small‐scale conditions.
In South Africa, there are seven goat breeds that are officially recognized by the Animal Improvement Act No. 62 of 1998, which includes the Angora goat for mohair production, three meat types namely the South African (SA) Boer, Kalahari Red and Savanna breeds and three dairy breeds consisting of the Saanen, Toggenburg and British Alpine. According to historical evidence, the meat breeds originate from indigenous goat breeds believed to have migrated to Southern Africa around 500 AD [3]. The Khoisan, a local tribe, moved with their herds southwards from Northern Botswana down to the Orange River from where two additional routes were used to reach the Southern and Western Cape. These goats kept by the local people were described by the Missionary J. Burrow as “handsome goats, speckled like the leopard” [4]. The indigenous goats most likely provided the genetic basis for the development of the current meat goat breeds. In contrast with the goat meat breeds, the dairy breeds have been imported from Europe and the United Kingdom. Besides these recognized goat breeds, South Africa has a large variety of indigenous or unimproved types that contribute meat, hides and milk to smallholders and subsistence farmers [5]. The majority of commercial goat farming takes place in the eastern and northern regions of South Africa where the species is well adapted to the vegetation [2].
The Angora goat was domesticated in Turkey, from where the animals were exported to Europe during the sixteenth century in an attempt to establish a rival mohair industry. The European climate was however not suited to these goats, and South Africa (a British colony at the time) presented a suitable region for Angora goat production. The first Angora goats were imported to South Africa during 1838, followed by another 3000 goats between 1856 and 1896 [6]. The Karoo and semiarid Eastern Cape region proved to be well suited to the Angora goats, and currently, the mohair industry in South Africa consists of approximately 644,000 Angora goats (
The Angora Goat Breeders’ Society was established in 1892 and is known today as the Angora Ram Breeders. The Angora goat is a relatively small, horned mohair goat with heavy and drooping ears, as shown in Figure 1. The hair and body of these goats are white, and an excess of color in the horns, hooves, ears and the skin is not allowed. An Angora goat should have a uniform fleece with regard to length and fineness, with good luster, solid style and good character, and should also be free from kemp or colored fibers [7].
A typical South African Angora doe and kid (University of Pretoria).
The South African Boer goat has the oldest official history with the establishment of the South African Boer Goat Association in 1959 [4]. In the development of goat breeds during the late sixties and early seventies, the Boer goat breeders’ society referred to five potential types of Boer goat in South Africa [8]. These included unimproved types such as the ordinary goat, long haired types and polled types that originated from crossbreeding with dairy breeds and native goats. The improved Boer goat was recognized as the desirable type, breed standards were formulated and a number of goat breeders commenced with directional selection and a well‐defined breeding policy that resulted in the modern SA Boer goat found in commercial and other farming systems today.
This breed is characterized by the red color of the head, long ears and a white soft coat (Figure 2). A sturdy head with a compressed nose and strong horns that have a gradual backward curve are favored. The goats have fleshy, well‐developed broad briskets, well‐sprung ribs, broad backs and muscular legs [9]. Mature Boer goat bucks weigh between 110 kg and 135 kg, and does weigh between 90 kg and 100 kg [10, 11]. The SA Boer goat does are known for their good mothering ability and can kid every 7–8 months. Some literature indicates a lower susceptibility to diseases such as blue tongue, prussic acid poisoning and, to a lesser extent, enterotoxaemia [8, 10].
Typical South African Boer goats with white body and red head and neck (University of Pretoria).
The origin of the Kalahari Red and Savanna goat breeds is not as well documented and according to available literature probability originated from indigenous goat types [4]. These breeds have only been officially recognized in South Africa in 1990 and 1993, respectively. The Kalahari Red has a dark red coat color and fully pigmented body that provides the advantage of high UV radiation tolerance. The Savanna goat is white in color and has short kempy hair with a black skin, horns, nose and udder [11]. These goats are also known to have well‐muscled forequarters with a long neck for easy browsing. Typical Kalahari Red and Savanna goats are shown in Figures 3 and 4, respectively.
A Kalahari Red goat with the characteristic uniform red coat color (University of Pretoria).
A herd of Savanna goats with primarily white coat color (University of Pretoria).
In Table 1, a summary is provided of descriptive measurements analyzed for the three commercial meat goat breeds. These breeds have been fully commercialized with official structures such as individual breed societies and well‐defined breed standards. They are the main contributors to the official goat meat produced in South Africa [12] and are recognized for their superior growth and carcass traits [1].
