Factors affecting milk yield,milk fat,bacterial score,and bulk tank somatic cell count of dairy farms in the central region of Thailand

A study was conducted to determine the effects of season, farm location, and farm size on farm milk yield (FMY), average milk yield per cow (AYC), milk fat, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the districts of Kaeng Khoi, Muaklek, Pak Chong, and Wang Muang. Collection of data was at the farm level; individual animal records were unavailable. A total of 967,110 daily farm milk yield, 58,575 milk fat and bacterial score, and 24,109 BTSCC records from 1,034 farms were collected from July of 2003 to June of 2006. There were three seasons: rainy, summer and winter. Farms were categorized into small, medium, and large according to the number of cows milked per day. Results showed that FMY and AYC were higher (p <0.05) in winter and lower in the summer and rainy seasons. In addition, the majority of small size farms had higher (p < 0.05) AYC and milk fat values, and lower bacterial score and BTSCC values than medium and large size farms.     

Incidence of clinical mastitis on farms with low somatic cell counts in bulk milk

A total of 1140 clinical cases of mastitis, with at least one inflamed quarter, were reported on 125 farms with somatic cell counts in bulk milk less than 150,000/ml. The average annual incidence was 17.9 cases per 100 cows and ranged from none to 80 cases per 100 cows. The microorganisms most frequently isolated were Escherichia coli (16.2 per cent), coagulase negative staphylococci (13.0 per cent), Staphylococcus aureus (9.6 per cent) and Streptococcus uberis (8.0 per cent). Only two cases of Streptococcus agalactiae were found. As the incidence of clinical mastitis increased, the proportion of S aureus also increased, while the proportions of E coli, S uberis and Streptococcus dysgalactiae remained about the same. Most of the clinical cases of mastitis occurred in early lactation, in November, December and January. However, after correction for the number of calvings per month, the incidence of mastitis was highest in the early summer months.     

Dynamics and regulation of bulk milk somatic cell counts.

Somatic cell count (SCC) in milk is inversely related to dairy cow productivity and milk quality. In an effort to improve product quality, and indirectly farm productivity, regulatory limits on somatic cell counts have been established by many of the major dairy producing countries. The purpose of this paper was to assess the impact of regulations on bulk milk somatic cell counts in Ontario and to assist producers in meeting regulatory limits through development of prediction models. Through the use of a transfer function model, provincial SCC was found to have dropped by approximately 60,000 as a result of the reduction program. Limits of the regulatory program, seasonality and herd characteristics were found through time series cross-sectional models to have an impact on prediction of SCC at the farm level, but the major influence was historical SCC levels.     

Seasonal variation of bulk milk somatic cell counts in UK dairy herds: investigations of the summer rise

Individual cow somatic cell count (SCC) patterns were explored over a one year period in 33 dairy herds to investigate the reason for a summer rise in bulk milk somatic cell counts (BMSCC). Cow test day somatic cell counts were categorised according to the magnitude of change since the previous test day reading, to examine which categories were responsible for the summer increase. Multilevel models using Markov chain Monte Carlo methods were specified to estimate the number of somatic cells/ml produced by different cell count categories. Stage of lactation and parity were accounted for in the models. There was an increase in the proportion of cows that remained above 200,000 cells/ml for two consecutive recordings in summer and this group of cows were responsible for 70.8% of the increase in somatic cells/ml produced from May to September compared with October to March. There was no evidence that a greater new infection rate (somatic cell counts moving from below 100,000 cells/ml to over 200,000 cells/ml) contributed to the increased summer bulk milk somatic cell counts. There was no indication that a general small increase in all somatic cell counts played an important role in the increased summer somatic cell counts. Markov chain Monte Carlo methods provided a valuable and flexible platform for parameter estimation in reasonably complex multilevel models.     

