Sub-clinical bovine mastitis decreases milk quality and production. Moreover, sub-clinical mastitis leads to the use of antibiotics with consequent increased risk of the emergence of ...antibiotic-resistant bacteria. Therefore, early detection of infected cows is of great importance. The Somatic Cell Count (SCC) day-test used for mastitis surveillance, gives data that fluctuate widely between days, creating questions about its reliability and early prediction power. The recent identification of risk parameters of sub-clinical mastitis based on milking parameters by machine learning models is emerging as a promising new tool to enhance early prediction of mastitis occurrence. To develop the optimal approach for early sub-clinical mastitis prediction, we implemented 2 steps: (1) Finding the best statistical models to accurately link patterns of risk factors to sub-clinical mastitis, and (2) Extending this application from the farms tested to new farms (method generalization). Herein, we applied various machine learning-based prediction systems on a big milking dataset to uncover the best predictive models of sub-clinical mastitis. Data from 364,249 milking instances were collected by an electronic automated in-line monitoring system where milk volume, lactose concentration, electrical conductivity (EC), protein concentration, peak flow and milking time for each sample were measured. To provide a platform for the application of the models developed to other farms, the Z transformation approach was employed. Following this, various prediction systems Deep Learning (DL), Naïve Bayes, Generalized Liner Model, Logistic Regression, Decision Tree, Gradient-Boosted Tree (GBT) and Random Forest were applied to the non-transformed milking dataset and to a Z-standardized dataset. ROC (Receiver Operating Characteristics Curve), AUC (Area Under The Curve), and high accuracy demonstrated the high sensitivity of GBT and DL in detecting sub-clinical mastitis. GBT was the most accurate model (accuracy of 84.9%) in prediction of sub-clinical bovine mastitis. These data demonstrate how these models could be applied for prediction of sub-clinical mastitis in multiple bovine herds regardless of the size and sampling techniques.
•Comparison of the efficiency of different machine learning models in prediction of sub-clinical mastitis based on in-line collected milking parameters.•The best predictive models were Deep Learning and Gradient-Based Tree.•Standardization was employed to provide the opportunity of extending the application of the predictive models of sub-clinical mastitis to other farms.•Lift Chart analysis demonstrated that Deep Learning, Gradient-Based Tree, and Generalized Linear models are able to provide high levels of confidence in prediction even with the smaller sized of milking data sets.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-scale mining of milk composition features by pattern recognition models can identify the best predictors ...of SCM within the milk composition features. To this end, using data mining algorithms, we conducted a large-scale and longitudinal study to evaluate the ability of various milk production parameters as indicators of SCM. SCM is the most prevalent disease of dairy cattle, causing substantial economic loss for the dairy industry. Developing new techniques to diagnose SCM in its early stages improves herd health and is of great importance. Test-day Somatic Cell Count (SCC) is the most common indicator of SCM and the primary mastitis surveillance approach worldwide. However, test-day SCC fluctuates widely between days, causing major concerns for its reliability. Consequently, there would be great benefit to identifying additional efficient indicators from large-scale and longitudinal studies. With this intent, data was collected at every milking (twice per day) for a period of 2 months from a single farm using in-line electronic equipment (346 248 records in total). The following data were analysed: milk volume, protein concentration, lactose concentration, electrical conductivity (EC), milking time and peak flow. Three SCC cut-offs were used to estimate the prevalence of SCM: Australian ≥ 250 000 cells/ml, European ≥200 000 cells/ml and New Zealand ≥ 150 000 cells/ml. At first, 10 different Attribute Weighting Algorithms (AWM) were applied to the data. In the absence of SCC, lactose concentration featured as the most important variable, followed by EC. For the first time, using attribute weighted modelling, we showed that the concentration of lactose in milk can be used as a strong indicator of SCM. The development of machine-learning expert systems using two or more milk variables (such as lactose concentration and EC) may produce a predictive pattern for early SCM detection.
•A simple and cost-effective method for mastitis risk management by milking parameters.•Complementary approach to promoting Somatic Cell Count in mastitis surveillance.•Increasing the reliability of ...test-day Somatic Cell Count.•Milking parameters, mined by the Decision Tree, accurately predict mastitis.
