Assessing the within-herd prevalence of Coxiella burnetii milk-shedder cows using a real-time PCR applied to bulk tank milk

Thirty-seven bulk tank milk (BTM) and individual milk samples of all contributing cows were tested for Coxiella burnetii detection by a real-time PCR assay and used to assess the relationship between the BTM PCR-response and (i) the within-herd prevalence of milk-shedder cows and (ii) the proportion of heavy milk-shedder cows. The within-herd prevalence of milk-shedder cows (i) was found to be significantly higher in herds with a positive BTM and (ii) increased significantly with the estimated titre in Coxiella burnetii obtained in positive BTM. The proportion of heavy milk-shedder cows among the milk-shedder cows increased significantly with an increased estimated titre in Coxiella burnetii in positive BTM. Therefore, a real-time PCR assay applied to BTM samples collected repeatedly over time appears to be a valuable tool to assess on a larger scale the status of herds towards Coxiella shedding, and to evaluate the efficiency of control actions aimed at controlling and/or preventing Coxiella shedding in dairy herds.     

Loser cows in Danish dairy herds: definition, prevalence and consequences

During the last few years, many Danish dairy farmers have expressed increasing concerns regarding a group of cows, which we have chosen to term ‘loser cows’. Until now, a loser cow has not been described scientifically. We defined a loser cow on the basis of a clinical examination of the cow. A total of 15,151 clinical examinations were made on 6,451 individual cows from 39 randomly selected, large Danish dairy herds with loose-housing systems using a clinical protocol. Scores for the clinical signs lameness, body condition, hock lesions, other cutaneous lesions, vaginal discharge, condition of hair coat and general condition were converted into a loser cow score. Cows with a loser cow score of 8 or more were classified as loser cows. The overall prevalence of loser cows was 2.15%, 4.50% and 2.98% during the first, second and third round of herd visits, respectively.

The associations between the loser cow state and milk production, mortality, morbidity, culling and workload for the farmer were evaluated using data from herd visits and from the Danish Cattle Database and a number of different statistical techniques. It was concluded that the loser cow state has significant negative consequences for both the farmer and the cow. On average, loser cows yielded 0.61 to 2.24 kg energy corrected milk less per day than non-loser cows depending on parity. Hazard ratio for death or euthanasia was 5.69 for loser cows compared to non-loser cows. Incidence rate ratio for disease treatments was 0.69 for non-loser cows compared to loser cows. Loser cows were often culled in an ‘unfavourable’ way and generally caused extra workload for the farmer.

A simplified version of the loser cow score was evaluated and is recommended for future research and use in practice.     

Effects of Bacillus amylolyticus on Rumen Dry Matter Digestibility,Fermentation Parameters and Metabolites of Dairy Cows北大核心CSCD

