Fuzzy Logic Model for Determining Optimal Temperature-Humidity Index Values in Dairy Farms in Temperate Climate.

In livestock, temperature, humidity, and Temperature-Humidity Index (THI) affect the welfare, yields, health and viability of animals. This study aimed to develop optimal temperature, humidity, and THI thresholds for dairy farms in temperate climate regions using a fuzzy logic model. THI values were calculated using three different literature-derived equations, considering different temperature and humidity situations in dairy farms. The Mamdani-type fuzzy logic method was utilized to formulate linguistic expressions for temperature, humidity, and THI values. According to the THI thresholds, the areas below the Receiver Operating Characteristic (ROC) were found to be significant (p < 0.001) in all fuzzy algorithms. The study found 100% harmony with the THI thresholds of 66 and 72 for cattle in temperate climates, but only 73.6% harmony with the threshold of 74 for cattle adapted to tropical climate. Briefly, in temperate dairy farms, the fuzzy logic revealed that the optimal temperature, humidity and THI values should be between 14-18.5°C, 65-70% and 52.5-64.5, respectively. However, further research is required to understand the impact of thresholds determined by fuzzy logic on dairy cow production and welfare.

Repeatability of whole herd lameness scoring: an analysis of a New Zealand dataset.

AIMS: To assess whether a whole-herd lameness score on a New Zealand dairy farm in spring could predict lameness prevalence on the same farm in summer (and vice versa) and whether a single-herd lameness score could be used to determine whether herd lameness prevalence was < 5% in both spring and summer. METHODS: Prevalence data (proportion of the herd with lameness score ≥ 2 and with score 3; 0-3 scale) from a study where 120 dairy farms across New Zealand were scored in spring and in the following summer were analysed using limits-of-agreement analysis. In addition, farms were categorised as having either acceptable welfare (lameness prevalence < 5% in both spring and summer) or not (lameness prevalence ≥ 5% in either spring or summer or both). The accuracy and specificity of a single, whole-herd lameness score at identifying herds with acceptable welfare were then calculated. RESULTS: The limits-of-agreement analysis suggests that 95% of the time, the prevalence of lameness in summer would be expected to be between 0.23 and 4.3 times that of the prevalence in spring. The specificity and accuracy of identifying a farm as acceptable on both occasions from a single observation were, respectively, 74% and 92% in spring, and 59% and 87% in summer. CONCLUSIONS: A single, one-off, whole-herd lameness score does not accurately predict future lameness prevalence. Similarly, acceptable status (lameness prevalence < 5%) in one season is not sufficiently specific to be used to predict welfare status in subsequent seasons. CLINICAL RELEVANCE: Whole-herd lameness scoring should be used principally as a means of detecting lame cows for treatment. A single whole-herd lameness score by an independent assessor should not be used to determine a herd's welfare status.

Development and evaluation of predictive models for pregnancy risk in UK dairy cows.

One suggested approach to improve the reproductive performance of dairy herds is through the targeted management of subgroups of biologically similar animals, such as those with similar probabilities of becoming pregnant, termed pregnancy risk. We aimed to use readily available farm data to develop predictive models of pregnancy risk in dairy cows. Data from a convenience sample of 108 dairy herds in the UK were collated and each herd was randomly allocated, at a ratio of 80:20, to either training or testing data sets. Following data cleaning, there were a total of 78 herds in the training data set and 20 herds in the testing data set. Data were further split by parity into nulliparous, primiparous, and multiparous subsets. An XGBoost model was trained to predict the insemination outcome in each parity subset, with predictors from farm records of breeding, calving and milk recording. Training data comprised 74,511 inseminations in 45,909 nulliparous animals, 86,420 inseminations in 39,439 primiparous animals, and 158,294 inseminations in 32,520 multiparous animals. The final models were evaluated by predicting with the testing data, comprising 31,740 inseminations in 19,647 nulliparous animals, 38,588 inseminations in 16,215 primiparous animals, and 65,049 inseminations in 12,439 multiparous animals. Model discrimination was assessed by calculating the area under receiver operating characteristic curves (AUC); model calibration was assessed by plotting calibration curves and compared across test herds by calculating the expected calibration error (ECE) in each test herd. The models were unable to discriminate between insemination outcomes with high accuracy, with an AUC of 0.63, 0.59 and 0.62 in the nulliparous, primiparous and multiparous subsets, respectively. The models were generally well-calibrated, meaning the model-predicted pregnancy risks were similar to the observed pregnancy risks. The mean (SD) ECE in the test herds was 0.038 (0.023), 0.028 (0.012) and 0.020 (0.008) in the nulliparous, primiparous and multiparous subsets respectively. The predictive models reported here could theoretically be used to identify subgroups of animals with similar pregnancy risk to facilitate targeted reproductive management; or provide information about cows' relative pregnancy risk compared with the herd average, which may support on-farm decision-making. Further research is needed to evaluate the generalizability of these predictive models and understand the source of variation in ECE between herds; however, this study demonstrates that it is possible to accurately predict pregnancy risk in dairy cows using readily available farm data.

