Cows In Lactation Research Articles

Effects of Oregano on Lactation Performance, Nutrient Digestibility, Ruminal Fermentation Parameters, and Methane Emissions in Dairy Cows: A Meta-Analysis

Growing concerns regarding antibiotic use in livestock, due to antibiotic resistance and potential human transmission, have led to increased interest in herbs and their derivatives, including essential oils, which possess antimicrobial properties that may enhance overall productivity and serve as a strategy for methane mitigation. The objective of this meta-analysis was to investigate the effects of adding oregano to the diet in different forms (essential oils, plant materials, or leaves) on the dry matter intake (DMI), milk yield (MY), milk components, nutrient digestibility, ruminal fermentation parameters, and methane (CH4) emissions of dairy cows. A literature search was conducted to identify papers published from 2000 to 2023. Effect size for all outcomes was reported as a standardized means difference (SMD) and raw means difference with 95% confidence intervals. Heterogeneity was determined using the Q test and I2 statistic. The results of the meta-analysis indicated that adding oregano had no effect on DMI (SMD = 0.081; p = 0.507) and MY (SMD = 0.060; p = 0.665). Milk fat percentage, milk protein percentage, and milk lactose percentage were not affected by oregano. The addition of oregano to the diet significantly decreased dry matter digestibility (SMD = −0.502; p = 0.013), crude protein digestibility (SMD = −0.374; p = 0.040), and neutral detergent fiber digestibility (SMD = −0.505; p = 0.014). Ruminal pH (SMD = −0.122; p = 0.411), total volatile fatty acids concentration (SMD = −0.038; p = 0.798), acetate (SMD = −0.046; p = 0.757), propionate (SMD = 0.007; p = 0.960), and butyrate (SMD = 0.037; p = 0.801) proportion were not affected by oregano. The addition of oregano to the diet tended to decrease CH4/DMI (SMD = −0.275; p = 0.095) but did not affect CH4 production (SMD = −0.156; p = 0.282). Heterogeneity (Q and I2) was non-significant for all parameters. We conclude that the inclusion of oregano in various forms (essential oils, plant materials, or leaves) in the diet of dairy cows reduces nutrient digestibility but does not significantly affect DMI, MY, milk components, ruminal fermentation parameters, or CH4 production. Future research should focus on optimizing the dosage of oregano (both EOs and plant materials) and exploring the impact of its form on lactation, nutrient digestibility, ruminal fermentation, and CH4 emissions in dairy cows.

The economic optimization of lactation and fertility in dairy cows

The economic optimization of lactation and fertility in dairy cows

Enzymatic Activity of Lactoperoxidase in the Colostrum of Cows in different lactations

In order to evaluate the activity of the lactoperoxidase enzyme (LPO), in colostrum and milk at the first month of lactation, the characterization of colostrum in cows was carried out from the first day postpartum and during the first month of lactation, in first, second, third and more lactations for six (06) months, the parameters were analyzed: acidity, pH, temperature, qualitative detection of the lactoperoxidase enzyme, quantifying the volume of the LPO activity. Descriptive statistics were applied using the STATISTIX 4.0 package (1985-1992) and one-way nonparametric statistics Kruskal – Wallis test for the levels First, second, third and more lactations and for the characterized parameters, using the SAS-STAT statistical system, to know the independence of the variables under study. It was found that the acidity is high and varies in a decreasing manner as follows: 37.68; 27.13 and 26.13 ml of NaOH O.1N/100ml. respectively, the pH was observed below that of milk, ranging between 5.0 and 6.2 (equiv/L). The enzymatic activity registered values of up to 182.89 U/lt., considered low compared to milk in the first month of lactation; from one to more than three lactations, according to the values found: 383.9, 394.39 and 753.54 U/ml respectively. It is concluded that the enzymatic activity is low in colostrum and then increases, until reaching the values of normal milk in the first month of lactation. The independence of each parameter (variable) in colostrum was also verified.