Body measurements in cm (least square means ± SE) | |||
---|---|---|---|
Boer goat | Kalahari Red | Savanna | |
Height (H) | 56.5a ± 0.5 | 54.1a ± 0.5 | 55.7a ± 0.5 |
Length (L) | 68.2ab ± 0.8 | 69.8a ± 0.8 | 64.9b ± 0.7 |
Depth (D) | 26.4ab ± 0.3 | 27.1a ± 0.3 | 24.9b ± 0.3 |
Heart girth (HG) | 90.3ab ± 1 | 95.3a ± 1 | 86.5b ± 1 |
Hock length (HL) | 28.3a ± 0.5 | 27.7a ± 0.5 | 23.5b ± 0.5 |
Head width (HW) | 7.7a ± 0.2 | 6.6b ± 0.3 | 5.6c ± 0.2 |
Head length (HL) | 17.2a ± 0.3 | 15.7b ± 0.2 | 15.8ab ± 0.2 |
Neck circumference (N) | 48.3a ± 4 | 42.5ab ± 3.8 | 37.7ab ± 3.7 |
Tail length (TL) | 12.2ab ± 0.3 | 13.2a ± 0.3 | 13.3a ± 03 |
Pelvic width (PW) | 13.8a ± 0.3 | 11.1b ± 0.3 | 11.4b ± 0.3 |
Pelvic length (PL) | 19.7a ± 0.4 | 20.5a ± 0.3 | 19.1a ± 0.3 |
Ear length (EL) | 21.4a ± 0.3 | 19.2b ± 0.2 | 19.5b ± 0.2 |
Description of body measurements (cm) recorded for Boer goats, Kalahari Red and Savanna goats (adapted from Ref. [11]).
South African indigenous goats are mostly characterized based on color variations and phenotypic characteristics such as ear length and horn shape. There is virtually no distinct breed identification, and populations are often named or identified according to the geographical region where they are kept. Various types are known, such as the Pedi, Nguni and Xhosa Lop ear ecotypes [1]. These uncharacterized veld‐type goats generally have small body frames (mature females weigh approximately 40–50 kg) and low carcass yields. The goats are multipurpose and are used for meat, hides and sometimes even milk for younger children, mostly in small farming systems and or for household food production.
The indigenous veld‐type goats have been subjected to limited selection and are largely unimproved genotypes. They have however contributed to the development of the local meat‐type goats such as the Boer goat [4] through crossbreeding. The indigenous types vary in size and are often promoted as having special adaptive characteristics, including a higher tolerance for tick‐borne diseases compared to the commercial goat breeds [8, 10]. In Figure 5, a typical South African veld goat is shown.
A herd of South African unimproved veld goats (Rauri Alcock).
The Tankwa goat refers to a population of feral goats that are found in the Northern Cape. Although they have been known to roam the Tankwa National Park for at least 80 years, they have only been identified and studied as a distinct population over the past decade. Their current population size is estimated at approximately 200 goats [1]. These goats have survived and reproduced in one of the harshest climatic regions of South Africa with regard to temperature and vegetation and hold potential for their unique adaptive traits.
Dairy goats were introduced to South Africa at the turn of the twentieth century, originating primarily from Switzerland and the United Kingdom. The SA Mich Goat Breeders’ Society was formed in 1958 but formal milk recording for dairy goats only started in the 1981/82 production year as the number of lactation records was low and variable before then [13]. Originally four breeds were officially recognized in South Africa, namely the Saanen, Toggenburg, British Alpine and an Anglo‐Nubian Swiss composite [29]. Currently, the milk goat breeds include Saanen, Toggenburg and British Alpine breeds and crosses between these breeds are often used in commercial milk goat production systems [29]. The Saanen breed was the first milk goat breed to be imported to South Africa in 1898 [13] and is known for its high milk yield. The Toggenburg and British Alpine were imported during the early 1900s. These two breeds with dark pigmentation are favored for their adaptability to the climatic challenges of South Africa that includes high average temperatures and UV intensity. The Toggenburg furthermore also produces milk with a higher butterfat compared to the Saanen [13], which is important for production of cheese.
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 measurements, 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 limits 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 practices 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 farmers 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.
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 challenges 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 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].
Trait | h2 |
---|---|
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** |
Standard deviation of fiber diameter along the length of the staple (µm) | 0.14 ± 0.08** |
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.
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 performances 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 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.
Participation of meat goat breeders in the National Small Stock Improvement Scheme [24].
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 estimates are presented for reproductive and growth traits. The available records for postweaning 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].
Trait | h2 | References |
---|---|---|
Birth weight | 0.05–0.14 | Schoeman et al.[26] |
Weaning weight direct | 0.18–0.15 | Van Niekerk et al. [26]; Schoeman et al. [27] |
Weaning weight maternal | 0.05–0.45 | Van Niekerk et al. [26]; Schoeman et al. [27] |
ADG | 0.170 | Schoeman et al. [26] |
Heritability estimates for preweaning weights of Boer goats.