The aim of this study was to develop a predictive model for mastitis incidence, independent from Somatic Cell Count (SCC), to provide an alternative, simple, and cost-effective approach for mastitis risk management based on available milking parameters. The test-day Somatic Cell Count (SCC) is the most common indicator for Sub-Clinical Mastitis (SCM) surveillance in dairy industries worldwide. However, SCC is highly variable between days, raising major concerns for its reliability. This caveat highlights the need for longitudinal/frequent monitoring of SCC and/or developing alternative approaches for SCM surveillance. A considerable proportion of available milking data such as Milk Volume, Protein, Lactose, Electrical Conductivity (EC), Milking Time, and Peak Flow provide the possibility of pattern recognition and model discovery towards mastitis occurrence. Developing a predictive model involves: (1) finding the threshold (cutoff) of different predictive milking parameters and (2) finding the best combination of features that lead to mastitis and their hierarchical pattern/order. Here, in a large-scale study on 346,248 milking records, for the first time, we evaluated four different decision tree algorithms (Decision Tree, Stump Decision Tree, Parallel Decision Tree and Random Forest Decision Tree) with four different criteria (Accuracy, Info Gain, Gini Index and Gain Ratio) run on 11 datasets (original dataset and 10 created datasets by attribute weighting selection algorithms). Therefore, 572 models were evaluated and compared by 10-fold cross validation. The performance of each decision tree in drawing an inverted tree; with the most important feature at the root and less important variables as the leaf; was calculated by 10-fold cross validation. Random Forest Decision Tree with Gini Index criterion was the best model for predicting mastitis from milking parameters with a high accuracy of 90%. Decision Tree models identified a strong pattern for SCM in milking data where all (100%) of cows with low levels of lactose (Lactose ≤ 4.5 g/L) and low milk volume (Volume ≤ 21.7 L) had mastitis. In addition, a significant pattern was found for identifying healthy cows by high levels of lactose (Lactose ≥ 4.5 g/L) and low levels of EC (EC ≤ 5.2). This study doccuments that milking parameters mined by the Decision Tree Random Forest model can be utilised to accurately predict SCM. The findings can be employed to increase the reliability of test-day SCC or as SCC-independent and cost-effective predictors of SCM.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
High‐temperature short‐time (HTST) pasteurisation is not sufficient for complete elimination of Bacillus sp. in milk. Hence, it is important to assess their prevalence, phenotypic and genetic ...antimicrobial resistance profiles in pasteurised milk. In this study, we investigated Bacillus prevalence and their phenotypic resistance to 25 antimicrobials and prevalence of five plasmid antimicrobial resistance genes. All isolates were resistant to β‐lactams; most isolates were susceptible to chloramphenicol (n = 52), ciprofloxacin, meropenem, sulphonamides, tetracycline and vancomycin (n = 56). Intriguingly, despite phenotypic sulphonamide and tetracycline sensitivity, Sul2 and tetA genes were detected in different Bacillus species, signifying a potential risk of horizontal gene transfer of these mobile resistance genes through pasteurised milk.
The phenotypic and genotypic resistance profiles of Bacillus species isolated from commercially pasteurised milk with an emphasis on the plasmid‐mediated antimicrobial resistance genes and their potential horizontal gene transfer.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Despite the considerable advances that have been made to improve dairy food safety, there is rising concern that pasteurization is not sufficient for the destruction of plasmid-mediated antimicrobial ...resistance (AMR) genes of resistant bacteria and could stimulate bacteria to enter into a viable but nonculturable (VBNC) state. In the current study, we surveyed the prevalence of 1 genomic and 9 plasmid-mediated AMR genes in 100 samples (bulk tank milk and milk filter socks) at the farm level and 152 commercial milk samples (pasteurized and UHT milks) and assessed the VBNC state in dairy bacteria. Results revealed that sul2 was the most prevalent plasmid-mediated gene in milk filter socks (96%), bulk tank milk (48%), pasteurized milk (68%), and UHT (43%) milk; in contrast, mecA was not detected in any sample. Additionally, commercial pasteurization (as currently practiced) failed to decrease the prevalence of the blaTEM-B1 (43%), tetK (30%), and tetA (55%) plasmid-mediated AMR genes; thus, commercial pasteurization may be one of the factors creating the VBNC state in some dairy bacteria. Continued research is necessary to identify bacterial species entering the VBNC state after pasteurization, to assess their potential hazard level and shed more light on the expression and possibility of horizontal gene transfer of those plasmid-mediated AMR