The expansion of smallholder dairy farming in the developing countries is associated with an increase in manure production. However, the poor management of manure leads to an increase in methane gas emissions. This study was designed to evaluate methane gas emission from manure under different manure management practices in the smallholder dairy farms in Arusha City (urban) and Arusha District Council (peri-urban), Northern Tanzania. Data were collected through a semi- structured questionnaire, and the Intergovernmental Panel on Climate Change (IPCC) tier two methodology was used to estimate methane gas emissions from different manure management systems, including solid storage, daily spread, anaerobic digester, composting and slurry. Data on the dairy herds’ structure and the manure management system were analysed using Chi-square. The general linear model (GLM) of the statistical package of social sciences (SPSS) was used to estimate the effect of feed types and manure management systems on manure composition and methane gas emission from different management practices. The result revealed that there were significant differences in nutritional composition across feed types. There was a significant difference in dairy herd structure where urban farmers had more lactating cows, heifers and calves than those farmers in peri-urban areas. Furthermore, feed type significantly influenced manure composition, particularly volatile solids (VS) and total carbon (TC). Additionally, there were significant differences in manure composition across the manure management system in terms of volatile solids, pH, moisture, total organic matter, and total carbon. Methane gas emissions differed significantly across the manure management practices (P <0.05). The daily spread had less emission of 0.14 kg CH 4 head -1 year -1 which was attributed to aerobic conditions that limit methane emission, while higher emission from other management systems was due to anaerobic conditions that facilitate emissions. In conclusion, a significant variation in methane emissions was found among the manure management systems, with the highest emissions occurring in the slurry management system and the lowest in the daily spread system. The study recommends the anaerobic digestion system than over daily spread system because previous studies showed that anaerobic digester system not only mitigates methane gas emissions among smallholder dairy farmers but also optimizes the value of manure, while daily spread leads to water pollution due to runoff to surface water resources, hence causing waterborne diseases to both humans and animal.

Evidence of the impact of advanced technologies in genetics, nutrition and health management in the last seven decades has led to a twofold increase in the milk produced by a Holstein cow and a fourfold increase in the size of a broiler chicken in Western countries. Therefore, harnessing breakthrough technologies of genomic breeding, reproduction, management practices (health and environment), etc., with supporting infrastructure, funding and technical know-how is key to solving current problems and achieving rapid developments in the African livestock sector. This chapter presents an overview of some modern technologies that have played and continue to play significant roles in advancing sustainable genetic improvement in the livestock sector. Firstly, Section 20.2 presents the key issues impeding sustainable livestock improvement within Africa's complex livestock production systems. Then the phenomics technologies used for data capture to support genetic selection are presented in Section 20.3 followed by the breakthrough genomics technologies responsible for sustained genetic improvements in livestock traits (Section 20.4). The emerging technologies of genome editing (Section 20.4.3) and cellular agriculture (Section 20.4.4) are also presented. Breakthrough reproductive technologies that have been responsible for the spread of highmerit genetics are examined in Section 20.5. This chapter concludes with future perspectives (Section 20.6) on how the adoption and implementation of modern genomic technologies can accelerate desired improvements in the African livestock sector.

The previous chapter discussed the fundamental concepts and principles that underpin the definition of breeding goals and strategies. In this chapter, some of the peculiar aspects of breeding goals and strategies for the improvement of cattle and buffaloes in Africa, in addition to lessons drawn from past cattle improvement projects, are examined. The chapter is broadly presented in four sections. Section 16.1 deals with the concept of breeding goals in the context of the most dominant production system in Africa and examines evolving trends in breeding goals that incorporate health and welfare considerations. This is followed by Sect. 16.2 which presents the fundamental role of market situations in the design of breeding goals and the influence of some regional institutions and policies on breeding programmes. Breeding goals for beef and dairy cattle production and some lessons from the design of breeding goals from previous breeding programmes were then outlined. Section 16.3 considers breeding strategies aimed at promoting sustainable animal production systems in African diverse environments. It then delves into the different breeding strategies including breed substitution and cross-breeding, selection approaches for cattle improvement, nucleus or group breeding schemes, communitybased livestock breeding schemes and unplanned selection programmes. Section 16.3.2 is focused on emerging molecular and reproductive technologies in breeding strategies relevant to genetic improvement in various cattle and buffalo production systems in Africa. It deep dived into the different technologies as follows: molecular and genomic technologies for breeding strategies, reproductive technologies for African cattle and buffalo breeding strategies, nucleus breeding schemes for assisted reproduction in cattle and buffaloes, in vitro fertilization, somatic cell nuclear transfer and multiple ovulation and embryo transfer. The chapter concludes with some final remarks and future perspectives.