A comprehensive analysis of the effects of DGAT1 K232A polymorphism on milk production and fertility traits in Holstein Friesian and Jersey cows reared in Türkiye

Abstract. Research on the diacylglycerol acyltransferase 1 (DGAT1) K232A marker in cattle shows inconsistent results across regions, largely due to small sample sizes, limited genetic variation, and data restricted to few lactations, which complicates establishing a reliable genotype–phenotype correlation. This research aimed to determine the effect of the K232A polymorphism of the bovine DGAT1 gene on milk production and quality traits in dairy cattle. We used 1104 cattle, including 828 Holstein Friesian and 276 Jersey cows. The analysis utilized extensive data from six lactations of cows raised on four commercial dairy farms. We genotyped the population using the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) technique and Sanger sequencing for verification. We then evaluated the 305 d and test-day milk yields as well as fat and protein yields and percentages. The number of inseminations per conception and calving ease were also assessed as reproduction indices. Genotype–phenotype associations were quantified using linear mixed models. The AA genotype was absent in Jersey cows, and the heterozygous genotype was predominant in both breeds. The K232A marker was significantly associated with test-day milk yield, fat, and protein content in Jersey cows. Further, it substantially affected the fat percentage of milk in Holstein Friesian cows (p<0.001). We found that the KK genotype is highly desirable for milk quality and especially fat content. This comprehensive assessment demonstrated that the KK genotype of the DGAT1 K232A polymorphism significantly influenced fat and protein contents in dairy cattle.

Genetic parameters for methane production, intensity, and yield predicted from milk mid-infrared spectra throughout lactation in Holstein dairy cows

Genetic selection to reduce methane (CH4) emissions is a promising solution for reducing the environmental impact of dairy cattle production. Before such a selection program can be implemented, however, it is necessary to have a better understanding of the genetic determinism of CH4 emissions and how this might influence other traits of interest. In this study, we performed a genetic analysis of 6 CH4 traits predicted from milk mid-infrared spectra. We predicted 4 CH4 traits in g/d (MeP, calculated using different prediction equations), one in g/kg of fat- and protein-corrected milk (MeI), and one in g/kg of dry matter intake (MeY). Using an external data set, we determined these prediction equations to be applicable in the range of 70 to 200 DIM. We then estimated genetic parameters in this DIM range using random regression models on a large data set of 829,025 spectra collected between January 2013 and February 2023 from 167,514 first- and second-parity Holstein cows. The 6 CH4 traits were found to be genetically stable throughout and across lactations, with average genetic correlations within a lactation ranging from 0.93 to 0.98, and those between lactations ranging from 0.92 to 0.98. All 6 CH4 traits were also found to be heritable, with average heritability ranging from 0.24 to 0.45. The average pairwise genetic correlations between the 6 CH4 traits ranged from -0.15 to 0.77, revealing that they are genetically distinct, including the 4 measurements of MeP. Of the 6 traits, 2 measures of MeP and MeI did not present antagonistic genetic correlations with milk yield, fat and protein contents, and SCS, and can probably be included in breeding goals with limited impact on other traits of interest.

Association of Production and Selected Dimensional Conformation Traits in Holstein Friesian Cows.

The objective of this study was to estimate the heritability of dairy production traits and that for dimensional traits and to calculate the correlation between the two heritability values in a Holstein Friesian cow herd bred in Hungary. Data of 15,032 Holstein Friesian cows born in the period 2008-2018 from 666 sires were collected for the study in 6 large dairy herds. Among the conformation traits, stature (ST), chest width (CW), body depth (BD), and rump width (RW), and for production traits, in the first lactation of cows, the 305-day milk yield (MY), milk butterfat yield (FY), and milk protein yield (MY) were evaluated. Heritability estimates of ST, CW, BD, and RW were 0.49, 0.25, 0.31, and 0.30, and those of MY, FY, and PY were 0.40, 0.35, and 0.30, respectively. BD and RW had no phenotypic (b = -0.01) or genetic (b = 0.00-0.01) change. The production traits (MY, FY, PY) increased to a greater extent (b = 2.2-43.3) than the examined conformation traits over time. Consequently, it is indicated that the selection for dairy production did not result in an increase in the studied dimensional traits.

Hepatic Transcriptome Reveals Potential Key Genes Contributing to Differential Milk Production.

