Holstein Dairy Farms Research Articles

Prediction of individual total amino acids and free amino acids in Chinese Holstein cows milk using mid-infrared spectroscopy and their phenotypic variability

Establishing a high-throughput detection technology for amino acid (AA) content in milk using mid-infrared (MIR) spectroscopy has profound implications for enhancing nutritional value of milk, identifying superior milk sources, producing specialty dairy products, and expanding Dairy Herd Improvement (DHI) metrics. The aim of this study was to evaluate the effectiveness of MIR spectroscopy in predicting the content of 15 individual total AA (TAAs) and 16 free AA (FAAs) in bovine milk as well as to investigate the major factors affecting the phenotypic variability of AA content. From March 2023 to March 2024, 513 milk samples were collected from 10 Holstein dairy farms in China and analyzed using Bentley spectrometers for MIR measurements. Their TAAs and FAAs concentrations were assessed through an AA autoanalyzer. Separate quantitative prediction models were developed for each AA using partial least squares regression; accuracy of prediction was assessed using Cow-independent external validation (CEV) and Farm-independent external validation (FEV) set. In CEV, the ratio of performance to deviation (RPD) of the TAAs models ranged from 1.45 (Ser) to 2.19 (Leu), while the FAA models ranged from 1.15 (Ser) to 2.44 (Met). In FEV, the RPD of the TAAs models ranged from 0.98 (Met) to 1.76 (Asp, Glu, and Ala), and the FAAs models ranged from 0.33 (Phe) to 1.23 (Asp and Tyr). For farms included in the calibration set, MIR spectroscopy provided a rough quantitative estimation for 4 individual TAAs (Ile, Leu, Glu, and Tyr) and 2 FAAs (Met and His), as well as a qualitative determination for high and low values in 9 individual TAAs (Phe, Met, Val, Lys, Thr, Asp, Ala, His, and Arg). For farms outside the calibration set, MIR spectroscopy could only distinguish between high and low contents for 5 individual TAAs (Glu, Asp, Ala, Leu, and Arg). Phenotypically, the variation pattern in TAAs contents mirrored that of protein, while FAAs did not show a clear trend, though mastitis led to a significant elevation of FAAs in milk (p < 0.05). Overall, the application of MIR spectroscopy can be considered very promising for a low-cost, rapid, large-scale assessment of individual TAAs and FAAs contents in milk. After refinement, some models could potentially be incorporated into DHI, which would greatly benefit the milk production and food industries.

Evaluating the performance of herd-specific long short-term memory models to identify automated health alerts associated with a ketosis diagnosis in early-lactation cows

The growing use of automated systems in the dairy industry generates a vast amount of cow-level data daily, creating opportunities for using these data to support real-time decision-making. Currently, various commercial systems offer built-in alert algorithms to identify cows requiring attention. To our knowledge, no work has been done to compare the use of models accounting for herd-level variability on their predictive ability against automated systems. Long Short-Term Memory (LSTM) models are machine learning models capable of learning temporal patterns and making predictions based on time series data. The objective of our study was to evaluate the ability of LSTM models to identify a health alert associated with a ketosis diagnosis (HAK) using deviations of daily milk yield, milk FPR, number of successful milkings, rumination time, and activity index from the herd median by parity and DIM, considering various time series lengths and numbers of d before HAK. Additionally, we aimed to use Explainable Artificial Intelligence method to understand the relationships between input variables and model outputs. Data on daily milk yield, milk fat-to-protein ratio (FPR), number of successful milkings, rumination time, activity, and health events during 0 to 21 d in milk (DIM) were retrospectively obtained from a commercial Holstein dairy farm in northern Indiana from February 2020 to January 2023. A total of 1,743 cows were included in the analysis (non-HAK = 1,550; HAK = 193). Variables were transformed based on deviations from the herd median by parity and DIM. Six LSTM models were developed to identify HAK 1, 2, and 3 d before farm diagnosis using historic cow-level data with varying time series lengths. Model performance was assessed using repeated stratified 10-fold cross-validation for 20 repeats. The Shapley additive explanations framework (SHAP) was used for model explanation. Model accuracy was 83, 74, and 70%, balanced error rate was 17 to 18, 26 to 28, and 34%, sensitivity was 81 to 83, 71 to 74, and 62%, specificity was 83, 74, and 71%, positive predictive value was 38, 25 to 27, and 21%, negative predictive value was 97 to 98, 95 to 96, and 94%, and area under the curve was 0.89 to 0.90, 0.80 to 0.81, and 0.72 for models identifying HAK 1, 2, and 3 d before diagnosis, respectively. Performance declined as the time interval between identification and farm diagnosis increased, and extending the time series length did not improve model performance. Model explanation revealed that cows with lower milk yield, number of successful milkings, rumination time, and activity, and higher milk FPR compared with herdmates of the same parity and DIM were more likely to be classified as HAK. Our results demonstrate the potential of LSTM models in identifying HAK using deviations of daily milk production variables, rumination time, and activity index from the herd median by parity and DIM. Future studies are needed to evaluate the performance of health alerts using LSTM models controlling for herd-specific metrics against commercial built-in algorithms in multiple farms and for other disorders.