Smallholder dairy production systems in low-and middle-income countries are characterised by large phenotypic variance due to diverse environmental effects, farming practices, and crossbreeding. Furthermore, small herds, low genetic connectedness, and limited data recording challenge accurate separation of environmental and genetic effect in such settings, limiting genetic improvement. Here, we evaluated the impact of modelling spatial variation between herds to address these challenges and improve the accuracy of genomic evaluation for Tanzanian smallholder dairy cattle. We analysed 19,375 test-day milk yield records of 1894 dairy cows from 1386 herds across four distinct geographical regions in Tanzania. The cows had 664,822 SNP marker genotypes after quality control and were highly admixed. We fitted a series of GBLUP models to evaluate the impact of modelling the herd effect and the spatial effect on. The herd effect was fitted as an independent random effect, while the spatial effect was fitted as a random effect with Euclidean distance-based Matérn covariance function. The models were compared based on: model fit; estimates of variance components and breeding values; correlations between the estimated contribution of breeding values, herd effect, and spatial effect to phenotype values; and the accuracy of phenotype prediction in cross-validation and forward validation. The results showed large differences in milk yield between and within regions, as well as significant variation due to the spatial effect, which were not fully captured by modelling the herd effect. The results also strongly indicate that a model with just the herd effect underestimated breeding values of animals in less favourable environments and overestimated breeding values of animals in more favourable environments. This study demonstrated the challenge of achieving accurate genomic evaluation in smallholder settings. By leveraging spatial modelling we maximised the use of available data and improved the separation of genetic and environmental effects. Further work is required to improve smallholder genetic evaluations by understanding environmental and genetic processes that drive the large phenotypic variance in African smallholder setting.

This chapter discusses the prospects of the utilization of modern technologies for cattle improvement in African livestock production systems. The first section gives a general overview of modern technologies and their application for improving cattle in the African continent. Section 22.1 discusses the general overview of how different molecular information improves the development of large ruminants in Africa. The section outlines some practical case studies where molecular information has been used for the detection of genomic variations in African cattle and buffalo, the use of genetic markers to assign individuals to breeds, and parentage identification. It concludes with the use of molecular information in gene editing and transgenic animals in animal production. In Sect. 22.3, the prospect for the application of modern technology in developing livestock feeds and feeding is discussed with practical examples. The subsequent sections discuss the application of modern technologies in improving livestock housing and husbandry systems (Sect. 22.4). Other modern technological advancements, including the development of diagnostic tests for detecting genetic defects using single nucleotide polymorphisms (SNPs), using genomic markers for selective breeding, and genome editing to improve productivity and control of deleterious alleles in livestock, are also discussed. The chapter also reviews the application of modern technologies to improve livestock health. In each case, practical examples are outlined as case studies where the technologies are applied in the African setting. The chapter concludes by looking at challenges and constraints in the implementation of modern technologies in cattle and buffalo production in Africa. Potential solutions are suggested.

Enteric methane (CH4) emissions from dairy cattle are a major contributor to greenhouse gas footprint in the livestock sector. This study applied Intergovernmental Panel on Climate Change (IPCC) Tier 2 equations to estimate enteric methane emissions in Italian Holstein, Brown Swiss, and Red Pied herds using either default dietary assumptions or farm-specific diet information. By combining individual Dairy Herd Improvement (DHI) test-day records with primary ration data, the analysis examined how improved input data resolution affected methane estimates across breeds and animal categories under commercial farming conditions. Data were collected from 138 Italian dairy farms participating in the national Dairy Herd Improvement (DHI) program between January 2021 and December 2022, with farm rations recorded concurrently during DHI test days by trained technicians using a standardized questionnaire. Breed, emission estimation approach, and their interaction were analyzed using aligned rank transform (ART) procedures with permutation-based P-values. Holstein cows exhibited greater daily methane production (MeP = 443.60 ± 5.68 g/d; P < 0.001), whereas Red Pied herds showed the greatest methane intensity (MeI = 29.99 ± 0.70 g/kg fat- and protein-corrected milk; P < 0.001). Breed and CH4 estimation approaches affected emission estimates, however, their interaction was not significant, indicating consistent breed rankings across methods. Post hoc analyses revealed no significant differences in methane indices among breeds. Incorporation of farm-specific ration data impacted emission estimates, particularly for nonproductive groups such as dry cows and heifers, highlighting the importance of context-specific dietary inputs for improving the accuracy and representativeness of CH4 inventories.