Heat stress effect on fertility of two imported dairy cattle breeds from different Algerian agro-ecological areas.

The present study investigates the susceptibility of two imported dairy cattle breeds to Algerian local climatic conditions, with a primary focus on heat stress (HS) and its repercussions on fertility traits. The dataset comprises 20,926 artificial insemination records involving 6,191 Prim'Holstein and 5,279 Montbéliarde cows. The animals originated from three distinct agro-ecological regions: littoral (L), semi-arid (SA), and arid (Ar), characterized by average annual Temperature-Humidity Index (THI) values of 75.2, 69.53, and 74.75, respectively. Logistic and linear regression models were performed to analyze the relationship between the THI on the AI day, season, and agro-ecological origin of the animals with the Conception Rate at 1st Artificial Insemination (CR 1stAI), Conception Risk (CR), Services per Conception (SPC), and reproductive period (RP). The results demonstrated a significant negative impact (P < 0.001) of THI > 72 compared to THI ≤ 72 on CR1st AI and CR for both cattle breeds (Prim'Holstein: -49.7% and - 17%, respectively; Montbéliarde: -20.7% and - 15%, respectively). Seasonal effects revealed a notably higher CR1stAI in winter and spring (≈ 25%) for Prim'Holstein and Montbéliarde cows compared to summer (19.41%) and autumn (19.12%), respectively. Furthermore, a reduced likelihood of conception at 1stAI and subsequent AI was observed during summer (0.839) and autumn (0.818) compared to winter for the Montbéliarde cows. Taking into account the littoral region as a reference, the likelihood of 1stAI success increased for both breeds in the SA region and decreased for the Ar region (P < 0.001). SPC increased for both breeds in THI > 72 categories (Prim'Holstein: 6.3%, Montbéliarde: 7.1%, P < 0.01), in the Ar region (Prim'Holstein: 30.9%, Montbéliarde: 26%, P < 0.001), and in the SA region (4%, P < 0.05) compared to the L region No significant seasonal effect on SPC was observed for either breed (P > 0.05). The RP increased in the THI > 72 category (Prim'Holstein: 4.1%, Montbéliarde: 7.4%, P < 0.001) and in the Ar region (Prim'Holstein: 122%, Montbéliarde: 73.4%) for both breeds. RP decreased in autumn compared to winter (Prim'Holstein: 15.3%, Montbéliarde: 8.4%). This study underscores the adverse impact of mild to severe heat stress (HS) and related factors (season, region) on fertility of Prim'Holstein and Montbéliarde cows under Algerian conditions, emphasizing the necessity for heat stress mitigation strategies, especially in adverse littoral humid and Saharan-arid environmental conditions.

Sample Type and Processing Plant Differences in the Proportion of Enterohemorrhagic Escherichia coli O157 and Non-O157 Serogroups in Feces and on Hides of Cull Dairy Cattle at Slaughter.

The study was conducted to determine the proportion and concentration of enterohemorrhagic Escherichia coli (EHEC) O157 and six non-O157 (O26, O45, O103, O111, O121, and O145) serogroups and identify seasonal and processing plant differences in feces and on hides of cull dairy cattle processed in commercial slaughterhouses in the United States. Approximately 60 rectal and 60 hide-on samples from matched carcasses were collected in each of three processing plants, in two periods; summer of 2017 and spring of 2018. Samples before enrichment were spiral plated to quantify EHEC, and postenriched samples underwent culture methods that included immuno-magnetic separation, plating on selective media, and PCR assays for identification and serogroup confirmation of putative isolates. An isolate was considered EHEC O157 positive if it harbored serogroup-specific (rfbE), Shiga toxin (stx1 and/or stx2), and intimin (eae) genes and EHEC non-O157 positive if at least one of the non-O157 serogroup-specific, stx1 and/or stx2, and eae genes was identified. Generalized linear mixed models were fitted to estimate overall proportion of positives for EHEC O157 and non-O157 EHEC serogroups, as well as seasonal and processing plant differences in fecal and hide-on proportion of positives. The fecal EHEC proportion at the sample level was 1.8% (95% CI = 0.0-92.2%) and 4.2% (95% CI = 0.0-100.0%) for EHEC O157 and EHEC non-O157, respectively. Hide sample level proportion of positives was 3.0% (95% CI = 0.0-99.9%) for EHEC O157 and 1.6% (95% CI = 0.0-100.0%) for EHEC non-O157. The proportion of EHEC O157 and non-O157 significantly differed by processing plant and sample type (hide vs. feces), but not by season. The association between proportion of EHEC serogroups in feces with the proportion on hides collected from matched cattle was 7.8% (95% CI = 0.6-53.3%) and 3.8% (95% CI = 0.3-30.8%) for EHEC O157 and non-O157, respectively. Taken together, our findings provide evidence of a low proportion of EHEC serogroups in the feces and on hides of cull dairy cattle and that their proportion varies across processing plants.