Despite the widespread adoption of TMR or PMR and the formulas designed to sufficiently cover the cows' requirements, individual dairy cows' milk production varies significantly. The liver is one of the most important organs in cow lactation metabolism and plays an essential role in the initiation of lactation. This study aimed to investigate the potential key genes in the liver contributing to the different milk production. We enrolled 64 cows and assigned them to high or low milk yield (MY) groups according to their first 3 weeks of milk production. We performed RNAseq for 35 liver samples with 18 from prepartum and 17 from postpartum cows. The continuous milk yield observation showed a persistently higher milk yield in high MY cows than low MY cows in the first 3 weeks. High MY cows showed better feed conversion efficiency. We identified 795 differentially expressed genes (DGEs) in the liver of high MY cows compared with low MY cows, with up-regulated genes linked to morphogenesis and development pathways. Weighted gene co-expression network analysis (WGCNA) revealed four gene modules positively correlating with milk yield, and protein and lactose yield (p < 0.05). Using the intersected genes between the four gene modules and DEGs, we constructed the linear mixed-effects models and identified six hub genes positively associated and two hub genes negatively associated with milk yield (Coefficients > 0.25, p < 0.05). Random forest machine learning model training based on these eight hub genes could efficiently predict the milk yield (p < 0.001, R2 = 0.946). Interestingly, the expression patterns of these eight hub genes remained remarkably similar before and after parturition. The present study indicated the critical role of liver in milk production. Activated processes involved in morphogenesis and development in liver may contribute to the higher milk production. Eight hub genes identified in this study may provide genetic research materials for dairy cow breeding.

Comparative study of first lactation performance of Norwegian Red crossbred cows with traditional breeds in New Zealand dairy systems

ABSTRACT Some New Zealand dairy farmers are using semen from Norwegian Red (NR) bulls to explore the performance of this breed under local grazing conditions. The objective of this study was to compare the first lactation performance of first cross NR cattle with traditional New Zealand breeds. Data were collected from six dairy farms in Southland, New Zealand, during 2022–2023 milk production seasons. Data were collected from 1178 first lactation cows including herd test of daily yields of milk, fat and protein and somatic cell counts, and persistency. Breeds included 386 NR cross (NRX), 231 Holstein Friesian (F), 84 Holstein Friesian cross (FX), 134 Holstein Friesian x Jersey (FJ) and 58 Jersey cross (JX) cows. Findings indicate F cows produced the greatest cumulative milk yield (3,744 kg), 138.6 kg more than NRX cows. There were no significant differences among the breed groups for milk yield and milk solids yield persistency and SCS (SCS = Log2 SCC). The total lactation milk yield of NRX cows was lower than that of the other breeds, excluding JX. These results pertain specifically to first lactation cows; therefore, it is necessary to undertake further analysis to evaluate the long-term productivity and longevity of NR breeds under New Zealand conditions.

517 The effects of pellet starch concentration and allocation amount for Holstein cows in peak, mid, and late lactation in an automatic milking system

Abstract This study evaluated the effects of pellet starch concentration and amount of pellet delivered in an automated milking system (AMS) on AMS pellet and partial mixed ration (PMR) intake, milk and milk component yield, and milking and feeding behavior for Holstein cows at different stages of lactation. Twenty-four Holstein cows at peak [n = 8; 85 ± 25.7 days in milk (DIM)], mid (n = 8; 185 ± 35.1 DIM) or late (n = 8; 290 ± 69.5 DIM) lactation (3 squares/DIM category), housed in a free-stall barn with a feed-first guided traffic flow AMS, were used. Treatments included low (LS; 24% DM) or high (HS; 34% DM) starch pellets that were provided at low (LA; 2 kg/d DM) or high (HA; 6 kg/d DM) quantities within replicated 4 × 4 Latin square design. Each period lasted 21 d including 16 d of adaptation and 5 d of data and sample collection to evaluate feed intake and behavior, milking characteristics, milk and milk component yields. Pellet starch did not affect the amount of pellet consumed, but HA cows consumed more pellet than LA (4.3 vs. 1.8 kg/d; P &amp;lt; 0.01). Relative to LA, HA had greater pellet refused in the AMS (P &amp;lt; 0.01) and decreased PMR intake (P = 0.04). Total DMI was 1.3 kg/d greater for HA than LA cows (P = 0.05). Pellet starch and DIM did not affect PMR intake or DMI. Neither pellet starch nor allocation affected the number of PMR meals; however, LA increased PMR eating time by 20 min/d (P &amp;lt; 0.01) and PMR meal length by 2 min/meal (P = 0.03). Milking frequency was not affected by pellet starch or DIM, but HA tended to increase total milking frequency (2.7 vs. 2.6 no/d; P = 0.06) over LA, with greater voluntary milkings (2.5 vs 2.3 no/d; P &amp;lt; 0.01). Milk yield/visit and milking duration were not affected by pellet starch or allocation. Milk yield was not affected by pellet starch, or the amount allocated averaging 43.2, 41.3 and 43.2 kg/d for peak, mid, and late lactation cows (P ≥ 0.19). Compared with LS, HS decreased milk fat concentration (4.1 vs 3.9%; P &amp;lt; 0.01) and providing the HA reduced milk fat concentration (4.1 vs 3.96%; P &amp;lt; 0.01) when compared with LA; however, neither pellet starch nor allocation affected fat yield, averaging 1.67 kg/d (P ≥ 0.15). True protein yield was not affected. Cows fed the LA had greater milk urea nitrogen (14.8 mg/dL) relative to HA (14.3 mg/dL; P = 0.03). Increasing the amount of pellet allocated in the AMS reduced PMR intake, while increasing total DMI and resulted in greater amounts of pellet refusals by cows; however, greater amounts of pellet may increase attendance at the AMS without affecting milk or milk component yields. Starch concentration of the pellet had little effect on productivity.

