Cow Health Research Articles

Review: Linking animal health measures in dairy cows to farm-level economic outcomes: a systematic literature mapping.

Farm animal health is an area of increasing interest to both the public and industry stakeholders. There is an ongoing debate on whether improving animal health, and thereby increasing welfare, is profitable or not. Improving animal health often requires investments in the farm or increases labour costs. As a result, the impact of animal health on farm economy is particularly interesting. This study systematically maps and assesses the available evidence in the published scientific literature regarding the link between farms' economic outcomes on dairy cow health, with the aim of identifying knowledge gaps in this field of research. In total, 59 peer-reviewed articles were included using a broad range of animal health variables and economic outcomes. We found a heterogeneous body of evidence in terms of both methods, animal health measures (AHMs) and economic outcome measures used. None of the included studies makes explicit causal claims between AHMs and economic outcomes. The results suggest that common production diseases such as clinical mastitis and lameness, which are painful and affect cow health and welfare, are costly for farmers. We found a knowledge gap and lack of evidence on the impact of animal health interventions on farms' economic outcomes, as well as the long-term effects of such interventions. Future research should aim to investigate the causal links between animal health and economic outcomes.

Seasonal effects on multiparous dairy cow behavior in early lactation

Controlled studies have shown that heat stress abatement positively influences health, productivity, behavior, and reproductive performance of dairy cows during all stages of the lactation cycle. Based on previous findings, the present study focused on a better understanding of how seasonal changes affect the behavior of multiparous lactating dairy cows kept in typical free-stall housing with the objective to aid in the management of lactating cows exposed to variable environmental conditions. Automated monitoring devices (Nedap, the Netherlands) were used to assess behavioral activity of mature Holstein dairy cows during the “hot season” (HS; n = 19; July, August, and September) and the “cool season” (CS; n = 15; December, January, and February) under normal management conditions. Cows received a leg tag to measure daily lying time, and number of steps and standing bouts, and a neck tag to measure eating and rumination time. All cows were housed in sand-bedded freestall barns equipped with cooling systems (soakers and fans). Behavior, milk production and milk components were recorded for the first 9 wk of lactation after calving. Average temperature-humidity index (THI) was 78.2 ± 0.4 (± standard error) in the HS and 54.4 ± 0.2 in the CS. Fat-corrected milk yield was greater in the CS compared with HS during the first 5 wk of lactation. Milk protein percentage was lower in CS during the first 2 wk of lactation. In contrast with HS, milk fat percentage was greater in the CS. Compared with CS, overall, during HS cows spent less time eating, lying down, and tended to spend less time ruminating. In addition, exposure to high THI resulted in increases in standing bouts, and overall standing time in HS relative to CS. No differences in number of steps were observed between HS and CS. In summary, exposure to high THI during lactation seems to negatively affect the behavior and consequently the daily time budget of lactating Holstein cows, even under housing conditions with active cooling. A better understanding on how different seasons affect the daily time budget of lactating dairy cows may contribute to the development of more effective management strategies to decrease the negative effects of heat exposure.

A Comparative Evaluation of the Alternative Anatomical Sites for Body Temperature Measurement Using Digital Thermometers in Dairy Cows

The measurement of body temperature is a critical aspect of assessing the health and reproductive status of dairy cows. The standard method used to estimate this temperature is rectal thermometry. However, this technique has limitations, including disease spread, distress, and or risks of rectal injuries. The current study was undertaken to validate the potential of alternative anatomical sites for temperature measurement using a digital thermometer (DT). The study employed a one-factor experimental design considering the anatomical site as the main factor, with four treatments or factor levels, namely rectal (DTtrectal), inguinal (DTtinguinal), axillary (DTtaxillary), and undertail (DTtundertail) sites. A simple random sampling technique was employed to determine the order of site selection for temperature measurement. In total, 26 adult Holstein Friesian-Boran cows with an average weight of 482 kg were used to conduct this study. Each cow was assessed for all the treatments considered in this study. The temperature measured at different anatomical sites was evaluated. The highest mean temperature was observed for rectal temperature (38.27 ± 0.42℃), while that of mean axillary temperature was the lowest (37.75 ± 0.53℃). The mean temperature readings were significantly affected by the anatomical site. There was no significant difference between mean rectal and inguinal or undertail temperature. There was a significant correlation between the rectal and undertail temperature, while no significant correlation was observed between rectal and inguinal temperature. The equivalence analysis between the rectal and undertail pair revealed a significant bias. This bias suggests that the two anatomical sites cannot be used interchangeably, particularly with digital thermometer application in Holstein Friesian-Boran cows. However, the observed mean undertail temperature and its correlation with rectal temperature indicated that the undertail site still holds promise as an alternative site for temperature-taking under conditions different from this study.

