Login / Signup

Rural household chicken management and challenges in the Upper River Region of the Gambia.

Olawale Festus OlaniyanSamba Camara
Published in: Tropical animal health and production (2018)
Systematic assessment and documentation of extensive livestock production systems are necessary to design or review breeding programs, extension services, and policies. This study therefore examined management practices and challenges concerning village chicken production in the Upper River Region of the Gambia. The data gathered with 45-variable semi-structured questionnaires were analyzed based on the household head's education status and gender. Illiteracy level was high, and only 38% indicated that they attended certain schools. There was a significant relationship (p < 0.05) and phi coefficient of 0.35 between household heads' education status and record keeping. None of the examined management practices had a statistically significant relationship (p > 0.05) with household heads' gender. Children (10-14 years) were mostly responsible for providing care to the chickens. Foundation and replacement stocks were mainly acquired through purchase (78%). Many households (74%) indicated supplementary feeding of their flocks but only 34% provided separate houses apart from the household dwellings. Newcastle (68%) was the most common disease. Sick birds were recognized by restlessness (34%) and diarrhea (28%). External parasites were mainly controlled through local practices (52%) while the most common way to dispose dead birds was to throw them away (88%). Up to 90% indicated no formal training on disease management and access to extension agents was also low (20%). Control of chicken movement was occasionally done to protect birds from predators (60%) and then, to avoid contagious diseases (38%). Individual farmers and their associations need to be supported by stakeholders to access relevant information and uptake improved management techniques.
Keyphrases
  • healthcare
  • primary care
  • public health
  • mental health
  • quality improvement
  • electronic health record
  • south africa
  • magnetic resonance imaging
  • magnetic resonance
  • big data
  • deep learning
  • artificial intelligence