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The Effects of Several Cow and Herd Level Factors on Lameness in Holstein Cows Reared in Izmir Province of Turkey

机译:土耳其伊兹密尔省饲养的荷斯坦奶牛中几种母牛和绵羊水平因子对Level行的影响

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This study was carried out to determine the prevalence of lameness and risk factors for lameness. Data of 1078 Holstein cows from 34 farms in Izmir province of Turkey were evaluated. Lameness was determined by using a Lameness Score (LS) scale with 5 levels. Mean prevalence of lameness (LS≥3) was 28.3%. The percent of the cows with LS 1-5 were found to be 37.9, 33.8, 20.9, 5.8 and 1.6%, respectively. Cow-level variables were parity, days in milk, body condition score and hygiene score of lower rear legs. There were 18 herd level variables used to explain the variation in the prevalence of lameness among the herds. LS data were analysed using individual and multifactorial binary logistic regression. About 12 of the 22 potential risk factors investigated in the study were found to be significant (p<0.10) in the individual logistic regression analysis. However, only 9 of the 12 factors remained in the final multifactorial logistic regression model. These significant 9 factors on lameness were parity, body condition score, herd size, animal keeper, total area per cow, soil area per cow, frequency of scraping, ratio of concentrate feed to total feed intake and consulting a feeding expert. Lameness risk was increased with increasing parity, herd size and ratio of concentrate feed to total feed intake and it was increased with decreasing in body condition score, total area per cow and soil area per cow and the risk was also increased if a feeding expert was not available or animal keeper was the stockman (p<0.10). Frequency of scraping was found a significant (p = 0.031) risk factor for lameness. Minimum prevalence of lameness was determined in the herds scraped once in 6-10 days.
机译:进行这项研究以确定determine行的患病率和risk行的危险因素。评价了来自土耳其伊兹密尔省34个农场的1078头荷斯坦奶牛的数据。 using行是通过使用5级的La行分数(LS)量表确定的。平均la行患病率(LS≥3)为28.3%。发现LS 1-5的奶牛百分比分别为37.9%,33.8%,20.9%,5.8%和1.6%。母牛的水平变量包括胎次,产奶天数,身体状况评分和小腿后肢的卫生评分。有18个牛群水平变量用于解释牛群中la行患病率的变化。使用个体和多因素二元logistic回归分析LS数据。在个人逻辑回归分析中,研究中调查的22种潜在危险因素中约有12种是显着的(p <0.10)。但是,在最终的多因素逻辑回归模型中,只有12个因素中的9个仍然存在。影响la行的这9个重要因素包括:胎次,身体状况评分,牛群大小,动物饲养者,每头母牛的总面积,每头母牛的土壤面积,刮frequency的频率,精饲料的采食量与总采食量的比例以及咨询喂养专家。 par行风险随着胎次,牛群大小和精饲料占总饲料摄入量的增加而增加,并且随着身体状况评分,每头牛的总面积和每头牛的土壤面积的减少而增加,如果喂食专家,则该风险也会增加。牲畜饲养员(p <0.10)没有可用的动物饲养员。发现刮擦的频率是造成me行的重要危险因素(p = 0.031)。确定每6-10天刮一次牛群的最低of行率。

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