Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). While indicators of ...general resilience have been proposed and evaluated in other regions, their applicability in SSA remains unexplored. This study sought to test the viability of utilizing log-transformed variance (LnVar), autocorrelation (r
), and skewness (Skew) of deviations in milk yield as indicators of general resilience of dairy cows performing in the tropical environment of Kenya.
Test-day milk yield records of 2,670 first-parity cows performing in three distinct agroecological zones of Kenya were used. To predict expected milk yield, quantile regression was used to model lactation curve for each cow. Subsequently, resilience indicators were defined based on actual and standardized deviations of observed milk yield from the expected milk yield. The genetic parameters of these indicators were estimated, and their associations with longevity and average test-day milk yield were examined.
All indicators were heritable except skewness of actual and standardized deviation. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 ± 0.04 and 0.17 ± 0.04, respectively. Auto-correlation of actual (r
1) and standardized (r
2) deviations had heritabilities of 0.05 ± 0.03 and 0.07 ± 0.03, respectively. Weak to moderate genetic correlations were observed among resilience indicators. Both r
and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield. LnVar1 and LnVar2 were genetically associated with better longevity (rg = -0.47 ± 0.26 and -0.49 ± 0.26, respectively). Whereas LnVar1 suggested that resilient animals produce lower average test-day milk yield, LnVar2 revealed a genetic association between resilience and higher average test-day milk yield.
Log transformed variance of deviations in milk yield holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be employed in defining resilience indicators because the resultant indicator does not inaccurately infer that low-producing animals are inherently resilient. This study offers an opportunity for enhancing the productivity of dairy cattle performing in SSA through selective breeding for resilience to environmental stressors.
The flow harmonics upsilon sub(2,3) for charged hadrons are studied for a broad range of centrality selections and beam collision energies in Au + Au (radicalS sub(N)N= 7.7-200 Gev) and Pb + Pb ...(radicalS sub(N)N= 2.76 Tev) collisions. They validate the characteristic signature expected for the system size dependence of viscous damping at each collision energy studied. The extracted viscous coefficients that encode the magnitude of the ratio of shear viscosity to entropy density eta/s are observed to decrease to an apparent minimum as the collision energy is increased from radicalS sub(N)N= 7.7 to approximately 62.4 GeV; thereafter, they show a slow increase with radicalS sub(N)Nup to 2.76 TeV. This pattern of viscous damping provides the first experimental constraint for eta/s in the temperature-baryon chemical potential (T, mu sub(B) plane and could be an initial indication for decay trajectories that lie close to the critical end point in the phase diagram for nuclear matter.
Smallholder dairy farming in much of the developing world is based on the use of crossbred cows that combine local adaptation traits of indigenous breeds with high milk yield potential of exotic ...dairy breeds. Pedigree recording is rare in such systems which means that it is impossible to make informed breeding decisions. High-density single nucleotide polymorphism (SNP) assays allow accurate estimation of breed composition and parentage assignment but are too expensive for routine application. Our aim was to determine the level of accuracy achieved with low-density SNP assays.
We constructed subsets of 100 to 1500 SNPs from the 735k-SNP Illumina panel by selecting: (a) on high minor allele frequencies (MAF) in a crossbred population; (b) on large differences in allele frequency between ancestral breeds; (c) at random; or (d) with a differential evolution algorithm. These panels were tested on a dataset of 1933 crossbred dairy cattle from Kenya/Uganda and on crossbred populations from Ethiopia (N = 545) and Tanzania (N = 462). Dairy breed proportions were estimated by using the ADMIXTURE program, a regression approach, and SNP-best linear unbiased prediction, and tested against estimates obtained by ADMIXTURE based on the 735k-SNP panel. Performance for parentage assignment was based on opposing homozygotes which were used to calculate the separation value (sv) between true and false assignments.
Panels of SNPs based on the largest differences in allele frequency between European dairy breeds and a combined Nelore/N'Dama population gave the best predictions of dairy breed proportion (r
= 0.962 to 0.994 for 100 to 1500 SNPs) with an average absolute bias of 0.026. Panels of SNPs based on the highest MAF in the crossbred population (Kenya/Uganda) gave the most accurate parentage assignments (sv = -1 to 15 for 100 to 1500 SNPs).
Due to the different required properties of SNPs, panels that did well for breed composition did poorly for parentage assignment and vice versa. A combined panel of 400 SNPs was not able to assign parentages correctly, thus we recommend the use of 200 SNPs either for breed proportion prediction or parentage assignment, independently.