Investigation of risk factors for clinical mastitis in British dairy herds with bulk milk somatic cell counts less than 150,000 cells/ml

A sample of dairy farms in Great Britain with a monthly bulk milk somatic cell count of less than 150,000 cells/ml was enrolled into a 12-month prospective study. At the end of the study, a questionnaire on milking practice and other farm management practices was sent to the 482 farmers who had collected data on the occurrence of mastitis throughout the 12 months. The response rate was 93 per cent. The reported mean incidence of clinical mastitis was 36.9 cases per 100 cow-years. Factors associated with an increase in the incidence of clinical mastitis were cleaning out the straw yard less frequently than every six weeks, more than 5 per cent of cows leaking milk outside the parlour, checking the foremilk, wearing gloves during milking, an average annual milk yield of more than 7000 litres per cow, dipping or spraying teats before milking and keeping milk with a high somatic cell count out of the bulk tank. Factors associated with a decrease in the incidence of clinical mastitis were using a cloth to dry the teats after washing them as part of premilking preparation, using calving boxes for less than 40 per cent of calvings, and using both cubicles and straw yards to house dry cows, as opposed to other housing.     

Intramammary infections and risk factors for clinical mastitis in herds with low somatic cell counts in bulk milk

Ten herds with low somatic cell counts in bulk milk had an incidence of clinical mastitis of only 2.2 per 100 cows whereas 10 other herds with similarly low cell counts had an incidence of 53.6 per 100 cows. The major pathogens in the herds with a high incidence were Escherichia coli, Streptococcus uberis, Staphylococcus aureus and the coagulase-negative staphylococci. The percentage of uninfected quarters in the herds with a high incidence of clinical mastitis was 21.4 per cent compared with 12.2 per cent in the herds with a low incidence of clinical mastitis. The prevalence of coagulase-negative staphylococci, Corynebacterium bovis and Micrococcus species was higher in the herds with a low incidence of clinical mastitis. There was a significant linear relationship between the percentage of uninfected quarters and the incidence of clinical mastitis in the herds with a high incidence of clinical mastitis. In herds with a low incidence of clinical mastitis significantly less teat disinfection after milking was practised. The results suggest that infections with minor pathogens tend to protect cows against mastitis, and that teat disinfection after milking may increase the percentage of uninfected quarters and lead to an increased risk of clinical mastitis in herds with low somatic cell counts in bulk milk.     

Dietary factors associated with milk somatic cell counts in dairy cows in Brittany, France

A survey (Enquête Ecopathologique Bretagne) was conducted in France for 4 years (1986–1990) in 48 commercial dairy herds (25–80 cows per herd) located in Brittany. Three groups of herd-years were made up to study peripartum dietary factors associated with milk somatic cell counts in the early lactation period (ECC). The first group included 20 herd-years with high ECC (over 400 000 cells ml⁻¹). The second group included herdyears with medium ECC (n = 20, median ECC 222 000) and the last group herd-years with low ECC (n = 20, median ECC 95 000). Herd data (components of the diet, milk yield and reproduction parameters, clinical diseases, biochemical and hematological indicators, body and dirtiness scores) were analyzed using discrimination by barycentric analysis. Two separate analysis were conducted according to study period (LG period, last 60 days of gestation; EL period, first 60 days of lactation).

The high ECC group had the following characteristics: (1) higher plasma gamma glutamyl transferase levels in the LG period; (2) higher quantities of cereal-based concentrates in the diet in the EL period; (3) shorter durations of feeding with Italian rye grass silage in the EL period. The relevance of the risk factors for high ECC are discussed with reference to dietary linolenic acid/linoleic acid ratio (through the synthesis of leukotrienes as chemotactic agents for the polymorphonuclear leukocytes), dietary energy supplies and liver fluke infestation in the herds. We speculate that nutritional factors could modulate the leukocyte activity in the milk and that supplementations with certain polyunsaturated fatty acids would be able to prevent the development of inflammation in the udder.     