Liver transcriptome and proteome are modulated by nutrient restriction in early lactation cows challenged with intramammary lipopolysaccharide

The objective was to evaluate the effects of nutrient restriction on liver function 24 h after an intramammary lipopolysaccharide (LPS) challenge in early lactation cows using transcriptomic and proteomic analyses. Multiparous Holstein cows were fed a lactation diet (CONT, n = 8) throughout the study or were switched to a diet diluted with barley straw (48 % DM) for 96 h (REST, n = 8) starting at 24 (18 to 30) days in milk. At 72 h, a healthy rear mammary quarter was infused with 50 μg of LPS in all cows. Blood and liver biopsies were collected at 96 h, corresponding to 24 h after LPS challenge. Liver transcriptome was analyzed with a 44 K bovine microarray and proteome by LC MS/MS. Transcriptomic and proteomic data were analyzed using GeneSpring (moderated t-test with Westfall-Young correction) and the “between subject design”, respectively. Data mining was performed using Panther and Pathway Studio software. By design, the negative energy balance was −68 and −37 MJ/d in REST and CONT, respectively. Plasma non-esterified FAs, and β-hydroxybutyrate were significantly greater in REST compared to CONT, which is consistent with 96 h of nutrient restriction in REST and ketosis induction. We detected 77 and 91 differentially expressed genes at mRNA and protein levels, respectively, between CONT and REST. Genes involved in fatty acid synthesis (e.g.: ACAT, FASN, SCD) were downregulated in REST, whereas those involved in fatty acid oxidation, detoxification, cholesterol synthesis, lipoprotein lipid secretion, and gluconeogenesis (e.g.: ACAD, CPT1A, CPT1B, CPT2) were upregulated. Differentially abundant mRNAs and proteins were consistent with negative energy balance and plasma metabolite concentrations, and reflected a state of intense lipomobilization, glucose deficit and ketogenesis in REST cows. Nutrient restriction did not change in deep liver expression of genes directly involved in immune function 24 h after an intramammary LPS challenge.

Impact of heat stress during close-up dry period on performance, fertility and immunometabolic blood indices of dairy cows: prospective cohort study

This study aimed to investigate whether heat stress, as defined by the temperature-humidity index (THI) during the close-up dry period, had any impact on the productive performance, fertility, and immunometabolic blood indices of dairy cows in the subsequent lactation. Lactation performance was associated with increasing THI values on − 21, − 14, and − 7 d before calving resulting in decreased milk yield by about 2.30, 2.60, and 2.90 kg, respectively. The THI on the − 7 d before the calving was negatively associated with fertility parameters such as delayed first estrus postpartum, an elongated calving interval by approximately 32 d, a higher number of services per conception by 1.00, and an elongated artificial insemination service period, days open, and inter-calving period by about 20, 52, and 52 d, respectively. The study found that the immunometabolic blood indices were associated with increasing THI values during the close-up dry period. The study showed that exposing dairy cows to close-up dry period heat stress had negative consequences on performance, fertility, and immunometabolic blood indices in the subsequent lactation. Therefore, it is recommended that herd management and barn microclimate changes be implemented earlier, starting from the late dry period, to mitigate the negative impact of heat stress.