A Review on Information Technologies Applicable to Precision Dairy Farming: Focus on Behavior, Health Monitoring, and the Precise Feeding of Dairy Cows

Milk production plays an essential role in the global economy. With the development of herds and farming systems, the collection of fine-scale data to enhance efficiency and decision-making on dairy farms still faces challenges. The behavior of animals reflects their physical state and health level. In recent years, the rapid development of the Internet of Things (IoT), artificial intelligence (AI), and computer vision (CV) has made great progress in the research of precision dairy farming. Combining data from image, sound, and movement sensors with algorithms, these methods are conducive to monitoring the behavior, health, and management practices of dairy cows. In this review, we summarize the latest research on contact sensors, vision analysis, and machine-learning technologies applicable to dairy cattle, and we focus on the individual recognition, behavior, and health monitoring of dairy cattle and precise feeding. The utilization of state-of-the-art technologies allows for monitoring behavior in near real-time conditions, detecting cow mastitis in a timely manner, and assessing body conditions and feed intake accurately, which enables the promotion of the health and management level of dairy cows. Although there are limitations in implementing machine vision algorithms in commercial settings, technologies exist today and continue to be developed in order to be hopefully used in future commercial pasture management, which ultimately results in better value for producers.

Association of transition cow health with pregnancy per artificial insemination and pregnancy loss in Holstein cows submitted to a Double-Ovsynch protocol for first service

This observational study was conducted to evaluate the effect of transition cow health on pregnancy per artificial insemination (P/AI) and pregnancy loss (PL) in cows submitted to a Double-Ovsynch protocol (DO) for first service. Lactating Holstein cows (n = 15,041) from one commercial dairy farm in northern Germany between January 2015 to December 2021 were enrolled into a modified Double-Ovsynch protocol (GnRH, 7 d later PGF2α, 3 d later GnRH, 7 d later GnRH, 7 d later PGF2α, 24 h later PGF2α, 32 h later GnRH, and 16 to 18 h later timed artificial insemination) for first service at 72 ± 3 d in milk. Pregnancy was diagnosed at 32 and 60 d post-AI via transrectal ultrasonography. Pregnancy loss was defined as the proportion of cows diagnosed pregnant 32 d post-artificial insemination that were diagnosed nonpregnant 60 d post-artificial insemination. Health-related events (i.e., milk fever [MF], hyperketonemia [KET], retained fetal membranes [RFM], metritis, mastitis, left displaced abomasum [LDA]) were assessed by farm personnel using standard operating procedures. Multivariable logistic regression was used for testing potential associations between transition cow health event occurrence and outcome variables, including P/AI and PL. Three separate models were built for cows in first lactation, second lactation, and ≥third lactation. Overall, 20.0% (885/4,430), 34.9% (1,391/3,989), and 53.9% (3,570/6,622) of cows had at least one transition cow health event for first, second, and ≥third lactations, respectively. The most prevalent transition cow health event for first-lactation cows was metritis (10.7%; [473/4,430]), whereas second-lactation cows suffered mostly from mastitis (16.6%; [664/3,989] and KET (16.6%; [661/3,989]), and cows with ≥third lactations were mostly affected by KET (33.2%; [2,198/6,622]). We observed a negative association between inflammatory disorders (i.e., RFM, metritis, mastitis) and P/AI in all cows irrespective of parity. Metabolic disorders (i.e., MF, KET, LDA) were negatively associated with P/AI only in multiparous cows. Irrespective of parity, only uterine diseases (i.e., RFM, metritis) were significantly associated with PL. These results show that enrolling cows into a fertility protocol, such as DO, cannot overcome the carryover effects of inflammatory and metabolic disorders on P/AI and PL and highlight the importance of optimizing transition cow health as a prerequisite for achieving high fertility in a DO protocol.

Review and analysis on fertility and milk production in commercial dairy farms with customized lactation length during the last ten years

Approximately 150 million households around the globe are engaged in milk production. In most developing countries, milk is produced by smallholders, and milk production contributes to household livelihoods, food security and nutrition. Milk provides relatively quick returns for small-scale producers and is an important source of cash income. In recent decades, developing countries have increased their share in global dairy production. This growth is mostly the result of an increase in numbers of producing animals rather than a rise in productivity per head. In many developing countries, dairy productivity is constrained by poor-quality feed resources, diseases, limited access to markets and services (e.g., health, credit and training) and dairy animals’ low genetic potential for milk production. Unlike developed countries, many developing countries have hot and/or humid climates that are unfavourable for dairying. Traditionally, dairy farmers are recommended to aim for a 1-yr calving interval, as this would maximize milk production and income. Longer calving intervals would extend the period in late lactation, when milk production is lower. However, there may be several reasons to re-evaluate the traditional lactation length, including increased productivity of modern dairy cows, and potential benefits of longer lactations for cow health and welfare. Moreover, although farmers are advised to aim for a 1-yr calving interval, in practice calving intervals mostly exceed 1 yr. Some cows might be better suited for an extended CInt than others, due to differences in milk yield level, lactation persistency, or health status, which would justify a customized CInt based on individual cow characteristics. This study aims to investigate 13 farms with customized CInt, with respect to calving to first service interval (CFSI), accomplished CInt, services per conception (SC), conception rate at first artificial insemination (CR1AI), peak yield, lactation persistency, 305-d yield, and effective lactation yield. In total, 4,858 complete lactations of Holstein Friesian cows between 2012 and 2022 from the 13 farms were grouped by parity and CFSI or CInt.

