Small ruminants which are mainly sheep and goats play significant role in providing food and financial security for rural populations. However, the slaughter of breeding stock and pregnant animals serves as threat to the production of these animals because of foetal wastages. This study was conducted to determine the proportion of foetuses destroyed due to slaughter of pregnant sheep and goats in Jalingo abattoir, Taraba State, and the consequent economic implications. The abattoir was visited every day for a period of two months between August and September, 2017. The number of pregnant sheep and goats slaughtered, and foetuses wasted were recorded. Data obtained were analyzed using descriptive statistics. A total of 3,455 goats and 1554 sheep were slaughtered during the study period and 313 (22.1%) out of 1417 does, 341 (27.4%) out of 1,243 ewes were pregnant respectively. 368(23.1%) fetuses from pregnant does and 386(31.1%) foetuses from pregnant ewes were wasted. There was an estimated economic loss of ₦ 3,404,000.00 and ₦ 10,615,000.00 from goats and sheep respectively. These values hold at $9,455.55 and $29,486.11. The study revealed that foetal wastage was high in Jalingo abattoir with a consequent high economic loss in the livestock industry. Foetal waste also presents a threat on food security with resultant effects of decreased nutritional values of animal origin to humans. Proper ante mortem inspection especially, pregnancy diagnosis, should always be carried out prior to slaughter to curtail foetal wastages and most importantly, laws prohibiting the slaughter of pregnant sheep and goats be enforced, and policy efforts should concentrate on instituting routine veterinary checks at control posts and abattoirs.
The aim of this study was to compare three different models (Linear, cubic and quadratic) to find best model for predicting milk yield. Data originated from the monthly milk yields records of 251 Bunaji Holstein Friesian crossed and Holstein Friesian cows from 2010 to 2015. The daily milk yield data were regressed against time (day of lactation) for individual cow, using the procedure of SAS, (2002). The resulting polynomial regression coefficients (linear, quadratic and cubic) were then subjected to variance of analysis. All models provided an acceptable level of accuracy in predicting milk yield for Bunaji Holstein Friesian crossed and Holstein Friesian cows, but cubic model is observed to be the most suitable with (R 2) values of (0.659, 0.582, 0.810 and 0.621) followed by quadratic model (0.447, 0.516, 0.614 and 0.605) while linear model has the least R 2 values (0.02, 0.496, 0.548 and 0.309) in all the study farms.
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