Farm-Level Risk Factors for Lameness in 659 German Dairy Herds Kept in Loose Housing Systems.

Six hundred fifty-nine farms in three regions of Germany (North: n = 240, East: n = 247, and South: n = 172) were included in the study, which aims at determining the association of management-related risk factors with farm-level lameness in German dairy herds. For each risk factor, a generalised linear regression model with negative binomial distribution and logit link was built. Results showed that cows housed in deep-bedded cubicles had a lower risk of being lame than cows housed in other cubicle types. A larger cubicle width was associated with a lower risk of being lame. Feeding a total mixed ration was associated with lower lameness prevalence (compared to feeding a partial mixed ration or single components). For first lactation cows, lameness assessment performed daily (compared to less than daily) and during other work tasks (compared to lameness assessment as a separate work task) were associated with lower risk for lameness. Finally, the present study provided evidence for crucial associations of management-related risk factors with lameness in German dairy cows, especially in the fields of cubicle design, feeding management, and lameness assessment.

Accuracy and precision of diets fed to close-up cows on dairy farms and its association with early lactation performance

Ensuring a consistent ration is critical for maximizing lactating cow performance, but this is not known for dry cows. The objectives of this cohort observational study were to: 1) characterize close-up dry cow diets fed on commercial farms in Ontario, Canada, 2) describe the accuracy of the nutrient composition between the formulated close-up diet and the diet offered to the cows, 3) describe the precision of the close-up diets across time, and 4) explore potential associations of that accuracy and precision with blood metabolic parameters and milk yield of cows in early lactation. Forty free-stall dairy farms were visited once every 4 wk, for a total of 6 visits to each farm, from April to October 2022. At each visit, samples of the close-up diet were collected and analyzed for dry matter (DM) content and chemical composition. Close-up diet formulations were also obtained by each farm's nutritionists. During each visit, fresh cows (0 to 14 d in milk [DIM]) had blood samples taken for blood metabolites. The same cows were also monitored for milk yield up to 120 DIM. Multivariable models were used to analyze associations between variability (in relation to the formulated diet and across time) of nutrients in the close-up diet, as measured by coefficient of variation (CV), and outcomes in fresh cows. Corn silage (67.6% of farms) and straw (24.3% of farms) were the predominant primary forage sources used in the close-up dry cow diets. Soybean meal (37.8% of farms) and canola meal (18.9% of farms) were the main ingredients used as primary concentrate sources. Overall, the diets offered did not accurately represent the formulated diets. With the exception of net energy for lactation (NEL), the CVs for the other nutrients were all greater than 5%. Diet variability, both between fed and formulated diets and from visit to visit during the close-up period, was associated with metabolic markers and dairy cow production. Lower variability in non-fiber carbohydrates (NFC) between the fed and formulated diets was associated with better liver health index scores. Visit-to-visit variability in fat% and NFC% were associated with blood β-hydroxybutyrate (BHB) concentrations, while NFC% variability was associated with blood glucose levels. Serum nonesterified fatty acids (NEFA) concentrations were associated with visit-to-visit variability in DM% and CP%. These results underscore the importance of maintaining consistency between diet formulations and feeding practices over time to optimize early-lactation dairy herd performance and health, granted that these diets are correctly formulated to meet the nutritional needs of cows in the close-up period and applied with recommended feeding practices.

Weighed ssGBLUP enhances the genomic prediction accuracy for milk citrate predicted by milk mid-infrared spectra of Holstein cows in early lactation

Previous studies have shown that milk citrate predicted by milk mid-infrared spectra (MIR) is strongly affected by a few genomic regions. This study aimed to explore the effect of the weighted single-step GBLUP on the accuracy of genomic prediction (GP) for MIR-predicted milk citrate in early lactation Holstein cows. A total of 134,517 test-day predicted milk citrate collected within the first 50 d in milk on 52,198 Holstein cows from the first 5 parities were used. There were 122,218 animals in the pedigree, of them 4,479 had genotypic data for 566,170 SNPs. Two data sets (partial and whole data sets) were used to verify whether the accuracy of GP is improved using the following different methods. The (genomic) estimated breeding values (EBV or GEBV) in the partial and whole data sets were estimated by pedigree-based BLUP (ABLUP), single-step GBLUP (ssGBLUP, pedigree-genomic combined using no weight for SNP), weighted ssGBLUP (WssGBLUP, pedigree-genomic combined using weighted SNP), respectively. The difference between the 2 data sets is that the phenotypic data from 2017 to 2019 in the partial data set were set as missing values. 181 youngest cows with genomic were selected as the validation population. A linear regression method was used to compare EBV (GEBV) predicted for partial and whole data sets. The accuracies of GP for ABLUP and ssGBLUP were 0.42 and 0.70, respectively. The accuracies of GP for WssGBLUP in the 5 iterations with different CT (constant) values (determines departure from normality for SNP effects) ranged from 0.70 to 0.86. This study showed that weighted SNP is beneficial in improving prediction accuracy for predicted milk citrate.

