Pathogen-specific patterns of milking traits in automatic milking systems.

Early detection of intramammary infection (IMI) can improve animal health and welfare in dairy herds. The implementation of sensors and automatic milking systems (AMS) in dairy production inherently increases the amount of available data and hence also the potential for new approaches to mastitis management. To utilize the full potential of data from AMS and auxiliary sensors, a better understanding of physiological and pathological changes in milking traits associated with different udder pathogens may be imperative. This observational study aimed to investigate pathogen-specific patterns in milking traits recorded in AMS. The milking traits included; online somatic cell count (OCC), electrical conductivity (EC), milk yield (MY), and average milk flow rate (AMF). Data were collected for a study period of 2 years and included 101 492 milkings from 237 lactations in 169 cows from one farm. Measurements of OCC were recorded at cow-level and data on EC, MY, and AMF were obtained at quarter-level. In addition to the data obtained from the AMS, altogether 5756 quarter milk samples (QMS) were collected. Milk samples were obtained monthly for bacteriological culturing. We included findings of 13 known mastitis pathogens to study pathogen-specific patterns in milking traits. These patterns were compared with those in a baseline group consisting of cows that did not have any positive milk culture results throughout the lactation period. Patterns of the milking traits are described for all positive samples both across 305 d in milk (DIM), and in the 15-d period before a positive bacteriological sample. The association between a positive sample and the milking traits (ln(OCC), EC-IQR; the ratio between the quarter with the highest and the quarter with the lowest level of EC, and MY) for the 15 d before the detection of a pathogen was assessed using mixed effects linear regression models. All pathogens were associated with alterations in the level and variability of ln(OCC) relative to lactations with no positive bacteriological samples. A positive sample for Staph. aureus was associated with increased values for MY during the 15 d before a positive diagnosis. It is biologically plausible to interpret changes in OCC and EC-IQR as consequences of an intramammary infection (IMI), while higher MY in bacteriologically-positive cows is most likely linked to the increased risk of infection in high-yielding cows. In this study, the most notable changes in the traits (OCC and EC-IQR) were observed for Staph. aureus and Strep. dysgalactiae, followed by Strep. simulans, Strep. uberis, and Lactococcus lactis. Even if we did not detect significant associations between positive bacteriology and EC-IQR, visual assessment and descriptive statistics indicated that there might be differences suggesting that it could be an informative trait for detecting infection when combined with OCC and possibly other relevant traits using machine learning algorithms.

Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow's Lactation.

The use of technologies for measurements of health parameters of individual cows may ensure early detection of diseases and maximization of individual cow and herd potential. In the present study, dry-film Fourier transform infrared spectroscopy (FTIR) was evaluated for the purpose of detecting and quantifying milk components during cows' lactation. This was done in order to investigate if these systematic changes can be used to identify cows experiencing subclinical ketosis. The data included 2329 milk samples from 61 Norwegian Red dairy cows collected during the first 100 days in milk (DIM). The resulting FTIR spectra were used for explorative analyses of the milk composition. Principal component analysis (PCA) was used to search for systematic changes in the milk during the lactation. Partial least squares regression (PLSR) was used to predict the fatty acid (FA) composition of all milk samples and the models obtained were used to evaluate systematic changes in the predicted FA composition during the lactation. The results reveal that systematic changes related to both gross milk composition and fatty acid features can be seen throughout lactation. Differences in the predicted FA composition between cows with subclinical ketosis and normal cows, in particular C14:0 and C18:1cis9, showed that dietary energy deficits may be detected by deviations in distinct fatty acid features.

Fourier transform infrared spectroscopy of milk samples as a tool to estimate energy balance, energy- and dry matter intake in lactating dairy cows.