Occurrence, serotypes and virulence characteristics of Shiga toxin-producing and Enteropathogenic Escherichia coli isolates from dairy cattle in South Africa.

Shiga toxin-producing and Enteropathogenic Escherichia coli are foodborne pathogens commonly associated with diarrheal disease in humans. This study investigated the presence of STEC and EPEC in 771 dairy cattle fecal samples which were collected from 5 abattoirs and 9 dairy farms in South Africa. STEC and EPEC were detected, isolated and identified using culture and PCR. Furthermore, 339 STEC and 136 EPEC isolates were characterized by serotype and major virulence genes including stx1, stx2, eaeA and hlyA and the presence of eaeA and bfpA in EPEC. PCR screening of bacterial sweeps which were grown from fecal samples revealed that 42.2% and 23.3% were STEC and EPEC positive, respectively. PCR serotyping of 339 STEC and 136 EPEC isolates revealed 53 different STEC and 19 EPEC serotypes, respectively. The three most frequent STEC serotypes were O82:H8, OgX18:H2, and O157:H7. Only 10% of the isolates were classified as "Top 7" STEC serotypes: O26:H2, 0.3%; O26:H11, 3.2%; O103:H8, 0.6%; and O157:H7, 5.9%. The three most frequent EPEC serotypes were O10:H2, OgN9:H28, and O26:H11. The distribution of major virulence genes among the 339 STEC isolates was as follows: stx1, 72.9%; stx2, 85.7%; eaeA, 13.6% and hlyA, 69.9%. All the 136 EPEC isolates were eaeA-positive but bfpA-negative, while 46.5% carried hlyA. This study revealed that dairy cattle are a major reservoir of STEC and EPEC in South Africa. Further comparative studies of cattle and human STEC and EPEC isolates will be needed to determine the role played by dairy cattle STEC and EPEC in the occurrence of foodborne disease in humans.Please kindly check and confirm the country and city name in affiliation [6].This affiliation is correct.Please kindly check and confirm the affiliationsConfirmed. All Affiliations are accurate.

Respiratory illness in young and adult cattle caused by bovine viral diarrhea virus subgenotype 2b in singular and mixed bacterial infection in a BVDV-vaccinated dairy herd.

Bovine respiratory disease (BRD) is a common global health problem in dairy cattle. The definitive diagnosis of BRD is complex because its etiology involves several predisposing and determining factors. This report describes the etiology of a BRD outbreak in a dairy herd in the mesoregion of Central Eastern Paraná, which simultaneously affected young (calves and heifers) and adult (cows) Holstein-Friesian cattle. Nine biological samples, consisting of five lung samples from two cows and three suckling calves, and four nasal swab samples from heifers, were used for etiological diagnosis. The nucleic acids extracted from lung fragments and nasal swabs were subjected to PCR and RT-PCR assays for partial amplification of the genes of five viruses [bovine viral diarrhea virus (BVDV), bovine alphaherpesvirus 1 (BoAHV1), bovine respiratory syncytial virus (BRSV), bovine parainfluenza virus 3 (BPIV-3), and bovine coronavirus (BCoV)] and four bacteria (Mycoplasma bovis, Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni) involved in the etiology of BRD. All nine biological samples from the animals with BRD tested negative for BoAHV1, BRSV, BPIV-3, BCoV, and H. somni. Therefore, the involvement of these microorganisms in the etiology of BRD outbreak can be ruled out. It was possible to identify the presence of BVDV and M. bovis in singular and mixed infections of the lower respiratory tract in cattle. BVDV was also identified in two nasal swabs: one as a single etiological agent and the other in association with two bacteria (P. multocida and M. haemolytica). The phylogenetic analysis conducted in the nucleotide sequence of the 5'UTR region and Npro gene of the BVDV amplicons demonstrated that the BVDV field strains of this BRD outbreak belong to subgenotype 2b. To the best of our knowledge, this is the first report of BVDV-2b involvement in the etiology of BRD in Brazil. Finally, it is necessary to highlight that the cattle were obtained from an open dairy herd with biannual vaccinations for BVDV-1a and - 2a.