Dynamics of automated body condition scores in grazing Holstein cows in a year-round calving system

This observational study aimed to characterize the seasonal dynamics of automated body condition scores (BCS) through the lactation of Holstein cows in a pasture-based system with year-round calvings. Examining the association between nadir BCS (nBCS; defined as the lowest daily BCS after calving) and peak milk yield within each calving period (calendar seasons equally divided in early and late) was a secondary objective of this research. Retrospective data included 2,164 lactations in 539 primiparous (PRI) and 1,625 multiparous (MLT) Holstein cows that calved from July 2021 to June 2023 in a commercial dairy farm located in Southern Chile. Individual BCS were generated in every milking by an automated BCS camera system. Body condition score at calving (BCSc), nBCS, and the change in BCS from calving to nadir (ΔBCS) were considered for the analysis. Peak milk yield (greatest daily milk yield) values were retrieved from on-farm software and lactations were categorized considering quartiles (Q1 = 25% lowest peak milk yield; Q4 = 25% greatest peak milk yield). Data were examined in PRI and MLT cows separately using multivariable linear models that considered calving period and peak milk yield as the main explanatory variables of interest, while BCSc and health status were included as covariables when appropriate. The differences in BCSc among calving periods were more evident in primiparous cows that had the lowest BCSc in early spring (3.13 ± 0.03) and the greatest BCSc in late fall (3.51 ± 0.03). In MLT cows, the lowest and greatest BCSc were recognized in late fall (3.07 ± 0.04) and early summer (3.23 ± 0.03), respectively. Only MLT cows had differences in nBCS and ΔBCS across calving periods: The lowest nBCS were identified in late spring (2.71 ± 0.02), early summer (2.71 ± 0.02), and in late summer (2.71 ± 0.02). The greatest losses in BCS also occurred in early summer (−0.41 ± 0.02) and in late spring (−0.41 ± 0.02). Time from calving to nBCS varied among calving periods and depended on parity category. Primiparous cows reached nBCS earlier in late summer (65 ± 8 DIM) and late spring (68 ± 7 DIM), while MLT had the shortest times to nBCS in late and early fall (67 ± 5 DIM; 68 ± 5 DIM). Greater values at milk peak were associated with lower nBCS only in multiparous cows during the late spring period. We concluded that the dynamics of BCS were associated with calving period in both parity groups. This data could help guide decisions on nutrition and breeding strategies in farms facing comparable conditions.

Longitudinal characterization of the muscle metabolome in dairy cows during the transition from lactation cessation to lactation resumption

