A time-series assessment of the productive and reproductive performance of Balochi sheep.

This study was carried out to find the environmental factors which have a significant effect on the productive and reproductive characteristics of the Balochi sheep. The study used data from 729 ewes and 71 rams for a period of 13 years (2003 to 2016) at the Sheep Research Center, Yet Abad, Balochistan, Pakistan. The productive characteristics considered for current study were weight, birth weight (BW), 90 days weight (3 MW), 180 days weight (6 MW), 270 days weight (9 MW), 365 days (12 MW), and 2 years weight (24 MW). Reproductive characteristics measured were ewe age at first service (AFS), service period (SP) of ewe, age at 1st lambing (AFL) of ewe, lambing interval (LI), and sex ratio. Restricted maximum likelihood (REML) assessments of different characteristics were analyzed for the Balochi sheep on the basis of location, birth year (YOB), season of birth (SOB), type of birth (TOB), and sex of lamb. The average means ± SE for BW, WW, 6 MW, 9 MW, 12 MW, and 24 MW, were 3.28 ± 0.83, 17.20 ± 2.04, 21.94 ± 1.60, 26.20 ± 2.87, 30.21 ± 3.58, and 37.11 ± 2.84 for ram and 2.56 ± 0.53, 15.69 ± 1.45, 19.57 ± 1.77, 24.07 ± 2.70, 27.46 ± 2.09, and 34.61 ± 2.32 for ewes respectively. The results of reproductive performance of the Balochi sheep age of ewe at the time of breeding, age at first service (AFS), service period (SP), age at first lambing (AFL), and lambing interval (LI) were 1078 ± 2.2, 579.61 ± 0.6, 206.25 ± 0.2, 731.67 ± 0.3, and 256.60 ± 0.3 days respectively. The twining and lambing rates were 10.12% and 86.78%, while the sex proportion for ram and ewes was 50.12:49.37. Area, sex, and TOB had a significant (p < 0.05) effect on weight while TOB (twinning rate) was higher in Balochi sheep. These conditions affected the productive and reproductive performance of the Balochi sheep. At Sheep Research Center, Yet Abad, Balochistan, Pakistan, performed fundamentally better in all qualities such as weight gain and reproductive performance. Supplements were given with feed to get maximum profit from the sheep of Yet Abad farm. The birth weight of males was higher than that of females and single conceived Balochi sheep were heavier than that of twins. Thus, it was concluded that the Balochi sheep can be improved with better management practices, feeding, and disease control.

Use of multivariate adaptive regression splines for prediction of body weight from body measurements in Marecha (Camelus dromedaries) camels in Pakistan.

The aim of the present work was to predict live body weight by means of some body measurements, i.e., SH, CG, and BG in indigenous Marecha camel breed. For this purpose, multivariate adaptive regression splines (MARS) algorithm was used at proportions of various training and test sets, i.e., 65:35, 70:30, and 80:20 in V-tenfold cross-validation. In prediction of live body weight of the Marecha camels (160 female and 145 male animals) in the MARS predictive models, pairs of sex-SH (model 1), sex-CG (model 2), and sex-BG (model 3) as potential predictors. The best MARS model in LW prediction was obtained using sex and SH independent variables for 80:20 training and test set. Sex was determined to be an important source of variation in SH, CG, and BG as a result of sexual dimorphism in camels (P < 0.01). MARS results indicated that SH could be used as an indirect selection criterion to obtain elite camel herds on LW of Marecha camels. If genetically confirmed, the Marecha camels whose SH is taller than 165.1 cm could be selected for providing genetic progress in LW. In conclusion, use of MARS algorithm may be worthy of consideration for better identification of camel breed standards and selection of superior Marecha camels for meat productivity in Pakistan.

Prediction of live body weight based on body measurements in Thalli sheep under tropical conditions of Pakistan using cart and mars.

Thalli sheep is a significant breed reared under tropical region of Punjab province of Pakistan. The present study was conducted to predict live body weight (LBW) by means of from some body measurements, i.e., chest girth (CG), belly girth (BG), rump height (RH), withers height (WH), neck girth (NG), and body length (BL) taken from 155 Thalli indigenous sheep of Pakistan. Age factor is determined to be a significant source of variation for BL, BG, CG, BG, WH, and NG (p < 0.05). LBW is correlated significantly with BL (0.850), CG (0.825), BG (0.849), RH (0.579), WH (0.547), and NG (0.7760), respectively (p < 0.01). For LBW prediction, CART and MARS data mining algorithms were comparatively used based on ten cross-validation method. Among 185 candidate MARS models with 1-5 degrees of interaction and 2-38 terms, the MARS model with 7 terms and no interaction effect in R software was the best model for LBW prediction on the basis of the smallest cross-validated RMSE value. Also, the optimal CART tree structure was obtained with 9 terminal nodes for the smallest cross-validated RMSE value. MARS algorithm outperformed CART in LBW prediction and explained 90.3 (%) of variability in LBW of Thalli sheep. Results of the optimal CART structure reflected that Thalli sheep with BL > 75 cm, RH > 83 cm, and NG > 55 cm has the heaviest LBW of 72 kg. The optimal MARS model displays that the heaviest LBW can be produced by Thalli sheep with BL > 71.12 cm, BG > 106.68 cm, WH > 76.2 cm, NG > 50.8 cm in 5th age group. In conclusion, it coud be recommended that MARS predictive modeling may enable animal breeders to obtain elite Thalli sheep population and to detect body measurement positively influencing LBW as indirect selection criteria for not only describing breed characterization and developing flock management standards, but also ensuring sustainable meat production and rural development in Pakistan.

