MohammadTaghi Fayazikia; Mohammad Dadpasand; Hamideh Keshavarzi
Volume 25, Issue 2 , July 2023, , Pages 123-132
Abstract
Introduction Mastitis is one of the most frequent and costly diseases of the dairy cattle industry and causes many economic losses, which negatively affects milk yield and composition, fertility, longevity and welfare of cows. The best solution for reducing the economic and biological consequences is ...
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Introduction Mastitis is one of the most frequent and costly diseases of the dairy cattle industry and causes many economic losses, which negatively affects milk yield and composition, fertility, longevity and welfare of cows. The best solution for reducing the economic and biological consequences is early and accurate prediction of mastitis based on indicator factors. So far, various statistical methods have been used to predict mastitis such as linear and multiple regression, and threshold models. Machine learning is another method that has recently widely been used to predict farm profitability, reproductive traits, longevity and abortion in dairy cow. Machine learning is defined as a set of methods for automatically finding patterns in data and then using those patterns to predict possible future data.Material and Methods In this research, the performance of four machine learning algorithms including random forest, decision tree, Naïve Bayes and logistic regression and two sampling methods, over-sampling and under-sampling, were compared to predict risk of clinical mastitis based on data collected in two Holstein dairy herds in Isfahan province. Final dataset included 393504 records on cows calved during 2007 to 2017 of which 13653 cases (3.47%) were infected and 379851 cases (96.53%) were healthy. Factors related to mastitis, including parity, daily milk production, calving
Sina Azad; hamid Amanlou; Najme Eslamian Farsuni; Tahere Amirabadi Farahani; Mohammad hadi Khabbazan
Volume 25, Issue 1 , April 2023, , Pages 37-50
Abstract
In the current study, the effect of source and level of copper in the diet on production and health of dairy cows using 105 multiparous pregnant Holstein cows from -21 until +15 days relative to calving in randomized complete block design with 3 treatments and 35 replications were investigated. The experimental ...
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In the current study, the effect of source and level of copper in the diet on production and health of dairy cows using 105 multiparous pregnant Holstein cows from -21 until +15 days relative to calving in randomized complete block design with 3 treatments and 35 replications were investigated. The experimental treatments include: 1) diet containing copper at the NRC recommended levels from copper sulfate source (NRC-S), 2) diet containing copper at twice the NRC recommended levels from copper glycinate source (2NRC-Gly) and 3) diet containing copper at twice the NRC recommended levels from copper sulfate source (2NRC-S). Milk yield and composition were not affected by experimental treatments, but treatment by time interaction showed that cows fed by 2NRC-Gly had more milk than NRC-S group (P<0.05) at 60, 90,120 DIM and cow in 2NRC-Gly produced more milk at 90 and 120 days in milk compared to NRC-S (P<0.05). The somatic cells count for 2NRC-Gly cows was lower compared to NRC-S cows (P 0.05). The incidence of subclinical mastitis at 15 DIM in 2NRC-Gly was lower compared to the other two treatments (P = 0.05). No difference in body weight and body condition score changes were observed across treatments. Blood metabolites and liver enzymes were not affected by adding different Cu sources, but serum albumin postpartum was increased in 2NRC-Gly group relative to the other two groups (P 0.05). Based on the results, adding copper especially by copper glycinate source at twice the NRC recommended levels led to an increase in the serum albumin concentration, a decrease in milk somatic cells count and lower incidence of subclinical mastitis, which could indicate an improvement in health of cows during transition period.
Maryam Mohammadnezhad; Ghodrat Rahimi Mianji; Ayoub Farhadi
Volume 23, Issue 1 , March 2021, , Pages 1-11
Abstract
The aim of this study was to identify the allelic variants of C4-A and LF genes and to investigate their associations with the nunber of milk somatic cells in Holstein cows. Mastitis is one of the most common diseases in dairy cows, that reduces milk production and imposes high costs on breeders. C4-A ...
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The aim of this study was to identify the allelic variants of C4-A and LF genes and to investigate their associations with the nunber of milk somatic cells in Holstein cows. Mastitis is one of the most common diseases in dairy cows, that reduces milk production and imposes high costs on breeders. C4-A and lactoferrin genes are amonge the genes that affect the immune system to fight pathogens, microbial agents and mastitis. 384 blood samples were prepared from Holstein cows and DNA extraction was performed using optimized salting out method. IPLEX technique was used to determine the genotype of the samples. To identify single nucleotide polymorphisms, the marker sites of 1-rs137485678; C<G and 2-rs132741478; C<T for C4- A complement gene and 1-rs384176726; A<G and 2-rs445918028; A<T were selected for the LF gene. Genotyping at 1-rs137485678; C<G locus of C4-A gene showed two C and G alleles with frequencies of 58 and 42 %, and also three genotypes CC, CG and GG with frequencies of 31, 53 and 16%, respectively. No polymorphisms were observed at the other sites. Marker-trait analysis showed a statistically significant association (P<0.05), so that cows with CG genotype had the lowest number of somatic cells. Phase software was used to identify haplotypes. Based on the results of this research, the marker rs137485678; C <G-1 of the C4-A gene can be used as a genetic marker to improve mastitis in dairy cows.
Negin Jamali Emam Gheis; Ali Sadeghisefidmazgi; Mohammad Mehdi Moeini
Volume 15, Issue 1 , July 2014, , Pages 21-29
Abstract
In this study, somatic cell counts (SCC) of milk were determined in six industrial and traditional dairyfarms in Tehran province during different seasons. The prevalence of udder disorders and mastitis wasestimated on the base of SCC as an indicator as well. In this research, industrial and traditional ...
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In this study, somatic cell counts (SCC) of milk were determined in six industrial and traditional dairyfarms in Tehran province during different seasons. The prevalence of udder disorders and mastitis wasestimated on the base of SCC as an indicator as well. In this research, industrial and traditional dairyfarms during 9 months were studied by total 32620 SCC records. Milk samples were collectedindividually. Least square mean (±standard error) (n×1000 per ml) in industrial and traditional culturesystems were 80.11 (±12.60) and 234.57 (±12.97), respectively. The SCC in traditional dairy farms wasapproximately 2.9 times higher than those of industrial ones (P<0.05). The highest SCC was found insummer that was statistically different from spring and autumn (P<0.05). In industrial dairy farms, subclinicaland clinical mastitis were estimated to 36.6 and 11.8%, respectively. The corresponding valuesfor traditional ones were 59.6 and 34.7%, respectively. The results showed that if the SCC decreases by ahalf, mastitis disease incidence would be reduced up to 30-50 percent.