Selection progress for preweaning weights is likely to be slow due to low heritability estimates, 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 studies have highlighted the meat characteristics of South African Boer goat [28], but no genetic parameters are available for selection for improved carcass traits.
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 official 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, respectively [29].
Despite this relatively small population size, a niche market is served with the production 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 markets. 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.
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 characterization studies. Genetic characterization assists in the conservation of unique characteristics of indigenous populations, whereas genetic diversity has a direct influence on genetic progress, selection strategies and the control of inbreeding levels. The identification of quantitative 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 frequencies 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.
Without a doubt, the Angora goat breed is the South African goat breed on which most molecular research has been performed. The SA Angora goat served as the model breed for improving 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 number of studies performed on the SA Angora goat.
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 parentage verification panel was created, using 14 microsatellite markers with a combined probability 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, especially for growth traits. DNA‐based parentage verification enhanced selection accuracy and would result in faster genetic progress.
Phenotypic recording and EBV selection on mohair and growth traits were relatively successful 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 studies were performed to identify chromosomal segments associated with product and quality 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 and two candidate regions for weaning weight on CHI 16 and 19, respectively [34]. Although putative QTL were identified in both studies, the QTL explained limited phenotypic variation of the traits, which is one of the main restrictions of marker‐assisted selection. No MAS has yet been implemented in the SA Angora goat breed.
The QTL identification study did however indicate that QTL associated with mohair production and quality were located on chromosomes where the KRT and KAP genes have previously been assigned to mainly CHI 1 and 5 [33]. Polymerase chain reaction (PCR) and sequencing technology were used to identify and characterize KAP 1.1, KAP 8.1 and KAP 13.3 in South African Angora, Boer and Angora x Boer goat populations. A total of 19 novel variants were identified in total, and in these, three genes were responsible for structure and quality of hair fibers. The predominant alleles differed between the various populations and together with high levels of observed heterozygosity hold promise for selection based on favorable allelic associations [35].
The development of a moderate‐density genotyping tool, the 50K SNP chip (Illumina Inc., San Diego, CA) [36], was a key milestone for molecular research in goats. Due to the fact that no fiber‐producing breeds were included in the development of this commercial chip, it was first validated in the SA Angora goat population [37]. Fortunately, the high level of polymorphism observed (88.1% of loci) and the sufficient observed heterozygosity levels in the population (0.365) made the bead chip suitable for application in this breed.
The 50K SNP chip was subsequently used to estimate genetic diversity in the SA Angora goat. Results indicated that sufficient genetic diversity still exists within this breed to allow successful selection strategies and genetic improvement [38]. A high proportion of SNP with low minor allele frequency (MAF) values suggested a high proportion of fixed alleles, which was in line with the high selection pressure on specific traits within this population. An linkage disequilibrium (LD) estimate (using the r2 measure) of 0.15 was calculated, which implied that a denser SNP genotyping array would be necessary before genomic selection (GS) could be considered for the SA Angora.
The SA Angora goat was included in a study to analyze the genetic variability of Angora goats from three distinct geographical locations (South Africa, France and Argentina) in order to assess the influence of genetic and geographical isolation [39]. The fixation index (FST) indicated three distinct subpopulations, with intrapopulation values (0.12) corresponding to those normally observed between breeds. An effective population size (Ne) of 93 was estimated for the SA Angora goat, 100 generations ago, and is currently probably even lower. The distinctiveness of the South African population indicated strict directional selection which has resulted in a well‐defined cluster. The high diversity between populations could be useful when exchanging genetic material to improve certain unfavorable characteristics of specific populations.
Both commercial and indigenous goats have been included in studies where DNA markers have been applied to gain insight into their genetic diversity and population structure. However, significantly, less research in terms of molecular studies has been performed on meat goats than on the Angora goat breed.
The first molecular study on SA meat goats was performed in 2004 when the genetic variation of the three commercial breeds as well as three indigenous goat populations were investigated using microsatellite markers [40]. A clear differentiation between the Kalahari Red and Boer goat breeds was observed, whereas the Savanna breed showed significant genetic similarity to the Boer goat. Limited differentiation was observed between the veld goat populations, as was expected. Of all the breeds and populations, the Kalahari Red breed was the most clearly differentiated on a genetic level. The distinctiveness of the Kalahari Red breed was further investigated [41], also using microsatellite markers. Although it appeared that the breed was largely uniform, limited differences suggested local selection and adaptation. The clear genetic differentiation of the Kalahari Red breed was confirmed by a later study focusing on only commercial goat breeds [11]. A factorial correspondence analysis was performed with microsatellite data and the Kalahari Red goats clustered on their own, while the Boer goat and Savanna populations tended to overlap.