Phenotypic and Genetic Analyses of Mastitis, Endometritis, and Ketosis on Milk Production and Reproduction Traits in Chinese Holstein Cattle.

Mastitis (MAS), endometritis (MET), and ketosis (KET) are prevalent diseases in dairy cows that result in substantial economic losses for the dairy farming industry. This study gathered 26,014 records of the health and sickness of dairy cows and 99,102 data of reproduction from 13 Holstein dairy farms in Central China; the milk protein and milk fat content from 56,640 milk samples, as well as the pedigree data of 37,836 dairy cows were obtained. The logistic regression method was used to analyze the variations in the prevalence rates of MAS, MET, and KET among various parities; the mixed linear model was used to examine the effects of the three diseases on milk production, milk quality, and reproductive traits. DMU software (version 5.2) utilized the DMUAI module in conjunction with the single-trait and two-trait animal model, as well as best linear unbiased prediction (BLUP), to estimate the genetic parameters for the three diseases, milk production, milk quality, and reproductive traits in dairy cows. The primary findings of the investigation comprised the following: (1) The prevalence rates of MAS, MET, and KET in dairy farms were 20.04%, 10.68%, and 7.33%, respectively. (2) MAS and MET had a substantial impact (p < 0.01) on milk production, resulting in significant decreases of 112 kg and 372 kg in 305-d Milk Yield (305-d MY), 4 kg and 12 kg in 305-d Protein Yield (305-d PY), and 6 kg and 16 kg in 305-d Fat Yield (305-d FY). As a result of their excessive 305-d MY, some cows were diagnosed with KET due to glucose metabolism disorder. The 305-d MY of cows with KET was significantly higher than that of healthy cows (205 kg, p < 0.01). (3) All three diseases resulted in an increase in the Interval from Calving to First Service (CTFS, 0.60-1.50 d), Interval from First Service to Conception (FSTC, 0.20-16.20 d), Calving Interval (CI, 4.00-7.00 d), and Number of Services (NUMS, 0.07-0.35). (4) The heritabilities of cows with MAS, MET, and KET were found to be low, with values of 0.09, 0.01, and 0.02, respectively. The genetic correlation between these traits ranged from 0.14 to 0.44. This study offers valuable insights on the prevention and control of the three diseases, as well as feeding management and genetic breeding.

Exploring herd-level perinatal calf mortality risk factors in eastern Canadian dairy farms

This closed cohort study aimed to identify the associations between dairy calf management practices and herd-level perinatal calf mortality risk. From February 2020 to June 2021, predominantly Holstein dairy farms in Québec (n = 1,832) and New Brunswick (n = 52), Canada, that were registered in the dairy herd improvement program were visited once. A questionnaire covering all aspects of precalving, calving, and colostrum management was administered. Data regarding perinatal mortality were retrieved from the dairy herd improvement program database for each farm for 2021. Perinatal mortality was calculated for each farm as the proportion of calves dead at birth or dying within 24 h after birth. A multivariable negative binomial model was used to assess herd-level factors associated with the risk of perinatal mortality. The final model included the lying surface in the calving area, the typical time to first colostrum intake, typical cow-calf contact time, the proportion of males born, the proportion of assisted calvings, and herd size. Herd-level perinatal mortality risk ranged from 0% to 38.1% (mean ± SE = 7.6% ± 0.1%). A greater proportion of males born, a higher proportion of assisted calvings, and delayed colostrum feeding were associated with increased herd-level perinatal mortality. Factors associated with a decreased herd-level perinatal mortality risk were having a typical cow-calf contact time between 7 and 12 h after calving compared with reduced cow-calf contact time, soft lying surfaces in the calving area compared with concrete and mat-lying surfaces, and an increased number of calvings per year. Our results show that although some of the significant risk factors are not well understood (i.e., calving area lying surface, typical cow-calf contact time), Canadian farmers could focus on the factors under their control (i.e., time to first colostrum feeding, proportion of difficult calvings, males born, and calvings per year) to reduce the risk of perinatal mortality. Future work should focus on qualitative research to understand the dairy farmer motivations and limitations to implementing practices identified in this and other studies to reduce perinatal mortality.