The objectives of this study were to determine the genetic variation and phylogenetic relationships of Holstein Friesian, Jersey and Ayrshire crossbred dairy cows and Zebu cattle reared in the humid coastal region of Tanzania based on the HSF1 and HSPA6 genes responsible for heat tolerance. The animals used in the study were obtained from Tanzania Livestock Research Institute (TALIRI) - Tanga and Livestock Training Agency (LITA) Buhuri dairy farms located in Tanga districts and Mruazi Heifer Breeding Unit dairy farm located in Korogwe district. Sixty - five blood samples were collected from Holstein Friesian (23), Ayrshire (15), Jersey (12) crosses, and pure Zebu (15). For each animal, 10 ml of blood was collected by Jugular vein puncture. Total genomic DNA was extracted and amplification performed following manufacturer’s instructions. The polymorphic sites, haplotype diversity (Hd), nucleotide diversity (π), expected heterozygosity (He) and neutrality (FU’s FS and Tajima’s D) tests were calculated. The He was 0.23 ± 0.13, 0.22 ± 0.14, 0.16 ± 0.13, and 0.00 ± 0.00 in Zebu, Holstein Friesian crosses, Jersey crosses and Ayrshire crosses, respectively. The zebu had the highest Hd (0.47 ± 0.08) followed by Holstein Friesian (0.34 ± 0.14), and Jersey (0.33 ± 0.21), while the lowest Hd was observed in Ayrshire crosses (0.00 ± 0.00). The average π was 0.23 ± 0.14, 0.22 ± 0.13, 0.16 ± 0.11, and 0.00 ± 0.00 for Zebu, Holstein Friesian crosses, Jersey crosses and Ayrshire crosses, respectively. Dairy cattle breeds were grouped in one and three clusters based on HSPA6 and HSF1 genes, respectively. There is low genetic diversity and no significant genetic differentiation among the four dairy cattle breeds, an indication of a single panmictic population.

This chapter presents an overview of the concept and functions of breeding goals in livestock improvement programs. The first section (Sect. 15.1 Breeding Goals in Livestock Improvement Programs) provides an overview of the definition and functions of breeding goals, critical elements required for their development, and variations in their adoption across different species. The section also outlines global and continental frameworks and intervention initiatives aimed to facilitate the wide adoption of breeding goals for the diverse species and breeds found in Africa. The second section (Sect. 15.2 Breeding Strategies and Livestock Improvement) presents the concept and options related to breeding strategies to realize the defined breeding goals. The section highlights essential elements for successful breeding strategies to increase productivity and incomes including livestock performance data, farmer participation, appropriate dissemination of outcomes, and continuous evaluation. Examples of breeding strategies for cattle and small ruminants are presented to highlight the integration of some of the essential elements of breeding strategies in the African context. The last section of this chapter (Sect. 15.3 Future Perspective) stresses the futuristic importance of breeding goals and strategies for livestock production in line with changing environments and global demands for products.

Multi-country initiatives have facilitated the development and adoption of technologies in developed nations, but such cooperations are less evident in Africa. National breed-specific genetic evaluations have been the most commonly practiced globally; however, there has been a growing interest and opportunities have arisen for across-country collaborations, or international consortiums combining data into large-scale multi-country genetic evaluations to achieve better genetic gains. Despite the need to establish multi-country genetic evaluation schemes for livestock production suitable for the African continent, few initiatives have been put in place to achieve this. This chapter draws attention to multi-country initiatives and benefits for performance recording as well as success stories in Africa (Sect. 29.2), the benefits of data sharing (Sect. 29.3), the role and importance of core facilities, especially those associated with the technologies of genomics, proteomics, metabolomics, metagenomics, and statistical/bioinformatics management of data (Sect. 29.4), germplasm centers for the storage of genetic materials or seed stock (Sect. 29.5), and the important place and prospect of multi-country genetic evaluations and practical application in Africa (Sects. 29.6 and 29.7). Such initiatives may provide an opportunity for genetic improvement of indigenous livestock populations and the possibility to open up new markets for African germplasm as well as inter-country germplasm trade within the continent. This would have a positive impact on the continent's livestock economy.