The objective of the study was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) analysis of milk samples to predict body energy status and related traits (energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows. The data included 2371 milk samples from 63 Norwegian Red dairy cows collected during the first 105 days in milk (DIM). To predict the body energy status traits, calibration models were developed using Partial Least Squares Regression (PLSR). Calibration models were established using split-sample (leave-one cow-out) cross-validation approach and validated using an external test set. The PLSR method was implemented using just the FTIR spectra or using the FTIR together with milk yield (MY) or concentrate intake (CONCTR) as predictors of traits. Analyses were conducted for the entire first 105 DIM and separately for the two lactation periods: 5 ≤ DIM ≤ 55 and 55 < DIM ≤ 105. To test the models, an external validation using an independent test set was performed. Predictions depending on the parity (1st, 2nd and 3rd-to 6th parities) in early lactation were also investigated. Accuracy of prediction (r) for both cross-validation and external test set was defined as the correlation between the predicted and observed values for body energy status traits. Analyzing FTIR in combination with MY by PLSR, resulted in relatively high r-values to estimate EB (r = 0.63), DMI (r = 0.83), EEI (r = 0.84) using an external validation. Only moderate correlations between FTIR spectra and traits like EB, EEI and dry matter intake (DMI) have so far been published. Our hypothesis was that improvements in the FTIR predictions of EB, EEI and DMI can be obtained by (1) stratification into different stages of lactations and different parities, or (2) by adding additional information on milking and feeding traits. Stratification of the lactation stages improved predictions compared with the analyses including all data 5 ≤ DIM ≤105. The accuracy was improved if additional data (MY or CONCTR) were included in the prediction model. Furthermore, stratification into parity groups, improved the predictions of body energy status. Our results show that FTIR spectral data combined with MY or CONCTR can be used to obtain improved estimation of body energy status compared to only using the FTIR spectra in Norwegian Red dairy cattle. The best prediction results were achieved using FTIR spectra together with MY for early lactation. The results obtained in the study suggest that the modeling approach used in this paper can be considered as a viable method for predicting an individual cow's energy status.

Factors associated with milking-to-milking variability in somatic cell counts from healthy cows in an automatic milking system.

Fully automated on-line analysis equipment is available for analysis of somatic cell count (SCC) at every milking in automatic milking systems. In addition to results from on-line cell counters (OCC), an array of additional cow-level and quarter-level factors considered important for udder health are recorded in these systems. However, the amount of variability in SCC that can be explained by available data is unknown, and so is the proportion of the variability that may be due to physiological or normal variability. Our aim was to increase our knowledge on OCC as an indicator for disturbances in udder health by assessing the variability in OCC in cows free from clinical mastitis. The first objective was to evaluate how much of the variability in OCC could be explained by different potential sources of variability, including intramammary infection (IMI) status (assessed by bacterial culture of quarter milk samples). The second objective was to evaluate the repeatability of the OCC sensor used in our study and the agreement between OCC values and SCC measured in a dairy herd improvement (DHI) laboratory. A longitudinal study was performed in the research herd of the Norwegian University of Life Sciences from January 5th 2016 to May 22nd 2017. Data from 62,471 milkings from 173 lactations in 129 cows were analyzed. We used ln-transformed OCC values (in 1000 cells/ml) as the outcome (lnOCC) in linear mixed models, with random intercepts at cow-level and lactation-level within cow. We were able to explain 15.0% of the variability in lnOCC with the following fixed effects: lactation stage, parity, milk yield, OCC in residual milk from the previous milking, inter-quarter difference between the highest and lowest conductivity, season, IMI status, and genetic lineage. When including the random intercepts, the degree of explanation was 55.2%. The individual variables explained only a small part of the total variability in lnOCC. We concluded that physiological or normal variability is probably responsible for a large part of the overall variability in OCC in cows without clinical mastitis. This is important to consider when using OCC data for research purposes or in decision-support tools. Sensor repeatability was evaluated by analyzing milk from the same sample multiple times. The coefficient of variation was 0.11 at an OCC level relevant for detection of subclinical mastitis. The agreement study showed a concordance correlation coefficient of 0.82 when comparing results from the OCC with results from a DHI laboratory.

Dynamics of somatic cell count patterns as a proxy for transmission of mastitis pathogens.

