In this (modest) study, we developed artificial neural network (ANN) models for predicting body weight using various independent (input) variables in eight-week old New Zealand white purebred and crossbred rabbits. From the whole data sets of similar age groups, 75 percent were used to train the neural network model and 25 percent were used to test the effectiveness of the model. Five predictor variables were used viz, breed, sex, heart girth, body length and height at wither as input variables and body weight was considered as dependent variable from the model. The ANN used was multilayer feed forward network with back propagation of error for efficient learning. Our ANN models (with R 2 = 0.68 at ten thousand iterations, and R 2 = 0.71 one million iterations) performed better than traditional multivariate linear regression (MLR) models (R 2 = 0.66) indicating that the ANN models were able to more accurately capture how the variations in input variables explained the variations in body weight. It is concluded that ANN models are more powerful than MLR models in predicting animals' body weight. Nonetheless, we recognize that fitting an ANN model requires more computation resources than fitting a tradition MLR model but the benefits of its accuracy outweigh any demerit from the associated computation overhead.
This study was conducted to characterise phenotypically helmeted Guinea fowls in three agro-ecologies in Nigeria using multivariate approach. Eighteen biometric characters, four morphological indices and eleven qualitative physical traits were investigated in a total of 569 adult birds (158 males and 411 females). Descriptive statistics, non-parametric Kruskal–Wallis H test followed by the Mann–Whitney U and Dunn-Bonferroni tests for post hoc, Multiple Correspondence Analysis (MCA), Univariate Analysis, Canonical Discriminant Analysis, Categorical Principal Component Analysis and Decision Trees were employed to discern the effects of agro-ecological zone and sex on the morphostructural parameters. Agro-ecology had significant effect (P<0.05; P<0.01) on all the colour traits. In general, the most frequently observed colour phenotype of Guinea fowl had pearl plumage colour (54.0%), pale red skin colour (94.2%), black shank colour (68.7%), brown eye colour (49.7%), white earlobe colour (54.8%) and brown helmet colour (72.6%). The frequencies of helmet shape and wattle size were significantly influenced (P<0.01) by agro-ecology and sex. Overall, birds from the Southern Guinea Savanna zone had significantly higher values (P<0.05) for most biometric traits compared to their Sudano-Sahelian and Tropical Rainforest counterparts. They were also more compact (120.00 vs. 110.00 vs. 107.69) but had lesser condition index (7.66 vs. 9.45 vs. 9.30) and lower long-leggedness (19.71 vs. 19.23 vs. 9.51) than their counterparts from the two other zones. Sexual dimorphism (P<0.05) was in favour of male birds especially those in Southern Guinea Savanna and Sudano-Sahelian zones. However, the MCA and discriminant analysis revealed considerable intermingling of the qualitative physical traits, biometric traits and body indices especially between the Sudano-Sahelian and Tropical Rainforest birds. In spite of the high level of genetic admixture, the Guinea fowl populations could to a relative extent be distinguished using wing length, body length and eye colour. Generally, the birds from the three zones appeared to be more homogeneous than heterogeneous in nature. However, further complementary work on genomics will guide future selection and breeding programs geared towards improving the productivity, survival and environmental adaptation of indigenous helmeted Guinea fowls in the tropics.
An eight week feeding trial was conducted to assess the replacement value of instant noodle waste meal (INW) on the performance characteristic, carcass and haematological parameters of broiler chickens. Ninety, one-day old Anak 2000 chicks were randomly allocated to three treatment groups namely, diet 1 (0% INW), diet 2 (50% INW) and diet 3 (100% INW) in a completely randomized design (CRD). Each treatment group had three replicates of ten chicks each. The inclusion of instant noodle in the diet did not have significant (P>0.05) effect on the performance of the broiler chickens at both starter and finisher phases. The inclusion of instant noodle waste had no significant (P>0.05) effect on the carcass traits and organ weights in broiler chickens. No significant (P>0.05) effect was observed for the packed cell volume, hematocrit, haemoglobin, leucocytes, and mean corpuscular haemoglobin concentration among the treatments. However, mean corpuscular volume and mean corpuscular haemoglobin were significantly (P< 0.05) influenced by the instant noodles inclusion, in the diets. Based on the present results INW could replace maize fraction of the diet partially or wholly without any adverse effect on performance, carcass and health status of broiler chickens.
The quest for renewable and sustainable energy generation is fast becoming widespread across Africa due to the understanding that there is a need to seek an alternative to fuels of fossil origin, which currently sustains the largest portion of the world's energy need. Research into the generation of renewable fuels had been on-going in continents like Europe, South America, Asia, and other developed countries bearing in mind the extinction nature of fossil fuels. Globally, attentions are being drawn to fuel generation from biomass and its derivatives such as lignin, triglycerides, cellulose, and hemicelluloses. The aim is to use such fuels for cooking and heating and in vehicles, jet engines, and other applications. Therefore, the integration of the African continent in the race for biofuel production is germane in the quest for survival and developments considering favorable factors like climate, soil, and land mass among other environmental-friendly resources in different African countries.
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