Sensor-based behavioral patterns can identify heat-sensitive lactating dairy cows

Heat stress impairs the health and performance of dairy cows, yet only a few studies have investigated the diversity of cattle behavioral responses to heat waves. This research was conducted on an Italian Holstein dairy farm equipped with precision livestock farming sensors to assess potential different behavioral patterns of the animals. Three heat waves, defined as at least five consecutive days with mean daily temperature-humidity index higher than 72, were recorded in the farm area during the summer of 2021. Individual daily milk yield data of 102 cows were used to identify “heat-sensitive” animals, meaning the cows that, under a given heat wave, experienced a milk yield drop that was not linked with other health events (e.g., mastitis). Milk yield drops were detected as perturbations of the lactation curve estimated by iteratively using Wood’s equation. Individual daily minutes of lying, chewing, and activity were retrieved from ear-tag-based accelerometer sensors. Semi-parametric generalized estimating equations models were used to assess behavioral deviations of heat-sensitive cows from the herd means under heat stress conditions. Heat waves were associated with an overall increase in the herd’s chewing and activity times, along with an overall decrease of lying time. Heat-sensitive cows spent approximately 15 min/days more chewing and performing activities (p < 0.05). The findings of this research suggest that the information provided by high-frequency sensor data could assist farmers in identifying cows for which personalized interventions to alleviate heat stress are needed.

Epidemiology of bovine colostrum production in New York Holstein herds: Cow, management, and environmental factors

Adequate supply of high-quality colostrum is essential for calf health. Colostrum production, at first milking, varies between animals and seasons, but herd-level and management associations with colostrum production have not been well described. Our objectives were to (1) describe colostrum production and colostrum handling practices and (2) to identify individual cow, herd management, and environmental factors associated with colostrum production. A convenience sample of 19 New York Holstein dairy farms (620 to 4,600 cows) were enrolled in this observational study to describe colostrum production and to evaluate cow, management, and prepartum environmental factors associated with colostrum yield and Brix %. Herd owners or managers were given a colostrum management questionnaire, and farm personnel recorded individual colostrum yield and Brix % for primiparous (PP; n = 5,978) and multiparous (MPS; n = 13,228) cows between October 2019 and February 2021. Temperature, relative humidity, and light intensity were measured by sensors placed in each farm's close-up dry cow pens for the entire length of the study. Median colostrum yield for each farm ranged from 2.5 to 7.6 kg for PP and 4.0 to 7.7 kg for MPS cows. Mean Brix % from each farm ranged from 22.2 to 27.9% for PP and 22.0 to 28.8% for MPS cows. Lowest colostrum yield from PP animals was associated with calf sex (female) and colostrum Brix % (≤22%). Greatest colostrum yield from MPS cows was associated with colostrum Brix % (≤22%), calf sex (twin), dry period length (>67 d), gestation length (283-293 d), an alive calf, second parity, previous lactation length (>344 d) and previous lactation 305-d mature equivalent milk yield (>13,091 kg), heat and humidity exposure area under the curve (AUC) 7 d before calving (>69.2 average temperature-humidity index per 30-min interval), and light intensity AUC 14 d before calving (>154.2 average lux per 15-min interval). Greatest colostrum Brix % from PP animals was associated with calf sex (male), an alive calf, and light intensity AUC 14 d before calving (≤64.0 average lux per 15-min interval). Greatest colostrum Brix % from MPS cows was associated with dry period length (>67 d), an alive calf, 305-d mature equivalent milk yield of previous lactation (≤15,862 kg), gestation length (274-282 d), colostrum yield (<6 kg), fifth or greater parity, and heat and humidity exposure AUC 7 d before calving (≤50.1 average temperature-humidity index per 30-min interval). Dairy producers can use this information to recognize the variation in colostrum production and alter colostrum management programs in anticipation of periods of low production or quality.

Joint Models to Predict Dairy Cow Survival from Sensor Data Recorded during the First Lactation.

Early predictions of cows' probability of survival to different lactations would help farmers in making successful management and breeding decisions. For this purpose, this research explored the adoption of joint models for longitudinal and survival data in the dairy field. An algorithm jointly modelled daily first-lactation sensor data (milk yield, body weight, rumination time) and survival data (i.e., time to culling) from 6 Holstein dairy farms. The algorithm was set to predict survival to the beginning of the second and third lactations (i.e., second and third calving) from sensor observations of the first 60, 150, and 240 days in milk of cows' first lactation. Using 3-time-repeated 3-fold cross-validation, the performance was evaluated in terms of Area Under the Curve and expected error of prediction. Across the different scenarios and farms, the former varied between 45% and 76%, while the latter was between 3.5% and 26%. Significant results were obtained in terms of expected error of prediction, meaning that the method provided survival probabilities in line with the observed events in the datasets (i.e., culling). Furthermore, the performances were stable among farms. These features may justify further research on the use of joint models to predict the survival of dairy cattle.