This experiment was conducted to study the effects of Bacillus amylolyticus on rumen dry matter digestibility, fermentation parameters and metabolites of dairy cows. Experiment 1: six dairy cows with permanent fistula and had the similar parity (2 to 3 fetuses), body weight [(662 ±57) kg], lactation days [(160 ± 22) d] and milk yield [(36.1 ±3.8) kg / d], were randomly divided into 3 groups with 2 cows per group. Using 3 ×3 Latin square design, each group was extra fed 0 (control group), 5 ×109 and 5 ×1010 CFU / d Bacillus amylolyticus, the trial period was 3 periods, 13 days for each period, including 10 days for the pre-trial period and 3 days for the trial period. At the beginning of the trial period, the rumen dry matter digestibility of cows was measured by nylon bag method. Experiment 2: thirty dairy cows with similar parity [(2.5 ±0.3) fetuses], initial body weight [(559.2 ± 7. 4) kg], milk yield [(35. 2 ± 1. 5) kg / d] and lactation days [(99 ± 22) d] were randomly divided into three groups with 10 cows in each group. Cows in the 3 groups were extra fed with 0 (control group), 5 ×109 and 5 ×1010 CFU / d Bacillus amylolyticus, respectively. The pre-trial period was 10 days and the trial period was 42 days. The rumen fluid was collected on the last day of the trial period, and the rumen fermentation parameters and metabolites were determined. The results showed as follows: compared with the control group, 1) supplementary feeding of 5 × 1010 CFU / d Bacillus amylolyticus could significantly improve the rumen dry matter digestibility of dairy cows at 12, 24, 36, 48 and 72 h (P <0.05), supplementary feeding of 5 ×109 CFU / d Bacillus amylolyticus could significantly improve the rumen dry matter digestibility of dairy cows at 36 and 48 h (P <0.05); 2) supplementary feeding of 5 ×109 CFU / d Bacillus amylolyticus could significantly increase the contents of isobutyric acid, butyric acid, isovaleric acid, valeric acid, total volatile fatty acid and microbial protein in the rumen of dairy cows (P < 0. 05), supplementary feeding of 5 × 1010 CFU / d Bacillus amylolyticus could significantly increase the contents of isobutyric acid and isovaleric acid in the rumen of dairy cows and significantly reduce the rumen acetic acid / propionic acid (P < 0. 05), supplementary feeding of 5 ×109 and 5 ×1010 Bacillus amylolyticus had no effects on rumen pH and ammonia nitrogen content (P >0.05); 3) eleven metabolic pathways related to differential metabolites were detected, and ascorbic acid and alginate metabolism were significantly enriched (P < 0. 05) . In conclusion, Bacillus amylolyticus can increase the rumen dry matter digestibility, and improve the rumen fermentation function of dairy cows by affecting the content of rumen metabolites. By comprehensive analysis, supplementary feeding of 5 × 109 CFU / d Bacillus amylolyticus can achieve better effect. © 2023 Authors. All rights reserved.     

小型乳制品加工厂的研究与设计

牛奶是人类生长发育全过程中最适宜的食品。牛奶中含有大量的优质蛋白质、氨基酸、脂肪、乳糖、多种维生素、多种免疫活性因子及人体必需的矿物质微量元素，是营养最全面、营养价值最高、最容易消化吸收的食品。为此，从牛奶在人们饮食中所处的地位出发，介绍了乳制品加工厂研究的意义，阐述了小型乳制品加工的生产工艺、厂房分布图和主要设备。     

奶牛养殖场粪污处理沼气工程技术与模式

本文综述了国内外奶牛养殖场沼气工程技术应用现状,分析了奶牛粪沼气发酵潜力和三种主要沼气发酵工艺的技术特点.     

基于超参数优化算法下的随机森林模型预测奶牛呼吸频率

奶牛呼吸频率是评估环境造成的奶牛热应激程度的重要指标之一。该研究基于随机森林（random forest,RF）算法提出了适用于生产条件下的奶牛个体呼吸频率准确预测模型,为了平衡模型精度与计算效率问题,利用遗传算法（genetic algorithm,GA）、差分进化（differential evolution,DE）算法、粒子群优化（particle swarm optimization,PSO）算法、贝叶斯优化（Bayesian optimization,BO）算法对模型超参数进行优化,并与网格搜索（grid search,GS）下的人工神经网络（artificial neural network,ANN）和极限梯度提升机（extreme gradient boosting,XGBoost）模型进行了对比分析。研究结果表明,使用融合环境参数的修正温湿指数（adjusted temperature-humidity index,ATHI）、时间区域、奶牛产奶量、泌乳天数、身体姿势以及胎次作为输入特征时,基准RF模型的预测性能最佳。在此基础上,4种智能优化算法下的RF模型性能优于GS-ANN和GS-XGBoost,其中BO-RF的综合性能最优,其决定系数、平均绝对误差、平均绝对百分比误差以及均方根误差分别为0.614、7.723、14.4%、9.737,超参数优化耗时约为DE-RF的1/220。特征重要性分析表明,输入因子对奶牛呼吸频率的影响程度不同,ATHI是影响力最高的因子,相对重要性（relative importance,RI）为0.71,其次是时间区域（RI=0.09）和奶牛产奶量（RI=0.07）。研究为奶牛生产、健康评价及牛舍环境精准调控提供了有效方法和基础。     

