‘Keep calm and carry on’ was a wartime message to the British public that has achieved renewed fame in the last few years. The strategy was simple: in times of extreme difficulty a cool head combined with stoicism is an appropriate response to ensure a successful outcome. The latest major challenge to society (COVID-19) met with a very different response, and only history will reveal whether ‘Stay home and worry’ will be equally effective. In devising blueprints or strategies it is extremely important to have a clear idea of what you are trying to achieve, whether it be maintaining world freedom or stopping a pandemic. In the case of livestock agriculture, it is helping to feed a rapidly growing global population in harmony with the needs of current and future generations. I hope that I have stated this clearly, and calmly. If so, I ask you to picture a scene. We are on a Calm Farm. Dairy animals go about their daily lives contented, unhurried and focused on the simple feeding and socialising activities that are so important to them. Unstressed, their productive capacities and abilities to avoid and, when necessary, cope with physiological and pathological challenges are maximised. They are not alone: the exact same characteristics also apply to the farmer and husbandry staff that we meet. How is this calm farming approach relevant to the aspirations we had when we established the EU COST Action DairyCare? Our objective was to harness the power of computing technologies to assist our management of dairy livestock. A simple rearrangement leads us to Computing Assisted Livestock Management, CALM. In this short Research Reflection I shall assess how far we have come towards the achievement of sensible goals related to technological assessment of dairy animal wellbeing, and speculate on what more things both can and need to be done to finish the job. It is a personal account. DairyCare was a major collaboration involving several hundred active researchers. To involve them all would be impossible, and I do not pretend to speak for them all. As will become evident, the wide skills base that was assembled was so successful in its primary objectives that different skills, chiefly in economics, are now needed to exploit all of the technological advance that has been achieved. DairyCare succeeded in a second direction. Whilst the focus was technology development, by assembling a large cohort of biologists with animal welfare interests, it soon became apparent that technology should run alongside and help to enable improved management practices. This Special Issue is, therefore, in two sections. The first is dedicated to technology development and the second to a novel management practice that has the potential to significantly improve the wellbeing of cows and calves: cow-calf contact rearing. That section is introduced by my DairyCare colleague, Sigrid Agenäs.

The objectives of the current study were to detect putative genomic loci and to identify candidate genes associated with milk production traits in Egyptian buffalo. A total number of 161 479 daily milk yield (DMY) records and 60 318 monthly measures for fat and protein percentages (FP and PP, respectively), along with fat and protein yields (FY and PY, respectively) from 1670 animals were used. Genotyping was performed using Axiom® Buffalo Genotyping 90 K array. Genome-wide association study (GWAS) for each trait was performed using PLINK. After Bonferroni correction, 47 SNPs were associated with one or more milk production traits. These SNPs were distributed over 36 quantitative trait loci (QTL) and located on 20 buffalo chromosomes (BBU). For the 47 SNPs, one was overlapped for three traits (DMY, FY, and PY), six were associated with two traits (one for PP and PY and five for FY and PY) while the rest were associated with only one trait. Out of 36 identified QTL, eleven were overlapped with previously reported loci in buffalo and/or cattle populations. Some of these SNPs are placed within or close to potential candidate genes, for example: TPD52, ZBTB10, RALYL and SNX16 on BBU15, ADGRD1 on BBU17, ESRRG on BBU5 and GRIP1 on BBU4. This is the first reported study between genome-wide markers and milk components in Egyptian buffalo. Our findings provide useful information to explore the genetic mechanisms and relevant genes contributing to the variation in milk production traits. Further confirmation studies with larger population size are necessary to validate the findings and detect the causal genetic variants.

This review deals with the prospects and achievements of individual dairy cow management (IDCM) and the obstacles and difficulties encountered in attempts to successfully apply IDCM into routine dairy management. All aspects of dairy farm management, health, reproduction, nutrition and welfare are discussed in relation to IDCM. In addition, new IDCM R&D goals in these management fields are suggested, with practical steps to achieve them. The development of management technologies is spurred by the availability of off-the-shelf sensors and expanded recording capacity, data storage, and computing capabilities, as well as by demands for sustainable dairy production and improved animal wellbeing at a time of increasing herd size and milk production per cow. Management technologies are sought that would enable the full expression of genetic and physiological potential of each cow in the herd, to achieve the dairy operation's economic goals whilst optimizing the animal's wellbeing. Results and conclusions from the literature, as well as practical experience supported by published and unpublished data are analyzed and discussed. The object of these efforts is to identify knowledge and management routine gaps in the practical dairy operation, in order to point out directions and improvements for successful implementation of IDCM in the dairy cows' health, reproduction, nutrition and wellbeing.

