Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa

Richard D. Oloo; Julie M.K. Ojango; Chinyere C. Ekine-Dzivenu; Gebregziabher Gebreyohanes; Raphael Mrode; Okeyo A. Mwai; Mizeck G.G. Chagunda

doi:10.3389/fanim.2023.1254877

Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa

Richard D. Oloo^*, Julie M.K. Ojango, Chinyere C. Ekine-Dzivenu, Gebregziabher Gebreyohanes, Raphael Mrode, Okeyo A. Mwai, Mizeck G.G. Chagunda

^*Corresponding author for this work

Genetics Unit

Research output: Contribution to journal › Review article › peer-review

2 Citations (Scopus)

49 Downloads (Pure)

Abstract

The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.

Original language	English
Article number	1254877
Journal	Frontiers in Animal Science
Volume	4
Early online date	22 Sept 2023
DOIs	https://doi.org/10.3389/fanim.2023.1254877
Publication status	First published - 22 Sept 2023

Bibliographical note

Funding Information:
The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis.

Funding Information:
Perhaps the resources being allocated to improve resilience in a trait-by-trait manner could be channeled to the frequent collection of quality longitudinal data, such as milk yield, growth traits, and activity patterns. Improved data quality and quantity would not only help to assess resilience but also improve production performance. Projects such as African and Asian Dairy Genetic Gains (AADGG, https://portal.adgg.ilri.org/ ) program have come up with innovative digital recording and farmer education systems and solutions to help address these situations. AADGG program led by ILRI is funded by the Bill & Melinda Gates Foundation (BMGF) and is an integral part of the CGIAR Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition and Gender Inclusion (SAPLING). It is capturing and managing large volumes of performance data from both small- and large-scale farmers in eastern Africa and is pulling related weather data to derive indicative resilience traits. Future efforts aim to capture resilience related traits using various sensor-based technologies more directly. Over time, accumulated data can be used in genetic evaluations. Another ILRI-led BMGF funded project, EnviroCow, is developing phenotyping tools as well as genetic selection tools in SSA for novel animal traits such as methane emission intensity, feed requirements for maintenance and milk production, calf survival rate, and stability of milk. These projects aim to grant small-scale farmers in SSA access to more productive, feed-efficient, and resilient cattle genotypes, ultimately increasing their income levels.

Funding Information:
The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis.

Publisher Copyright:
Copyright © 2023 Oloo, Ojango, Ekine-Dzivenu, Gebreyohanes, Mrode, Mwai and Chagunda.

Keywords

dairy cattle
environmental disturbances
productivity
resilience
sub-Saharan Africa

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

Oloo, R. D., Ojango, J. M. K., Ekine-Dzivenu, C. C., Gebreyohanes, G., Mrode, R., Mwai, O. A., & Chagunda, M. G. G. (2023). Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa. Frontiers in Animal Science , 4, Article 1254877. Advance online publication. https://doi.org/10.3389/fanim.2023.1254877

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abstract = "The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA{\textquoteright}s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.",

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author = "Oloo, {Richard D.} and Ojango, {Julie M.K.} and Ekine-Dzivenu, {Chinyere C.} and Gebregziabher Gebreyohanes and Raphael Mrode and Mwai, {Okeyo A.} and Chagunda, {Mizeck G.G.}",

