Dairy Cattle

Ruminal gases, particularly methane, generated during the fermentative process in rumen, represent a partial loss of feed energy and are also pointed to as an important factors in greenhouse effect. This study aimed at quantifying methane (CH4) emission rates from lactating and dry cows and heifers, 24 month-old in average, on pasture under Southeast Brazil tropical conditions, using the tracer gas technique, sulphur hexafluoride (SF6), four animals per category, distributed in four blocks. Measurements were performed in February and June, 2002, with Holstein and Brazilian Dairy Crossbred (Holstein ¾ x Gir (Zebu) ¼), maintained on fertilized Tanzania-grass (Panicum maximum Jacq. cv. Tanzania) and fertilized Brachiaria-grass (Brachiaria decumbens cv. Basilisk) pastures. Heifers of both breeds were maintained on unfertilized Brachiaria-grass to simulate conditions of extensive cattle farming systems. CH4 and SF6 levels were measured with gas chromatography. Differences in CH4 emissions were measured (p < 0.05) for genetical groups. Holstein produced more methane (299.3 g day-1) than the Crossbred (264.2 g day-1). Lactating cows produced more methane (353.8 g day-1) than dry cows (268.8 g day-1) and heifers (222.6 g day-1). Holstein, with greater milk production potential, produced less CH4 (p < 0.05) per unit of dry matter intake (19.1 g kg-1) than the Crossbred (22.0 g kg-1). Methane emission by heifers grazing fertilized pasture (intensive system) was 222.6 g day-1, greater (p < 0.05) than that of heifers on unfertilized pasture (179.2 g day-1). Methane emission varied as function of animal category and management intensity of production system.

Dedicated to Professor Dr. D. Simon on the occasion ofhis 70lh birthday Summary A study where Casein loci were used to be markers for improving milk yield, fat content and protein yield in a marker assisted selection experiment focused on possible side effects of this process on longevity traits. Using the data of two samples of cows a Simulation on the data was carried out evaluating the selection differences in period of use, period of life and production of the whole life indirectly. The selection criteria were flexible using one of the milk production traits each as well as marker information. During the investigated period no negative effect of simulated selection using EBV for milk yield, fat content and protein yield alone or in combination with the Casein loci used as markers on longevity traits occurred in the population. There are no significant differences regarding the longevity traits caused by selection for Single milk trait based on pure EBV and MAS.

Lameness is one of the greatest infringements of welfare in dairy cows. The objective of this study was to investigate associations between milk yield and foot lesions causing lameness in Chilean dairy cattle with the hypothesis that if we can demonstrate that lameness reduces yield, and so income, from lame dairy cows then we have both economic and welfare arguments for reducing lameness in dairy cattle. For one year, all lame cows from seven farms with Holstein Friesian cattle were treated by their herdsmen. Herdsmen were trained by the researcher and a colour atlas was utilised to assist in diagnosis of lesions. All abnormalities on the foot and the suspected cause of lameness were recorded, and cattle were treated. A two-level hierarchical model with repeated monthly test-day yields within cows was used to investigate the impact of double sole (DS), sole ulcer (SU), white line disease (WLD), digital dermatitis (DD) and all 'other' causes of lameness on milk yield before and after treatment. There were 1,635 cows with complete data. Cattle with a DS were higher yielding than cattle that were never lame with a reduction in yield from four months before treatment. Cattle lame with DD were higher yielding than non-lame cattle before and after treatment. For all causes of lameness, yield increased the month after treatment. We conclude that lesions causing lameness reduced the milk yield of dairy cows in these seven herds in Chile. We discuss the current evidence base for prevention of lameness in dairy cows and hypothesise that rapid treatment is a feasible current approach to improve cow welfare immediately and probably reduce milk lost; more evidence for effective prevention is required.

To face the worldwide threat of Surra caused by Trypanosoma evansi, international organizations have stressed the need to evaluate and standardize diagnostic tools. PCR detection of T. evansi has known a great expansion during the last 20 years, but primer sets are often insufficiently assessed and compared. In this work, we compared the performances of six primer pairs–TBR1/2 ( Masiga et al., 1992), ESAG6/7 ( 12 and 13), TEPAN1/2 ( Panyim et al., 1993), pMUTEC F/R ( Wuyts et al., 1994), TRYP1 R/S ( Desquesnes et al., 2001) and TRYP4 R/S (Desquesnes et al., unpublished)–tested with purified T. evansi DNA serial dilutions, T. evansi-infected rat blood serial dilutions and Thai dairy cattle samples.TBR1/2 primer set was able to detect 0.01 pg of purified DNA, and a parasitaemia below one parasite per ml in rat blood. They presented the highest sensitivity in cattle samples as well as a high specificity, without non-specific products nor false positive reactions out of 84 negative cattle samples tested. ESAG6/7 showed equivalent results with purified DNA and rat samples but presented non-specific products with Thai dairy cattle samples, leading to non interpretable results. TEPAN1/2 was not able to detect less than 0.1 pg of purified DNA or 50 trypanosomes/ml in rat blood. In cattle, TEPAN1/2 primers detected only 36% of the positives detected by TBR1/2. Given the parasitemic level detected, pMUTEC F/R, TRYP1 R/S and TRYP4 R/S were not more sensitive than classical microscopic examination of the buffy coat. TBR1/2, TEPAN1/2, pMUTEC F/R and TRYP4 R/S did not cross-reacted with Babesia sp., Trypanosoma theileri and Anaplasma marginale. TBR1/2 was the most sensitive primer set to detect T. evansi in purified DNA, rodent blood and cattle blood, and did not show cross reaction with the other pathogens tested: it should be therefore preferred for epidemiological surveys. These results confirmed that TBR1/2 primers remain the reference for the detection of Trypanozoon DNA and should therefore be included in subsequent evaluations of new diagnosis tools based on DNA detection.