The commercial Boer goat and Kalahari Red breeds, as well the Tankwa and two indigenous populations, were included in a study to characterize African goat populations using the Illumina Goat SNP50K genotyping array [42]. These South African breeds showed a higher level of variation when compared to other African populations. Preliminary results were reported by [43, 44] on the population structure and landscape genomics of indigenous goats using genome‐wide SNP data. The goat populations showed sufficient genetic diversity, and the Tankwa population was revealed as a distinct breed. Associations between the genomic variation of the goats and climatic conditions were limited to associations with longitude, temperature and altitude using the spatial analyses method.
The genetic architecture of the three commercial meat breeds, the Tankwa and five distinct ecotypes (Nguni, Venda, Xhosa, Zulu and Tswana) were investigated by Ref. [45]. Ecotypes were found to have the highest levels of genetic diversity and low levels of inbreeding, probably due to the lack of directional selection in communal systems. Most of the ecotypes showed some level of genetic relatedness with one another. The Tankwa breed was again identified as a unique genetic resource with low genetic diversity and high inbreeding levels, which can be attributed to the small population size and geographical isolation of these animals.
The Saanen, British Alpine and Toggenburg are the three breeds contributing to South Africa’s small dairy goat industry. Most goat milk is processed and sold as goat’s cheese; thus, the quality of the milk produced and specifically the casein content is of importance. Limited molecular research has been performed on these breeds.
To date, two studies have been performed to characterize casein in the SA goat breeds, one on κ‐casein [46] and another on αS2‐casein [47]. The first study investigated indigenous, Boer and Saanen goats using restriction fragment length polymorphism (RFLP) and DNA sequencing. Two less favorable alleles (B’ and H) were found exclusively in the meat goat populations, while the favorable B allele was fixated in the Saanen goats. In the latter study, αS2‐casein was genotyped in the three SA dairy breeds, as well as in some meat‐type goats using DNA sequencing. Four alleles and 10 genotypes were observed across the populations, with the A allele being the most frequent in all the breeds. Limited gene‐specific selection opportunities are possible based on these results.
The genetic diversity of SA dairy goats was investigated using a panel of 25 microsatellite markers [48]. High levels of diversity were estimated in all three breeds, with heterozygosity values exceeding 60%. Limited inbreeding was observed within the populations. The genetic differentiation between the dairy breeds was very low, as could be expected within one production type. An admixture group of animals was identified, suggesting that inadvertent crossbreeding between purebred animals was taking place. The SA Milch Goat Breeders’ Society allows the registration of goats with unknown pedigree, based on a physical inspection (mainly color pattern and functional efficiency). It has however been clearly demonstrated that coat color is not a definitive way of assigning breed status. Some dairy goats were included in the SNP‐based genetic diversity study by Ref. [38]. The results corresponded with that of the previous study, with relatively high gene diversity estimates within the breeds. A 30% co‐ancestry was calculated between the breeds, supporting the previous findings [48] regarding admixture.
The various goat breeds and populations in South Africa serve a number of purposes ranging from important economic contributions to the commercial livestock production sector, to the improvement of livelihoods and food security in rural communities. Genetic progress can primarily be attributed selection following a quantitative approach, with a focus on fertility, growth and some breed‐specific production traits such as fiber yield. Future research and selection for genetic improvement will most likely be targeted toward molecular‐based approaches. Molecular research has shown that most SA goat breeds have sufficient genetic diversity to be exploited in selection programs. Specific projects are targeted toward the identification of genes associated with traits of economic importance, managing inbreeding levels and sustainable conservation and utilization of scarce genotypes.
In 1933 Fritz Zwicky [1] indicated a problem related to the galaxy cluster Coma. Galaxy cluster studied by Zwicky appeared to contain some 400 times more matter than an ordinary, visible, i.e., luminous matter. The content of the luminous matter was estimated form the amount of light emitted by the cluster. However, there was no response for that finding. Only 40 years later in 1970s the problem was rediscovered and concerned almost all of the galaxies. Research of Vera Rubin discovered that the galaxies rotate in a way that cannot be explained by taking into account visible, luminous matter. Today we know that most of the matter in the Universe is dark. Various attempts to resolve the problem of the existence of a mysterious form of matter, dark matter, have been taken ever since. One such idea is to find a particle to possibly complete the standard model. The most important property of such particle would be that it is not a subject to electromagnetic force; hence the dark matter is invisible in all electromagnetic wavelengths. In order to detect such particle, sensitive detectors are built, but still final conclusion has not been made. Another attempt of explaining the problem of missing matter was based on the assumption of existence of astrophysical objects such as black hole or dim brown dwarfs. This idea has rather been discredited as the abundance and masses of such objects are too small comparing to the amount of the matter that is missing. On different grounds stands the idea of modifying gravity in low acceleration regime. Modified Newtonian dynamics (MOND) proposed by M. Milgrom in 1983 is a phenomenological approach attempting to provide explanation of rotation of galaxies without invoking hidden matter at all. Yet such an approach seems to be in tension with recent findings of van Dokkum et al. about the ultra-diffuse galaxies. There appear to exist galaxies devoided of dark matter—then what about MOND predictions? This contribution is completed with the rotational curve of the Milky Way determined with 3 m in diameter radio telescope in the Astronomical Observatory of the Jagiellonian University. Obtained rotational curve is flat which indicates the presence of dark matter in the halo of our galaxy.
