Repository logo

Masters Degrees (Animal and Poultry Science)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6571

Browse

Browsing Masters Degrees (Animal and Poultry Science) by Author "Adebayo, Rasheed Adekunle."

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Effect of roughage quality and period of meal termination on rumen fill.
    (2015) Adebayo, Rasheed Adekunle.; Verla, Nsahlai Ignatius.
    This study was conducted to test the hypotheses that (1) reticulo-rumen fill remains the same with changes in nutritional quality of roughages and (2) irrespective of when meal termination occurs, reticulo-rumen fill in morning, afternoon or evening would be equal. Based on these hypotheses, while it sought to develop a generic model for predicting the 'fill' of the reticulo-rumen of goats, it specifically determined (1) the reticulo-rumen fill and digesta loads in other compartments of the GIT of goats upon termination of meal in the morning, afternoon and evening (2) the effect of period of meal termination on the size of reticulo-rumen fill and other digesta loads (3) the effect of diet quality on feed intake, water intake, weight changes, digestibility and feeding behaviour of goats. Complementary to this, it lends a hand using artificial neural network (ANN) for prediction of reticulo-rumen fill. The study used 18 goats which were in groups of six assigned to three dietary treatments comprising urea-treated hay (UTH), urea-sprayed hay (USH) and non-treated hay (NTH). Reticulo-rumen fill decreased with increased quality of roughages while treatments also affected digesta load in other distal compartments of the digestive tract. Also, reticulo-rumen fill measured in the evening was larger than those of morning and afternoon. By implication, period of measurement also influenced the size of the fill. Besides, diet quality enhanced dry matter intake but its effect on water intake was not significant. Also, dietary treatments have great impact on dry matter degradation, digestibility of nutrients and the feeding behaviour of goats. ANN explained 37% and 22% of the variation between the observed and predicted reticulo-rumen fill of goats, in its training and validation model, respectively. In conclusion, ANN could be used for prediction of reticulo-rumen fill of goats.