Monitoring livestock behaviour can be a useful way to improve farm animal management and to detect individual health events. The use of automated systems that predict several daily behaviours from accelerometer data is growing and studies have often focused on the comparison of datamining classification methods. However, few studies have attempted to evaluate the effect of the step preceding the classification, namely accelerometer signal pre-processing. This study aimed to evaluate the effect of several pre-processing methods on the prediction of dairy cows behaviour from accelerometer data. Ten Holstein cows equipped with a three-dimensional accelerometer fixed on a neck collar were simultaneously observed by two observers. Observed behaviours were predicted with decision tree using pre-processed accelerometer data as inputs. Different procedures were evaluated for each of these following pre-processing steps: signal filtering, signal segmentation and feature calculation. For signal filtering, low-pass filters and high-pass filters were considered. For signal seg-mentation, various window sizes and percentages of overlap between windows were implemented. Sixty-one features were computed. This resulted in 150 different combinations of pre-processing steps. For each combination a decision tree model predicting the observed behaviours was trained. The performance of each model to predict the observed behaviours was compared based on accuracy and F-score measures. The relative importance of each pre-processing configuration on the performance of prediction was evaluated with a linear regression model. The best configurations led to an accuracy of 0.95 and a F-score of 0.96 against 0.76 and 0.65 respectively with the worse combinations. The best combinations included a window size of 20 s and 30 s, with an overlap of 90% and no high-pass filter. High-pass filter had the most significant effect on the classification (P < 0.001), with a substantial decrease when it was applied. Performance of the classification was also significantly improved when increasing the percentage of overlapping (P < 0.001). The decline of the accuracy observed for the window size of 20 s without overlap was prevented when an overlap higher than 50% was applied. This suggested that overlap should be considered when there is not sufficient data available. No impact was found for the low-pas filter. In conclusion, the way of pre-processing the accelerometer signal deserves to be considered in the classification and adapted according to the aim and design of the study.

Automatic Milking Systems (AMS) milk cows any time without the need for a human worker to be present. Cows choose when to be milked and detailed data is recorded by the robot which can be accessed remotely by computer or mobile device meaning farmers can check the health and performance of their herd from a distance. It is claimed that robotic milking improves the working conditions and lifestyle of the dairy farmer, as well as having economic advantages and benefits for cow health and welfare. This paper focuses on the relationship between AMS and the role of the stockperson. Although AMS reduces the need for labour in the milking parlour and in theory creates freedom and flexibility for the farmer, in practice farmers found their work routines changed rather than lessened. Ultimately, the role of the stockperson is still vital in maintaining and improving cow health and welfare when compared to conventional milking routines.

This study determined the nitrogen balance in two types of template pastures: a mixed pasture of two grass kikuyu (Pennisetum clandestinum) and tall fescue (Festuca arundinacea) pasture and the associated tall fescue grass and legume bird foot trefoil (Lotus uliginosus), in an area of 1 ha, with a completely randomized design with cow as the experimental unit and pasture treatment.

Bovine tuberculosis (BTB) is endemic in Ethiopian livestock. Disease prevalence varies greatly by species, geography, husband-ry system and diagnostic methods used. A substantial body of work has been done on BTB prevalence in Ethiopia over the last decade, the true burden of BTB however, is still largely unknown. This review highlighted gaps and weakness in BTB diagnostics and the urgent need to standardize/harmonize testing methods. It discusses the prevalence of M. tuberculosis and Non Tuber-culous Mycobacteria (NTM) in livestock and their possible interference with the BTB diagnostic methods. This paper finally discusses possible control options for the disease, particularly in the intensive milk farm systems in the wake of increased and or emerging dairy farms in the country.

All stakeholders within the livestock industry face a considerable challenge in achieving a balance between economic viability, environmental responsibility and social acceptability; and thus maintaining sustainable food production. This is exacerbated by information about farming practices and management systems that accentuate consumer concerns and lead to confusion as to the roles of productivity, efficiency and animal health in modern agriculture. The suggestions that intensive farms or large-scale herds have negative effects on cattle health; that we can assess cattle welfare by applying anthropomorphic philosophies; and that extensive systems are inherently beneficial to the environment, appear to be intuitively correct. Yet these suppositions are not as simple as they are often presented in mass media articles aimed at the consumer and lead to a multitude of other questions. Although it is tempting to try and overcome these issues by providing factual information, we cannot overcome negative publicity simply by supplying data and statistics. As an industry, we need to combine improved communication mechanisms with a better understanding of how consumer food-buying decisions are made to ensure future social acceptability and sustainability.