Study of clinical mastitis in British dairy herds with bulk milk somatic cell counts less than 150,000 cells/ml

A 12-month prospective study of clinical mastitis was conducted in 482 British dairy herds with a bulk milk somatic cell count (BMSCC) of less than 150,000 cells/ml. The mean proportion of cows in the herd with clinical mastitis was 23.1 per cent (range 0 to 80), with a mean of 1.50 quarter cases per cow. The mean incidence rate of clinical mastitis was 36.7 quarter cases per 100 cow years (range 0 to 208.2). Twelve per cent of the quarter cases showed systemic signs, including inappetence and severe lethargy. Over 22 per cent of quarter cases occurred in the first seven days of lactation and over 50 per cent occurred in the first 90 days of lactation. Cluster analysis indicated that the main difference between herds with a low and average incidence of mastitis was the proportion of clinical cases occurring in the first seven days of lactation, 14 per cent compared with 44 per cent, respectively. The risk of severe clinical mastitis compared with mild clinical mastitis decreased significantly as the individual cow somatic cell count (SCC) in the month before clinical mastitis was diagnosed increased.     

Risk factors for smallholder dairy cattle mortality in Tanzania

A retrospective cross-sectional study of mortality was conducted on smallholder dairy farms in 2 separate regions (Iringa and Tanga) of Tanzania during the period of January to April 1999. A total of 1789 cattle from 400 randomly sampled smallholder dairy farms (200 each from Iringa and Tanga regions) were included in the study. These animals contributed a total risk period of 690.4 and 653.95 years for Tanga and Iringa, respectively. The overall mortality rates were estimated to be 8.5 and 14.2 per 100 cattle years risk for Tanga and Iringa regions, respectively; 57.7% of the reported deaths were of young stock less than 12 months old; 45% of reported young stock deaths (< or = 12 months old) were due to tickborne diseases, mainly East Coast Fever (ECF) and anaplasmosis. Disease events including ECF were reported to occur in all months of the year. Survival analysis using Cox proportional hazard models indicated that, in both regions, death rate and risk was higher in young stock less than 12 months than in older animals (relative risk RR = 4.92, P < 0.001 for Iringa; RR = 5.03 P = 0.005 for Tanga). In the Tanga region reported mortality rates were significantly higher for male animals (RR = 3.66, P = 0.001) and F2 compared with F1 animals (RR = 3.04, P = 0.003). In the Iringa region, reported mortality rates were lower for cattle on farms where the owner had attended a dairy development project training course (RR = 0.47, P = 0.012). Farms located in Iringa urban district and Pangani were associated with higher risk (mortality risk 21% for Iringa urban and 34% for Pangani). Our findings suggest that timely health and management interventions on these factors are necessary to alleviate losses from disease and emphasise that understanding variation in mortality risk within a population can enhance early response to potential outbreaks, reducing losses.     

Total and differential bulk cow milk somatic cell counts and their relation with lipolysis

Endocrine system plays a major role in the control of reproductive functions which are regulated by the hypothalamus–pituitary–gonad axis and its interactions. FSH and LH receptor genes are expressed at the gonads and GnRH receptor gene is expressed at the anterior pituitary gland. Misense mutations of the FSH, LH or GnRH receptors, activating or inactivating their functions in mammals, are potentially useful to allow the understanding of the role of this group of gonadotropins in reproductive phenotypes as early puberty and birth interval length. In the present study, polymorphisms in bovine exon 11 and 3′UTR of LHR, exon 10 and 3′UTR of FSHR and GnRHR genes were characterized with some of them resulting in changes in the aminoacidic chain. These polymorphic sites were found in a Bos taurus indicus (Nellore) female population by means of PCR–SSCP and DNA sequencing. Association between nucleotidic/aminoacidic changes and early puberty were determined by Chi-square analysis. It was found association between FSHR 3′UTR polymorphisms at position 2181, 2248 and 2249 bp and early puberty phenotype (p < 0.05). The presence of these new molecular markers might be considered in further studies to validate its correlation with early puberty or other reproduction associated phenotypes in cattle breeds.     

