Mastitis is one of the most important diseases in dairy cattle farms, and it can affect the health status of the udder and the quantity and quality of milk yielded. The correct management of mastitis is based both on preventive and treatment action. With the increasing concern for antimicrobial resistance, it is strongly recommended to treat only the mammary quarters presenting intramammary infection. For this reason, a timely and accurate diagnosis is fundamental. The possibility to detect and characterize mastitis directly on farm would be very useful to choose the correct management protocol. Some on-field diagnostic tools are already routinely applied to detect mastitis, such as the California Mastitis Test and on-farm culture. Other instruments are emerging to perform a timely diagnosis and to characterize mastitis, such as Infra-Red Thermography, mammary ultrasound evaluation and blood gas analysis, even if their application still needs to be improved. The main purpose of this article is to present an overview of the methods currently used to control, detect, and characterize mastitis in dairy cows, in order to perform a timely diagnosis and to choose the most appropriate management protocol, with a specific focus on on-farm diagnostic tools.

The aim of this study was to investigate the effects of two feed supplements on rumen bacterial communities of heifers fed a high grain diet. Six Holstein-Friesian heifers received one of the following dietary treatments according to a Latin square design: no supplement (control, C), 60 g/day of fumarate-malate (organic acid, O) and 100 g/day of polyphenol-essential oil (P). Rumen fluid was analyzed to assess the microbial population using Illumina sequencing and quantitative real time PCR. The P treatment had the highest number of observed species (P < 0.10), Chao1 index (P < 0.05), abundance based coverage estimated (ACE) (P < 0.05), and Fisher’s alpha diversity (P < 0.10). The O treatment had intermediate values between C and P treatments with the exception of the Chao1 index. The PCoA with unweighted Unifrac distance showed a separation among dietary treatments (P = 0.09), above all between the C and P (P = 0.05). The O and P treatments showed a significant increase of the family Christenenellaceae and a decline of Prevotella brevis compared to C. Additionally, the P treatment enhanced the abundance of many taxa belonging to Bacteroidetes, Firmicutes and Tenericutes phyla due to a potential antimicrobial activity of flavonoids that increased competition among bacteria. Organic acid and polyphenols significantly modified rumen bacterial populations during high-grain feeding in dairy heifers. In particular the polyphenol treatment increased the richness and diversity of rumen microbiota, which are usually high in conditions of physiological rumen pH and rumen function.

Pregnancy and lactation are physiological periods that result in an increased metabolic demand that, if not satisfied, could provoke a threat to homeostasis. In this study changes in the values of Non-Esterified Fatty Acids (NEFA) and β-hydroxybutyrate (BHB), glucose, insulin, thyroid hormones, milk composition and yield were investigated in buffaloes during the late pregnancy and early lactation. From a total of 50 buffaloes, blood samples were collected -7±5 days before expected calving; +7±5; +30±5 and +50±5 days post-partum; milk samples were collected at the same post-partum time points. On serum samples, the values of Non-Esterified Fatty Acids (NEFA), β-hydroxybutyrate (BHB), glucose, insulin, Triiodothyronine (T3), Thyroxine (T4) and Thyroid-stimulating hormone (TSH) were evaluated. On milk, fat %, protein %, lactose %, somatic cells score (SCS), milk yield and daily milk production (DMP) were assessed. Peripartum period significantly influenced all studied parameters (P<0.05). Milk constituents and productivity statistically changed throughout monitoring period (P<0.005). Milk yield resulted positively correlated with insulin and TSH values, negatively correlated with NEFA and BHB. Insulin was negatively correlated with lactose % and positively correlated with SCS. The obtained results showed that the peripartum period and lactation are accompanied by marked changes in some biochemical variables and in the thyroid hormones values in Italian Mediterranean Buffaloes. Moreover, the relationship found between TSH values and milk yield seems to suggest a possible role of thyroid gland on the maintenance of lactogenesis. This study underlines the importance of monitoring the hormonal status of buffalo during the transition period in order to understand when adjustments of regulatory mechanisms break through physiological limits predisposing the buffalo to metabolic problems.

The transition period is a central moment in dairy cows breeding because metabolic disorders may occur in relation to a dramatic increase in energy demand. This research aimed to identify new biomarkers for the diagnosis of hyperketonemia in bovine in early lactation phase with different value of plasmatic non-esterified fatty acid (NEFA). The profile of plasma fatty acids (FAs) divided into four lipid classes was evaluated using thin layer chromatography and gas chromatographic techniques (TLC-GC). A group of 60 multiparous Holstein–Friesian dairy cows were recruited in the present study. Blood samples were collected from the coccygeal vein and NEFA and the β-hydroxybutyrate (BHB) were evaluated. All animals were divided in 2 groups based on NEFA, NEFA0 group had as mean value 0.24 ± 0.12 mEq/L and NEFA1 group had as mean value 0.87 ± 0.23 mEq/L. Plasma FA concentrations were analyzed separately in free fatty acids, cholesterol esters, phospholipids and triglycerides. Six FAs demonstrated a predictive value in the hyperketonemic dairy cows. In the free fatty acid class, the predictive FAs were C14:0 (AUC = 0.77), C18:1 ω 9 (AUC = 0.72), C18:1 ω 7 (AUC = 0.70) and C18:3 ω 3 (AUC = 0.68). In the phospholipids class the predictive parameters were C12:0 (AUC = 0.78) and C8:0 (AUC = 0.73). In cholesterol, esters and triglycerides lipidic classes no FA had a predictive function.