Implementation of hypocalcaemia prevention programmes in commercial dairy herds: From theory to practice

Hypocalcaemia prevention programmes have been widely studied in experimental settings, but their feasibility has not been assessed under field conditions. The main objective of this study was to evaluate, in the context of small dairy farms in western France, whether and how dairy farmers implement prevention programmes and manage the feeding of dry cows to prevent hypocalcaemia. Seventy-nine commercial Holstein dairy farms in Brittany (France) were enrolled in a qualitative study in 2019. We conducted in-person interviews with the farmers to 1) understand the rationale behind the type and seasonality of prevention programmes they implemented and 2) assess how closely they followed common recommendations when implementing them. Most farmers (80 %) used at least one prevention programme, especially supplying a mineral mix formulated to meet the needs of dry cows in late gestation (53 %), acidifying the diet in late gestation (37 %), and supplying calcium at calving (oral or injectable form, 37 %). The use of programmes depended on whether the diet composition varied throughout the year. Among farmers who provided an acidified diet, 25 % did not supply a specific mineral mix to dry cows to ensure an adequate amount of P, Ca, and Mg, which could decrease the effectiveness of the acidification programme. A lack of reliability in feeding practices, such as not weighing feed or not delivering feed frequently enough, was identified for 61 % of contributing farms. Management practices could result in supplying an unsuitable amount of P, Ca, or Mg immediately before calving; for example, inappropriate batching practices around calving were identified for 22 % (cows) to 32 % (heifers) of farms. In addition, nearly all contributing farmers had no processes in place to monitor the effectiveness of the programmes implemented. Reasons for this overall lack of compliance should be explored.

Association of housing and management practices with milk yield, milk composition, and fatty acid profile, predicted using Fourier transform mid-infrared spectroscopy, in farms with automated milking systems

Milk fatty acid (FA) profile can be divided into (1) de novo (C4-C14) that are synthesized in the mammary gland; (2) preformed (≥C18) that are absorbed from blood and originate from mobilized adipose tissues or dietary fat; and (3) mixed (C16), which have both origins. Our objectives were to describe the FA profile, as predicted using Fourier transform mid-infrared spectroscopy, of bulk tank milk from automated milking system (AMS) farms and to assess the association of management and housing factors with the bulk tank milk composition and FA profile of those AMS farms. The data used were collected from 124 commercial Canadian Holstein dairy farms with AMS, located in the provinces of Ontario (n = 68) and Quebec (n = 56). The farms were visited once from April to September 2019, and information were collected on barn design and herd management practices. Information regarding individual cow milk yield (kg/d), days in milk, parity, and the number of milking cows were automatically collected by the AMS units on each farm. These data were extracted for the entire period that the bulk tank milk samples were monitored, from April 2019 to April 2020 in Quebec and from August 2019 to May 2020 in Ontario. Across herds, milk yield averaged (mean ± standard error) 35.9 ± 0.4 kg/d, with 3.97 ± 0.01% fat and 3.09 ± 0.01% protein, whereas FA profile averaged 26.2 ± 0.1, 33.1 ± 0.1, and 40.7 ± 0.2 g/100 g of FA for de novo, mixed, and preformed, respectively. The FA yield averaged 0.34 ± 0.01, 0.44 ± 0.01, and 0.54 ± 0.01 kg/d for de novo, mixed, and preformed, respectively. Multivariable regression models were used to associate herd-level housing factors and management practices with milk production, composition, and FA profile. Milk yield was positively associated with using a robot feed pusher (+2.1 kg/d) and the use of deep bedding (+2.6 kg/d). The use of a robot feed pusher, deep bedding, and greater stall raking frequency were positively associated with greater yield (kg/d) of de novo, mixed, preformed, and de novo + mixed FA. Use of deep bedding was negatively associated with concentration of fat, de novo FA, mixed FA, and de novo + mixed FA, expressed in grams per 100 g (%) of milk. A wider lying alley width (≥305 cm) was associated with a greater concentration (g/100 g of milk) of de novo and de novo + mixed FA. Greater frequency of partial mixed ration delivery (>2×/d vs. 1 and 2×/d) was positively associated with a greater proportion (g/100 g of FA) of de novo, mixed, and de novo + mixed FA and negatively associated with the proportion of preformed FA. Overall, these associations indicated that bulk tank FA profile can be used as a tool to monitor and adjust management and housing in AMS farms.

