Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa
Despite the relevance of dairy production in the fight against food insecurity in sub-Saharan Africa (SSA), the negative effects of climate change and general changes in the production environment pose tremendous challenges to its profitability. Genetic improvement of resilience, the capacity of ani...
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| Formato: | Tesis |
| Lenguaje: | Inglés |
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University of Hohenheim
2025
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| Acceso en línea: | https://hdl.handle.net/10568/173569 |
| _version_ | 1855523881161326592 |
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| author | Oloo, Richard Dooso |
| author_browse | Oloo, Richard Dooso |
| author_facet | Oloo, Richard Dooso |
| author_sort | Oloo, Richard Dooso |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Despite the relevance of dairy production in the fight against food insecurity in sub-Saharan Africa (SSA), the negative effects of climate change and general changes in the production environment pose tremendous challenges to its profitability. Genetic improvement of resilience, the capacity of animals to be either minimally affected by an environmental disturbance or rapidly recover from a disturbance in their environment, is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in SSA. However, to breed for resilience, reliable and practical methods for quantifying and analyzing resilience in SSA need to be described and undertaken. This thesis explored the measurement of resilience using different indicators and examined the relationships of resilience with fertility and milk production in dairy cows performing in SSA.
Chapter two of this thesis reviewed potential solutions to enhance the sustainability and productivity of the dairy sector in SSA with an emphasis on breeding for resilience. It described the dairy production in SSA, and environmental challenges cattle have to weather in this region. The chapter further discussed different forms of resilience (general resilience and specialized resilience), indicators for measuring resilience, and provided insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. It is concluded that improving resilience of dairy animals in SSA would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in this region.
In chapter three, the potential of quantifying general resilience using indicators based on deviations in milk yield was examined. Three indicators of general resilience were defined: variance (LnVar), lag-1 autocorrelation (rauto), and skewness (Skew) of deviations in milk yield based on actual and standardized deviations of observed milk yield from predicted milk yield. The heritability estimates of all resilience indicators except Skew were significant and ranged from 0.05 to 0.19. Weak to moderate genetic correlations were observed among indicators of general resilience, suggesting that these indicators captured different aspects of resilience. LnVar indicators indicated that resilient cows are genetically associated with better longevity. The use of actual deviations and standardized deviations to define indicators yielded identical traits except in LnVar. Standardization of deviations or correcting for the milk production potential of animals ensures that the resultant LnVar indicator does not inaccurately categorize low-producing animals as inherently resilient. The study concluded that LnVar holds a significant potential as a robust resilience indicator for dairy animals performing in SSA.
The fourth chapter investigated the response of milk production at varying heat loads as an indication of heat tolerance, which is a specialized resilience. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: the slope of the reaction norm (Slope), and its absolute value (Absolute), reflecting changes in milk yield in response to varying heat load. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero. The correlation analysis between these indicators and average milk yield revealed that high- producing cows are more vulnerable to heat stress and have less stable milk production under heat-stress conditions. The study demonstrated the possibility of using the slope of the reaction norm and its absolute value to measure the specialized resilience of dairy cattle to heat stress conditions in SSA.
Chapter 5 examined the genetic parameters and relationships among resilience, fertility, and milk production traits. The heritability estimates of age at first calving (AFC), calving interval (CI), and test-day milk yield (MY) were 0.17, 0.06, and 0.35 respectively, and were all significantly different from zero. AFC was negatively correlated with both CI and MY, showing that animals that attain sexual maturity earlier exhibit longer calving intervals and higher milk production. A positive correlation between CI and MY showed that high-yielding cows faced challenges in maintaining shorter calving intervals. There was a generally positive correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except the variance of actual deviation corrected for milk production and variance of standardized deviations, revealed an antagonistic relationship between resilience and milk production.