note = "Funding Information: The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft f{\"u}r Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis. Funding Information: Perhaps the resources being allocated to improve resilience in a trait-by-trait manner could be channeled to the frequent collection of quality longitudinal data, such as milk yield, growth traits, and activity patterns. Improved data quality and quantity would not only help to assess resilience but also improve production performance. Projects such as African and Asian Dairy Genetic Gains (AADGG, https://portal.adgg.ilri.org/ ) program have come up with innovative digital recording and farmer education systems and solutions to help address these situations. AADGG program led by ILRI is funded by the Bill & Melinda Gates Foundation (BMGF) and is an integral part of the CGIAR Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition and Gender Inclusion (SAPLING). It is capturing and managing large volumes of performance data from both small- and large-scale farmers in eastern Africa and is pulling related weather data to derive indicative resilience traits. Future efforts aim to capture resilience related traits using various sensor-based technologies more directly. Over time, accumulated data can be used in genetic evaluations. Another ILRI-led BMGF funded project, EnviroCow, is developing phenotyping tools as well as genetic selection tools in SSA for novel animal traits such as methane emission intensity, feed requirements for maintenance and milk production, calf survival rate, and stability of milk. These projects aim to grant small-scale farmers in SSA access to more productive, feed-efficient, and resilient cattle genotypes, ultimately increasing their income levels. Funding Information: The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft f{\"u}r Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis. Publisher Copyright: Copyright {\textcopyright} 2023 Oloo, Ojango, Ekine-Dzivenu, Gebreyohanes, Mrode, Mwai and Chagunda.",

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T1 - Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa

AU - Oloo, Richard D.

AU - Ojango, Julie M.K.

AU - Ekine-Dzivenu, Chinyere C.

AU - Gebreyohanes, Gebregziabher

AU - Mrode, Raphael

AU - Mwai, Okeyo A.

AU - Chagunda, Mizeck G.G.

N1 - Funding Information: The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis. Funding Information: Perhaps the resources being allocated to improve resilience in a trait-by-trait manner could be channeled to the frequent collection of quality longitudinal data, such as milk yield, growth traits, and activity patterns. Improved data quality and quantity would not only help to assess resilience but also improve production performance. Projects such as African and Asian Dairy Genetic Gains (AADGG, https://portal.adgg.ilri.org/ ) program have come up with innovative digital recording and farmer education systems and solutions to help address these situations. AADGG program led by ILRI is funded by the Bill & Melinda Gates Foundation (BMGF) and is an integral part of the CGIAR Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition and Gender Inclusion (SAPLING). It is capturing and managing large volumes of performance data from both small- and large-scale farmers in eastern Africa and is pulling related weather data to derive indicative resilience traits. Future efforts aim to capture resilience related traits using various sensor-based technologies more directly. Over time, accumulated data can be used in genetic evaluations. Another ILRI-led BMGF funded project, EnviroCow, is developing phenotyping tools as well as genetic selection tools in SSA for novel animal traits such as methane emission intensity, feed requirements for maintenance and milk production, calf survival rate, and stability of milk. These projects aim to grant small-scale farmers in SSA access to more productive, feed-efficient, and resilient cattle genotypes, ultimately increasing their income levels. Funding Information: The authors acknowledge financial support from the Academy for International Agricultural Research (ACINAR) and African Asian Dairy Genetic Gains (AADGG) projects. ACINAR work is commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) and carried out by the Council for Tropical and Subtropical Agricultural Research (ATSAF e.V) on behalf of the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. AADGG project is led by the International Livestock Research Institute (ILRI) and funded by Bill and Melinda Gates Foundation (BMGF). This work was conducted as part of the CGIAR Research Initiative on Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING). CGIAR research is supported by contributors to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis. Publisher Copyright: Copyright © 2023 Oloo, Ojango, Ekine-Dzivenu, Gebreyohanes, Mrode, Mwai and Chagunda.

PY - 2023/9/22

Y1 - 2023/9/22

N2 - The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.

AB - The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.

KW - dairy cattle

KW - environmental disturbances

KW - productivity

KW - resilience

KW - sub-Saharan Africa

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U2 - 10.3389/fanim.2023.1254877

DO - 10.3389/fanim.2023.1254877

M3 - Review article

AN - SCOPUS:85173778115

SN - 2673-6225

VL - 4

JO - Frontiers in Animal Science

JF - Frontiers in Animal Science

M1 - 1254877

ER -

Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa

Abstract

Bibliographical note

Keywords

UN SDGs

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