Conventional and unsupervised artificial intelligence analyses identified risk factors for antimicrobial resistance on dairy farms in the province of Québec, Canada.

Antimicrobial resistance (AMR) is one of the greatest threats to global health worldwide and is threatening not only humans, but also animal production systems, including dairy farms. The objective of this paper was to describe risks factors associated with AMR on dairy farms in Québec, Canada. This observational cross-sectional study included 101 commercial dairy farms and took place between the springs of 2017 and 2018 for a one-year period. We explored risk factors such as farm practices and producer's knowledge (measured using a questionnaire), antimicrobial use (quantified using veterinary invoices), and the presence of Salmonella Dublin (tested by serology). We evaluated AMR with fecal Escherichia coli retrieved from pre-weaned calves and lactating cows using the following outcomes: the presence of extended-spectrum-ß-lactamase/AmpC resistance and the number of resistances to antimicrobial classes. We used logistic regression models to evaluate the association between each risk factor and the 2 outcomes for the 2 types of samples (pre-weaned calves and lactating cows). Furthermore, we explored the relationships between these risk factors utilizing data dimensionality reduction and hierarchical clustering. Outputs of these analyses were used as regressors for AMR in regression models. While the results for univariate analyses were ambiguous, the unsupervised analysis naturally categorized the sample of farms according to their health/treatment status (dimension 1, explaining 12.9% of the variance) and herd size (dimension 2, explaining 7.8%). Three clusters of farms were identified (cluster 1: mainly healthy herds and low ceftiofur users, cluster 2: relatively high ceftiofur users, cluster 3: farms with a higher incidence of diseases and higher antimicrobial treatment rates). Dimension 1 and cluster membership were statistically associated with the presence of extended-spectrum-ß-lactamase/AmpC resistance in lactating cows and in pre-weaned calves. Dimension 1 was also statistically associated with the number of resistances in lactating cows and in pre-weaned calves. This study highlights the complexity of analyzing risk factors associated with AMR. Our results suggest that the herd health status and the AMU-related practices used are associated with AMR in dairy farms. However, prospective studies are needed to confirm a causal relation.

Short-Term Effects of Heat Stress on Cow Behavior, Registered by Innovative Technologies and Blood Gas Parameters.

Heat stress (HS) is one of the key factors affecting an animal's immune system and productivity, as a result of a physiological reaction combined with environmental factors. This study examined the short-term effects of heat stress on cow behavior, as recorded by innovative technologies, and its impact on blood gas parameters, using 56 of the 1070 cows clinically evaluated during the second and subsequent lactations within the first 30 days postpartum. Throughout the experiment (from 4 June 2024 until 1 July 2024), cow behavior parameters (rumination time min/d. (RT), body temperature (°C), reticulorumen pH, water consumption (L/day), cow activity (h/day)) were monitored using specialized SmaXtec boluses and employing a blood gas analyzer (Siemens Healthineers, 1200 Courtneypark Dr E Mississauga, L5T 1P2, Canada). During the study period, the temperature-humidity index (THI), based on ambient temperature and humidity, was recorded and used to calculate THI and to categorize the data into four THI classes as follows: 1-THI 60-63 (4 June 2024-12 June 2024); 2-THI 65-69 (13 June 2024-18 June 2024); 3-THI 73-75 (19 June 2024-25 June 2024); and 4-THI 73-78 (26 June 2024-1 July 2024). The results showed that heat stress significantly reduced rumination time by up to 70% in cows within the highest THI class (73 to 78) and increased body temperature by 2%. It also caused a 12.6% decrease in partial carbon dioxide pressure (pCO2) and a 32% increase in partial oxygen pressure (pO2), also decreasing plasma sodium by 1.36% and potassium by 6%, while increasing chloride by 3%. The findings underscore the critical need for continuous monitoring, early detection, and proactive management to mitigate the adverse impacts of heat stress on dairy cow health and productivity. Recommendations include the use of advanced monitoring technologies and specific blood gas parameter tracking to detect the early signs of heat stress and implement more timely interventions.