Milk production intensification has led to several unwanted aspects, such as sustainability issues and environmental pollution. Among these, increased milk outputs that have been achieved over the last 70 years have led to several health and pathophysiological conditions in high yielding dairy animals, including metabolic diseases that were uncommon in the past. Increased occurrence of diverse metabolic diseases in cattle and other domestic animals is a key feature of domestication that not only affects the animals' health and productivity, but also may have important and adverse health impacts on human consumers through the elevated use of drugs and antibiotics. These aspects will influence economical and ethical aspects in the near future. Therefore, finding and establishing proper biomarkers for early detection of metabolic diseases is of great interest. In the present review, recent work on the discovery of fitness, stress and welfare biomarkers in dairy cows is presented, focusing in particular on possible biomarkers of energy balance and oxidative stress in plasma and milk, and biomarkers of production-related diseases and decreased fertility.

This Research Reflection raises awareness of the need to broaden perspectives and levels of multidisciplinary and interdisciplinary approaches when considering on-farm dairy cattle welfare. It starts with a brief overview of current animal welfare issues on dairy farms and how they are perceived by different stakeholders. Some divergences in points of view are discussed in more detail and the first steps in networking are mentioned. Particular emphasis is given to both milk and dairy product waste in industrialized countries and the potential effects of its reduction on changes in the production system. The needs for a quantification of such quota and retailer involvement are also analyzed from the perspective that on-farm animal welfare is directly linked to the amount of milk that might be removed from the food chain by adoption of welfare-friendly management, such as cow-calf systems.

We have learned a lot about infections of the mammary gland of dairy cows from experimental investigations of the pathogenesis of the various diseases. The understanding gained has contributed to huge successes in reducing the prevalence of infection in properly managed dairy herds. Now descriptive studies using DNA technologies reject previous concepts of mammary gland sterility by default. Bacteria, at least markers of genes, of many genera are reported even from absolutely healthy mammary glands. This may be a technological artefact. No direct evidence exists because experimental studies of infection are no longer fashionable. A regeneration of the lost arts in the pathogenesis of infection is essential to separate truth from conjecture and deal with coming challenges from rapidly changing farm systems and the reduction in access to antimicrobial drugs. In this Opinion Paper I argue for a return to experimental approaches that construct hypotheses, and then test them, in intramammary disease research.

The objectives of this work were (a) to determine the presence of streptococci in samples from small ruminant dairy farms (bulk-tank milk and, where possible, teatcup swabs), (b) to investigate the potential adverse effects of streptococci on milk quality and (c) to investigate the importance of some husbandry factors for the isolation of streptococci. Bulk-tank milk samples and teatcups swab samples were examined bacteriologically for the presence of streptococci. Somatic cell counting and milk composition measurements were also performed. The husbandry factors present in each farm were assessed for potential associations with the isolation of streptococci. Streptococci were isolated from milk samples from 31.4% of sheep and 17.4% of goat farms and from 4.8% of sheep and 5.9% of goat teatcups. Streptococci were isolated more frequently from the upper part than the lower part of teatcups: 5.0% vs. 1.9%. Most isolates (57.9%) were identified as Streptococcus uberis. Most isolates (68.4%) were slime-producing; slime-production was more frequent among isolates from teatcups (83.3%) than from bulk-tank milk (55.0%). Somatic cell counts and milk composition did not differ between farms in which streptococci were or were not isolated. Machine-milking was associated with the isolation of streptococci from bulk-tank milk samples. The initial stage of the milking period (first two months) was found to be associated with the isolation of streptococci from milking machine teatcups in sheep farms only.