Skeletal muscle is vital in maintaining metabolic homeostasis and adapting to the physiological needs of pregnancy and lactation. Despite advancements in understanding metabolic changes in dairy cows around calving and early lactation, there are still gaps in our knowledge, especially concerning muscle metabolism and the changes associated with drying off. This study aimed to characterize the skeletal muscle metabolome in the context of the dietary and metabolic changes occurring during the transition from the cessation of lactation to the resumption of lactation in dairy cows. Twelve Holstein dairy cows housed in tie stalls were dried off 6 weeks (wk) before the expected calving date. Cows were individually fed ad libitum total mixed rations composed of grass silage, corn silage, and concentrate during lactation and of corn silage, barley straw, and concentrate during the dry period. The metabolome was characterized in skeletal muscle samples (M. longissimus dorsi) collected on wk -7 (9 d before dry-off), -5 (6 d after dry-off), and wk -1, and 1 relative to calving. The targeted metabolomics approach was conducted using the MxP Quant 500 kit (Biocrates Life Sciences AG) with liquid chromatography, flow injection, and electrospray ionization triple quadrupole mass spectrometry. Statistical analysis on the muscle metabolite data was performed using MetaboAnalyst 5.0, which allowed us to conduct various multivariate analyses such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), informative heat map generation, and hierarchical clustering. The statistical analysis revealed a clear separation between pregnancy (wk -7, -5, and -1) and post-calving (wk 1). Starting 5 wk before calving and continuing through the first wk thereafter, the concentration of 3-methylhistidine (3-MH) in the muscle increased. This coincided with an increase in the concentrations of 11 AA (Phe, His, Tyr, Trp, Arg, Asn, Leu, Ile, Gly, Ser, and Thr) in the first wk after calving, whereas Gln decreased. l-arginine pathway metabolites (homoarginine, ornithine, citrulline, and asymmetric dimethylarginine), betaine, and sarcosine followed a similar pattern, increasing from wk -7 to -5, but decreasing from wk -1 to 1. The transition from pregnancy to lactation was associated with an increase in concentrations of the long-chain acylcarnitine species C16, C16:1, C18, and C18:1 in the muscle, whereas the concentrations of phosphatidylcholine and sphingomyelin in the muscle remained stable. The significant changes observed in the metabolome mainly concerned the AA and AA-related metabolites, indicating muscle protein breakdown in the first wk after calving. The metabolites produced by the L-Arg pathway might contribute to regulating skeletal muscle mass and function in periparturient dairy cows. The elevated concentrations of long-chain acylcarnitine species in the muscle in the first wk after calving suggest incomplete fatty acid oxidation, likely due to insufficient metabolic adaptation in response to the fatty acid load around the time of calving.

Comparison of a machine learning model with a conventional rule-based selective dry cow therapy algorithm for detection of intramammary infections

We trained machine learning models to identify intramammary infections (IMI) in late lactation cows at dry-off to guide antibiotic treatment, and compared their performance to a rule-based algorithm that is currently used on dairy farms in the US. We conducted an observational test-characteristics study using a data set of 3,645 cows approaching dry-off from 68 US dairy herds. The outcome variables of interest were cow-level IMI caused by all pathogens, major pathogens, and Streptococcus and Strep-like organisms (SSLO), which were determined using aerobic culture of aseptic quarter-milk samples and identification of isolates using MALDI-TOF. Individual cow records were extracted from the farm software to create 53 feature variables at the cow and 39 at the herd-level which were derived from cow-level descriptive data, records of clinical mastitis events, results from routine testing of milk for volume and concentrations of somatic cell count (SCC), fat, and protein. ML algorithms evaluated were logistic regression, decision tree, random forest, light gradient-boosting machine, naïve bayes, and neural networks. For comparison, cows were also classified according to a conventional rule-based algorithm that considered a cow as high risk for IMI if she had at one or more high SCC (>200,000 cells/ml) tests or ≥2 cases of clinical mastitis during the lactation of enrollment. Area under the curve (AUC) and Youden's index were used to compare models, in addition to binary classification metrics, including sensitivity, specificity, and predictive values. ML models had slightly higher AUC and Youden's index values than the rule-based algorithm for all IMI outcomes of interest. However, these improvements in prediction accuracy were substantially less than what we had considered necessary for the technology to be a worthwhile alternative to the rule-based algorithm. Therefore, evidence is lacking to support the wholesale use of ML-guided selective dry cow therapy at the moment. We recommend that producers wanting to implement algorithm-guided SDCT use a rule-based method.

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.

The effect of flow-responsive vacuum and pulsation with early attachment of milking unit on teat tissue condition and milking performance in Holstein dairy cows