Knowledge on how adaptive evolution and human socio‐cultural and economic interests shaped livestock genomes particularly in sub‐Saharan Africa remains limited. Ethiopia is in a geographic region ...that has been critical in the history of African agriculture with ancient and diverse human ethnicity and bio‐climatic conditions. Using 52K genome‐wide data analysed in 646 individuals from 13 Ethiopian indigenous goat populations, we observed high levels of genetic variation. Although runs of homozygosity (ROH) were ubiquitous genome‐wide, there were clear differences in patterns of ROH length and abundance and in effective population sizes illustrating differences in genome homozygosity, evolutionary history, and management. Phylogenetic analysis incorporating patterns of genetic differentiation and gene flow with ancestry modelling highlighted past and recent intermixing and possible two deep ancient genetic ancestries that could have been brought by humans with the first introduction of goats in Africa. We observed four strong selection signatures that were specific to Arsi‐Bale and Nubian goats. These signatures overlapped genomic regions with genes associated with morphological, adaptation, reproduction and production traits due possibly to selection under environmental constraints and/or human preferences. The regions also overlapped uncharacterized genes, calling for a comprehensive annotation of the goat genome. Our results provide insights into mechanisms leading to genome variation and differentiation in sub‐Saharan Africa indigenous goats.
The African livestock sector plays a key role in improving the livelihoods of people through the supply of food, improved nutrition and consequently health. However, its impact on the economy of the ...people and contribution to national GDP is highly variable and generally below its potential. This study was conducted to assess the current state of livestock phenomics and genetic evaluation methods being used across the continent, the main challenges, and to demonstrate the effects of various genetic models on the accuracy and rate of genetic gain that could be achieved. An online survey of livestock experts, academics, scientists, national focal points for animal genetic resources, policymakers, extension agents and animal breeding industry was conducted in 38 African countries. The results revealed 1) limited national livestock identification and data recording systems, 2) limited data on livestock production and health traits and genomic information, 3) mass selection was the common method used for genetic improvement with very limited application of genetic and genomic-based selection and evaluation, 4) limited human capacity, infrastructure, and funding for livestock genetic improvement programmes, as well as enabling animal breeding policies. A joint genetic evaluation of Holstein-Friesian using pooled data from Kenya and South Africa was piloted. The pilot analysis yielded higher accuracy of prediction of breeding values, pointing to possibility of higher genetic gains that could be achieved and demonstrating the potential power of multi-country evaluations: Kenya benefited on the 305-days milk yield and the age at first calving and South Africa on the age at first calving and the first calving interval. The findings from this study will help in developing harmonized protocols for animal identification, livestock data recording, and genetic evaluations (both national and across-countries) as well as in designing subsequent capacity building and training programmes for animal breeders and livestock farmers in Africa. National governments need to put in place enabling policies, the necessary infrastructure and funding for national and across country collaborations for a joint genetic evaluation which will revolutionize the livestock genetic improvement in Africa.
In smallholder dairy-cattle farming, identifying positive deviants that attain outstanding performance can inform targeted improvements in typical, comparable farms under similar environmental ...stresses. Mostly, positive deviants are identified subjectively, introducing bias and limiting generalisation. The aim of the study was to objectively identify positive deviant farms using the Pareto-optimality ranking technique in a sample of smallholder dairy farms under contrasting stressful environments in Tanzania to test the hypothesis that positive deviant farms that simultaneously outperform typical farms in multiple performance indicators also outperform in yield gap, productivity and livelihood benefits. The selection criteria set five performance indicators: energy balance ≥ 0.35 Mcal NEL/d, disease-incidence density ≤ 12.75 per 100 animal-years at risk, daily milk yield ≥ 6.32 L/cow/day, age at first calving ≤ 1153.28 days and calving interval ≤ 633.68 days. Findings proved the hypothesis. A few farms (27: 3.4%) emerged as positive deviants, outperforming typical farms in yield gap, productivity and livelihood benefits. The estimated yield gap in typical farms was 76.88% under low-stress environments and 48.04% under high-stress environments. On average, total cash income, gross margins and total benefits in dairy farming were higher in positive deviants than in typical farms in both low- and high-stress environments. These results show that the Pareto-optimality ranking technique applied in a large population objectively identified a few positive deviant farms that attained higher productivity and livelihood benefits in both low- and high-stress environments. However, positive deviants invested more in inputs. With positive deviant farms objectively identified, it is possible to characterise management practices that they deploy differently from typical farms and learn lessons to inform the uptake of best practices and extension messages to be directed to improving dairy management.