The present study aimed to explore runs of homozygosity (ROH), Heterozygosity Enriched Regions (HER) using the sliding window approach in both PLINK and detectRUNS, as well as the consecutive SNP approach in detectRUNS and their association with important economic traits. Genomic inbreeding coefficient based on ROH and heterosis coefficient based on HER were also estimated among crossbred (n = 81) by using GGP_HDv3_C genotyping assay. Total ROH varied from around 600 in the sliding window approach and almost double in the Consecutive SNP approach of detectRUNS. Similarly, the HER are 756 in the sliding window and 771 in the Consecutive SNP method. The mean inbreeding coefficient range varied in different approaches, i.e., 0.016–0.022 is observed based on ROH (Froh), and the heterosis coefficient based on HER (Frohet) is 0.0019. Top ROH and HER regions contain important genes related to dairy (EHHADH, CACNA1C, MICALL1, EIF3L, GTPBP1, SYNGR1, ATF4, GRAP2, FAM83F, ACO2), immunity (LIPH, TMEM41A, PEX26, CDC42EPI, CXXC5, PSD2, PURA, CYSTM1, RNF14), growth and carcass (MAGEF1, TGS1, LYN, CHCHD7, FAM110B, SDCBP, SH3BP1, GGA1, TRIOBP, PICK1, MAFF, TOMM22, MGAT3, TNRC6B, ADSL, EP300, SMDT1, MATR3) traits. These findings may provide valuable insights into the understanding of genome-wide homozygosity and heterozygosity patterns and genetic architecture of the Pakistani crossbred cattle.

Change in climate over the past years and its impact on the environment have necessitated the inclusion of resilience traits in the breeding objectives of dairy cattle. However, the relationship between resilience and other traits of economic importance in dairy production is currently not well known. This study examined the genetic parameters and relationships among resilience, fertility and milk production traits in dairy cattle in Kenya. Indicators of general resilience and heat tolerance were defined from the first parity test-day milk yield records. Indicators of general resilience included variance of actual deviations (LnVar1), variance of standardised deviations (LnVar2), lag-1 autocorrelation (rauto) and skewness (Skew) of standardised deviations in milk yield. Heat tolerance indicators at temperature-humidity index 80 included the slope of the reaction norm (Slope), absolute slope of the reaction norm (Absolute), and the intercept of the reaction norm model (Intercept). Cows with > 50% taurine genes had lower age at first calving (AFC), longer calving intervals (CI) and higher test-day milk yield (MY). The heritability estimates of AFC, CI and MY were 0.17 ± 0.033, 0.06 ± 0.012 and 0.35 ± 0.021, respectively. The repeatability estimates of CI and MY were 0.06 ± 0.012 and 0.47 ± 0.009, respectively. The low heritability and non-significant permanent environmental variance of CI showed that CI is heavily influenced by external factors, such as management practices. AFC was negatively genetically correlated with both CI (-0.88 ± 0.077) and MY (-0.53 ± 0.059) showing that animals that attain sexual maturity earlier exhibit longer CI and higher milk production. A positive genetic correlation (0.62 ± 0.077) between CI and MY shows that high-yielding cows face challenges in maintaining shorter calving intervals. Heritability estimates of nearly all resilience indicators were significant and ranged from 0.05 to 0.34. Heat tolerance indicators showed low to non-significant genetic correlations with general resilience indicators, suggesting that different genetic factors are involved in responses to different types of disturbances. There was a generally positive genetic correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except LnVar1 and LnVar2, revealed an antagonistic genetic relationship between resilience and milk production. The findings present an opportunity for including resilience in the development and application of selection indices in dairy cattle, especially for the tropics.