Exploratory study of volatile fatty acids and the rumen-and-gut microbiota of dairy cows in a single farm, with respect to subclinical infection with bovine leukemia virus

BackgroundSubclinical infection with bovine leukemia virus (BLV) in cows can cause economic losses in milk and meat production in many countries, as BLV-related negative effects. The volatile fatty acids (VFAs) and microbiota present in the digestive tracts of cows can contribute to cow health. Here, we exploratorily investigated the VFAs and microbiota in the rumen and gut with respect to subclinical BLV infection using cows housed at a single farm.ResultsWe analyzed a herd of 38 cows kept at one farm, which included 15 uninfected and 23 BLV-infected cows. First, the analysis of the VFAs in the rumen, gut, and blood revealed an absence of statistically significant differences between the uninfected and BLV-infected groups. Thus, BLV infection did not cause major changes in VFA levels in all tested specimens. Next, we analyzed the rumen and gut microbiota. The analysis of the microbial diversity revealed a modest difference between the uninfected and BLV-infected groups in the gut; by contrast, no differences were observed in the rumen. In addition, the investigation of the bacteria that were predominant in the uninfected and BLV-infected groups via a differential abundance analysis showed that no significant bacteria were present in either of the microbiota. Thus, BLV infection possibly affected the gut microbiota to a small extent. Moreover, bacterial associations were compared between the uninfected and BLV-infected groups. The results of this analysis suggested that BLV infection affected the equilibrium of the bacterial associations in both microbiota, which might be related to the BLV-related negative effects. Thus, BLV infection may negatively affect the equilibrium of bacterial associations in both microbiota.ConclusionsSubclinical BLV infection is likely to affect the rumen and gut microbiota, which may partly explain the BLV-related negative effects.

A 2-year study reveals implications of feeding management and exposure to mycotoxins on udder health, performance, and fertility in dairy herds

We recently reported the ubiquitous occurrence of mycotoxins and their secondary metabolites in dairy rations and a substantial variation in the feeding management among Austrian dairy farms. The present study aimed to characterize to which extent these factors contribute to the fertility, udder health traits, and performance of dairy herds. During 2019 and 2020, we surveyed 100 dairy farms, visiting each farm 2 times and collecting data and feed samples. Data collection involved information on the main feed ingredients, nutrient composition, and the levels of mycotoxin and other metabolites in the diet. The annual fertility and milk data of the herds were obtained from the national reporting agency. Calving interval was the target criterion for fertility performance, whereas the percentage of primiparous and multiparous in the herd with somatic cell counts (SCC) above 200,000 cells/mL for impaired udder health. For each criterion, herds were classified into 3 groups: High/Long, Mid and Low/Short, with the cut-off corresponding to the < 25th and > 75th percentiles and the rest of the data, respectively. Accordingly, for the calving interval, the cut-offs for the Long and Short groups were ≥400 d and ≤380 d, for the udder health in primiparous cows were ≥20% and ≤8% of the herd, and for the udder health in multiparous cows were ≥35% and ≤20% % of the herd, respectively. Quantitative approaches were further performed to define potential risk factors in the herds. The High SCC group had higher dietary concentrations of enniatins (ENNs) (2.8 vs. 1.62 mg/cow/day), deoxynivalenol (DON) (4.91 vs. 2.3 mg/cow/day), culmorin (CUL) (9.48 vs. 5.72 mg/cow/day), beauvericin (BEA) (0.32 vs. 0.18 mg/cow/d) and siccanol (13.3 vs. 5.15 mg/cow/d), total Fusarium metabolites (42.8 vs. 23.2 mg/cow/d) and used more corn silage in the ration (26.9 vs. 17.3% diet DM) compared with the Low counterparts. BEA was the most substantial contributing variable among the Fusarium metabolites, as indicated by logistic regression and modeling analyses. Logistic analysis indicated that herds with high proportions of cows with milk fat-to-protein ratio >1.5 had an increased odds for a longer calving interval, which was found significant for primiparous cows (odds ratio = 5.5, 95% confidence interval (CI) = 1.65 - 21.7). As well, herds with high proportions of multiparous cows showing levels of milk urea nitrogen > 30 mg/dL had an increased odds for longer calving intervals (odds ratio = 2.96, CI = 1.22 - 7.87). In conclusion, the present findings suggest that dietary contamination of Fusarium mycotoxins (especially emerging ones), likely due to increased use of corn silage in the diet, seems to be a risk factor for impairing the udder health of primiparous cows. Mismatching dietary energy and protein supply of multiparous cows contributed to reduced herd fertility performance.

