Ethiopia holds the largest livestock population in Africa, with roughly 66 million cattle, 46 million goats, 38 million sheep and 41 million chickens. Livestock contribute about 45 percent of agricultural gross domestic product and 13 to 16 percent of total GDP, supplying more than 3.8 billion liters of milk and one million tons of beef each year. Yet the sector is dominated by indigenous breeds: according to the national Central Statistical Agency, 98.24 percent of the country’s cattle are local breeds, with hybrids accounting for just 1.54 percent and exotic breeds a mere 0.22 percent. National milk output falls well short of demand, and the productivity gap between what Ethiopian cows could produce and what they actually produce is one of the defining challenges of the country’s agricultural development.

To understand why, the research team stratified each milk production system into adopters and non-adopters of modern dairy technologies, defining adopters as farmers using at least one improved practice such as artificial insemination or improved forage varieties. Respondents were selected by simple random sampling, with sample size determined using the Yamane formula at a 5 percent precision level. The final sample comprised 141 producers from the urban system, 43 from the peri-urban system and 40 from the rural system. Data were collected through face-to-face interviews using semi-structured questionnaires and analyzed with general linear models in SPSS, treating production system, adoption level and their interaction as fixed effects, with Tukey-adjusted pairwise comparisons and significance declared at p below 0.05.

The reproductive numbers tell a clear story. Crossbred cows reached first service at an average of 20.02 months of age, first calving at 34.30 months, and maintained a calving interval of 11.95 months. Local breed cows lagged far behind, with age at first service of 31.55 months, age at first calving of 45.14 months and a calving interval of 15.09 months. These differences were highly statistically significant across production systems. Reproductive performance matters enormously in dairy economics because every month of delay in first calving or every extension of the calving interval reduces the number of calves and the total liters of milk a cow delivers over her lifetime. The crossbred advantage observed here was shorter than some figures reported elsewhere in Ethiopia, which the authors attribute to differences in feeding and management inputs.

Production performance showed an even starker contrast. Crossbred cows yielded an average of 8.26, 8.31 and 7.05 liters per day in the urban, peri-urban and rural systems respectively, while local cows produced a national-average-level 1.65 liters per day overall. Over a full lactation, local cows gave 355, 294 and 260 liters in the three systems, whereas crossbreds produced 2,374, 2,402 and 2,015 liters. Most tellingly, adopters outperformed non-adopters across the board: average daily milk yield was 9.51 liters for crossbred adopters versus 6.24 liters for non-adopters, and 1.67 versus 1.41 liters for local breeds. Lactation length was 26.1 days longer in adopters’ crossbred cows and 23.4 days longer in their local cows, differences that were highly significant statistically.

Why does adoption matter so much? The study points to the compounding effect of better management. Adopters tend to practice improved feeding, health care, breeding selection, housing and hygiene simultaneously, and these practices reinforce one another. Feed and nutrition alone account for roughly 70 percent of total dairy production costs, and a balanced diet underpins both cow health and milk output. Farmers who treat sick animals promptly, house cows appropriately and breed them at the right time effectively convert the genetic potential of crossbred animals into actual liters of milk. The researchers note that this pattern matches earlier findings from Bangladesh and elsewhere showing higher milk yields among technology adopters, reinforcing the conclusion that the technologies themselves, when actually used, have a positive effect on productivity.

Yet the constraint rankings reveal why so many farmers never make that leap. In feeding, the dominant barriers were the high price and low supply of concentrate feed, shortages of green feed and fodder land, and financial limitations. In calf rearing, shortage of green feed, inadequate farmer knowledge and skill, and shortages of veterinary medicines ranked highest. For housing, land shortage, lack of roofing materials and low awareness topped the list. Breeding services were perhaps the most discouraging bottleneck of all: ill-equipped artificial insemination centers offering negligible service ranked first, followed by inefficient synchronization, inadequate AI knowledge, farmers’ ignorance of mating timing, unskilled technicians and a poor supply of quality bulls. Health constraints included no space to isolate sick animals, poor farmer knowledge of vaccines, weak veterinary infrastructure and poor extension services.

The socioeconomic picture compounds these technical problems. Many farmers lack capital to invest in animals, sheds and feed, credit facilities are scarce, interest rates are high, and training on new technologies is limited. The survey found that 68.3 percent of households were male-headed, that the average farmer was 46.2 years old with a family of 5.3 members, and that 30.3 percent of respondents were illiterate while 45.1 percent had only primary schooling. Education and farming experience both correlated with higher adoption rates, consistent with the idea that awareness and decision-making capacity drive uptake of new agricultural practices. Age showed a negative association with adoption in some cited studies, and family size was statistically larger among non-adopters in rural and urban systems, a pattern the authors suggest may reflect better family management awareness among adopters.

The authors’ conclusion is direct: extension services and the use of improved technologies should be intensified across all milk production systems, but especially in the rural system and among non-adopters, where the productivity gap is widest. Rural households in Genfel, dependent on subsistence farming of teff and sorghum, rely on dairying primarily for household nutrition rather than cash income and have minimal exposure to modern technologies due to lack of finance, knowledge and infrastructure. Bridging that gap, the study argues, would raise cow performance where it matters most for food security. The researchers also flag a critical caveat for future work: the benefits of higher productivity can only be realized if dairy farmers have reliable market access for their milk, a factor that remains to be interrogated in this context. For now, the message from Tigray is that the genetics and the technologies exist; the challenge is getting them into farmers’ hands.

Subject of Research: Dairy cattle productivity and adoption of improved dairy technologies among smallholder farmers in Tigray, northern Ethiopia

Article Title: Dairy cattle performance and technology adoption constraints in Tigray, Northern Ethiopia

Article References: Woldegebriel, D., Atsbha, T., Gebremariam, T., & Begashaw, T. (2025). Dairy cattle performance and technology adoption constraints in Tigray, Northern Ethiopia. BMC Agriculture, 1(1), Article 21. https://doi.org/10.1186/s44399-025-00022-w

Image Credits: AI Generated

DOI: 10.1186/s44399-025-00022-w

Keywords: dairy farming, Ethiopia, Tigray, crossbred cattle, technology adoption, milk yield, artificial insemination, smallholder farmers, reproductive performance, feed constraints, extension services, livestock