Sheep production in Arid and Semi-Arid lands face immense heat stress with the changing climate. This study assessed the effect of heat stress on growth and developed resilience phenotypes of sheep raised in a semi-arid environment. Heat stress was measured by Temperature-Humidity Index (THI). Live body weight records of 4078 animals, belonging to pure Red Maasai (RRRR), pure Dorper (DDDD), and their crosses: 50%Dorper-50% RedMaasai (DDRR) and 75%Dorper-25%Red Maasai (DDDR) collected between 2003 and 2024 were analysed. Random regression models fitted with reaction norm functions were used to develop two resilience phenotypes: Response and Stability, at THI 70 and THI 85 representing varying heat stress. Animal mixed models were used to estimate genetic parameters. The THI breakpoints were 78.75, 78.71, 78.42 and 77.93 with a decline rate of 0.06 Kgs, 0.09 Kgs, 0.05 Kgs and 0.15 in live weight gain per unit change in THI for RRRR, DDDD, DDRR and DDDR respectively. The breed, sex, type of birth, dams' parity and season of birth significantly (P<0.05) affected the stability of growth at low and high heat stress. The heritability estimates of resilience traits ranged from 0.12 to 0.16. Genetic correlations of resilience phenotypes at THI 85 with pre-weaning live weight gain were antagonistic and significant (P<0.05). With the changing climate, resilience phenotypes should be included in selection programs for sheep in the Arid and Semi-Arid lands for robust growth.

Reproduction traits are important factors determining the efficiency of any sheep production system. This study evaluates the age at first lambing (AFL), lambing interval (LI), litter weight at birth (LBWT), litter weight at weaning (LWWT), birth weight of ewe (EBWT) and weaning weight of ewes (EWWT) in a crossbreeding program between the Red Maasai (RRRR) and Dorper sheep and their crosses, 75% Dorper and 50% Dorper (DDRR) breeds. All the traits significantly (P < 0.05) differed across breeds and season of birth of the ewe. LBWT and LWWT were significantly affected by the sex of the lamb, type of birth of the lamb and parity in which the lambs were born in. AFL and LI had very high environmental variances. Overall heritability estimates of AFL (0.09 +/- 0.04) and LI (0.00 +/- 0.01) were not significant from zero while the heritability estimates for EBWT (0.38 +/- 0.04), EWWT (0.23 +/- 0.03), LBWT (0.19 +/- 0.03) and LWWT (0.0 9 +/- 0.02) were significant (P < 0.05). The RRRR had the highest genetic gain for all traits while the DDRR had a higher genetic gain among the crosses. LI had negative genetic correlations with LBWT ( 0.53 +/- 0.08) and LWWT ( 0.28 +/- 19.59) while AFL had positive genetic correlations with LBWT (0.2 7 +/- 0.46) and LWWT (0.31 +/- 0.34). The phenotypic trends for AFL and LWWT showed a negative and positive association, respectively, with the rainfall index over the years. With proper farm management, improved reproduction performance of ewes is possible by indirect selection using LBWT and LWWT for the Red Maasai, Dorper and their crosses within the semi-arid lands. (c) 2024 The Author(s). Published by Elsevier B.V. on behalf of The Animal Consortium. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract Heat stress (HS) causes a decline in the productivity of livestock through reduced dry matter intake, decreased reproduction rate and adverse effects on the physiological state (e.g., respiration rate, rectal temperature, heart rates, pulse rates, panting score, sweating rates, and drooling score). Indigenous breeds have higher tolerance to HS than their exotic counterparts. However, indigenous breeds have low productivity. Therefore, genetically improving the heat tolerance of high-producing livestock breeds in Africa can enhance animal welfare and reduce production losses during HS conditions. Identifying and measuring appropriate phenotypic indicators of heat tolerance and understanding the genetic basis are very important steps for breeding heat-tolerant animals that are highly adaptable to the climatic conditions in Africa. This case study highlights recent advances on heat tolerance in livestock reared in tropical countries with a focus on Africa, the challenges faced by African countries in estimating the genetic value of heat-tolerant livestock and indicate the future directions for heat tolerance studies in Africa. Moreover, the case study reports genes that have been shown to influence heat tolerance in livestock and discusses the possibility of using them in genomic selection programs. Information © The Authors 2025

Transforming Africa's agricultural production and food systems is an imperative to achieve the United Nations Sustainable Development Goals and deliver on the Africa Union's 2063 vision, 'the Africa we want'. Transforming livestock systems through genetic improvement will sustainably increase productivity and proffer an inclusive socioeconomic development of farming communities. The African Animal Breeding Network (AABNet) is a platform of highly knowledgeable geneticists, animal breeders and professionals willing to provide information, training, advice and support across the continent. It will leverage available human resources among its members, facilitate partnerships and investment and develop infrastructure for innovative livestock genetic improvement in Africa.