The aims of the study were to determine the long-term effects of dietary supplementation with microalgae (SCIM) on milk and blood fatty acid (FA) composition and reproductive hormones in early lactation dairy cows. Sixty Holstein–Friesian dairy cows (30 per treatment) were unsupplemented (Control) or supplemented with 100 g of SCIM (Schizochytrium limacinum sp.) per cow per day from 25 ± 0.5 d post-partum for 98 d. Intake and milk yield were recorded daily, with milk samples collected at weeks 0, 1, 2, 4, 8 and 14, and blood samples collected from 12 representative pairs per treatment at weeks 0, 2, 4, 8, and 14 for subsequent analysis of FA, β-hydroxybutyrate, non-esterified fatty acids and glucose. At 33 ± 0.9 d postpartum the oestrus cycle of 24 cows (12 per treatment) were synchronized and plasma 13,14-dihydro-15-keto PGF2α (PGFM) concentrations determined following an oxytocin challenge. Data were analysed by repeated measures analysis of variance. There was no effect of treatment on dry matter intake, milk yield or milk fat content, with mean values across treatments of 22.1 and 40.6, and 37.2 g/kg respectively. Milk fat concentration of C22:6 n-3 increased rapidly in cows receiving SCIM, reaching a maximum of 0.38 g/100 g FA by week 14. Similarly, blood concentration of C22:6 n-3 increased to 1.6 g/100 g FA by week 14 in cows fed SCIM. There was no effect of treatment on plasma metabolites, but plasma glucose was lower in cows fed SCIM compared to the Control at week 2, and higher in week 8. There was no effect of treatment on peak plasma PGFM concentration or area under the curve. It is concluded that feeding SCIM rapidly increases blood and milk concentrations of C22:6 n-3 which are maintained over time, but does not improve plasma PGFM in dairy cows.

Yaks (Bos grunniens) live primarily in the Qinghai-Tibetan plateau (altitude: 2000–5000 m). Their milk presents unusual characteristics, containing large amounts of solids including fat and protein, and it is, therefore, important to understand the genetic makeup of the yak. To identify potentially critical genes playing a role in yak mammary tissue from colostrum to mature milk phase of lactogenesis, the early lactation (colostrum) stage (ELS; day 1 after parturition) and mature lactation (milk) stage (MLS; day 15) were chosen for comparison. An ELS-specific cDNA library was established by suppression subtractive hybridization and 25 expressed sequence tags at ELS were identified by sequencing and alignment. To further confirm our results the expression levels of 21 genes during the lactation cycle were measured using quantitative real-time RT-PCR (qRT-PCR). The qRT-PCR results confirmed 9 significantly up-regulated genes at ELS vs. MLS in yak mammary tissue, in which the l-amino acid oxidase 1 (LAO1) and collagen, type I, alpha I (COL1A1) were the most significantly up-regulated. During the lactation cycle, the highest expression of some milk fat genes (i.e., XDH and FABP3) in yak mammary tissue appears earlier than that in dairy cow. Our data also indicate MYC potentially playing a central role through putative regulation of COL1A1, CD44, SPARC, FASN and GPAM.

Animal welfare is an essential component of dairy production and several systems exist to evaluate the welfare of dairy cows. Here, we review and compare three well-known systems that operate at farm level from around the world (FARM, Welfare Quality®, and The Code of Welfare) and discuss their advantages and limitations. Despite having some commonalities, the programs evaluate different elements. We also briefly review an emerging system (Integrated Diagnostic Welfare System) that might address some of the shortcomings of the existing systems, especially the possibility of automating the evaluation of animal well-being and identifying any cause of poor welfare. None of the aforementioned systems has been fully validated for their ability to assess animal welfare using independent measurements. The future holds increased attention around the well-being of dairy cows and increased use of sensing technologies. There is an urgent need for dairy welfare evaluation systems that are scientifically validated, holistic, and that can take advantage of the use of sensing technologies to continuously monitor animal welfare.

This research communication presents a study evaluating the effects of dried sainfoin (Onobrychis viciifolia) supplemented to dairy goats on their milking performance and feed protein efficiency under commercial conditions. During July and August 2015, a herd of 20 Alpine goats was divided into two treatments (n = 10), balanced by milk yield and days in milk. They were supplied with either 700 g/d sainfoin pellets (condensed tannins: 4.0 g/kg DM) or 700 g/d lucerne (Medicago sativa) pellets (condensed tannins: 0.3 g/kg DM). The goats remained in one herd and were separated by treatments only during milking. In the milking parlour each goat received 350 g of the respective pellets, twice daily. During the day, the herd had 5 h access to a high-quality pasture (crude protein >200 g/kg DM), whilst during the rest of the day and the night animals were housed and offered grass hay ad libitum. The experiment lasted for seven weeks. Individual milk yields and composition were controlled in weeks 1, 3, 5, and 7 after the start of the experiment. No differences between the treatments were found, either for milk, protein or urea yields, nor for protein, urea and fat concentrations. Urea to protein ratio in milk was lower with the sainfoin treatment. In conclusion, sainfoin compared to lucerne, supplied for 7 weeks to dairy goats at approximately 25% of the diet, had only weak beneficial and no adverse effects on milking performance, milk composition and feed protein efficiency under commercial conditions of pasture-based dairy production.