\nThe term “dark matter” (DM) was introduced due to the contribution by Fritz Zwicky as early as in 1930s of the twentieth century. Studying the Coma cluster (of galaxies) located 320 million light-years away, Zwicky estimated [1] masses of the galaxies that make up this cluster based on the amount of light they emit. It turned out that such an amount of (luminous) matter wasn’t large enough to explain the trajectories and velocities of those galaxies. Zwicky claimed then that the gravitational attraction exerted by the luminous matter was not enough to hold the cluster together and if there wasn’t some kind of additional, nonluminous matter that provide extra gravity force, the galaxies would fly apart. These findings seemingly intriguing by themselves had not been taken seriously by scientific community. And only findings of Vera Rubin [2], some 40 years later, led to the formulation of the fundamental and still unresolved problem. Rubin studied rotational curves of galaxies. Rotational curve of a galaxy is a plot presenting how the orbital velocity of objects in this galaxy changes with increasing distance from the galaxy’s center (see Figure 1). It turned out that the shapes of the curves did not comply with the theoretical predictions based on the mount of matter estimated due to the emitted light.
\nFigure schematically representing discrepancy between observed (B) and predicted (A) rotational curves of galaxies that indicates presence of dark matter in halos of such galaxies. Credit: PhilHibbs, Wikipedia, https://pl.wikipedia.org/wiki/Krzywa_rotacji_galaktyki#/media/Plik:GalacticRotation2.svg, Creative Commons Attribution-Share Alike 3.0 Unported license.
Figure 1 illustrates this discrepancy. When being close to the center of the galaxy, the plot agrees with what one would expect: the rotational curve increases rapidly that reflects an obvious fact that the velocity of a test object (a “star”) increases as the effective gravitational force is growing (at a given radius, only the mass enclosed within a sphere of that radius is relevant in terms of excreting gravitational force—Newton’s Shell Theorem). Past a certain distance though (when increasing a distance from the massive center of galaxy does not enclose adequately bigger amounts of mass), the effective force of gravity should decline (as R2 will increase faster than the mass enclosed in a sphere of a radius being that distance from the center so the force of gravity will decline) which should result in lower orbital velocities.
\nVera Rubin and Kent Ford published their first rotational curve in paper [2]. They presented there the rotation of Andromeda based on spectroscopic survey of emission regions applying neutral hydrogen, Hα, and [NII] λ6583 emission lines. Further works, see, e.g., [3], revealed that most of the galaxies have rather flat rotational curves like the one in Figure 1. The fact that more distant stars have almost constant velocity attracted the attention of scientists. The circular velocities of the stars are due to gravity which plays the role of centripetal force. Combining Newton’s law of gravity with an expression for centripetal force yields the following relation:
\nwhere G is universal gravitational constant, M is mass exerting a gravitational force, V denotes velocity of a (test) object orbiting mass M, and R is the distance between them. One obtains from Eq. (1)
\nSince G is constant and V appears to be constant as we can see in rotational curves (see Figure 1), it would mean that the mass of a galaxy increases linearly with the distance from its center:
\nAs we know most of galaxies including the Milky Way have a bright massive center, a bulge, with majority of stars placed in that range and possibly a supermassive black hole in the middle. The farther away from the center, the fainter the regions are, i.e., less stars hence less matter is present, and linear dependence (3) is almost impossible to be obeyed. Computer simulations show that the galaxies move in a way we can observe them only if there is another than ordinary, luminous, form of matter, namely, dark matter. The amount of dark matter should be as large as almost five times more than the amount of ordinary matter. This is in agreement with calculations made within lambda-cold dark matter model (Λ-CDM) and the data from Wilkinson Microwave Anisotropy Probe (WMAP) [4] as well as Planck mission [5]. Λ-CDM model is a parametrization of the Big Bang cosmological model in which the Universe contains three major components: first, a cosmological constant denoted by lambda (Greek Λ) and associated with dark energy; second, the postulated cold dark matter (abbreviated CDM); and third, ordinary matter. It is often referred to as the standard model of Big Bang cosmology because it is the simplest model that provides a reasonably good description of the content of the Universe. WAMP was a satellite designed to map the cosmic microwave background (CMB) radiation over the entire sky in five frequency bands. The agreement between Λ-CDM model and the data from WAMP is good enough, which supports the validity of this model [4, 5]. The Λ-CDM model indicates that the matter the stars (and us) are made of is just a tiny part of the mass-energy content of the Universe (see Figure 2).