Vaginal Microbiome Dynamics of Cows in Different Parities.

At present, there is still room for research on the relationship between the vaginal microbiome and the reproductive health of dairy cows. In this study, high-throughput 16S rRNA sequencing technology was used to explore the differences of bacterial communities of dairy cows of different births, gain a deeper understanding of cow reproductive physiology, and maintain cow health. With the increase in parity, the number of vaginal flora decreased from 3511 to 469, but the number of species increased significantly, and Chao1 increased from 1226.41 ± 345.40 to 1467.76 ± 269.76. There was a significant difference in the number of vaginal microbiome functions between uncounted cows and calving cows. There was no significant difference in microbial diversity in calves. The relative abundance variation of vaginal microbiota in high-parity cows is less than that in low-parity cows. The amino acid metabolism of calves increased, the endocrine function of high-parity cows was enhanced, and the function of the vaginal microbiome increased after the first delivery, which gradually decreased with the increase in parity. This study also found that Methanobacteria and Caviibacter may be involved in amino acid metabolism and endocrine function, and they may play a key role in cow reproduction. This study provides an important theoretical basis for studying changes in vaginal microorganisms in dairy cows, improves the understanding of reproductive health and production performance, and provides a scientific basis for improving the reproductive management of dairy cows.

Associations of cow- and herd-level factors during the dry period with indicators of udder health in early-lactation cows milked by automated milking systems

This observational study aimed to determine the association of cow-level factors and herd-level housing and management practices during the dry period with indicators of udder health in early-lactation cows in automated milking system (AMS) herds. Data were collected from 166 commercial AMS dairy farms (mean ± standard deviation = 116 ± 111 milking cows; range = 39 to 1,200) across Canada between October 2018 and September 2020. Information on herd demographics, housing, and management practices was obtained on each farm using 2 surveys. On each farm, we selected all cows that had available Dairy Herd Improvement (DHI) somatic cell count (SCC) data for their last milk test before dry-off (>250 d in milk) and their first milk test after calving (5-45 d in milk). Data from 14,007 cows were included after excluding cows with a dry period of <30 d and >120 d. Using the SCC data, we calculated for each cow the somatic cell score (SCS) for the last milk test before dry-off (PreSCS) and the first milk test after calving (PostSCS), which we then averaged per herd at a test-day level. Intramammary infection (IMI) was estimated using cow SCC data. Each cow was classified as not infected (SCC <200,000 cells/mL) or infected (SCC ≥200,000 cells/mL) at her last milk test before dry-off and her first milk test after calving. Based on this classification, cows were further categorized as never infected, always infected, new IMI, or cured IMI. At the cow level, a higher PostSCS was associated with longer dry periods. The odds of having a new IMI were higher for cows of higher parity and that had lower 305-d milk yield before dry-off. Cows with lower parity were more likely to cure an IMI. At the herd level, a higher 305-d milk yield before dry-off was associated with a lower incidence of new IMI and a higher incidence of cured IMI. Separating cows into a different pen as preparation for dry-off tended to be associated with a lower PostSCS and incidence of new IMI. At dry-off, herds that used teat sealants and blanket antibiotic dry cow therapy also had lower PostSCS. During the dry period, housing cows in different groups was associated with a higher PostSCS and a lower incidence of cured IMI, while housing cows in both pack pens and stalls compared with only pack pens was associated with a lower incidence of new IMI. Finally, placing cows onto the AMS to be milked one or more days after calving tended to be associated with a lower PostSCS compared with placing them in the AMS within the first day postpartum. In summary, indicators of udder health in early-lactation cows in AMS herds were associated with several cow-level factors and herd-level housing and management practices before dry-off, at dry-off, during the dry period, and at the beginning of lactation. Thus, if some of the associations identified are causal, AMS producers may be able to improve udder health through modifications of housing and management practices.