genes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Bovine colostrum contains a high concentration of immune-related microRNAs (miRNAs) that are packaged in exosomes and are very stable. In this study, 5 immune-related miRNAs (miR-142-5p, miR-150, ...miR-155, miR-181a, and miR-223) were quantified in dam blood, colostrum, and calf blood using reverse transcription quantitative PCR. Their levels in calf blood after colostrum ingestion were investigated to assess whether miRNAs are transferred from the dam to newborn calves. Three groups of Holstein–Friesian bull calves were bottle-fed 2 L of colostrum or milk from different sources twice per day. The group A calves received colostrum from their own dam and the group B calves were fed foster dam colostrum. Each pair of group A and group B calves were fed identical colostrum from the same milking of the corresponding group A dam for 3 d and then bulk tank milk for 7 d after birth. Group C calves were fed only 2L of “pooled colostrum” from multiple dams d 0 to 4 postpartum, and then fed bulk tank milk thereafter for 7 d after birth. The groups were fed colostrum from different sources and different amounts to assess possible miRNA absorption from the colostrum. All miRNAs were at the highest level in colostrum at d 0 and then decreased rapidly after d 1. The level of miR-150 had the largest decrease from 489 × 106 copies/µL (d 0) to 78 × 106 copies/µL (d 1). MicroRNA-223 and miR-155 were the most abundant in both colostrum and milk. Dam colostrum had significantly higher levels of miR-142-5p, miR-155, and miR-181a than the bulk tank milk. However, only the miR-155 concentration was significantly higher in the dam colostrum than in the pooled colostrum. The concentrations of miRNAs in the colostrum were less than in the cow blood (100- to 1,000-fold less). There was no significant correlation between the level of miRNAs in the dam blood and their colostrum, suggesting that miRNA is synthesized locally by the mammary gland rather than being transferred from the blood. MicroRNA-223 had the highest level in both calf and cow blood compared with the other 4 immune-related miRNAs. Calves were born with high levels of immune-related miRNAs in their blood, and there were no significant differences in miRNA levels between the 3 calf groups at birth or after they were fed different colostrum. This suggests that these miRNAs were not transferred from the colostrum to the newborn calves.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Colostrum quality is generally defined by the IgG concentration in colostrum, and many methods have been used to assess it. Methods to measure colostrum quality both in the laboratory and in the ...field have been validated in cattle; however, this is only a recent topic of interest for sheep colostrum. Laboratory-based methods are often time consuming and require trained personnel compared with new handheld evaluation tools such as the digital Brix refractometer, which gives real-time results. The aims of this study were to (1) evaluate the relationship between the digital Brix refractometer and constituents indicative of quality (IgG, protein, fat, and lactose) in colostrum and transition milk, and (2) determine an appropriate Brix % cut-off value for the Brix refractometer in sheep colostrum and transition milk. The study used 50 colostrum samples (collected at 0 h postpartum, before lambs' sucking) and 169 transitional milk samples (collected at 4 and 24 h postpartum, after lambs had sucked) collected over 6 lambing trials in 2 years (2019 and 2020). We concluded that the Brix refractometer results correlated weakly with IgG concentration determined by radial immunodiffusion assay in colostrum collected at 0 h postpartum (r = 0.11) and in transition milk collected at 4 h postpartum (r = 0.12); however, a moderate to strong correlation was shown in transition milk samples collected at 24 h (r = 0.66). Brix % was significantly correlated with fat %, lactose %, and protein % at all timepoints. To determine an appropriate Brix % cut-off value indicating an IgG concentration of 20 mg/mL, we analyzed sensitivity and specificity of the Brix refractometer at 0, 4, and 24 h. In samples collected at 0 and 4 h, the highest combination of sensitivity, specificity, and accuracy was achieved at a Brix % cut-off value of 29%; in samples collected at 24 h postpartum, a Brix % cut-off value of 27% gave the highest sensitivity, specificity, and accuracy. Overall, the Brix refractometer has potential as a useful in-field tool for researchers and producers in both extensively and intensively managed flocks to measure and determine the quality of sheep colostrum and transition milk.