\nEstimated distribution of matter and energy in the universe based on Planck data. Credit: ESA, Planck reveals an almost perfect Universe.
Hypothetical particles that constitute the dark matter are called WIMPs which stands for weakly interacting massive particles. All the matter that we know (and us) is made of baryonic matter, i.e., the matter is made of baryons. WIMPS would be a new type of particles beyond the standard model. Those should be massive, subject to the gravitational force, and possibly other forces that are comparable to the weak force. One such candidate for WIMP could be a stable supersymmetric particle. Supersymmetric model has a particle of this property which was even called a “Wimp Miracle,” but we have not yet observed any trace of supersymmetry, moreover, Wimp Miracle in any of the particle colliders. WIMPs also should not interact via electromagnetism; hence the DM is not visible in any wavelength. We only can “see” the DM due to its gravitational interactions, which are strong enough to cause a phenomenon known as gravitational lensing.
\nThis phenomenon is observed when the light rays passing near a very massive object are deflected (due to the curvature of space–time produced by this object) in such a way that a distant observer observes it lensed. Figure 3 illustrates gravitational lensing: the stretched structures are distant galaxies, whose light was bent by the DM between them and the observer. This allows to calculate the mass required to cause such phenomenon [6]. Large aggregations of massive DM particles are able to produce such image letting us to know it’s out there.
\nAn image of gravitational lensing obtained with Hubble space telescope showing a distant image of galaxies which had been stretched due to the warping of space–time caused by a massive object between them and the observer. Credit: ESA/Hubble https://www.spacetelescope.org/images/potw1506a/.
Massive astrophysical compact halo objects (MACHOs) was another hypothesis invoked to explain the presence of large amount of nonluminous matter in galactic halos. Those, contrary to the WIMPS, would have been regular astrophysical objects emitting little or no radiation such as black holes, neutron stars, as well as brown dwarfs and unassociated planets, which drift unseen through interstellar space providing extra gravity. Thorough investigations have shown that this concept rather fails to explain the expected amount of the DM. One way to detect MACHOS’ influence, as described in [7], is to look for events of microlensing caused by them. Such microlensing would cause observable apparent amplification of star’s flux. In [7] it was shown that the number of such events is far too less that would have been expected. That rules out MACHOS as the candidates for DM. Moreover, the studies of abundance of baryons created in the Big Bang show that baryon density is consistent with the mean cosmic density of matter visible optically and in X-rays. It implies that most of the baryons in the Universe are visible but not dark and that most of the matter in the Universe consists of nonbaryonic DM [7].
\nIn the former sections, we have discussed the attempts of solving or explaining the problem of the missing matter. That is to find or to claim existence of unknown, invisible substance. Yet there is another idea based on a different assumption. In 1983 Milgrom [8] proposed an idea that maybe it is the theory that needs to be modified rather than an invisible matter to be found. Modified Newtonian dynamics (MOND) is an empirically motivated modification of Newtonian dynamics at low accelerations, suggested as an alternative to dark matter concept [8, 9]. In Ref. [8] Milgrom considered the possibility that Newton’s second law does not describe the motion of objects under the conditions which prevail in galaxies and systems of galaxies. Newton’s laws have been tested in high-acceleration environment like the Earth or the solar system. The stars in the outer parts of the galaxies move in the circumstances of extremely low accelerations compared to what we know from everyday life. To illustrate how small such accelerations might be, let us calculate the acceleration of average star (the Sun) located on the suburbs of average galaxy (the Milky Way):
\nMilgrom proposed then a generalized form of Newton’s second principle, claiming the inertia term not to be simply proportional to the acceleration of an object but being rather a more general function of it:
\nIn expression (5)\n
The acceleration constant is found to be \n
Recent studies of van Dokkum et al. [10, 11] have uncovered new class of object referred to as ultra-diffuse galaxies. NGC1052-DF2 and NGC1052-DF4 are large, faint galaxies with an excess of luminous globular clusters, and they have a very low-velocity dispersion. Velocity dispersion is the dispersion of radial velocities about the mean velocity for a group of objects. Low-velocity dispersion indicates that the galaxy has little or no dark matter. NGC1052-DF2 was studied with the Keck Cosmic Web Imager (KCWI), a new instrument on the Keck II telescope that was optimized for precision sky-limited spectroscopy of low surface brightness phenomena at relatively high spectral resolution. The spectroscopy data was used to describe kinematics of the galaxy. This result was based on the radial velocities of globular clusters that were assumed to be associated with the galaxies. It was claimed in Ref. [10] that taking observational uncertainties into account, the determined intrinsic velocity dispersion is consistent with the expected value found for the stars alone and lower than expected from DM halo (see Figure 4). The dynamical mass of NGC1052-DF2 determined in [10] was \n
Constraints on the intrinsic velocity dispersion of NGC1052-DF2. The result found in [8] (red dot star) is consistent with two other studies mentioned by authors and shows that such velocity dispersion indicates lack of the dark matter. Credit: [10].