The objective of the research reported in this research communication was the identification and association of single nucleotide polymorphisms (SNP) in the ovine DGAT1, FASN, SCD1 and ACAA2 genes with milk fat percentage and fatty acid (FA) content. Three consecutive monthly milk samplings were obtained from a total of 429 purebred Chios ewes during mid-lactation. Genotypic data were jointly analyzed with 1184 fat content and 37 718 FA percentage records using mixed models. The 3′ untranslated region (UTR) of the DGAT1 gene and the 5′ and 3′UTRs of the SCD1 gene appeared to be monomorphic. The FASN g.14777C>T SNP on exon 31 was associated with C13:0 and the ACAA2 g.2982T>C SNP on the 3′UTR was associated with C9:0, C11:0, C12:1 cis-9, C13:0 and the ω6/ω3 index, while fat percentage was not affected by the identified SNPs. The results could be useful for breeding programs aiming to improve the quality and nutritional value of ovine milk.

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.

The aim of this research was to identify variation in the yak lipin-1 gene (LPIN1) and determine whether this variation affects milk traits. PCR-single stranded conformational polymorphism (PCR-SSCP) analysis was used to detect variation in the 5′ untranslated region of LPIN1 in 500 yaks from four populations: Tianzhu white yaks, Qinghai yaks, wild × domestic-cross yaks and Gannan yaks. Four unique PCR-SSCP patterns, representing four different DNA sequence variants (named A, B, C and D), were observed. These contained six single nucleotide polymorphisms. Female Gannan yaks with BC genotype produced milk with a higher fat content (P < 0.001) and total milk solids (P < 0.001), than those with the AA, AB and BB genotypes. These results would suggest that LPIN1 is having an effect on yak milk fat synthesis.

This research paper presents a study investigating if sensor data from an automatic milking rotary could be used to model cow somatic cell count (composite milk SCC: CMSCC). CMSCC is valuable for udder health monitoring and individual cow udder health surveillance could be improved by predicting CMSCC between routine samplings. Data regularly recorded in the automatic milking rotary, in one German dairy herd, were collected for analysis. The cows (Holstein-Friesian, n = 372) were milked twice daily and sampled once weekly in afternoon milkings for 8 weeks for CMSCC. From the potential independent variables, including quarter conductivity, milk flow, blood in milk, kick-offs, not milked quarters and incomplete milkings, new variables that combined quarter data were created. Past period records, i.e. lags, of up to seven days before the actual CMSCC sampling event were added in the dataset to investigate if they were of use in modeling the cell count. Univariable generalized additive models (GAM) were used to screen the data to select potential independent variables. Furthermore, several multivariable GAM were fitted in order to compare the importance of the potential independent variables and to explore how the model performance would be affected by using data from various number of days before the CMSCC sampling event. The result of the model selection showed that the best explanation of CMSCC was provided by the model incorporating all significant variables from the variable screening for the seven preceding days, including the day of the CMSCC sampling event. However, using data from only three days before the CMSCC sampling event is suggested to be sufficient to model CMSCC. Variables combining conductivity quarter data, together with quarter conductivity, are suggested to be important in describing CMSCC. We conclude that CMSCC can be modeled with a high degree of explanation using the information routinely recorded by the milking robot.

We aimed to evaluate the effect of replacing corn silage by orange peel silage on nutrient intake, ruminal parameters and milk production of multiparous lactating Holstein cows. Eight fistulated Holstein cows averaging 587.5 ± 39.6 kg and 111 ± 22 d in milking were randomly assigned to a double 4 × 4 Latin square design carried out two times to determine the effects of feeding with orange peel silage (OPS) in substitution of whole plant corn silage (WPCS). The treatments were a control diet with WPCS only or diets with OPS replacing WPCS in the total mixed diet (250, 500, or 750 g/kg DM). All cows were fed the same 750 : 250 g/kg roughage : concentrate ratio. The DM intake and milk production were reduced with the OPS inclusion, with decreases in consumption of neutral detergent fibre and increased consumption of non-fibrous carbohydrates. Diets with 250 and 500 g/kg OPS showed similar milk production and protein content in milk to the standard WCPS diet, whilst 750 g/kg orange peel silage as roughage increased fat and protein contents significantly. The orange peel silage as a substitute for corn silage for feeding dairy cows did not show adverse changes in the rumen environment and showed promising results in the increase of fat in milk of Holstein cows.