Observational study on the associations between milk yield, composition, and coagulation properties with blood biomarkers of health in Holstein cows

The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits). All milk traits (i.e., production, composition, and technological traits) were analyzed according to a linear mixed model that included the days in milk, the parity order, and the blood metabolites (tested one at a time) as fixed effects and the herd and date of sampling as random effects. Our findings revealed that milk yield and daily milk energy output were positively and linearly associated with total cholesterol, nonesterified fatty acids, urea, aspartate aminotransferase, γ-glutamyl transferase, total bilirubin, albumin, and ferric-reducing antioxidant power, whereas they were negatively associated with glucose, creatinine, alkaline phosphatase, total reactive oxygen metabolites, and proinflammatory proteins (ceruloplasmin, haptoglobin, and myeloperoxidase). Regarding composition traits, the protein percentage was negatively associated with nonesterified fatty acids and β-hydroxybutyrate (BHB), while the fat percentage was positively associated with BHB, and negatively associated with paraoxonase. Moreover, we found that the lactose percentage increased with increasing cholesterol and albumin and decreased with increasing ceruloplasmin, haptoglobin, and myeloperoxidase. Milk urea increased with an increase in cholesterol, blood urea, nonesterified fatty acids, and BHB, and decreased with an increase in proinflammatory proteins. Finally, no association was found between the blood metabolites and milk coagulation properties and curd-firming traits. In conclusion, this study showed that variations in blood metabolites had strong associations with milk productivity traits, the lactose percentage, and milk urea, but no relationships with technological traits of milk. Specifically, increasing levels of proinflammatory and oxidative stress metabolites, such as ceruloplasmin, haptoglobin, myeloperoxidase, and total reactive oxygen metabolites, were shown to be associated with reductions in milk yield, daily milk energy output, lactose percentage, and milk urea. These results highlight the close connection between the metabolic and innate immunity status and production performance. This connection is not limited to specific clinical diseases or to the transition phase but manifests throughout the entire lactation. These outcomes emphasize the importance of identifying cows with subacute inflammatory and oxidative stress as a means of reducing metabolic impairments and avoiding milk fluctuations.

Assessment of Ruminating, Eating, and Locomotion Behavior during Heat Stress in Dairy Cattle by Using Advanced Technological Monitoring.

Heat stress (HS) significantly impacts dairy farming, prompting interest in precision dairy farming (PDF) for gauging its effects on cow health. This study assessed the influence of the Temperature-Humidity Index (THI) on rumination, eating, and locomotor activity. Various parameters, like rumination time, drinking gulps, chews per minute, and others were analyzed. The hypothesis was that precision dairy farming technology could help detect HS. Nine healthy Lithuanian Black-and-White cows were randomly selected for the trial. RumiWatch noseband sensors recorded behaviors, while SmaXtec climate sensors monitored THI. The data collection spanned from 14 June to 30 June. Cows in the THI class ≥ 72 exhibited reduced drinking time (51.16% decrease, p < 0.01), fewer chews per minute (12.9% decrease, p < 0.01), and higher activity levels (16.99% increase, p < 0.01). THI showed an inverse correlation with drinking time (r = -0.191, p < 0.05) and chews per bolus (r = -0.172, p < 0.01). Innovative technologies like RumiWatch are effective in detecting HS effects on behaviors. Future studies should explore the impact of HS on RWS biomarkers, considering factors such as lactation stage, number, yield, and pregnancy.

Analysis of the influence of the Norwegian Red bull-sires with different breeding value on milk productivity, health, exterior and reproductive traits of daughters

An analysis of the influence of breeding bulls of the Norwegian Red (NR) breeds with different breeding values (BV) on the milk productivity of daughters, their health, reproductive characteristics, udder characteristics, exterior, and indices of productive use. The study material was the data from the electronic catalog of breeding bulls of the NR breed as of April 4, 2023. The sample was formed from the data of only those breeders recommended for reproduction in 2023 by Geno SA. The animals were grouped according to the Total Merit Index (TMI). Breeding bulls with the highest TMI – 53-35 (n = 24) were assigned to the I group, to the II group – with an average TMI – 34-25 (n = 25), and to the III group – bulls with the lowest TMI – 24-10 (n = 22). As a result of the research, it was established that the most significant influence on the indices of productive use of daughters was observed in breeding bulls of the NR breed of the I group (High production index (HPI) – 118.13 % (Р &lt; 0.001), Grazing index (GI) – 110.88 % (Р &lt; 0.05)). According to the TMI index, bulls of the I and II groups prevailed over the sires of the III group, according to their improving effect, on such signs of milk productivity of daughters as milk yield (Р &lt; 0.01), amount of milk fat (Р &lt; 0.05; Р &lt; 0.01) and protein (Р &lt; 0.01; Р &lt; 0.001) and milk productivity index (Р &lt; 0.001 and Р &lt; 0.01) in daughter cows. The greatest improving effect on the udder health of the daughter cows was observed in breeding bulls of the NR breed with TMI 53-35. Bull-sires of groups I and II reduced the number of somatic cells count in the milk of daughter cows by 15.58 and 9.16 %, and bulls of III – only by 3.82 %. Breeder bulls of groups I and III increased milking speed in daughter cows by 4.25 and 1.68 %, and breeders of group II decreased it by 1.96 %. However, the difference was significant only between groups I and II (P &lt; 0.05). Studied breeding sires increased daughters' stature (height) in all groups. Group I sires had the most significant influence on daughters' stature – 114.88, and III group sires had the most minor influence – 102.00. However, the difference was significant between the I and II and I and III groups (Р &lt; 0.05; Р &lt; 0.001). Bull-sires of the I group of the NR breed increased the feet and legs index in daughter cows, as well as the foot angle by 7.58 and 7.38 %, II breeders by 3.48 and 2.48 %, and bulls III reduced these traits in daughters by 0.41 and 0.14 %. The difference between the I and III groups was significant (P &lt; 0.05). Breeder bulls of the NR breed with TMI 53–35 were leaders in improving the udder index of daughters, as well as in reducing its udder depth, strengthening the fore udder attachment, increasing the rear udder width and rear udder height. Therefore, the most significant impact on most of the studied traits was observed in breeding bulls of the NR breed with the highest BV – TMI 53-35. The influence of sires with TMI 53-35 and 34-25 on daughters' milk production was almost the same and improving. However, in terms of the effect on the reproductive characteristics of daughter cows, no significant difference was found between all experimental groups of breeding bulls.