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Enterococcus faecium are commensal bacteria inhabiting the gastrointestinal tract of animals and humans and an important cause of drug-resistant nosocomial infections. This longitudinal study aimed ...to determine whether changes in the antimicrobial resistance (AMR) phenotype and genotype occurred among Enterococcus spp. isolated from cattle rectal samples obtained at the entry to and exit from an Australian feedlot. The samples obtained at the feedlot induction yielded enterococci (104/150; 69.3%), speciated as E. hirae (90/104; 86.5%), E. faecium (9/104; 8.7%), E. mundtii (3/104; 2.9%), E. durans, and E. casseliflavus (1/104; 1.0% each). AMR was observed to lincomycin (63/104; 60.6%), daptomycin (26/104; 25.0%), nitrofurantoin (9/104; 8.7%), ciprofloxacin (7/104; 6.7%), tetracycline (5/104; 4.8%), tigecycline (4/104; 3.9%), and quinupristin/dalfopristin (3/104; 2.9%). From the rectal swab samples collected at the abattoir from the same animals (i.e., the feedlot exit), the enterococci recovery was significantly higher (144/150; 96.0%), with a marked shift in species distribution dominated by E. faecium (117/144; 81.3%). However, the prevalence of AMR to individual antimicrobials remained largely static between the entry and exit except for the increased resistance to nitrofurantoin (77/144; 53.5%) and quinupristin/dalfopristin (26/144; 18.1%). Overall, 13 AMR genes were observed among the 62 E. faecium isolates. These included aac(6′)Ii, aac(6′)-Iid, and ant(6)-Ia (aminoglycosides); eatAv, lnu(G), vat(E), msr(C), and erm(B) (macrolides, lincosamides, and streptogramins); efmA (fluoroquinolones); and tet(45), tet(L), tet(M), and tet(S) (tetracyclines). The results confirm the presence of fluoroquinolone- and streptogramin-resistant enterococci in cattle faeces at the feedlot entry in the absence of antimicrobial selection pressure. E. faecium, exhibiting increased nitrofurantoin resistance, became the dominant Enterococcus spp. during the feeding period.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Little is known about veterinary entrepreneurial predisposition. Yet entrepreneurship and intrapreneurship (entrepreneurial behaviour of employees) foster business innovation and growth and support ...wealth creation and employment in both privately and corporately owned businesses which deliver contemporary veterinary services. We used responses from 515 final-year students in Australian entrepreneurship, nursing, and veterinary programs to capture entrepreneurial intention (EI), outcome expectations (OE-sb), entrepreneurial self-efficacy (ESE), and corporate/large organisation work intentions (CWIs). Veterinary respondents stood out for their high EI and high OE-sb, but low financial ESE and low CWI. Proportions of veterinary, entrepreneurship, and nursing respondents differed markedly across distinct cluster profiles representing entrepreneurial, intrapreneurial, both entrepreneurial and intrapreneurial, indifferent, and corporate employment intentions and attributes. Post hoc analysis revealed proportional cluster membership differences for respondents from different veterinary schools. Our findings raise questions regarding (1) the effectiveness of veterinary business curricula competencies which focus on expense management and (2) the implications of the mismatch of motivations and goals of new veterinary sector entrants whose low intent to work in a corporate environment is at odds with increasing corporate ownership of veterinary practices. To inform curricular change, we recommend further research to evaluate the relative impact of individual factors, admissions factors, and the formal or hidden curricula on entrepreneurial intention in veterinary final-year students.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Piglets are poor at thermoregulation immediately following birth and take up to 24 h to recover from their initial temperature drop. The present study aimed to determine if providing piglets with a ...15 mL intraperitoneal injection of warm (45 °C) saline at birth would improve their internal temperature recovery to 24 h of age, and how the treatment interacted with birth weight (BWC = 1; ≤0.80 kg, BWC = 2; 0.81 kg to 1.10 kg, and BWC = 3; >1.10 kg), rectal temperature at 1.5 h (RC = 1; ≤32.0 °C, RC = 2; 32.10 °C to 35.0 °C, and RC = 3; ≥35.10 °C), and colostrum intake (CI = 1; <200 g and CI = 2, ≥200 g) to affect preweaning survival. Treated BWC1 piglets had improved rectal temperatures from 2 to 24 h. BWC3 piglets who consumed insufficient colostrum also had improved rectal temperature between 1 and 24 h post-birth. Colostrum intake was improved with saline injection in BWC2 piglets of RC1 and RC3 (p < 0.001) and BWC3-RC3 piglets (p < 0.001). Treated BWC1 improved survival to 20 d (p < 0.001). Irrespective of BWC, piglets from all RC had greater survival when injected with saline. The greatest difference was for piglets in RC1, likely due to all BWC1 piglets falling within this category. The results suggest that an intraperitoneal injection of warmed saline is an effective way to improve piglet temperature recovery to 24 h, colostrum intake, and survival in low-birth-weight piglets. These findings will be helpful for producers who have large numbers of low-birth-weight piglets born and are able to provide individual care.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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