Management of udder health is particularly focused on preventing new infections. Data from the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) may be used in forecasting to improve decision support for improved udder health management. It provides online cell counts (OCC) as a proxy for somatic cell counts from every milking at the cow level. However, these values are typically too insensitive and nonspecific to indicate subclinical intramammary infection (IMI). Our aim was to describe and evaluate use of dynamic transmission models to forecast subclinical IMI episodes using milk cultures or changes in OCC patterns over time. The latter was expressed by an elevated mastitis risk variable. Data were obtained from the dairy herd of the Norwegian University of Life Sciences (Oslo, Norway). In total, 173 cows were sampled monthly for bacteriological milk culture during a 17-mo study period and 5,330 quarter milk samples were cultured. Mastitis pathogens identified were assigned to 1 of 2 groups, Pat 1 or Pat 2. Pathogens from which a high cell count would be expected during a subclinical IMI episode were assigned to the Pat 1 group. Pathogens not in the Pat 1 group were assigned to the Pat 2 group. Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae were the most common Pat 1 pathogens. Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus were the most common Pat 2 pathogens. The OCC were successfully recorded from 82,182 of 96,542 milkings. The current study included 324 subclinical IMI episodes. None of the mastitis pathogens demonstrated a basic reproduction number (R0) >1. Patterns of OCC change related to an episode of Pat 1 subclinical IMI at specificity levels of 80, 90, and 95% at sensitivity levels of 69, 59, and 48% respectively, demonstrated an R0 >1. An existing infection was significant for transmission for several Pat 2 pathogens, but only for Staphylococcus aureus and Staphylococcus epidermidis among Pat 1 pathogens. Dynamic transmission models showed that patterns of OCC change related to an episode of Pat 1 subclinical IMI were significantly related to the same pattern occurring in susceptible cows at specificity levels of 80, 90, and 99% at sensitivity levels of 69, 48, and 8%, respectively. We conclude that changes in herd prevalence of subclinical IMI can be predicted using dynamic transmission models based on patterns of OCC change. Choice of specificity level depends on management goals and tolerance for false-positive alerts.

The detection of intramammary infections using online somatic cell counts.

Timely and accurate identification of cows with intramammary infections is essential for optimal udder health management. Various sensor systems have been developed to provide udder health information that can be used as a decision support tool for the farmer. Among these sensors, the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) provides somatic cell counts from every milking at cow level. Our aim was to describe and evaluate diagnostic sensor properties of these online cell counts (OCC) for detecting an intramammary infection, defined as an episode of subclinical mastitis or a new case of clinical mastitis. The predictive abilities of a single OCC value, rolling averages of OCC values, and an elevated mastitis risk (EMR) variable were compared for their accuracy in identifying cows with episodes of subclinical mastitis or new cases of clinical mastitis. Detection of subclinical mastitis episodes by OCC was performed in 2 separate groups of different mastitis pathogens, Pat 1 and Pat 2, categorized by their known ability to increase somatic cell count. The data for this study were obtained in a field trial conducted in the dairy herd of the Norwegian University of Life Sciences. Altogether, 173 cows were sampled at least once during a 17-mo study period. The total number of quarter milk cultures was 5,330. The most common Pat 1 pathogens were Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae. The most common Pat 2 pathogens were Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus. The OCC were successfully recorded from 82,182 of 96,542 milkings during the study period. For episodes of subclinical mastitis the rolling 7-d average OCC and the EMR approach performed better than a single OCC value for detection of Pat 1 subclinical mastitis episodes. The EMR approach outperformed the OCC approaches for detection of Pat 2 subclinical mastitis episodes. For the 2 pathogen groups, the sensitivity of detection of subclinical mastitis episodes was 69% (Pat 1) and 31% (Pat 2), respectively, at a predefined specificity of 80% (EMR). All 3 approaches were equally good at detecting new cases of clinical mastitis, with an optimum sensitivity of 80% and specificity of 90% (single OCC value).

Large-scale cross-sectional study of relationships between somatic cell count and milking-time test results in different milking systems.