This study characterized breeding, housing, feeding and health management practices in positive deviants and typical average performing smallholder dairy farms in Tanzania. The objective was to ...distinguish management practices that positive deviant farms deploy differently from typical farms to ameliorate local prevalent environmental stresses. In a sample of 794 farms, positive deviants were classified on criteria of consistently outperforming typical farms (p < 0.05) in five production performance indicators: energy balance ≥ 0.35 Mcal NEL/d; disease-incidence density ≤ 12.75 per 100 animal-years at risk; daily milk yield ≥ 6.32 L/cow/day; age at first calving ≤ 1153.28 days; and calving interval ≤ 633.68 days. The study was a two-factor nested research design, with farms nested within the production environment, classified into low- and high-stress. Compared to typical farms, positive deviant farms had larger landholdings, as well as larger herds comprising more high-grade cattle housed in better quality zero-grazing stall units with larger floor spacing per animal. Positive deviants spent more on purchased fodder and water, and sourced professional veterinary services (p < 0.001) more frequently. These results show that management practices distinguishing positive deviants from typical farms were cattle upgrading, provision of larger animal floor spacing and investing more in cattle housing, fodder, watering, and professional veterinary services. These distinguishing practices can be associated with amelioration of feed scarcity, heat load stresses, and disease infections, as well as better animal welfare in positive deviant farms. Nutritional quality of the diet was not analyzed, for which research is recommended to ascertain whether the investments made by positive deviants are in quality of feeds.
In most smallholder dairy programmes, farmers are not fully benefitting from the genetic potential of their dairy cows. This is in part due to the mismatch between the available genotypes and the ...environment, including management, in which the animals perform. With sparse performance and pedigree records in smallholder dairy farms, the true degree of baseline genetic variability and breed composition is not known and hence rendering any genetic improvement initiative difficult to implement. Using the Girinka programme of Rwanda as an exemplar, the current study was aimed at better understanding the genetic diversity and population structure of dairy cattle in the smallholder dairy farm set up. Further, the association between farmer self-reported cow genotypes and genetically determined genotypes was investigated. The average heterozygosity estimates were highest (0.38 ± 0.13) for Rwandan dairy cattle and lowest for Gir and N'Dama (0.18 ± 0.19 and 0.25 ± 0.20, respectively). Systematic characterization of the genetic variation and diversity available may inform the formulation of sustainable improvement strategies such as targeting and matching the genotype of cows to productivity goals and farmer profile and hence reducing the negative impact of genotype by environment interaction.
The ability of smallholder dairy farming systems (SHDFS) to achieve desirable lactation-curve characteristics is constrained or reduced by environmental stresses. Under stressful production ...environments in the tropics, the better lactation-curve characteristics in smallholder dairy farms are a result of improved dairy genetics and husbandry practices. Better husbandry practices improve animal health and welfare status, which is important to sustain SHDFS in the tropics where dairy cattle are constantly exposed to multiple environmental stresses of feed scarcity, disease infections and heat load. In this case, lactating cows in smallholder dairy farms labelled positive deviants are expected to express lactation curve characteristics differently from typical farms, regardless of the stress levels confronted. Thus, this study tested this hypothesis with Holstein–Friesian and Ayrshire cows in two milksheds in Tanzania classified them into low-and high-stress environments. A two-factor nested research design was used, with farm (positive deviant and typical) nested within the environment. Positive deviant farms were farms that performed above the population average, attaining ≥0.35 Mcal NEL/d energy balance, ≥6.32 L/cow/day milk yield, ≤1153.28 days age at first calving, ≤633.68 days calving interval and ≤12.75 per 100 animal-years at risk disease-incidence density. In this study, a total of 3262 test-day milk production records from 524 complete lactations of 397 cows in 332 farms were fitted to the Jenkins and Ferrell model to estimate lactation curve parameters. In turn, the outcome parameters a and k were used to estimate lactation curve characteristics. The lactation curve characteristic estimates proved the study hypothesis. Regardless of the stress levels, cows in positive deviant farms expressed lactation curve characteristics differently from cows managed in typical farms. The scale (a) and shape (k) parameters together with peak yield and time to peak yield indicated higher lactation performance in positive deviant farms than in typical farms under low- and high-stress environments (p < 0.05). Lactation persistency was higher in positive deviants than typical farms by 14.37 g/day and 2.33 g/day for Holstein–Friesian cows and by 9.91 g/day and 2.16 g/day for Ayrshire cows in low- and high-stress environments. Compared to cows managed in typical farms, cows in positive deviant farms attained higher lactation performance under low- and high-stress; Holstein–Friesian produced 50.2% and 36.2% more milk, respectively, while Ayrshire produced 52.4% and 46.0% more milk, respectively. The higher milk productivity in positive deviant farms can be associated with the deployment of husbandry practices that more effectively ameliorated feed scarcity, heat load and disease infections stresses, which are prevalent in tropical smallholder dairy farms.
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