Environmental factors affecting milk composition in Holstein cattle breed

The incidence of mastitis in dairy herds is one of the main difficulties faced by dairy farmers, with a negative effect on the productivity of the herd and the welfare of the animals. Somatic cell count in milk is an indicator of udder health and frequency of clinical and subclinical mastitis incidence in dairy herds, and it is also often used to determine quality payments to dairy producers. Milk urea can be an indicator of the nutritional status of the dairy cows. The interpretation of these parameters assists in making important management decisions with regards to the health status and nutrition of dairy cattle. The objective of this study was to identify and evaluate environmental factors (farm, season, parity and stage of lactation) which affect the milk production and composition of Holstein breed, using field data. The presented research included 25,460 individual milk samples which were analysed as part of the Dairy Herd Improvement program, from 11 Holstein dairy farms in the region of Vojvodina, Northern Serbia. Analyses of raw milk samples were carried out on the FOSS instruments - CombiFossTMFT+, a combination instrument consisting of the MilcoScanTMFT+ and the FossomaticTMFC. Statistical data processing was carried out by applying General Linear Model procedure, Statistics 13. Farm, season of milk control, parity and stage of lactation were included in the models as fixed effects. Significant differences in milk urea concentrations and somatic cell count were observed between farms (P&lt;0.01), seasons (P&lt;0.01), parity (P&lt;0.01) and stage of lactation (P&lt;0.01). Results showed that there were a highly significant (P&lt;0.01) positive relationships between milk urea (MU) concentration and milk yield, MU and milk fat content, and between MU and solids non-fat (SNF), also between somatic cell count (SCC) and milk fat content, between SCC and protein content, as well as in between SCC and SNF. Highly significant negative relationships were found between milk urea and protein content and SCC, and between SCC and daily milk yield and lactose content. Proper analyses and interpretation of obtained results of milk samples obtained within the Dairy Herd Improvement program could contribute to better health management on the farms and it could have a positive impact on composition and nutritional value of milk, as well as on milk safety. It would be important to carry out further research in order to facilitate the detection of subclinical mastitis with MU as a potential indicator.

Short communication: The relationship between dietary particle size and undegraded neutral detergent fibre in lactating dairy cows: A prospective cohort observational study

Physically effective NDF (peNDF) and undegraded aNDF at 240 h (uNDF.240) are important parameters for characterizing NDF in fibre evaluation and are associated with dietary physical form and fibre digestibility characteristics. A new concept that combines peNDF and uNDF.240, physically effective uNDF.240 (peuNDF.240 = pef × uNDF.240), was recently established. The peuNDF.240 value allows determination of dry matter intake (DMI), and the productive response of cows even in the absence of variation in DMI or when cows are fed rations with low uNDF.240 and high peNDF or rations with high uNDF.240 and more finely chopped fibre. The aim of this study was to improve our understanding of the relationships between dietary uNDF.240 content to other fibre fractions, average cow DMI, gross feed efficiency, and milk yield at the farm level. Furthermore, the relation between peuNDF.240 and the productive response of cows was also investigated at the farm level. In the Po’ Valley, which is a representative area for dairy production in Italy, a cohort of 22 Holstein dairy farms was monitored over two years (2019–2020). Information regarding average cow DMI, milk yield, and ration composition was obtained through interviews with farmers, and feed samples were collected and chemically analysed. Farms were classified according to their dietary uNDF.240 (% of DM) content: low (uL) ≤ 8.29 or high (uH) > 8.29. Farms with low dietary uNDF.240 used less alfalfa forage as a fibre source compared with farms with high dietary uNDF.240 (6.27 vs. 15.5 % of DM) and showed higher average milk yield (35.9 vs. 33.6 kg/cow/day, respectively) and similar DMI (23.9 vs. 24.3 kg/cow/day, respectively). Dietary peuNDF.240 was negatively related to milk yield (milk yield = 47.4 – 1.87 peuNDF.240, R2 = 0.62, adjusted R2 = 0.60, residual standard error (RSE) = 1.87, P = 0.001) and gross feed efficiency (gross feed efficiency = 1.96 – 0.08 peuNDF.240, R2 = 0.65, adjusted R2 = 0.64, RSE = 0.07, P = 0.001). The results of this study have practical significance for farmers, as they suggest that the inclusion of low digestible forages in the ration (i.e., late-harvested alfalfa characterized by high uNDF.240) may require more fine shredding to reduce the overall value of peuNDF.240 and increase cow production.

A calf-level study on colostrum management practices associated with adequate transfer of passive immunity in Québec dairy herds