Seroprevalence and associated risk factors for Neospora caninum infection in dairy cattle in South Africa.

Bovine neosporosis is a widespread parasitic disease associated with significant economic losses. Its effects on the reproductive performance of cows have resulted in losses that run into the hundreds of millions of US dollars in dairy industries in various countries (Reichel et al., Int J Parasitol 43:133-142, 2013). Due to outdated and scant information on the occurrence of Neospora caninum infection in South Africa, the study aimed to determine the seroprevalence and risk factors associated with infection in dairy cattle in South Africa. A total of 1401 blood samples were randomly collected from cattle on 48 dairy farms in seven of the nine provinces in South Africa. A close-ended questionnaire was used in a cross-sectional study to obtain farm-level and animal-level data. Serological testing was done using a commercial IDvet Screen® Neospora caninum Indirect ELISA. An overall seroprevalence, adjusted for test sensitivity and specificity, of 2.3% (95% CI, 1.3-4.1) was detected and 48% (23/48) of sampled farms had at least one animal testing positive. The highest seroprevalence of N. caninum was in the KwaZulu-Natal province with 7.5% (95% CI, 3.8-14.3), and the lowest in Western Cape with 0.1% (95% CI, 0-1.2). The highest within-farm seroprevalence of 25% was detected on a farm in the North West Province. In a multivariable logistic regression model, the odds of N. caninum seropositivity were higher in Holstein-Friesian cattle when compared to other breeds. Good hygiene was identified as a protective factor. Cattle left out on pasture had increased odds of testing positive for N. caninum compared to those that were penned. The odds of testing seropositive for N. caninum was higher on farms that practised segregation of cattle into different age groups. The purchase of replacement animals was a significant risk factor, as open herds had increased odds of N. caninum seropositivity. Cattle on farms that did not have a specific calving location were more likely to be seropositive. This is the first such study in South Africa and shows that N. caninum is widely distributed in the country at a low seroprevalence, but it may be a cause of concern on certain farms.

Bovine leukemia virus transmission rates in persistent lymphocytotic infected dairy cows.

Bovine leukemia virus (BLV) establishes a lifelong persistent infection in dairy cattle. White blood cell count (WBC) is correlated with proviral load in the blood and milk of BLV-infected cattle, and testing WBC can be used to assess both BLV infectiousness levels and risk of BLV transmission from different types of infected animals. The objective of the study was to compare effective transmission rates (ß) and the basic reproduction ratio (R o) among two types of BLV-infected dairy cows in Chile: those affected with persistent lymphocytosis (PL) vs. aleukemic (AL).The estimated (ß) coefficient was higher in PL cattle [1.1; 95% Confidence interval (CI) (-1.6, 3.8)], compared to AL cattle (-3.1; 95% CI = -3.7, -2.5). In addition, the R o was higher in PL cattle (60.4; 95% CI = 3.5; 820.6), compared to AL cattle (1.5; 95% CI = 0.7, 3.1). The ratio between PL/AL expected rate of cases was 73.9. The estimated effective transmission rate and the Ro were higher in PL cattle compared to AL cattle. The WBC test is a convenient alternative that can be considered for risk identification and risk management of BLV infection in dairy herds; particularly in livestock regions where laboratory capacity is limited (e.g., use of PCR or gene sequencing techniques) and/or molecular tests are not cost-effective. Therefore, when prevalence of infection is high, the removal of PL cattle should be engaged to control BLV within-herds.

Continuous sampling of healthy and mastitic quarters of lactating cattle by ultrafiltration after intramammary ceftiofur hydrochloride administration.

BACKGROUND: Pharmacological activity of intramammary drugs depends on adequate drug concentrations within the cistern, but sampling is often limited. Insight into the active drug concentration within the mammary cistern may assist in determining effective and appropriate therapeutic decisions for cows being treated for mastitis. OBJECTIVE: Evaluate the disposition of ceftiofur hydrochloride administered intramammary in diseased and nondiseased quarters. Whole milk and ultrafiltrate sampling techniques were compared. ANIMALS: Ten mature, late lactation Holstein (n = 9) and Jersey (n = 1) dairy cows (422-670 kg) with naturally occurring clinical mastitis, producing between 1.4 and 15.9 kg/day of milk. METHODS: Ultrafiltration probes were placed in both mastitic and healthy quarters. Each quarter was treated with 2 doses of 125 mg ceftiofur hydrochloride suspension, and whole milk and milk ultrafiltrate samples were collected. Ceftiofur concentrations in composite whole milk and milk ultrafiltrate were analyzed. RESULTS: The maximum concentration of ceftiofur was higher in ultrafiltrate samples, but no differences were identified in healthy or mastitic quarters. The use of ultrafiltration probes provides a novel technique for free drug concentrations within the mastitic and healthy bovine mammary gland. CONCLUSIONS AND CLINICAL IMPORTANCE: Significant inter- and intracow variability and lower daily milk weights may overestimate ceftiofur concentrations available within the cistern. The pharmacokinetic (PK) parameters reported in milk ultrafiltrate will help establish a link between the PK and the corresponding drug effect, potentially providing a meaningful rationale for the selection of a safe and effective dose in cows with mastitis.

