Monitoring of dairy farm management determinants and production performance using structural equation modelling in the Amhara region, Ethiopia

• Published in: Veterinary medicine and science Vol. 9; no. 4; pp. 1742 - 1756
• Main Authors: Birhan, Malede, Mekuriaw, Yeshambel, Tassew, Asaminew, Tegegne, Firew
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.07.2023; John Wiley and Sons Inc; Wiley
• Subjects: Animals; Cattle; Causality; Dairy cattle; Dairy farms; Dairying; Data collection; Efficiency; Ethiopia; Farm management; Farms; Female; Hygiene; Hypotheses; Latent Class Analysis; management determinants; Milk; Milk production; monitoring; Nutrition; Original; RUMINANTS; Statistical analysis; Structural equation modeling; structural equation modelling; Variables; Waste management; Ethiopia; dairying; structural equation modelling; monitoring; management determinants
• DOI: 10.1002/vms3.1140
• ISSN: 2053-1095

Models have been presented to evaluate the link between dairy farm production factors and their degree of association with production determinants. Studies have found causal relationships between production parameters (dairy farm facility, farm hygiene and waste management, feed and nutrition, reproduction performance, health and extension services, mode of transportation, education level and gross revenue) as well as farm efficiency parameters. Furthermore, structural equation modelling (SEM) allows for the estimation of parameters that are not directly quantifiable, known as latent variables. The research was designed to identify the dairy management determinants and evaluate farm production performance using an SEM approach in the selected areas of the Amhara region, Ethiopia. In-person survey using a semi-structured pre-tested questionnaire was employed in 2021 to collect primary data on 117 randomly selected commercial dairy producers keeping cross-breed Holstein Frisian cows in the Amhara region. SEM was used to study the complexity of influences on efficiency measures in milk production utilizing the combined data. The model result revealed that the relationship between construct reliabilities and farm facilities was significantly varied (p < 0.01). The model analysis showed that the level of education has also a positive and statistically significant correlation with the reproduction performance of the dairy farms, (ρ = 0.337) and the gross revenue of the farm showed as (p = 0.849). Farm gross revenue articulated a positive, strong statistically significant association with feed and nutrition values (ρ = 0.906), dairy farm facilities (ρ = 0.934), and hygiene and waste management (ρ = 0.921). Consequently, the predictors of dairy farm facility's feed and nutrition and hygiene and waste management explained 93.40%, 84.0%, 80.20%, and 88.50% of the variance. The proposed model was scientifically valid, and training and education have an effect on management practices, subsequently affecting the production performance of the dairy farms.