In this study, we investigated associations among subclinical intra-mammary infection (IMI) and quarter-level milk composition, udder health indicators, and cheesemaking traits. The dataset included records from 450 Holstein cows belonging to three dairy herds. After an initial screening (T0) to identify animals infected by Streptococcus agalactiae, Streptococcus uberis, Staphylococcus aureus, and Prototheca spp., 613 quarter milk samples for 2 different sampling times (T1 and T2, 1 mo after T1) were used for analysis. Milk traits were analyzed using a hierarchical linear mixed model including the effects of days in milk, parity and herd, and bacteriological and inflammatory category [culture negative with somatic cell count (SCC) <200,000 cells/mL; culture negative with SCC ≥200,000 cells/mL; or culture positive]. All udder health indicators were associated with increased SCC and IMI at both sampling times. The largest effects were detected at T2 for milk lactose (-7% and -5%) and milk conductivity (+9% and +8%). In contrast, the increase in differential SCC (DSCC) in samples with elevated SCC was larger at T1 (+17%). Culture-negative samples with SCC ≥200,000 cells/mL had the highest SCC and greatest numbers of polymorphonuclear-neutrophils-lymphocytes and macrophages at both T1 and T2. Regarding milk cheesemaking ability, samples with elevated SCC showed the worst pattern of curd firmness at T1 and T2. At T2, increased SCC and IMI induced large decreases in recoveries of nutrients into the curd, in particular recovered protein (-14% and -16%) and recovered fat (-12% and -14%). Different behaviors were observed between Strep. agalactiae and Prototheca spp., especially at T2. In particular, samples that were positive for Strep. agalactiae had higher proportions of DSCC (+19%) compared with negative samples with low SCC, whereas samples that were positive for Prototheca spp. had lower DSCC (-11%). Intramammary infection with Prototheca spp. increased milk pH compared with culture-negative samples (+3%) and negative samples that had increased SCC (+2%). The greatest impairment in curd firmness at 30 min from rennet addition was observed for samples that were positive for Prototheca spp. (-99% compared with negative samples, and -98% compared with negative samples with high SCC). These results suggest that IMI caused by Prototheca spp. have detrimental effects on milk technological traits that deserve further investigation of the mechanisms underlying animals' responses to infection.

Background: Ruminal acidosis is responsible for the onset of different pathologies in dairy and feedlot cattle, but there are major difficulties in the diagnosis. This study modelled the data obtained from various blood variables to identify those that could indicate the severity of ruminal acidosis. Six heifers were fed three experimental rations throughout three periods. The diets were characterised by different starch levels: high starch (HS), medium starch (MS) and low starch, as the control diet (CT). Ruminal pH values were continuously measured using wireless sensors and compared with pH measurements obtained by rumenocentesis. Blood samples were analysed for complete blood count, biochemical profile, venous blood gas, blood lipopolysaccharide (LPS) and LPS-binding proteins (LBP). Results: The regression coefficient comparing the ruminal pH values, obtained using the two methods, was 0.56 (P = 0.040). Feeding the CT, MS and HS led to differences in the time spent below the 5.8, 5.5 and 5.0 pH thresholds and in several variables, including dry matter intake (7.7 vs. 6.9 vs. 5.1 kg/d; P = 0.002), ruminal nadir pH (5.69 vs. 5.47 vs. 5.44; P = 0.042), mean ruminal pH (6.50 vs. 6.34 vs. 6.31; P = 0.012), haemoglobin level (11.1 vs. 10.9 vs. 11.4 g/dL; P = 0.010), platelet count (506 vs. 481 vs. 601; P = 0.008), HCO₃ ^- (31.8 vs. 31.3 vs. 30.6 mmol/L; P = 0.071) and LBP (5.9 vs. 9.5 vs. 10.5 μg/mL; P < 0.001). A canonical discriminant analysis (CDA) was used to classify the animals into four ruminal pH classes (normal, risk of acidosis, subacute ruminal acidosis and acute ruminal acidosis) using haemoglobin, mean platelet volume, β-hydroxybutyrate, glucose and reduced haemoglobin. Conclusions: Although additional studies are necessary to confirm the reliability of these discriminant functions, the use of plasma variables in a multifactorial model appeared to be useful for the evaluation of ruminal acidosis severity.