Approaches for predicting dairy cattle methane emissions: from traditional methods to machine learning.

Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers the different modeling approaches taken in the prediction of dairy cattle CH4 emissions and highlights their individual strengths and limitations. Following the guidelines set out by the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA); Scopus, EBSCO, Web of Science, PubMed and PubAg were each queried for papers with titles that contained search terms related to a population of "Bovine," exposure of "Statistical Analysis or Machine Learning," and outcome of "Methane Emissions". The search was executed in December 2022 with no publication date range set. Eligible papers were those that investigated the prediction of CH4 emissions in dairy cattle via statistical or machine learning (ML) methods and were available in English. 299 papers were returned from the initial search, 55 of which, were eligible for inclusion in the discussion. Data from the 55 papers was synthesized by the CH4 emission prediction approach explored, including mechanistic modeling, empirical modeling, and machine learning. Mechanistic models were found to be highly accurate, yet they require difficult-to-obtain input data, which, if imprecise, can produce misleading results. Empirical models remain more versatile by comparison, yet suffer greatly when applied outside of their original developmental range. The prediction of CH4 emissions on commercial dairy farms can utilize any approach, however, the traits they use must be procurable in a commercial farm setting. Milk fatty acids (MFA) appear to be the most popular commercially accessible trait under investigation, however, MFA-based models have produced ambivalent results and should be consolidated before robust accuracies can be achieved. ML models provide a novel methodology for the prediction of dairy cattle CH4 emissions through a diverse range of advanced algorithms, and can facilitate the combination of heterogenous data types via hybridization or stacking techniques. In addition to this, they also offer the ability to improve dataset complexity through imputation strategies. These opportunities allow ML models to address the limitations faced by traditional prediction approaches, as well as enhance prediction on commercial farms.

This review provides a comprehensive overview of the different modeling approaches taken in the prediction of dairy cattle methane emissions. Mechanistic models, which mathematically simulate the methane production process of the dairy cattle rumen, are both accurate and adaptable, yet their necessary input data is difficult to obtain and if imprecise, can produce misinformative results. Empirical models, which statistically quantify the relationships between methane emissions and production factors, are a more accessible alternative to mechanistic models, yet their accessible structure limits them to the same range of data on which they were originally developed. Machine learning models, which are based on a particular learning pattern, can be trained to identify trends in methane production and use these lessons to make accurate predictions. Their application in the prediction of dairy cattle methane emissions remains scarce, yet those that have been show promising potential. Commercially deployable models can utilize any of the previous approaches, as long as the traits they use are obtainable in a commercial farm setting. Those developed favor the use of milk fatty acids, yet the variation in their results needs to be consolidated before robust predictions of methane emissions on commercial farms can be achieved.

In silico analysis of polyphenols modulate bovine PPARγ to increase milk fat synthesis in dairy cattle via the MAPK signalling pathways.

This study investigates the potential phytochemicals that modulate bovine peroxisome proliferator-activated receptor gamma (PPARγ) and the Mitogen-Activated Protein Kinase (MAPK) pathways to enhance milk fat production in dairy animals. Bovine PPARγ, a key member of nuclear hormone receptor superfamily, plays a vital role in regulating metabolic, cellular differentiation, apoptosis, and anti-inflammatory responses in livestock, while the MAPK pathway is contributory in cellular processes that impact milk fat synthesis. This approach involved an all-inclusive molecular docking analysis of 10,000 polyphenols to identify potential PPARγ ligands. From this extensive screening, top 10 compounds were selected that exhibited the highest binding affinities to bovine PPARγ. Particularly, Curcumin sulphate, Isoflavone and Quercetin emerged as the most promising candidates. These compounds demonstrated superior docking scores (-9.28 kcal/mol, -9.27 kcal/mol and -7.31 kcal/mol respectively) and lower RMSD values compared to the synthetic bovine PPARγ agonist, 2,4-Thiazolidinedione (-4.12 kcal/mol), indicating a strong potential for modulating the receptor. Molecular dynamics simulations (MDS) further affirmed the stability of these polyphenols-bovine PPARγ complexes, suggesting their effective and sustained interactions. These polyphenols, known as fatty acid synthase inhibitors, are suggested to influence lipid metabolism pathways crucial to milk fat production, possibly through the downregulation of the MAPK pathway. The screened compounds showed favorable pharmacokinetic profiles, including non-toxicity, carcinogenicity, and high gastrointestinal absorption, positioning them as viable candidates for enhancing dairy cattle health and milk production. These findings may open new possibilities for the use of phytochemicals as feed additives in dairy animals, suggesting a novel approach to improve milk fat synthesis through the dual modulation of bovine PPARγ and MAPK pathways.

