The Application of Digital-Genomic Tools to Improve Productivity and Profitability in Smallholder Dairy Systems in sub-Saharan Africa

Abstract The dairy sector contributes 30% and 44% of the livestock-related agricultural GDP in Tanzania and Kenya, respectively. Despite this significant contribution, it is predominantly comprised smallholder farmers with few cows providing vital support in terms of food security, household income and employment for millions of farmers. Research aimed at enhancing productivity and sustainability in these smallholder dairy systems is crucial for rural development, increasing farm incomes, creating employment and supporting women and youth. However, a major challenge is the absence of a routine performance data collection system. Previous efforts to address this limitation often relied on methods from well-established dairy systems in developed countries which frequently failed to adapt effectively. Advances in mobile technology have prompted attempts to investigate alternative cost-effective and practical data recording systems in the smallholder dairy farming with a major focus on information and communications technology (ICT). Successful implementation of digital tools for data collection and synthesis to generate management information as feedback to farmers using ICT-based extension tools has led to increased productivity and household income. Additionally, the use of genomic information allows for genetic evaluation with minimal pedigree information and supports the initiation of breed improvement programs for increased productivity. Information © The Authors 2024

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Publication Details

Journal
Animal Science Cases
Published
2024-11-27
DOI
https://doi.org/10.1079/animalsciencecases.2024.0009
Citations
1
Primary Topic
Agricultural Innovations and Practices
Type
article
Field-Weighted Citation Impact
1.34
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article

The Application of Digital-Genomic Tools to Improve Productivity and Profitability in Smallholder Dairy Systems in sub-Saharan Africa

Raphael Mrode, Okeyo Mwai, Gebregziabher Gebreyohanes, Julie M.K. Ojango et al.
1 citations
Animal Science Cases
Agricultural Innovations and Practices
1.34
article

The Application of Digital-Genomic Tools to Improve Productivity and Profitability in Smallholder Dairy Systems in sub-Saharan Africa

Raphael Mrode, Okeyo Mwai, Gebregziabher Gebreyohanes, Julie M.K. Ojango, Chinyere Ekine-Dzivenu
article en
1 citations

Abstract

Abstract The dairy sector contributes 30% and 44% of the livestock-related agricultural GDP in Tanzania and Kenya, respectively. Despite this significant contribution, it is predominantly comprised smallholder farmers with few cows providing vital support in terms of food security, household income and employment for millions of farmers. Research aimed at enhancing productivity and sustainability in these smallholder dairy systems is crucial for rural development, increasing farm incomes, creating employment and supporting women and youth. However, a major challenge is the absence of a routine performance data collection system. Previous efforts to address this limitation often relied on methods from well-established dairy systems in developed countries which frequently failed to adapt effectively. Advances in mobile technology have prompted attempts to investigate alternative cost-effective and practical data recording systems in the smallholder dairy farming with a major focus on information and communications technology (ICT). Successful implementation of digital tools for data collection and synthesis to generate management information as feedback to farmers using ICT-based extension tools has led to increased productivity and household income. Additionally, the use of genomic information allows for genetic evaluation with minimal pedigree information and supports the initiation of breed improvement programs for increased productivity. Information © The Authors 2024

Animal Science Cases
Scotland's Rural College (GB), International Livestock Research Institute (KE)
Openalex Percentile: Top 13%
Agricultural Innovations and Practices
1.34
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