Milking-time testing (MTT) is a method for evaluating the vacuum conditions in the teatcup during milking. The purpose is to evaluate the possible impact of the milking and milking equipment on udder health and milk quality. The method is commonly implemented by herd health advisory services, but results are interpreted empirically due to lack of scientific documentation on relationships between MTT result variables and objective measures of udder health. The current study was conducted to increase our understanding of associations between cow-level differences in composite milk somatic cell count (CMSCC) and MTT results in dairy cows milked in 3 different milking systems; automatic milking systems (AMS), milking parlors, and pipeline milking systems. Data from 7069 cows (predominantly Norwegian Red breed) in 1009 herds were used in a cross-sectional study. Multilevel linear regression models with a random intercept at herd level were used to describe relationships between CMSCC (on logarithmic scale) and the following MTT explanatory variables: average vacuum level in the short milk tube and mouthpiece chamber in the main milking and overmilking periods, the duration of these two periods, and vacuum stability, measured by sudden vacuum drops in the short milk tube. The models were corrected for the herd effect, mastitis history and differences in milk yield, lactation stage and parity between cows. Separate models were run for AMS, milking parlors, and pipeline milking systems, because this approach allowed for comparison between systems and for evaluation of the herd effect independently of milking system. The models described 8-10 % of the variation in CMSCC, indicating that MTT could only explain a relatively small proportion of a large total variation in CMSCC. In most observations, vacuum levels in the short milk tube during main milking were within the range recommended by the International Organization for Standardization. The results from our multivariable models showed decreasing CMSCC with increasing vacuum level in the short milk tube during the main milking period in AMS and milking parlors. Similarly, decreasing CMSCC was also associated with increasing duration of the main milking period in all 3 systems. These relationships are important for the interpretation of MTT results under practical conditions; finding high vacuum levels and long milking durations in a MTT is not associated with elevated CMSCC. In AMS herds, we also found indications that the relationships were different for cows where a case of mastitis had been treated before the MTT.

Milk-flow data collected routinely in an automatic milking system: an alternative to milking-time testing in the management of teat-end condition?

BACKGROUND: Having a poor teat-end condition is associated with increased mastitis risk, hence avoiding milking machine settings that have a negative effect on teat-end condition is important for successful dairy production. Milking-time testing (MTT) can be used in the evaluation of vacuum conditions during milking, but the method is less suited for herds using automatic milking systems (AMS) and relationships with teat end condition is poorly described. This study aimed to increase knowledge on interpretation of MTT in AMS and to assess whether milk-flow data obtained routinely by an AMS can be useful for the management of teat-end health. A cross-sectional study, including 251 teats of 79 Norwegian Red cows milked by AMS was performed in the research herd of the Norwegian University of Life Sciences. The following MTT variables were obtained at teat level: Average vacuum level in the short milk tube during main milking (MTVAC), average vacuum in the mouthpiece chamber during main milking and overmilking, teat compression intensity (COMPR) and overmilking time. Average and peak milk flow rates were obtained at quarter level from the AMS software. Teat-end callosity thickness and roughness was registered, and teat dimensions; length, and width at apex and base, were measured. Interrelationships among variables obtained by MTT, quarter milk flow variables, and teat dimensions were described. Associations between these variables and teat-end callosity thickness and roughness, were investigated. RESULTS: Principal component analysis showed clusters of strongly related variables. There was a strong negative relationship between MTVAC and average milk flow rate. The variables MTVAC, COMPR and average and peak milk flow rate were associated with both thickness and roughness of the callosity ring. CONCLUSIONS: Quarter milk flow rate obtained directly from the AMS software was useful in assessing associations between milking machine function and teat-end condition; low average milk flow rates were associated with a higher likelihood of the teat having a thickened or roughened teat-end callosity ring. Since information on milk flow rate is readily available from the herd management system, this information might be used when evaluating causes for impaired teat-end condition in AMS.

Transmission dynamics of intramammary infections caused by Corynebacterium species.

The development of reliable models for transmission of intramammary infections (IMI) is the subject of extensive research. Such models are useful to enhance the identification and understanding of factors that affect pathogen-specific IMI dynamics. Longitudinal transmission models are valuable for predicting infection outbreak risks, quantifying the effectiveness of response tactics, and performing response planning. In this work, we focused on modeling Corynebacterium spp. by using a compartmental model. Previous investigations have considered modeling the transmission dynamics of several bacterial pathogens, but not Corynebacterium spp. We established a Corynebacterium spp. Susceptible-Infectious-Susceptible (SIS) model. We simulated the model numerically by using parameters that we estimated by a generalized linear model approach, using month of study as the time variable. The data, from which the parameters of the model were estimated, were obtained in a field trial conducted in 2 US dairy herds. Altogether, 786 cows were sampled at least once during the 13-mo study period. The total number of quarter milk cultures and cases of IMI caused by Corynebacterium spp. were 11,744 and 556, respectively, in farm A; the corresponding figures for farm B were 11,804 and 179. Our modeling study included only transmission from persistent IMI caused by Corynebacterium spp. within the lactation pens. The rate of new infections was significantly related to preexisting IMI in both farms, underscoring the importance of preexisting Corynebacterium spp. IMI for the transmission of Corynebacterium spp. within lactation pens. The estimated basic reproduction numbers (R0) in the 2 farms were 1.18 and 0.98, respectively. The nonsignificant disparity in R0 was associated with significant differences in cure rates between farms.