Selected Monogenic Genetic Diseases in Holstein Cattle-A Review.

Genetic disorders arise from alterations in the hereditary information encoded in DNA, leading to potential detrimental effects on the well-being and vitality of organisms. Within the bovine population, genetic conditions inherited in an autosomal recessive manner are frequently associated with particular breeds. In recent years, several recessive haplotypes and a few causative mutations have been discovered in Holstein cattle: CDH (Holstein cholesterol deficiency), haplotypes with a homozygous deficiency in Holstein (HH1, HH3, HH4, HH5, HH6 and HH7), BLAD (bovine leukocyte adhesion deficiency) and DUMPS (deficiency of uridine monophosphate synthase). All of these diseases are inherited in an autosomal recessive manner. From a breeding perspective, recessive mutations specifically exhibit considerable detrimental effects and are a significant problem for breeders, exposing them to economic losses. Individual mutations can cause embryo death at any stage of pregnancy. Only genetic research and conscious selection of animals for mating will lead to a reduction in the number of carriers and elimination of mutations from the population.

Genome-wide association study for milk yield, frame, and udder conformation traits of Gir dairy cattle.

Genome-wide association studies (GWAS) are employed to identify genomic regions and candidate genes associated with several traits. The aim of this study was to perform a GWAS to identify causative variants and genes associated with milk yield, frame, and udder conformation traits in Gir dairy cattle. Body conformation traits were classified as "frame," and "udder" traits for this study. After genotyping imputation and quality control 42,105 polymorphisms were available for analyses and 24,489 cows with pedigree information had phenotypes. First, P-value was calculated based on the variance of the prediction error of the SNP-effects on the first iteration. After that, 2 more iterations were performed to carry out the weighted single-step genome-wide association methodology, performed using genomic moving windows defined based on linkage disequilibrium. The significant SNPs and top 10 windows explaining the highest percentage of additive genetic variance were selected and used for QTL and gene annotation. The variants identified in our work overlapped with QTLs from the animal QTL database on chromosomes 1 to 23, except for chromosome 4. The Gir breed is less studied than the Holstein breed and as such the animal QTL database is biased to Holstein results. Hence it is noteworthy that our GWAS had similarities with previously described QTLs. These previously known QTLs were related to milk yield, body height, rump angle, udder width, and udder depth. In total, 5 genes were annotated. Of these genes, FAM13A and CMSS1 had been previously related to bone and carcass weight in cattle.

Effects of dam metabolic profile and seasonality (Spring vs. Winter) on their offspring' metabolism, health, and immunity: maternal factors in dairy calves' analytes.

Maternal status during the transition period can significantly impact the health and performance of Holstein dairy calves, with lasting effects on various variables. However, the relationship between maternal late gestation metabolic status, seasonality, and their impact on offspring remains unclear. This study aimed to assess the influence of maternal variables at calving on the performance, metabolism, and immunity of 28 dairy calves during their first month of life. Blood samples were collected from 28 Holstein cows at calving. Median results for maternal variables including non-esterified fatty acids (NEFA), ß-hydroxybutyrate (BHB), glucose, total protein (TP), albumin, triglycerides (TG), total cholesterol (TC), haptoglobin (Hp), body weight (BW), and body condition score (BCS) were determined. These median values served as a basis for categorizing the offspring into two groups based on their dams' high or low degree of each maternal variable. Additionally, calves were categorized by the season of birth (Spring vs. Winter), with 14 in each. Blood samples were collected from the calves at birth and on days 1, 7, 14, and 28 to assess IgG, biochemical parameters, and haptoglobin concentration. Reactive oxygen species (ROS) production by polymorphonuclear cells stimulated by various agents was also evaluated. Clinical assessments were conducted for diarrhea and bovine respiratory disease frequencies. Despite the overall health of the cows, differences were observed in the calves between maternal groups. Heavier cows with high maternal BCS tended to have larger offspring, while high maternal BCS was associated with increased diarrhea prevalence. Low maternal BCS resulted in a stronger innate immune response, indicated by higher ROS production. Calves from cows experiencing metabolic changes during calving displayed elevated Hp concentrations. Spring-born calves were larger but had lower serum IgG concentration and reduced innate immune response compared to winter-born calves. Additionally, spring-born calves exhibited higher Hp and increased diarrhea prevalence on day 28. These findings underscore the importance of the prenatal period in determining neonatal health and suggest further research to elucidate the long-term clinical implications of maternal effects on offspring health and growth. Investigating offspring constituents later in life can provide insight into the persistence of maternal effects over time.