Heat stress affects dairy cow health status through blood oxygen availability

BackgroundRises in global warming and extreme weather occurrence make the risk of heat stress (HS) induced by high ambient temperatures more likely in high-yielding dairy cows, resulting in low milk quality and yield. In animals, oxygen is involved in many physiological and metabolic processes, but the effects of HS on oxygen metabolism remain unclear. Thus, the current study aimed to investigate how oxygen metabolism plays a role in health status of dairy cows by measuring the milk yield, milk composition, and blood biochemical variables of cows under different levels of HS: none (No-HS), mild (Mild-HS), and moderate HS (Mod-HS).ResultsThe HS significantly increased rectal temperature (Ptreat < 0.01) and respiration rate (Ptreat < 0.01). Under Mod-HS, greater Na+ (P < 0.05) and lower total CO2, and pH (P < 0.05) were observed relative to those under No-HS and Mild-HS. Oxygen concentrations in both coccygeal artery and mammary vein (Ptreat < 0.01) were lower under Mod-HS than under No-HS. Coccygeal vein concentrations of heat shock protein 90 (HSP90) (P < 0.05) increased during Mod-HS compared with those in cows under No-HS. Malondialdehyde increased during Mod-HS, and glutathione peroxidase (P < 0.01) increased during Mild-HS. Coccygeal vein concentrations of vascular endothelial growth factor (P < 0.01), heme oxygenase-1 (P < 0.01), and hypoxia-inducible factor 1α (P < 0.01) were greater in cows under Mod-HS than those under No-HS. Red blood cell count (P < 0.01) and hemoglobin concentration (P < 0.01) were lower in the coccygeal vein of dairy cows under Mild- and Mod-HS than those of cows under No-HS.ConclusionsExposure to HS negatively impacts the health status and lactation performance of dairy cows by limiting oxygen metabolism and transportation. However, the specific mechanism by which HS affects mammary function in cows remains unclear and requires further exploration.

Effect of Yeast Cell Wall on Gut Health, Immunity and Milk Production of Dairy Cattle in Normal and Heat Stress Conditions. Review

This review focuses on the most recent literature to bring to light the major beneficial effects of the yeast cell wall (YCW) and its products on dairy cattle. These products include viable yeast, yeast culture, nutritional yeast, and fractionated yeast products. The yeast cell wall is one of these products and belongs to the fractionated yeast products used to promote production performance and health in dairy cows. The yeast and YCW were proven to have positive impacts on dairy cattle performance in terms of milk yield, milk components, and overall quality. As well, these products showed beneficial effects under heat stress conditions. The YCW is a natural fermentation derivative of yeast cells such as Saccharomyces cerevisiae species consists mainly of β-glucan (29% to 64%), mannan (31%), and some other compounds like protein (13%), lipids (9%), chitin (1–2%) with β-glucan and mannan being the main bioactive molecules. The mode of action through which YCW elicit their beneficial functions in dairy cow explain their effect on cows' metabolism and digestion, immunity, rumen and intestine health, and subsequent performance and well-being. These modes of action include improving gastrointestinal (GI) tract health, stimulating immune system components as it is considered an immunomodulator additive, mycotoxin binding ability, and improving antioxidant capacity. Therefore, yeast and YCW products are one of the promising areas of ruminant nutrition in dairy cows, not only because of their nutritional and health benefits to dairy cows but also due to their negligible residual effects on dairy cows’ bodies and products.