Mastitis, an inflammation of the bovine mammary gland, reduces dairy productivity and poses significant health risks to Ethiopian dairy cattle. This study aimed to identify genomic regions associated with milk somatic cell score (SCS) and estimate its genetic parameters. The dataset included 1647 phenotypic cows, 6964 genotyped animals, and 39,976 single nucleotide polymorphism (SNP) markers. A single-step genome-wide association study (ssGWAS) was conducted, accounting for fixed effects of parity, genomic breed composition, altitude, and lactation stage, and random effects of herd-year-calving-season and permanent environment. Genetic variance using 20 adjacent SNPs sliding windows explaining ≥1% of the total genetic variance were used for candidate genes and quantitative trait loci (QTL) identifications. The estimated heritability of SCS was 0.11 ± 0.06. Genomic regions on BTA 15, 19, and 26 were identified associated with SCS, encompassing 116 genes, including MPP7, MPP8, MMP13, BIRC2, BIRC3, BTRC, SRSF1, and MPO, which are involved in immunity, inflammation, apoptosis, antimicrobial defense, and tissue remodeling. Gene enrichment analysis revealed that the genes are involved collagen catabolic process and IL-17 signaling pathway. These findings provide insights into genomic regions that could be targeted in genomic selection to improve mastitis resistance in Ethiopian dairy cattle.

Identifying the genetic determinants of host defence against infectious pathogens is central to enhancing disease resilience and therapeutic efficacy in livestock. Here, we investigated immune response heritability to important infectious diseases affecting smallholder dairy cattle using variance component analysis. We also conducted genome-wide association studies (GWAS) to identify genetic variants that may help understand the underlying biology of these health traits. By assessing 668,911 single-nucleotide polymorphisms (SNPs) genotyped in 2,045 crossbred cattle sampled from six regions of Tanzania, we identified high levels of interregional admixture and European introgression, which may increase infectious disease susceptibility relative to indigenous breeds. Heritability estimates were low to moderate, ranging from 0.03 (SE ± 0.06) to 0.44 (SE ± 0.07), depending on the health trait. GWAS results revealed several loci associated with seropositivity to the viral diseases Rift Valley fever and bovine viral diarrhoea, the protozoan parasites Neospora caninum and Toxoplasma gondii, and the bacterial pathogens Brucella sp, Leptospira hardjo, and Coxiella burnetii. The identified quantitative trait loci mapped to genes involved in immune defence, tumour suppression, neurological processes, and cell exocytosis. We propose that our results provide a basis for future understanding of the cellular pathways contributing to general and taxon-specific infection responses, and for advancing selective breeding and therapeutic target design.

A survey study was conducted to assess the influence of altitude and socioeconomic characteristics of smallholder dairy farmers in adaptation to feeding practices (FPs) and their ultimate effect on the nutrition of dairy cattle and milk production. One hundred and twenty dairy farmers from highland (60) and lowland (60) zones of Hai district, Tanzania were interviewed. Feed samples were collected for evaluation of proximate and Van Soest composition, in vitro dry matter (INVDMD) and organic matter (INVOMD) digestibility for three FPs, namely zero grazing (FP1), grazing with supplementation (FP2) and extensive grazing (FP3). Data on milk yield was obtained from the farmer record books and database of African Asian Dairy Genetic Gain program. Most respondents from both highland (88%) and lowland (53%) zones were practicing zero grazing (FP1) than grazing plus supplementation. High level of education, farming experience of >10 years, and dairying plus other sources of livelihood showed positive likelihood of influencing adaptation of zero grazing practice (FP1). Forage diets offered to cows under FP1 had lower mean values of crude protein (6.9%, CP) and metabolisable energy (5.01 MJ ME/kgDM) compared to other practices. Concentrate diets used in FP1 practice had higher CP (13.7%) compared to those in FP2 (10.9%). There was higher average milk yield from cows under FP1 in the highland (11.6 kg) compared to their counterparts. Cows under FP1 on the lowland had similar (P>0.05) average milk yield (8.7 kg) to those under FP2 in the highland zone (9.47 kg). Cows under FP3 in the lowland produced the lowest (P<0.05) milk yield of 4.61 kg. The study concluded that differences in socioeconomic characteristics of farmers and altitude zones have influence on the adaptation and domination of a specific feeding practice, which ultimately determines the level of performance of the dairy cattle. It is recommended that more studies are required to assess the influence of feeding and other management practices of dairy cows on the environmental effects.