Associations between the time of conception and the shape of the lactation curve in early lactation in Norwegian dairy cattle.

BACKGROUND: This study was carried out to determine if an association exists between the shape of the lactation curve before it is influenced by the event of conception and the time from calving to conception in Norwegian dairy cattle. Lactation curves of Norwegian Red cows during 5 to 42 days in milk (DIM) were compared between cows conceiving between 43 and 93 DIM and cows conceiving after 93 DIM. METHODS: Data from 23,049 cows, represented by one lactation each, with 219,538 monthly test days were extracted from the Norwegian Dairy Herd Recording System, which represents 97% of all Norwegian dairy cows. Besides veterinary treatments, these records also included information on daily milk yield at monthly test days. The data were stratified by parity groups (1, 2, and 3 and higher) and time to conception periods (43-93 DIM and >93 DIM). The sample was selected using the following selection criteria: conception later than 42 DIM, calving season July to September, no records of veterinary treatment and the level of energy fed as concentrates between 8.69 and 12.83 MJ. The shape of the lactation curves were parameterized using a modified Wilmink-model in a mixed model analysis. Differences in the parameters of the lactation curves with different conception times were evaluated using confidence intervals. RESULTS: Lactation curves characterized by a low intercept and a steep ascending slope and a steep descending slope were associated with early conception across all parities. The peak milk yield was not associated with time of conception. CONCLUSIONS: A practical application of the study results is the use of the shape of the lactation curve in future herd management. Groups of cows with impaired reproductive performance may be identified due to an unfavorable shape of the lactation curve. Monitoring lactation curves and adjusting the feeding strategy to adjust yield therefore may be useful for the improvement of reproductive performance at herd level.

Mastitis and the shape of the lactation curve in Norwegian dairy cows.

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.

Calf health and management in smallholder dairy farms in Tanzania.

Smallholder farmers' knowledge and practice of dairy calf management on 129 farms with calves less than 10 months of age in Southeastern and Southern Highland areas of Tanzania was assessed. The method of study included both a farm visit and completion of a questionnaire. Most of the farmers were female, with a primary level of education, and majority kept 1-3 milking cows that yielded 6-10 l milk/cow/day. Most of the calves were fed milk using a residual calf suckling system. Weaning age was 3-8 months. Overall, the body condition of the calves was poor, ranged from 1 to 2.5 with a mode of 2. The majority of the farmers believed that helminthosis was the most common disease condition affecting the calves; diarrhea was ranked as the second. Calf death was reported by 20% of the farmers to have occurred in their herd lasting the 2 years prior to the study. Calf body condition score was related to body weight for calves younger than 9 weeks, and older than 23 weeks of age, whereas no such relationship existed in the age group 9 to 23 weeks. The sex distribution was skewed with less male calves being older than 23 weeks. We hypothesize that male calves experience inferior management compared with female calves. This study demonstrates a low level of knowledge on, and poor practices of calf management among the surveyed farmers that suggest the need for educational intervention.

Assessment of progesterone profiles and postpartum onset of luteal activity in spring calving Hereford beef suckler cattle.

