Growth Performance of Arsi, Borana, Harar and HF-Crossbred Bulls Finished under Similar Feeding Condition

The study was conducted to evaluate the fattening performance of Arsi, Borana, Harar and Holstein Friesian crossbred bulls finished under a similar feeding condition at the beef farm in Haramaya University. The average daily weight gain of the four breeds ranges from 0.49 to 0.71 kg. Feed conversion efficiency also ranges from 0.11 - 0.15. Simple linear regression models were used to explore the relationship between live body weight change and change in body condition score as well as seven linear body measurements for all age groups. An average change for a unite of body condition score was equivalent to 20.3, 20.61, 22.42 and 27.78 kg for Borana, Arsi, Harar and Holstein Friesian crossbred bulls respectively. Body condition score was significantly influenced by breeds. There was a significant breed by age interaction effect on the initial body condition score of the four breeds. There was a significant and positive strong association between change in body weight and body condition score. There was a significant and strong correlation between change in body weight and change in Total topline, neck length, heart girth, flank circumference and rump length having correlation coefficients ranges from 0.57 to 0.97. A higher net profit of 7380.47 ETB per head was recorded by Borana bulls followed by Harar bulls, Arsi and Holstein Friesian crossbred with net profit of 5406.86, 5193.29 and 3384.98 ETB per head respectively. Borana bulls are more superior in weight gain and net profit. Bodyweight change could be predicted based on body condition score change during the fattening period.

Automatic body condition scoring system for dairy cows based on depth-image analysis

Body condition score(BCS)is an important management tool in the modern dairy industry,and one of the basic techniques for animal welfare and precision dairy farming.The objective of this study was to use a vision system to evaluate the fat cover on the back of cows and to automatically determine BCS.A 3D camera was used to capture the depth images of the back of cows twice a day as each cow passed beneath the camera.Through background subtraction,the back area of the cow was extracted from the depth image.The thurl,sacral ligament,hook bone,and pin bone were located via depth image analysis and evaluated by calculating their visibility and curvature,and those four anatomical features were used to measure fatness.A dataset containing 4820 depth images of cows with 7 BCS levels was built,among which 952 images were used as training data.Taking four anatomical features as input and BCS as output,decision tree learning,linear regression,and BP network were calibrated on the training dataset and tested on the entire dataset.On average,the BP network model scored each cow within 0.25 BCS points compared to their manual scores during the study period.The measured values of visibility and curvature used in this study have strong correlations with BCS and can be used to automatically assess BCS with high accuracy.This study demonstrates that the automatic body condition scoring system has the possibility of being more accurate than human scoring.

Comparison of Oestrous Synchronization Response and Pregnancy Rate of Village Cows Following Timed Artificial Insemination in KwaZulu-Natal and Limpopo Provinces

The objectives of the current study were to evaluate the estrous response and pregnancy rate following timed artificial insemination (TAI) with frozen-thawed semen in cows. The study was carried out in cows at different villages of KwaZulu-Natal (KZN;n = 160) and Limpopo provinces (L;n = 171). Cows were selected randomly as presented by the farmers, regardless of parity, age, breed and body weight following pregnancy diagnosis. The cows were grouped according to breed type and body condition score (BCS) on a scale of 1-5. Selected cows were inserted a controlled intravaginal drug release (CIDR®) and removed on day 8, followed by administration of prostaglandin. Heat was observed on day 9 with the aid of heat mount detectors (HMD) that were placed on the individual cow’s tail head. Cows on heat were then inseminated twice at 12 hours interval. Pregnancy diagnosis was performed by an ultrasound scanner and rectal palpation 90 days after TAI. Data were analyzed using SAS 2006. Estrous responses were 100% in KZN and 99% in Limpopo. The lowest pregnancy rate was recorded in Brahman and Bonsmara type cows with BCS ≤ 2.5 regardless of province. Interestingly, Nguni type cows with BCS ≤ 2.5 had higher average pregnancy rate of 59.5% in Limpopo and 53.5% in KZN. However, cows with BCS ≥ 3 had better pregnancy rate regardless of breed type and province. In conclusion, village cows can be synchronized successfully and inseminated with frozen-thawed semen. However, pregnancy rates are low in cows with lower body condition. Village Nguni type cows were not affected by body condition scoring as they had higher and similar pregnancy rate as those that had body condition of ≥3.

Genomic and transcriptomic analyses enable the identification of important genes associated with subcutaneous fat deposition in Holstein cows

Subcutaneous fat deposition has many important roles in dairy cattle,including immunological defense and mechanical protection.The main objectives of this study are to identify key candidate genes regulating subcutaneous fat deposition in high-producing dairy cows by integrating genomic and transcriptomic datasets.A total of 1654 genotyped Holstein cows are used to perform a genome-wide association study(GWAS)aiming to identify genes associated with subcutaneous fat deposition.Subsequently,weighted gene co-expression network analyses(WGCNA)are conducted based on RNA-sequencing data of 34 cows and cow yield deviations of subcutaneous fat deposition.Lastly,differentially expressed(DE)m RNA,lnc RNA,and differentially alternative splicing genes are obtained for 12 Holstein cows with extreme and divergent phenotypes for subcutaneous fat deposition.Forty-six protein-coding genes are identified as candidate genes regulating subcutaneous fat deposition in Holstein cattle based on GWAS.Eleven overlapping genes are identified based on the analyses of DE genes and WGCNA.Furthermore,the candidate genes identified based on GWAS,WGCNA,and analyses of DE genes are significantly enriched for pathways involved in metabolism,oxidative phosphorylation,thermogenesis,fatty acid degradation,and glycolysis/gluconeogenesis pathways.Integrating all findings,the NID2,STARD3,UFC1,DEDD,PPP1R1B,and USP21 genes are considered to be the most important candidate genes influencing subcutaneous fat deposition traits in Holstein cows.This study provides novel insights into the regulation mechanism underlying fat deposition in high-producing dairy cows,which will be useful when designing management and breeding strategies.