利用Kalman滤波和Hungarian算法的多目标奶牛嘴部跟踪及反刍监测

针对奶牛养殖场复杂环境下多目标奶牛嘴部自动跟踪及反刍监测的困难,该研究提出了一种基于嘴部区域跟踪的多目标奶牛反刍行为智能监测方法。在YOLOv4模型识别奶牛嘴部上下颚区域的基础上,以Kalman滤波和Hungarian算法跟踪上颚区域,并对同一奶牛目标的上颚和下颚区域进行关联匹配获取嘴部咀嚼曲线,以此获取反刍相关信息,从而实现多目标奶牛个体的嘴部跟踪和反刍行为监测;为解决奶牛快速摆头运动和棚舍栏杆遮挡引发奶牛标号变化的问题,提出未匹配跟踪框保持及扩大的方法。采集并选择实际养殖场环境下的反刍奶牛视频66段,对其中58段视频采取分帧操作得到图像,制作YOLOv4模型数据集,以其余8段视频验证跟踪方法和反刍行为判定方法的有效性。试验结果表明,YOLOv4模型对奶牛嘴部上颚、下颚区域的识别准确率分别为93.92%和92.46%;改进的跟踪算法可实现复杂环境下多目标奶牛嘴部区域的稳定跟踪,且有效解决了栏杆遮挡、快速摆头运动造成的奶牛标号变化现象,上下颚匹配率平均为99.89%,跟踪速度平均为31.85帧/s;由反刍行为判定方法获取的咀嚼次数正确率的平均值为96.93%,反刍时长误差的平均值为1.48 s。该研究可为实际养殖中多目标奶牛反刍行为的智能监测和分析提供参考,也可供其他群体动物运动部位的跟踪和行为监测借鉴。     

影响静态箱检测开放式气体排放源N2O排放通量的关键因子

为研究影响静态箱检测开放式气体排放源氧化亚氮(N2O)排放通量的关键因子,以提高静态箱检测气体排放通量的准确性,该文在实验室条件下,探究了箱体配置(有无通气孔、有无风扇)和检测条件(不同密闭时间:30、40、50和60 min;不同排放源表面风速:0、0.5、1.0、1.5和2.0 m/s)对300 mm(直径)×300 mm(高度)(D300 mm×H300 mm)的静态箱检测N2O排放通量准确性的影响规律。结果表明,不同配置的静态箱测量结果偏差率随时间的变化趋势均相同,其中有通气孔和风扇的箱体在不同风速下的检测稳定性较好,检测准确性最高。当排放源表面风速为0~2 m/s时,风扇对静态箱检测准确性无显著性影响,排放源表面的风主要通过通气孔影响静态箱的检测准确性。静态箱检测的气体排放通量与实际排放通量的偏差率随排放源表面风速和箱体密闭时间的增加而显著降低。该试验推荐在排放源表面风速小于2 m/s的无粪便堆积的奶牛运动场以及排放源介质相似的开放式气体排放系统中使用有通气孔和风扇的静态箱对N2O排放通量进行检测,密闭50 min。     

不同处理方式对奶牛粪细菌群落多样性及群落结构的影响

以腐熟牛粪、新鲜牛粪以及蚯蚓粪为材料,提取其微生物总DNA,利用细菌16SrDNAV3区扩增及变性梯度凝胶电泳（PCR-DGGE）法,分析了3种材料中细菌的多样性以及细菌群落结构的相似性。结果表明,蚯蚓粪的细菌多样性最丰富,腐熟牛粪次之,新鲜牛粪的细菌多样性最小。蚯蚓粪和腐熟牛粪的细菌群落结构有40%的相似性;蚯蚓粪和新鲜牛粪的细菌群落结构的相似性为25%;新鲜牛粪和腐熟牛粪的细菌群落结构的相似性则为35%。