To give a reader some intuition and place this in some context, it is worth to notice that the stellar mass of the Milky Way found in [12] was \n
In 2012 Moni Bidin et al. [14] published a paper in which they estimated surface mass density in the solar neighborhood. Results obtained match the expectations of visible matter alone without the need of adding the dark matter component. The difference between the measured mass of matter (derived in this study) and the mass of visible matter (i.e., mass of matter that is estimated in the independent way based on the amount of emitted) provides an estimate of the amount of DM in the volume under analysis, and constraints on the shape of the DM halo can be derived. The fundamental basis for this measurement is the application of the Poisson–Boltzmann and Jeans equations to a virialized system in steady state. This allows to estimate either the local density at the solar position or the surface density (mass per unit area) of the mass within a given volume. Authors in Ref. [14] derive analytical expression for surface density as a function of distance from the galactic disk plane Σ(Z) to estimate the surface mass density between 1.5 and 4.5 kpc distance from the galactic disk plane using data from of the kinematics studies of about 400 red giants kinematics. The authors in [14] claimed that the estimate of the surface mass density matches the expectation of visible mass alone and the degree of overlap between the two curves is striking. There is no need for any dark component to account for the results: the measured Σ(Z) implies a local DM density \n
Observational results for the surface mass density, as a function of distance from the galactic plane (black curve), compared to the expectations of the models discussed in the text (thick gray curves). The dotted and dashed lines indicate the observational 1σ and 3σ strip, respectively. Expectations for the known visible mass are indicated by the thick gray curve labeled as VIS. Credit: [14].
The experiments that aim at the direct detection due to scattering do not agree with each other yielding different constraints on the mass of the DM particles. The DAMA/LIBRA experiment [20] is the only one to claim positive result of detection which however has not been yet confirmed by the other groups (detectors). The aim of this experiment is detecting low-energy recoil photons from the scintillator crystals of thallium-doped sodium iodide NaI(Tl) placed in the detectors under the ground. Such photons would be emitted when the DM particle collides with one of the scintillators. If what we know about the DM is right, then since the Earth orbits the Sun, the DM particles should pass through the planet and hence have a chance to collide with those of the detectors. The idea of the experiment is that if one takes into account the revolution of the Earth around the Sun and the revolution of the Sun around the center of our galaxy, then the signals coming from the collisions should be modulated as in June the relative velocity of the Earth and the DM flux is the biggest hence yielding the biggest number of collisions. The data collected from the phase II of the experiment have all traits required to claim the presence of the DM in our part of the galaxy. The annual modulation is present only in the events concerning the photons with energies exactly within the energetic range theoretically predicted for the DM particles. Yet the DAMA/LIBRA is a singular case. Several groups have been working to develop experiments aiming at reproducing DAMA/LIBRA’s results using the same target medium. To determine whether there is evidence for an excess of events above the expected background in sodium iodide and to look for evidence of an annual modulation, the COSINE-100 experiment [21] uses the same target medium to carry out a model-independent test of DAMA/LIBRA’s claim. Their results from the initial operation of the COSINE-100 experiment were published in [21], and no excess of signal-like events above the expected background in the first 59.5 days of data from COSINE-100 has been observed. Assuming the so-called standard DM halo model, this result rules out spin-independent WIMP–nucleon interactions as the cause of the annual modulation observed by the DAMA/LIBRA collaboration. Another such experiment is the XENON100 experiment that searches for electronic recoil event rate modulation by measuring the scintillation light from a particle interacting in the liquid xenon. The results of this experiment published in [22] also exclude the DAMA/LIBRA results.
\nWe will present here very briefly the other two methods of detection of DM:
Production of DM particles in colliders—If the DM particles were created, for instance, in LHC, they would escape through the detectors unnoticed (due to their non-electromagnetic nature). However, they would carry away energy and momentum, so one could infer their existence from the amount of energy and momentum “missing” after a collision. The LHC also search for existence of supersymmetric particles which are one of the candidates for DM particle.
Searching for products of annihilation of its particles—Indirect detection. This experiments search for the products of the self-annihilation or decay of DM particles in outer space. For example, in regions of high DM density (e.g., the center of our galaxy), two DM particles could annihilate to produce gamma rays or standard model particle–antiparticle pairs. Alternatively if the DM particle is unstable, it could decay into standard model (or other) particles. These processes could be detected indirectly through an excess of gamma rays, antiprotons, or positrons emanating from high-density regions in the galaxy or others.