Radioimmunoassay of milk progesterone as a tool for fertility control in smallholder dairy farms

This study focused on the use of radioimmunoassay of progesterone in milk for the diagnosis of post-partum ovarian cyclicity and accurate detection of oestrus and non-pregnancy in cows in the artificial insemination (AI) programme in Bangladesh. In Investigation 1, milk samples were collected on day 0 (day of AI), day 9–13 and day 21–24 from 444 milking cows of various breeds presented for the first post-partum insemination by 413 farmers living at 182 villages/regions in Mymensingh District from 6 AI centres and sub-centres. Each cow was then examined three times after each AI until it stopped returning to oestrus. Sixty to 90 days after the last AI, the cows were examined per rectum to confirm the pregnancy. Milk progesterone data on day 21–24 contributed to a clear diagnosis with respect to non-pregnancy in 100% cows, indicating a possible use of this progesterone assay for identifying non-pregnant cows in AI programmes. In Investigation 2, milk progesterone was monitored two times in a month with a 10-day interval in 88 cows. The samples were taken between 10 days after calving and the first detected oestrus, followed by two more samples 10 days apart. The proportion of cows accurately detected in oestrus was 30%. Another 30% were stated to be in oestrus when they were not (false positive) and 40% were not detected when they were in oestrus (false negative). The mean intervals between calving and oestrus and between calving luteal activity were 40 to 362 days (median = 120, n = 82) and 34 to 398 (median = 111, n = 64) days, respectively. The body condition scores at calving and at the initiation of luteal activity influenced the interval between calving and luteal activity (p < 0.05). Cows suckled twice daily initiated luteal activity earlier than their counterparts suckled several times daily (p < 0.05). Determination of progesterone in milk on day 21–24 is a good means for detecting non-pregnant cows.     

Effects of systematic influences and intramammary infection on differential and total somatic cell counts in quarter milk samples from dairy cows

Effects of bacteriological status, stage of lactation, parity and season of sampling on differential and total somatic cell counts were estimated in quarter milk samples taken from 39 dairy cows. Log somatic cell count was affected by the bacteriological status of the quarter, as well as by the bacteriological status of adjacent quarters. Differential cell counts were affected by presence or absence of pathogens in the quarters themselves, but not by the bacteriological status of the adjacent quarters. Log somatic cell count was clearly affected by stage of lactation, due mainly to physiological variation, but possibly also accentuated by variation in infection rates throughout lactation. With the exception of early lactation, little physiological variation throughout lactation was detected for differential cell counts. Presence of infections seemed to have some indirect effect on trends throughout lactation as regards percentages of granulocytes and monocytes. Variation in somatic cell counts due to parity could be explained by variation in infection rates, rather than being physiologically determined.     

Risk factors for Coxiella burnetii antibodies in bulk tank milk from Danish dairy herds

The aim was to identify risk factors associated with Coxiella burnetii antibody positivity in bulk tank milk (BTM) samples from 100 randomly selected Danish dairy cattle herds. Antibody levels were measured by an enzyme-linked immuno-sorbent assay. Before testing the herds, the farm managers were interviewed about hired labour, biosecurity, housing and herd health during the 12 months prior to the study. Variables considered important for C. burnetii antibody positivity in multivariable logistic regression analysis included the sharing of machines between farms (OR = 3.6), human contacts (OR = 4.2), artificial insemination by other people than artificial insemination technicians (OR = 7.7), routine herd health contract with the veterinarian (OR = 4.3) and hygiene precautions taken by veterinarians (OR = 5). In addition, herd size, hired labour, trading of cattle between farms, quarantine and use of calving and disease pens also showed significant association in univariable analysis. This study demonstrates that strict biosecurity is important for the prevention of infections with C. burnetii.     

Risk factors and indicators of reduced welfare of grazing dairy cows from selected smallholder dairy farms in Midlands Province,Zimbabwe

Zimbabwe’s smallholder dairying faces many challenges that affect the welfare of dairy cows; however, the status of this welfare has not yet been determined. A cross-sectional study was conducted in Midlands Province on 41 active smallholder dairy farms with 86 cows in winter and summer to determine the risk factors and indicators to impaired cow welfare. These objectives were achieved using farmer questionnaires and direct observations. Eleven percent of the observed cows were severely lame in summer while only 5% were severely lame in winter. Lameness was significantly associated with season, absence of shade, breed, and low dipping frequency; 58% of the cows had low body condition scores (BC?<?3) and this low BC was associated with low frequency of protein (p?=?0.002) and vitamin (p?=?0.012) supplementation recorded in more than 52% of the farms visited. In winter, only 11% of the observed cows were heavily soiled (score 3), while in summer 64% of the cows were heavily soiled and this was associated with slurry accumulation in more than 80% of the observed cattle pens as well as the study season (p?<?0.001). A quarter (26%) of the studied animals had visible teat lesions on the teat skin and this was associated with the type of lubricant used (p?=?0.011). Only 34% of the cows allowed an approaching stockman to touch them and this was associated with shouting (p?=?0.012) and whipping of cows (p?=?0.002). The study concluded that welfare of dairy cows was poor in most of the smallholder dairy farms studied.     