PrunedYOLO-Tracker: An efficient multi-cows basic behavior recognition and tracking technique

Recognition and tracking of basic cow behaviors in natural environments are critical technologies for cows' health monitoring in smart farming. This study proposes an efficient cow behavior recognition and tracking method (PrunedYOLO-Tracker) to address the main problem of the lack of a real-time and identity-linked approach for analyzing and monitoring cow behaviors. Firstly, the channel pruning algorithm is employed to compress the size and parameters of the base model, YOLO v5l. Secondly, a multi-object tracking (MOT) method, Cascaded-Buffered IoU (C-BIoU), which expands the detection and trajectory matching space by increasing the buffer zone, is proposed to combine the behavior information from detection with the trajectory information from tracking, achieving multi-cows' behavior recognition and tracking. Through experimental verification, the pruned model maintains high detection accuracy while reducing the model size, floating-point operations (FLOPs) and parameters by 73.5%, 76.7% and 74.0%, respectively. Compared to the original model, the pruned model only experiences a slight decrease of 0.2% in F1 score, while achieving a 0.3% increase in mean Average Precision (mAP). In terms of cow tracking performance, when compared to six other multi-object tracking algorithms including DeepSort, DeepMot, OC-Sort, BotSort, StrongSort, and ByteTrack, the proposed method demonstrates the highest High Order Tracking Accuracy (HOTA), Multi-Object Tracking Precision (MOTP) and Identification F1 (IDF1) scores, reaching 72.4%, 86.1% and 80.3%, respectively. The results obtained from testing in multiple cow activity environments demonstrate that the proposed method exhibits excellent performance in behavior recognition and tracking, as well as high-speed processing capabilities, with an average video processing speed of 81 frames per second (FPS). This method possesses the ability to reliably monitor and manage cow behavior in real-time, providing technical support for promptly anomalies detection and cow health status monitoring for dairy farming managers.

The autumn low milk yield syndrome in Brown Swiss cows in continental climates: hypotheses and facts.

Extensive research has been conducted globally on the impact of heat stress (HS) on animal health and milk production in dairy cows. In this article, we examine the possible reasons for the decrease in milk production in Brown Swiss (BS) cows during the autumn season, known as the autumn low milk yield syndrome (ALMYS). This condition has been extensively studied in high-yielding Holstein Friesian (HF) cattle and has also been observed in BS cows with a daily milk yield of around 30kg. Our hypothesis is that the drop in milk yield and the increased prevalence of mastitis in autumn, as found in our recent studies, may be a long-term consequence of summer HS. We re-evaluate our previous findings in light of the possible manifestation of an HS-related form of ALMYS in BS cows. As milk yield, mastitis spread, and reproductive function of cows are interrelated and have seasonal dependence, we examine the consistency of our hypothesis with existing data. The significant drop in milk yield in BS cows in autumn (by 2.0-3.2kg), as well as the threshold of milk yield decrease (temperature-humidity index of 70.7), may point in favour of the manifestation of ALMYS in BS cows, similar to HF cows. Only the percentage effect of seasonal factor (59.4%; p < 0.05) on milk yield of BS cows was significant. HS-related ALMYS provides a robust conceptual framework for diverse sets of productive and animal health data in BS cows, similar to observations in high-yielding HF cattle. However, the limitations associated with the lack of additional data (e.g. immunological indicators) suggest the need for further research to confirm ALMYS in BS breed.

Effects of dietary inclusion of 3 Nordic brown macroalgae on enteric methane emission and productivity of dairy cows

Macroalgae are receiving increased attention as antimethanogenic feed additives for cattle, but most in vivo studies are limited to investigating effects of the red macroalgae Asparagopsis spp. Hence, this study aimed to investigate the CH4 mitigating potential of 3 brown macroalgae from the Northern Hemisphere when fed to dairy cows, and to study the effects on feed intake, milk production, feed digestibility, and animal health indicators. The experiment was conducted as a 4 × 4 Latin square design using 4 lactating rumen, duodenal, and ileal cannulated Danish Holstein dairy cows. The cows were fed a total mixed ration (TMR) without any macroalgae or the same TMR diluted with, on a dry matter basis, either 4% ensiled Saccharina latissima, 4% Ascophyllum nodosum (NOD), or 2% Sargassum muticum (MUT). Each period consisted of 14 d of adaptation, 3 d of digesta and blood sampling, and 4 d of gas exchange measurements using respiration chambers. Milk yield and dry matter intake (DMI) were recorded daily. Blood was sampled on d 13 and 16 and analyzed for health status indicators. None of the 3 species affected the CH4 emission. Moreover, milk yield and DMI were also unaffected. Total-tract digestibility of crude protein was significantly lower for NOD compared with other diets, and additionally, the NOD diet also tended to reduce total-tract digestibility of neutral detergent fiber compared with MUT. Blood biomarkers did not indicate negative effects of the dietary inclusion of macroalgae on cow health. In conclusion, none of the 3 brown macroalgae reduced CH4 emission and did not affect DMI and milk production of dairy cows, whereas negative effects on the digestibility of nutrients were observed when A. nodosum was added. None of the diets would be allowed to be fed in commercial dairy herds due to high contents of iodine, cadmium, and arsenic.