The objective of this study was to identify the calf-level colostrum management practices associated with an adequate transfer of passive immunity (TPI; defined as serum Brix refractance ≥8.4% in the first week of life) in small-sized herds. A total of 818 calves from 61 commercial Holstein dairy farms were included in this observational cross-sectional study. For each calf, sex, colostrum delivery method, colostrum volume fed at first meal, and time to first feeding (delay between birth and first colostrum meal) were noted. Blood and colostrum samples were collected to estimate the serum and colostrum quality using Brix refractometry. To quantify the level of bacterial contamination in colostrum samples, total bacteria count and total coliform count (TCC) were measured using the Petrifilm (3M, St. Paul, MN) culture system. In this study, 68% of calves had an adequate TPI (≥8.4%). For data distribution, the 25th, 50th, and 75th percentiles were 1.3, 2.8, and 3.3 L for the colostrum volume fed at the first meal; 20.9, 23.5, and 26.5% Brix; and 1.1, 3.1, and 6.5 h for the time to first feeding of colostrum, respectively. The odds of adequate TPI were 2.6 times higher in calves receiving ≥2.5 L colostrum at their first meal, 2.9 times higher in calves receiving colostrum with ≥24.5% Brix, and 1.6 times higher in calves receiving colostrum within 3 h after birth, than in calves not meeting these criteria. In the present study, median bacterial contamination distribution (interquartile range) in the first colostrum meal was 14,000 cfu/mL (3,000-83,000 cfu/mL) for total bacteria count, and 0 cfu/mL (0-1,000 cfu/mL) for TCC. Total bacteria count and TCC were not associated with the odds of adequate TPI in the final model. Overall, these results suggest that specific calf-level colostrum management practices are associated with adequate TPI in small- to medium-sized dairy herds.

A herd-level study on colostrum management factors associated with the prevalence of adequate transfer of passive immunity in Québec dairy herds

The objective of this study was to identify herd-level colostrum management factors associated with the adequate transfer of passive immunity (TPI; defined as serum Brix refractance ≥8.4% in the first week of life). A total of 59 commercial Holstein dairy farms were included in this observational cross-sectional study. In every participating herd, a minimum of 14 Holstein calves were sampled to measure their TPI using a digital Brix refractometer. Colostrum samples fed to each of these calves were collected to estimate IgG concentration (colostrum quality) using a digital Brix refractometer and bacterial contamination using the Petrifilm (3M, St. Paul, MN) culture system. Dairy producers completed a questionnaire on colostrum management to assess on-farm practices. The study outcome was the prevalence of adequate TPI calculated based on the proportion of adequate TPI (defined with an individual threshold ≥8.4% Brix) on the total samples tested within each herd. According to the threshold determined in a previous study investigating the influencing colostrum management factors to achieve adequate TPI at the calf level, the prevalence of an adequate colostrum volume fed at first meal (≥2.5 L), the prevalence of adequate colostrum quality (≥24.5% Brix), the prevalence of an adequate time to first feeding (delay between birth and the first colostrum meal, ≤3 h), the prevalence of low aerobic bacterial contamination (≤20,000 cfu/mL), the prevalence of low coliform contamination (≤1,000 cfu/mL), and the prevalence of females were calculated. The herd-level prevalence of adequate TPI ranged from 24% to 100%, with a median of 68%. The median herd prevalences of an adequate colostrum volume fed at first meal, of adequate colostrum quality, of an adequate time to first feeding, of low aerobic bacterial contamination, of low coliform contamination, and of females, were 71, 42, 41, 64, 88, and 61%, respectively. In the final model, the prevalence of adequate TPI was associated with the prevalence of an adequate colostrum volume fed at first meal and the prevalence of an adequate time to first feeding. In summary, management practices varied greatly between farms and influenced the prevalence of adequate TPI.

Short communication: Diagnostic accuracy of the Petrifilm culture system for identifying colostrum with excessive bacterial contamination in Quebec dairy herds

The objective of this study was to validate the diagnostic accuracy of the Petrifilm culture system (3M, St. Paul, MN) for identifying colostrum with excessive bacterial contamination. An observational cross-sectional study was conducted between October 2015 and February 2016. Two colostrum aliquots were collected during the first meal of 332 calves (33 commercial Holstein dairy farms) in Quebec, Canada. One aliquot per calf was used to quantify the total bacteria count and the total coliform count using standard bacteriological laboratory testing (reference test). These results were dichotomized to identify colostrum with excessive bacterial contamination [aerobic count plate (AC) >100,000 cfu/mL; coliform count plate (CC) >10,000 cfu/mL]. The Petrifilm system was used to quantify both aerobic and coliform contamination of the other colostrum aliquot from each calf. As such, AC and CC were used according to the manufacturer's recommendations. The area under the curve of the receiver operating characteristic curve of AC and CC compared with the laboratory were 0.83, and 0.95, respectively. Using the optimal threshold of >24,000 cfu/mL for AC results, the Petrifilm system had a sensitivity (Se) of 69%, specificity (Sp) of 86%, and a kappa value of 0.54. Using the optimal threshold of >4,000 cfu/mL for CC results, the Petrifilm system had a Se of 93%, Sp of 90%, and kappa value of 0.64. Overall, these results suggest that the Petrifilm system is an appropriate alternative for identifying colostrum with excessive bacterial contamination.