DM manifests its existence through the shape of rotational curves of galaxies, in particular, through the rotational curve of our own galaxy, the Milky Way. This is what motivated us to take a glimpse on that topic and to compare results to those present in literature [23]. We have studied the rotational curve of Milky Way with radio telescope located in the Astronomical Observatory of the Jagiellonian University provided by EU-HOU project (EU-HOU project was founded with support from the European Commission, grant 510,308-LLP-1-2010-FR-COMENIUS-CMP.
This 3 m in diameter telescope runs observations on 1420 MHz frequency which is the emission line of neutral hydrogen. When the hydrogen atom undergoes a transition from the state of higher energy when the spins of the proton and the electron are parallel to the state of lower energy that is when the spins are antiparallel, emitted photon is equivalent to radiation roughly 21 cm wavelength in vacuum (see Figure 6). Even though such process occurs very rarely, given the abundance of the hydrogen in the Universe (i.e., 74% of its baryonic mass), it is a common phenomenon. Hence the hydrogen is also present in the interstellar space around the stars, and radio observations yield information on how the matter is distributed inside the galaxy, and knowing the Doppler shift of the observed radiation, one can calculate the velocity of the hydrogen cloud from which it comes from. This in turn gives us an idea how the hydrogen and the nearby matter move within the galaxy, i.e., orbit around its center. Knowing the velocities and distance of such hydrogen clouds, one can plot the rotational curve of the galaxy. This is called tangent point method. Thus using the data obtained from the telescope, the Doppler equation:
\nHydrogen 21-cm emission line.
one can calculate the source’s velocity (speed) relative to us (\n
To find the speed of the hydrogen cloud, a simple fact is used, that is the radial velocity results in difference between the projection of ours (Sun’s) velocity on the line of sight and the hydrogen cloud’s velocity on the line of sight (see Figure 7). The line of sight is determined along the galactic longitude (see Figure 8) on which we set the radio telescope.
\nFigure presenting two objects (A, B) along the line of sight. Hence object B lies in tangent point, i.e., its distance from the center of the galaxy is smaller, and its velocity is greater than the velocity of object A.
Figure presenting galactic longitude. L = 0° is direction from the solar system to the center of galaxy. Credit: File:Artist’s_impression_of_the_Milky_Way.Jpg: NASA/JPL-Caltech/ESO/R.hurt.
This results in the following equation for velocity of observed hydrogen cloud:
\nAmong the objects observed along the given line of sight, the one with the smallest distance will have the biggest velocity. The smallest possible distance between us and the source is when it lies in the tangent point; hence simple trigonometry allows us to determine the distance:
\nwhich simplifies Eq. (8) to
\nEqs. (8) and (9) provide all required information to plot a rotational curve of the galaxy. This method works for objects in I and IV Quadrants of galactic longitude, that is for \n
Twenty-nine objects with galactic longitude \n
Map of the hydrogen clouds used to determine the rotational curve of the Milky Way.
Rotational curve obtained from 21-cm line observations of the Milky Way. Note that the velocity of the studied objects appears to be constant over roughly 3 kpc distance.
Our rotational curve plot, Figure 10, is comparable to the plot obtained from data from LAB survey [24] and consistent with the ones that can be found in literature [23, 25]. We follow [25] in their choice of function to fit the data, namely
\nwhere we put \n
We conclude that the rotational curve reveals the existence of dark matter within the Milky Way. Taking (nonrelativistic) law of gravity, that is, the force of gravity is proportional to inverse squared distance, one would expect that the farther away the hydrogen clouds (constituting the distribution of matter) are from the massive center of the galaxy, the lower their velocities will be. As one see from the rotational curve, Figure 10, this is not the case; the velocities seem to be constant over a distance of roughly 3 kpc. Which means there is nonluminous matter distributed in such a way just to “keep up” with the increasing distance from the center of galaxy and make it so that the velocities of hydrogen atoms are almost constant as the distance increases.
\nThe problem of missing matter discovered by Fritz Zwicky in 1933 appears to be still an open question. The most important premise of existence of the dark matter is the shape of rotational curves of galaxies, introduced as a tool for studying galaxy rotation by Vera Rubin. With our current understanding of the Universe, the dark matter, still a mysterious substance, makes up 86% of all the matter in the Universe. Throughout the years various attempts have been made to explain its nature. Some of the ideas have been proven unlikely (MACHOs). Some of them contradict each other (DAMA/LIBRA, the COSINE-100 collaboration). Yet even simple Milky Way’s observations as presented in Section 5 lead to the conclusion that the dark matter is present in the halo of our galaxy.
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