Smallholder milk-quality awareness in Indonesian dairy farms

In most low- and middle-income countries, milk is produced by smallholders, thereby contributing to the livelihood of their households. With the increasing importance of milk production in these countries, it is essential that milk quality is of a high level to ensure a safe product for consumers. It is, however, unclear whether smallholder dairy farmers are aware of the quality of their milk. The aim of this cross-sectional study was to gain insight on Indonesian smallholder dairy farmers' awareness of milk quality parameters and to identify factors associated with the total plate count (TPC) and somatic cell count (SCC). A stratified sampling method was utilized to select smallholder farms in 5 districts in West Java, Indonesia that were interviewed between August and September 2017. Factors putatively associated with awareness of TPC were investigated with multinomial regression models while a Firth-type logistic regression was applied to identify factors associated with SCC awareness. Of the total 600 farmers surveyed, 264 (44%), 109 (18%), 170 (28%), 111 (19%), and 23 (4%) farmers were aware of TPC, total solid (TS), fat content, milk density, and SCC, respectively, but did not know its value. Those that were conceptually aware of these quality parameters were generally unaware of their value. Furthermore, this study revealed that the following variables: cooperative, distance to neighboring dairy farmer, technology adoption index, TPC as the most important quality factors for the buyer, milk production information from cooperatives, and cow's health information from veterinarians were significantly associated with dairy farmers awareness of TPC. Similarly, cooperative, dairy business experience, and milk quality test adoption were significantly associated with dairy farmers' awareness of SCC. Cooperative was the only variable that was significant in both final statistical models. This indicates that cooperatives play an important role in increasing farmers' awareness of milk quality parameters in these smallholder dairies. This may be valid for other regions in the world also where milk production is dominated by smallholder dairy farmers.

Genetic parameters and evaluation of mortality and slaughter rate in Holstein and Jersey cows

The longevity of dairy cattle has economic, animal welfare, and health implications and is influenced by the frequency of mortality on the farm and sale for slaughter. In this study cows removed from the herd due to death or slaughter during the lactation were coded 1 and cows that were not terminated were coded 0. Genetic parameters for mortality rates (MR) and slaughter rates (SR) were estimated for Holstein (H) and Jersey (J) breeds by applying both linear (LM) and threshold (TM) sire models using about 1.2 million H and 2,860,000 J cows. Estimated breeding values (EBV) for MR and SR were predicted using animal models to assess the opportunity for selection and genetic trends. Cow termination data, recorded between 1990 and 2020 on a voluntary basis by Australian dairy farmers, were analyzed. Cow MR has increased from below 1% in the 1990s to 4.1% and 3.6% in H and J cows, respectively. Most dead cows (~36%) left the herd before 120 d of lactation, while cows that were slaughtered left the herd toward the end of the lactation. Using the LM, heritability (h2) estimates for MR were lower (1%) than those for SR (2%-3.5%). When h2 were estimated using a TM, the estimates for both traits varied between 4% and 20%, suggesting that the difference in incidence level is one of the reasons for the difference in the h2 values between MR and SR. Early test-day milk yield (MY) and 305-d MY (305-d MY) have unfavorable genetic correlations (0.32-0.41) with MR in both breeds. The genetic correlations of calving interval with MR were stronger (0.54 to 0.68) than with SR (0.28-0.45) suggesting that poor fertility can serve as an early indicator of poor cow health that may lead to increased risk of death. High early test-day somatic cell count is genetically associated with increased likelihood of slaughter (0.24-0.46), but not with increased likelihood of death. In H, 305-d protein yield (PY) had the strongest genetic correlation (-0.34--0.40) with SR whereas in J, both 305-d PY and Fat yield showed high genetic (-0.64--0.70) and moderate environmental (-0.35--0.37) correlations with SR. The genetic correlation of removal from the herd due to death and slaughter was negative (-0.3) in J and zero in H. Strong selection for improved fertility and survival and less selection emphasis for MY, has led to an improvement in the genetic trend for cow MR in H and the trend in J has stabilized. Although genetic evaluations for cow MR are feasible, the reliabilities of the EBV are low and the level of cow MR in Australia are relatively low compared with similar countries. Therefore, genetic evaluation for survival based on mortality and slaughter data could be sufficient in the current selection circumstances where breeding objectives are broadly defined. Nevertheless, all Australian farmers should be encouraged to continue recording mortality and slaughter data for monitoring of the trends and for future development of genetic evaluations.