A survey on sensor systems used in Italian dairy farms and comparison between performances of similar herds equipped or not equipped with sensors

Sensor systems (SS) were developed over the last few decades to help dairy farmers manage their herds. Such systems can provide both data and alerts to several productive, behavioral, and physiological indicators on individual cows. Currently, there is still a lack of knowledge on both the proportion of dairy farms that invested in SS and type of SS installed. Additionally, it is still unclear whether the performances of herds equipped with SS differ from those of similar herds managed without any technological aid. Therefore, the aims of this study were (1) to provide an insight into SS spread among Italian dairy farms and (2) to analyze the performances of similar herds equipped or not equipped with SS. To reach the former goal, a large survey was carried out on 964 dairy farms in the northeast of Italy. Farmers were interviewed by the technicians of the regional breeders association to collect information on the type of SS installed on farms and the main parameters recorded. Overall, 42% of the surveyed farms had at least 1 SS, and most of them (72%) reared more than 50 cows. Sensors for measuring individual cow milk yield were the most prevalent type installed (39% of the surveyed farms), whereas only 15% of farms had SS for estrus detection. More sophisticated parameters, such as rumination, were automatically monitored in less than 5% of the farms. To reach the latter goal of the study, a subset of 100 Holstein dairy farms with similar characteristics was selected: half of them were equipped with SS for monitoring at least individual milk yield and estrus, and the other half were managed without any SS. Average herd productive and reproductive data from official test days over 3 yr were analyzed. The outcomes of the comparison showed that farms with SS had higher mature-equivalent milk production. Further clustering analysis of the same 100 farms partitioned them into 3 clusters based on herd productive and reproductive data. Results of the Chi-squared test showed that the proportion of farms equipped with SS was greater in the cluster with the best performance (e.g., higher milk yield and shorter calving interval). However, the presence of a few farms equipped with SS in the least productive cluster for the same parameters pointed out that although the installation of SS may support farmers in time- and labor-saving or in data recording, it is not a guarantee of better herd performance.

Seroprevalence and risk factors assessment of the three main infectious agents associated with abortion in dairy cattle in Isfahan province, Iran.

This study aimed to determine the seroprevalence and identify the risk factors associated with Neospora caninum, Bovine herpesvirus type 1 (BHV-1), and Bovine viral diarrhea virus (BVDV) infection on industrial Holstein dairy cattle farms in Isfahan province, Central Iran. Blood samples were taken from 216 apparently healthy cattle from 16 randomly selected Holstein dairy farms in the North, South, East, and West of Isfahan in the summer of 2017. The antibodies to N. caninum, BHV-1, and BVDV were detected using a commercially available ELISA kit. The overall seroprevalence for N. caninum, BHV-1, and BVDV was 19%, 72.2%, and 52.8%, respectively. The significant major risk factors of BHV-1 in cattle were identified as farm direction, age groups, parity, and milk yield by the univariate analysis (p < 0.05). The significant major risk factors of BVDV in cattle were identified as age groups, parity, milk yield, and stage of pregnancy (p < 0.05). The only significant major risk factor of N. caninum was farm direction (p < 0.05). A significant association of concurrent infection with BVDV and BHV-1 has shown in the current study (p < 0.05). This study is the first to report the risk factors for N. caninum, BHV-1, and BVDV infection in the central part of Iran and allows us to conclude that these agents are widely distributed in this region.

Comparison of the therapeutic efficacy of salicylic acid paste with a polyurethane wound dressing for the treatment of digital dermatitis lesions in dairy cows

There is little evidence of the efficacy of artificial polymers for controlling bovine digital dermatitis (BDD) as a major problem of intensive dairy productions worldwide. We therefore aimed to compare salicylic acid (SA)-based paste with a polyurethane (PU) wound dressing on a German Holstein dairy farm over a maximum 56-d period. On d 0, 109 ft with active BDD lesions from 109 cows were randomly assigned to two treatment groups: (1) SA group received a topical SA-containing paste and (2) PU group was treated with a PU wound dressing. Dressing changes were performed according to manufacturer's instructions until clinical cure (transition from active M1 or M2 to non-active M4 or healed M0 stages), whereby a clinical scoring of lesions was additionally conducted. Data from 100 ft could be analyzed (nSA = 54; nPU = 46). There was a significant reduction of the lesion score over time within each group (SA: d 0–d 14; PU: d 0–d 28, p < .05). Score differences between first (d 0) and second (SA: d 7; PU: d 14) as well as between first and third (SA: d 14; PU: d 28) evaluation did not differ significantly (p > .05). The proportion of clinically cured cows was higher in SA than in PU on d 14 (96.3 vs. 32.6%) as well as on d 28 (100 vs. 54.3%) after initial treatment (p < .05). Analysis of survival to cure in a Cox regression model showed that hazard ratio (HR) was higher for SA with PU as baseline (HR: 6.324, 95% CI: 3.625–11.033, p < .05). However, while BDD scores at enrollment did not differ between treatments (p > .05), PU had a significantly lower final BDD score (p < .05). In conclusion, evidence on the efficacy of PU bandages to treat BDD lesions is provided and further studies on bacteriological cure as well as recurrence rates are needed.