Use of MARS algorithm for predicting mature weight of different camel (Camelus dromedarius) breeds reared in Pakistan and morphological characterization via cluster analysis.

Mature weight is a significant trait that can be influenced by age, sex, breed, production system, and climate conditions in camels. In camel breeding, it is essential to describe breed standards of the studied camel breeds as part of morphological characterization and to determine morphological traits positively influencing mature weight within the scope of indirect selection criteria. This study was to find the best one among candidate models in prediction of mature weight from several morphological traits measured for eight camel breeds (Bravhi, Kachi, Kharani, Kohi, Lassi, Makrani, Pishin, and Rodbari) raised under Pakistan conditions. The morphological measurements taken from the camels in the study were birth weight (BW), weaning weight (WW), mature weight (MW), age of ridding (ARD), face length (FL), face width (FW), head length (HL), head width (HW), ear length (EL), ear width (EW), neck length (NL), neck width (NW), hump length (HL), hump width (HuW), heart girth (HG), withers height (WH), body length (BL), fore leg length (FLL), and hind leg length (HLL), respectively. In the prediction of mature body weight as a response variable, the optimal MARS predictive model with 15 terms selected by train function of the caret package produced very high predictive performance without encountering overfitting problem. Goodness of fit criteria were estimated to measure predictive quality of the MARS model using ehaGoF package available in R environment. Morphological characterization of the camel breeds was performed with hierarchical cluster analysis (HCA) on the basis of Euclidean distance-Single linkage. At the first step of hierarchical cluster analysis, the similarity level of Bravhi and Kachi camel breeds was the highest with 85.3569 (%). At the second step, Makrani joined to new cluster of Bravhi and Kachi camels found at the first step, and the similarity level of the new cluster comprising Bravhi, Kachi, and Makrani breeds was found as 84.5562 (%). MW was significantly correlated with BW (0.677), WW (0.536), HL (0.524), HuW (0.529), and ARD (0.375) at P < 0.01, and there was the highest correlation of 0.994 between HHL and FLL (P < 0.01). As a result, it could be suggested that results of MARS modeling may help camel breeders to reproduce the elite camel populations and to describe characteristics associated positively with MW within the scope of indirect selection criteria.

Pancytopenia in two national ethnic groups of Baluchistan.

BACKGROUND: Pancytopenia is a recognisable haematological problem with common categorises diagnosis but best possible diagnostic approach is still to be defined. OBJECTIVE: The aim of this study was to determine the frequent causes and clinical presentation of pancytopenia in relation to age and sex in different ethnic groups of two national (Pakistani and Afghan) living in Baluchistan province. METHODS: This is a cross sectional descriptive type of study was carried out on patients (n = 180) for two years (July 2009-June 2011). Cases were successively registered in 2 provincial government hospital and 2 private clinics in Quetta with diagnosis of pancytopenia. RESULTS: The most frequent causes of pancytopenia in both national ethnic groups were malaria (29.44%) fallowed by tuberculosis (17.22%), leukaemia (16.67%), aplastic anaemia (13.33%), hepatitis (12.22%), other diseases (7.22%) and iron deficiency anaemia (3.89%). Overall, 63.89% male subjects were observed pancytopenia as compared to 36.11% female patients. The results also showed that patients with age > 41 years were highly (50%) affected by pancytopenia followed by 21-40 years (30.66%) and < 20 years (19.44%). Moreover, leukaemia cases were observed significantly higher in Afghan subjects (> 41 years). The most common symptom of patients was (71.11%) fever followed by Pallor (42.22%), fatigue (38.33%), weight loss (26.11%) and dizziness (25.56%). Leukaemia and aplastic anaemia were found to be the most serious causes of pancytopenia in Afghan ethnic group. CONCLUSIONS: Malaria, tuberculosis, aplastic anaemia, and leukaemia were the leading causes of pancytopenia in Pakistani and Afghan ethnic groups. Severe pancytopenia has significant relation with the clinical conclusion and can be used as a prognostic marker.