Detection and Phenotypic Antimicrobial Susceptibility of Salmonella enterica Serotypes in Dairy Cattle Farms in the Po Valley, Northern Italy.

The presence of Salmonella spp. in dairy cattle farms poses a major risk to animal health and welfare. This study focused on Salmonella detection in dairy farms located in the Cremona and Mantua provinces (northern Italy) in samples collected and submitted to laboratories in 2021-2022. A total of 2710 samples from different sources, including calf carcasses/organs (n = 128), rectal swabs (n = 1937), feces (n = 390), bulk milk (n = 93), and overshoes/swabs (n = 127) for environmental sampling, were analyzed for the presence of Salmonella spp. and were included in the present study. Our results indicate that Salmonella was most commonly firstly identified from calf carcasses and organs (61.67%) and that the serotypes most frequently detected in dairies were S. Dublin (38.33%), S. Typhimurium (23.33%), and S. Typhimurium monophasic variant (14.17%). The most common pathological findings in calf carcasses were enteritis, hepatosplenomegaly, and pneumonia. The antimicrobial resistance pattern analyzed using the MIC assay of 51 Salmonella isolates revealed the presence of multi-resistant strains, which pose a major risk to public and animal health.

A Review of the Effects of Stress on Dairy Cattle Behaviour.

In this narrative review, the authors summarise the relationship between stress and behaviour and how dairy cattle cope with stressors. Based on the available literature, the most common stressors in intensive dairy cattle farming, such as pain, disease, heat stress, poor comfort caused by technology, and social stress, are surveyed. The authors describe how these stressors modify the behaviour of dairy cattle, influencing their feeding patterns, social interactions, and overall well-being. Additionally, the review explores the effectiveness of various coping mechanisms employed by dairy cattle to mitigate stress, including physiological adaptations and behavioural responses. This review is a valuable resource for understanding and grading stress in dairy cattle through behavioural reactions. Elucidating the intricate interplay between stressors and behaviour offers insights into potential interventions to improve animal welfare and productivity in dairy farming. Furthermore, this review highlights areas for future research, suggesting avenues for more comprehensive behavioural studies to enhance our understanding of stress management strategies in dairy cattle.

Molecular Identification and Survey of Cyclospora spp. in Cattle in Shanxi Province, North China.

To date, more than 20 species in the genus Cyclospora have been reported. Among them, Cyclospora cayetanensis has been recognized as the causative agent of human cyclosporiasis, which is characterized by severe intestinal injury and prolonged diarrhea in patients with immune dysfunction. The presence of C. cayetanensis in cattle has been confirmed. To date, however, no surveillance data are available on the occurrence and prevalence of Cyclospora spp. in cattle in Shanxi Province, North China. In the present study, a total of 761 fecal samples collected from cattle in three representative counties (Qi, Jishan, and Shanyin) in this Province were examined for Cyclospora spp. by using a polymerase-chain-reaction-restriction-fragment-length polymorphism (PCR-RFLP) test based on the nuclear small subunit ribosomal RNA (SSU rRNA) gene. The prevalence of Cyclospora spp. in cattle was 2.1%, and region, age, sex, and breed were not identified to be risk factors. Molecular evolutionary analysis based on the SSU rRNA sequences revealed that all 12 of the isolates were relatively distant from the human pathogen C. cayetanensis; seven isolates were grouped with Cyclospora colobi, whereas the others were grouped with cattle Cyclospora spp. reported previously. Though C. cayetanensis was not detected in cattle in the present study, more investigations should be performed in human populations, other animal species, or cattle from other regions of Shanxi Province and other environmental sources from the One Health perspective.