BACKGROUND: Reproduction is the single greatest factor limiting beef cattle production. Previous research on beef suckler luteal activity has largely focused on the mechanisms, and duration, of postpartum anoestrus. However, the temporal pattern of luteal activity after resumption of post-partum ovarian activity, and the impact of pattern type on days open (DO) in purebred beef suckler cows, are unknown. METHODS: Progesterone concentration was measured in milk samples taken thrice weekly from 120 lactations, in 87 animals, on 3 farms, over two years. Onset of luteal activity (OLA) was defined as the first day milk progesterone concentration exceeded 3 ng/ml for two successive measurements, or exceeded 5 ng/ml once. It was defined as delayed if it occurred more than 61 days postpartum. A short initial luteal phase consisted of progesterone concentrations which exceeded 3 ng/ml for fewer than 4 sequential measurements. Temporal progesterone patterns were classified as: 1) Normal cyclicity; 2) Cessation of luteal activity; 3) Prolonged luteal activity; 4) Erratic phase: failure to conform to 1, 2 or 3. Data concerning parity, previous calving interval, breeding values, calf birth and 200-d weight were obtained from the Norwegian Beef Cattle Recording System database. RESULTS: The mean (SD) OLA was 41 d (20). Parity and calf birth weight were inversely correlated with OLA. Delayed OLA occurred in 14.4% of lactations. A short first luteal phase occurred in 61.5% of lactations, but this was unrelated to irregular luteal phase occurrence, pregnancy or DO. Irregular luteal phases occurred in 22% of lactations. The irregularities were: prolonged luteal phase (11%); cessation of luteal activity (5%); erratic luteal activity (6%). Early OLA was associated with prolonged luteal phases. DO was positively correlated with irregular luteal phases and negatively correlated with calf 200-d weight. CONCLUSIONS: This study demonstrates that irregular luteal phases negatively affect reproductive performance in purebred beef suckler cattle. A moderate incidence of irregular luteal phases was seen in the study population. Whilst a positive relationship was seen between OLA and DO, unfavourable associations between early OLA and incidence of irregular luteal phases should be considered when developing breeding programmes.

Reproductive performance, udder health, and antibiotic resistance in mastitis bacteria isolated from Norwegian Red cows in conventional and organic farming.

BACKGROUND: The objectives of this study were to investigate whether there were differences between Norwegian Red cows in conventional and organic farming with respect to reproductive performance, udder health, and antibiotic resistance in udder pathogens. METHODS: Twenty-five conventional and 24 organic herds from south-east and middle Norway participated in the study. Herds were matched such that geographical location, herd size, and barn types were similar across the cohorts. All organic herds were certified as organic between 1997 and 2003. All herds were members of the Norwegian Dairy Herd Recording System. The herds were visited once during the study. The relationship between the outcomes and explanatory variables were assessed using mixed linear models. RESULTS: There were less > 2nd parity cows in conventional farming. The conventional cows had higher milk yields and received more concentrates than organic cows. Although after adjustment for milk yield and parity, somatic cell count was lower in organic cows than conventional cows. There was a higher proportion of quarters that were dried off at the herd visit in organic herds. No differences in the interval to first AI, interval to last AI or calving interval was revealed between organic and conventional cows. There was no difference between conventional and organic cows in quarter samples positive for mastitis bacteria from the herd visit. Milk yield and parity were associated with the likelihood of at least one quarter positive for mastitis bacteria. There was few S. aureus isolates resistance to penicillin in both management systems. Penicillin resistance against Coagulase negative staphylococci isolated from subclinically infected quarters was 48.5% in conventional herds and 46.5% in organic herds. CONCLUSION: There were no large differences between reproductive performance and udder health between conventional and organic farming for Norwegian Red cows.

Effects of gestational and lactational exposure to low doses of PCBs 126 and 153 on anterior pituitary and gonadal hormones and on puberty in female goats.

The aim of the present study was to investigate if environmental doses of PCB 153 and PCB 126 could produce effects in a controlled animal model. Possible adverse effects on the hypothalamic-pitutitary-gonadal axis were examined by measuring gonadotrophins and gonadal steroid hormone concentrations in goat kids exposed during gestation and lactation. The concentrations of PCB 153 and PCB 126 in adipose tissue in the goat kids 9 months post-partum were 5800 ng/g (fat-weight, range; 2900-12700 ng/g) and 0.49 ng/g (fat-weight, range; 0.28-0.80 ng/g), respectively. The pre- and post-pubertal plasma concentrations of luteinizing hormone (LH), follicle stimulating hormone (FSH), prolactin (Prl) and progesterone (P4) were analysed. LH, FSH, Prl, and P4 were also measured during an induced oestrus cycle. The prepubertal LH concentration was significantly lower, the puberty was delayed and the P4 level during the luteal phase of an estrous cycle was higher in the group exposed to PCB 153. No significant effect of PCB 153 exposure was found on Prl and FSH. PCB 126 did not produce any effects at the exposure level tested in this study. In conclusion, perinatal exposure to PCB 153 affected the reproductive function and the puberty maturation in goats.