Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland P61 C996; Animal Production Systems Group, Department of Animal Sciences, Wageningen University and Research, 6700 AH, Wageningen, the Netherlands.
Animal Production Systems Group, Department of Animal Sciences, Wageningen University and Research, 6700 AH, Wageningen, the Netherlands.
J Dairy Sci. 2019 Sep;102(9):8332-8342. doi: 10.3168/jds.2018-15719. Epub 2019 Jul 10.
The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.
奶牛的移动能力质量会对福利、经济和环境产生重大影响，但目前尚未对基于牧场的系统进行广泛的量化。本研究的目的是通过检查特定的移动能力评分、蹄病（类型和严重程度）、体况评分（BCS）和奶牛胎次之间的关系来描述移动能力质量。本研究的数据来自 52 个基于牧场的奶牛场的 6927 头奶牛，包括移动能力评分（0=最佳移动能力；1、2 或 3=移动能力逐渐下降）、蹄病类型和严重程度、BCS 和奶牛胎次。采用多项逻辑回归进行分析。因变量是移动能力评分，预测变量是 BCS、蹄病类型和严重程度以及奶牛胎次。共运行了 3 个模型，每个模型都有 1 个参考类别（移动能力评分 0、1 或 2）。每个模型还包括蹄病（蹄过长、蹄底出血、白线病、蹄底溃疡和趾间皮炎）、BCS 和奶牛胎次作为预测变量。大多数类型的蹄病的出现都有大于 1 的优势比，这表明奶牛出现次优移动能力的可能性增加。低 BCS（BCS<3.00）与奶牛出现次优移动能力的风险增加有关，而相对较高的胎次也与出现次优移动能力的风险增加有关。这些结果证实了蹄病、BCS、奶牛胎次和奶牛移动能力评分之间的关联。因此，应该定期进行移动能力评分，以识别出与最佳移动模式略有偏差的奶牛，并采取预防措施防止问题恶化。