ANALYSING DAIRY OPERATIONS WITH THE INTERACTIVE MODEL OF A DAIRY FARM

The paper focuses on factors affecting the economics of milk production based on modelling future effects of present managerial decisions. We evaluate a sample Slovak dairy farms from the economic and performance indicator datasets of the National Agricultural and Food Centre – Research institute for animal production Nitra (NPPC-RIAP), referring to semi-intensive dairy farm and typical Holstein dairy farm. The EkonMOD milk decision support tool for dairy farm managers will be used to run various scenarios in heifer replacement strategies. If the average age at first calving (AFC) is reduced from 30 down to 24 months, the dairy could expect additional heifers for potential sale, growth, or culling pressure on the lactating herd. This approach means that in the first two years’ heifer development is emphasized, expenses in feed and management are decreased by 47,520 € per year, and 53,750 € worth of heifers are sold, bringing the total potential income for those two years to 101,270 €. The reduction of AFC in semi-intensive dairy farm in the what-if scenario 1 reduced the number of heifers needed for replacement from 290 to 269 heifers, also having the positive impact on the profitability resulting from these interrelations. In the what-if scenario 2 the AFC remained the same as in what-if scenario 1, meaning that the number of replacements needed was without any change. In the last–different sample farm case scenario presented in this paper, we considered the Holstein dairy farm with 500 productive dairy cows. The reduction in the AFC from 26 to 24 months reduced the number of feeding days in the heifer category by 12 410 feeding days, resulting to the reduction in total costs of at least 22 000 €, in this case.

The Impact of Feeding Factors on Holstein Dairy Farms Costs in Kosovo

One-year investigation is carried out aimed at evaluating all incomes and costs with a specific focus on the impact of feeding factors in 12 Holstein dairy farms (in total 284 cows) in Kosovo. The cost of on-farm produced feeds; the price of purchased feeds and the price of milk were used for the analysis. All costs created during this period are duly registered and considered in the analysis. Economic analysis showed that prices of on-farm produced feed were much lower (30 €/ton for silages and for hay). Average daily feed cost was 2.33 €/cow/day, while milk income was only 4.9 €/d. Individual feed groups contributed to total milk cost as follows: silages with 0.04 €/kg, dry roughages with 0.02 €/kg, and concentrates with 0.10 €/kg, while all other factors taken 0.13 €/kg of milk price. This study showed that feed was the largest farm expense making 68% of total farm costs.

Performance and financial consequences of stillbirth in Holstein dairy cattle

Stillbirth is an economically important trait on dairy farms. Knowledge of the consequences of, and the economic losses associated with stillbirth can help the producer when making management decisions. The objectives of this study were to determine the effects of stillbirth on productive and reproductive performance as well as financial losses due to stillbirth incidence in Iranian Holstein dairy farms. Economic and performance data were collected from nine Holstein dairy farms in Isfahan and Khorasan provinces of Iran from March 2008 to December 2013. The final data set included 160 410 calving records from 53 265 cows. A linear mixed model was developed to evaluate the effects of stillbirth on performance of primiparous and multiparous cows separately and overall. An economic model was used to estimate the economic losses due to stillbirth. The incidence of stillbirth cases per cow per year was 4.2% on average (3.4% to 6.8% at herd level). The least square means results showed that a case of stillbirth significantly (P<0.05) reduced 305-day milk production in multiparous cows and overall, but had no significant effects on primiparous cows production performance (P>0.05). Overall, a case of stillbirth reduced 305-day milk yield by 544.0±76.5 kg/cow per lactation. Stillbirth had no significant effects on 305-day fat and protein percentages in either primiparous or multiparous cows. Overall, cows that gave birth to stillborn calves had significantly increased days open by 14.6±2.6 days and the number of inseminations per conception by 0.2 compared with cows that gave birth to live calves (P<0.01). In general, the negative productive and reproductive effects associated with stillbirth were smaller and non-significant for primiparous cows compared with multiparous cows. The financial losses associated with stillbirth incidence averaged US$ 938 per case (range from $US 767 to $US 1189 in the nine investigated farms). The loss of a calf was not the only cost associated with stillbirth, as it accounted for 71.0% of the total cost. The costs of dystocia (7.6%) and culling and replacement expenses (6.3%) were the next most important costs associated with stillbirth. These results can be used to assess the potential return from management strategies to reduce the occurrence of stillbirths.