The objectives of this study were to assess the effect of flow-responsive vacuum and pulsation, in conjunction with the early attachment of the milking unit (TRT), on teat tissue conditions and milking characteristics in dairy cows. In a switch-back trial, 5,235 Holstein cows milked 3 times daily in a rotary parlor were assigned to the TRT or control (CON) group. The trial lasted 84 d and was comprised of 4 alternating 3-week periods of TRT and CON. For both groups, premilking udder preparation consisted of teat brushing, forestripping and predipping, and wiping of teats, resulting in a stimulation time of 4 s. In the TRT group, the preparation lag time was 58 s, and in the CON group, it was 91 s for early- and mid-lactation cows and 105 s for late-lactation animals. Upon milking unit attachment, the TRT cows were milked at a lower vacuum (37.6 kPa) and pulsation (50 cycles/min, pulsation ratio of 30:70). The vacuum and pulsation settings were changed to milking mode when the milk flow reached 0.5 kg/min (pulsation switch-point) and 1.6 kg/min (vacuum switch-point). For milking mode, the vacuum setting was 47.7 kPa, and the pulsation rate was 60 cycles/min at a ratio of 65:35. The CON cows were milked with a flow-responsive vacuum, using the same vacuum settings as the TRT group. We assessed machine milking-induced short-term teat tissue changes and teat-end hyperkeratosis by palpation and visual inspection postmilking. Electronic on-farm milk meters were used to assess milking characteristics. Generalized linear mixed models were used to analyze the effect of treatment on the outcome variables. Compared with cows in group CON, the odds ratios (95% confidence interval; 95% CI) of short-term teat-tissue changes in early-, mid-, and late lactation cows in group TRT were 0.62 (0.52-0.76), 0.61 (0.48-0.77), and 0.93 (0.76-1.14), respectively. The least squares means [LSM, (95% CI)] for milking unit-on time in early-, mid-, and late lactation animals, respectively, were 251 (248-253), 236 (234-238), and 220 (218-222) s for group TRT and 247 (245-249), 232 (230-234), and 214 (213-216) s for the CON group. The LSM (95% CI) of peak milk flow rate in early-, mid-, and late lactation animals, respectively, were 5.75 (5.68-5.82), 5.77 (5.70-5.84), and 5.54 (5.48-5.59) kg/min for the TRT cows and 5.65 (5.58-5.72), 5.74 (5.68-5.81), and 5.45 (5.40-5.51) kg/min for the CON cows. The odds ratios (95% CI) of forced take-off in group TRT for early-, mid-, and late lactation cows, respectively, were 0.39 (0.37-0.41), 0.32 (0.30-0.34), and 0.47 (0.44-0.52) compared with their respective CON groups. In this study, cows that were milked using flow-responsive vacuum and pulsation with early attachment of the milking unit had lower odds of short-term teat tissue changes and forced take-off, as well as a higher peak milk flow rate. Our data suggest that the application of flow-responsive vacuum and pulsation facilitates early attachment of the milking unit, improves teat tissue condition, and has the potential to improve parlor efficiency.

Essential oils and capsaicin in the diet of Jersey cows at early lactation and their positive impact on anti-inflammatory, antioxidant and immunological responses.

The objective of this work was to determine whether the addition of phytogenic compounds based on essential oils (carvacrol, eugenol, cinnamaldehyde) and resinous pepper oil (capsaicin) to the diet of Jersey cows at the beginning of lactation affects anti-inflammatory, antioxidant and immunomodulatory responses, as well as whether there are effects of EO on blood metabolites, ruminal fermentation, digestibility and milk production and composition. Six primiparous cows (370.00 ± 17kg body weight (BW); 13.02kg dry matter intake (DMI); 21 days of lactation and average milk production of 20 ± 2L per day) were allocated to crossed experimental design (2 × 2) with two experimental periods of 28 days and two treatments. Blood, milk and rumen fluid were collected and, at the end of each period, feed and feces samples were collected to evaluate the apparent digestibility of nutrients. The groups were control (CLT) without supplementation and treated (BEO) with the addition of 150mg/kg of dry matter of the phytogenic to the concentrated portion of the diet. Cows in the BEO group had lower numbers of leukocytes (P ≤ 0.05) and lymphocytes (P ≤ 0.02), but total protein and globulin levels were higher on days 21 and 28 (P ≤ 0.01). In the BEO group, the levels of immunoglobulin A, immunoglobulin heavy chain and transferrin were higher (P ≤ 0.05). The levels of ceruloplasmin, haptoglobin and C-reactive protein were lower in the BEO group (P ≤ 0.05). Lipid peroxidation levels and protein carbonyl content were lower in the BEO group. The total antioxidant capacity (P ≤ 0.09) and the activity of glutathione S-transferase (P ≤ 0.03) and glutathione peroxidase (P ≤ 0.05) were higher in the BEO group. Cows in the BEO group had lower pH (P ≤ 0.05), acetic acid concentrations (P ≤ 0.01) and higher protozoa counts (P ≤ 0.01). Our results suggest that phytogenic supplementation has positive effects on the health of Jersey cows in early lactation, characterized by immunostimulant, antioxidant and anti-inflammatory effects.