This thesis showed the potential for quantifying and breeding for resilience in dairy cattle performing in SSA. Cows with more than 50% Zebu genes and those performing in semi-arid environments had higher resilience, higher AFC, shorter CI, and lower MY. This suggests that zebu genes confer resilience advantage to animals and exposure of animals to various disturbances in semi-arid environments improved their resilience capacity. Different directions of relationship observed among the traits studied imply that developing a multi-trait selection index that combines all these traits could strike the right balance among resilience, fertility, and milk production. The implications of these findings are valuable in improving the productivity of dairy cattle through selective breeding for resilience to environmental stressors, particularly in low-income countries situated in tropical regions. |
| format | Tesis |
| id | CGSpace173569 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | University of Hohenheim |
| publisherStr | University of Hohenheim |
| record_format | dspace |
| spelling | CGSpace1735692025-11-05T04:04:34Z Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa Oloo, Richard Dooso climate change dairying genetics Despite the relevance of dairy production in the fight against food insecurity in sub-Saharan Africa (SSA), the negative effects of climate change and general changes in the production environment pose tremendous challenges to its profitability. Genetic improvement of resilience, the capacity of animals to be either minimally affected by an environmental disturbance or rapidly recover from a disturbance in their environment, is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in SSA. However, to breed for resilience, reliable and practical methods for quantifying and analyzing resilience in SSA need to be described and undertaken. This thesis explored the measurement of resilience using different indicators and examined the relationships of resilience with fertility and milk production in dairy cows performing in SSA. Chapter two of this thesis reviewed potential solutions to enhance the sustainability and productivity of the dairy sector in SSA with an emphasis on breeding for resilience. It described the dairy production in SSA, and environmental challenges cattle have to weather in this region. The chapter further discussed different forms of resilience (general resilience and specialized resilience), indicators for measuring resilience, and provided insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. It is concluded that improving resilience of dairy animals in SSA would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in this region. In chapter three, the potential of quantifying general resilience using indicators based on deviations in milk yield was examined. Three indicators of general resilience were defined: variance (LnVar), lag-1 autocorrelation (rauto), and skewness (Skew) of deviations in milk yield based on actual and standardized deviations of observed milk yield from predicted milk yield. The heritability estimates of all resilience indicators except Skew were significant and ranged from 0.05 to 0.19. Weak to moderate genetic correlations were observed among indicators of general resilience, suggesting that these indicators captured different aspects of resilience. LnVar indicators indicated that resilient cows are genetically associated with better longevity. The use of actual deviations and standardized deviations to define indicators yielded identical traits except in LnVar. Standardization of deviations or correcting for the milk production potential of animals ensures that the resultant LnVar indicator does not inaccurately categorize low-producing animals as inherently resilient. The study concluded that LnVar holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. The fourth chapter investigated the response of milk production at varying heat loads as an indication of heat tolerance, which is a specialized resilience. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: the slope of the reaction norm (Slope), and its absolute value (Absolute), reflecting changes in milk yield in response to varying heat load. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero. The correlation analysis between these indicators and average milk yield revealed that high- producing cows are more vulnerable to heat stress and have less stable milk production under heat-stress conditions. The study demonstrated the possibility of using the slope of the reaction norm and its absolute value to measure the specialized resilience of dairy cattle to heat stress conditions in SSA. Chapter 5 examined the genetic parameters and relationships among resilience, fertility, and milk production traits. The heritability estimates of age at first calving (AFC), calving interval (CI), and test-day milk yield (MY) were 0.17, 0.06, and 0.35 respectively, and were all significantly different from zero. AFC was negatively correlated with both CI and MY, showing that animals that attain sexual maturity earlier exhibit longer calving intervals and higher milk production. A positive correlation between CI and MY showed that high-yielding cows faced challenges in maintaining shorter calving intervals. There was a generally positive correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except the variance of actual deviation corrected for milk production and variance of standardized deviations, revealed an antagonistic relationship between resilience and milk production. This thesis showed the potential for quantifying and breeding for resilience in dairy cattle performing in SSA. Cows with more than 50% Zebu genes and those performing in semi-arid environments had higher resilience, higher AFC, shorter CI, and lower MY. This suggests that zebu genes confer resilience advantage to animals and exposure of animals to various disturbances in semi-arid environments improved their resilience capacity. Different directions of relationship observed among the traits studied imply that developing a multi-trait selection index that combines all these traits could strike the right balance among resilience, fertility, and milk production. The implications of these findings are valuable in improving the productivity of dairy cattle through selective breeding for resilience to environmental stressors, particularly in low-income countries situated in tropical regions. 2025-02-25 2025-03-11T12:12:57Z 2025-03-11T12:12:57Z Thesis https://hdl.handle.net/10568/173569 en Open Access application/pdf University of Hohenheim Oloo, R.D. 2025. Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa. PhD thesis. Hohenheim, Germany: University of Hohenheim. |
| spellingShingle | climate change dairying genetics Oloo, Richard Dooso Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title | Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title_full | Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title_fullStr | Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title_full_unstemmed | Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title_short | Genetic relationships among resilience, fertility, and milk yield in dairy cattle performing in sub-Saharan Africa |
| title_sort | genetic relationships among resilience fertility and milk yield in dairy cattle performing in sub saharan africa |
| topic | climate change dairying genetics |
| url | https://hdl.handle.net/10568/173569 |
| work_keys_str_mv | AT olooricharddooso geneticrelationshipsamongresiliencefertilityandmilkyieldindairycattleperforminginsubsaharanafrica |