Record keeping,genetic selection,educational experience and farm management effects on average milk yield per cow,milk fat percentage,bacterial score and bulk tank somatic cell count of dairy farms in the Central region of Thailand

A study was conducted to estimate the record keeping, genetic selection, educational, and farm management effects on average milk yield per cow (AYC), milk fat percentage, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the provinces of Saraburi and Nakhon Ratchisima and were members of the Muaklek dairy cooperative. Records from individual animals were unavailable. Thus, farm records of milk yield, milk fat percentage, bacterial score, and BTCCC were collected from July 1, 2003 through June 30, 2006. Additional record keeping, genetic selection, education, and farm management information was collected through a questionnaire in May of 2006. Data from the Muaklek dairy cooperative and the questionnaire were then merged by a farm identification number. A single trait mixed model was used to analyze AYC, milk fat percentage, and BTSCC, while a log linear model was used to analyze bacterial score. Results showed that farms that kept records on individual animals had higher (P < 0.05) milk fat percentages and lower bacterial scores than farms that did not. Farms that used genetic information (EBV) and phenotypes when selecting sires were higher (P < 0.05) for milk fat percentage than farms that used only phenotypes and personal opinion. Farms milking cows with a single unit milking machine and by hand, had higher (P < 0.05) bacterial scores and BTSCC than farms using only a single or multi unit machine. Overall farms that kept individual animal records, used EBV when selecting sires, used a single method for collecting milk, and used family labor achieved higher performance from their herds than farms that did not.     

Cell counts in bulked milk supplies from dairy farms of northern Nigeria

Somatic cells in 596 milk samples collected from bulked supplies of 3 northern Nigeria dairy farms were counted by an electronic method following a standard method for the preparation of the milk samples. Mean somatic cell counts per ml indicating low level of infection were 158,597, 166,742 and 155,032 for the 3 farms, without any significant differences. Mean somatic cell counts per ml indicating herd mastitis averaged 354,768 +/- 66,348 and the pathogenic organisms isolated were Escherichia coli and Staphylocucus aureus. Counts useful for future regular monitoring of somatic cells in bulked milk supplies in northern Nigeria are presented.     

The association between high milk somatic cell counts in the first lactation and somatic cell counts in the second lactation

With the advent of web-based recording and analysis systems, individual cow composite somatic cell count (SCC) data are being increasingly used for decision support in mastitis control at both the individual cow and herd level. SCC data from first and second lactation dairy cows (n=1912) from 12 farms were analysed using multinomial logistic regression to investigate possible associations between high SCC patterns in the first lactation and the subsequent lactation. Animals with three non-consecutive counts >200,000 cells/mL in their first lactation were significantly more likely to have three non-consecutive counts >200,000 cells/mL (OR 3.11; 95% CI 1.72-5.62) or three consecutive counts >200,000 cells/mL (OR 2.00; 95% CI 1.09-3.68) in their second lactation. Similarly animals with three consecutive counts >200,000 cells/mL in their first lactation were significantly more likely to have three non-consecutive counts >200,000 cells/mL (OR 1.90; 95% CI 1.13-3.19) or three consecutive counts >200,000 cells/mL (OR 4.14; 95% CI 2.81-6.08) in their second lactation. These findings suggest that patterns established in the first lactation may have an impact on udder health in the subsequent lactation. However, simulation modelling of positive predictive values for the first lactation cell count patterns as predictors of second lactation patterns demonstrated that, at prevalences likely to be encountered on UK dairy farms, the associations were not a sufficient basis for major management decisions such as culling.