Cheese ripening involves successional changes of the rind microbial composition that harbors a key role on the quality and safety of the final products. In this study, we analyzed the evolution of the rind microbiota (bacteria and fungi) throughout the ripening of Austrian Vorarlberger Bergkäse (VB), an artisanal surface-ripened cheese, by using quantitative and qualitative approaches. The real-time quantitative PCR results revealed that bacteria were more abundant than fungi in VB rinds throughout ripening, although both kingdoms were abundant along the process. The qualitative investigation was performed by high-throughput gene-targeted (amplicon) sequencing. The results showed dynamic changes of the rind microbiota throughout ripening. In the fresh products, VB rinds were dominated by Staphylococcus equorum and Candida. At early ripening times (14–30 days) Psychrobacter and Debaryomyces flourished, although their high abundance was limited to these time points. At the latest ripening times (90–160 days), VB rinds were dominated by S. equorum, Brevibacterium, Corynebacterium, and Scopulariopsis. Strong correlations were shown for specific bacteria and fungi linked to specific ripening periods. This study deepens our understanding of VB ripening and highlights different bacteria and fungi associated to specific ripening periods which may influence the organoleptic properties of the final products.

Accelerometers (ACL) can identify behavioral and activity changes in calves. In the present study, we examined the association between bovine respiratory disease (BRD) and behavioral changes detected by an ear-tag based ACL system in weaned dairy calves. Accelerometer data were analyzed from 7 d before to 1 d after clinical diagnosis of BRD. All calves in the study (n = 508) were checked daily by an adapted University of Wisconsin Calf Scoring System. Calves with a score ≥ 4 and fever for at least two consecutive days were categorized as diseased (DIS). The day of clinical diagnosis of BRD was defined as d 0. The data analysis showed a significant difference in high active times between DIS and healthy control calves (CON), with CON showing more high active times on every day, except d −3. Diseased calves showed significantly more inactive times on d −4, −2, and 0, as well as longer lying times on d −5, −2, and +1. These results indicate the potential of the ACL to detect BRD prior to a clinical diagnosis in group-housed calves. Furthermore, in this study, we described the ‘normal’ behavior in 428 clinically healthy weaned dairy calves obtained by the ACL system.

Monitoring animal behavior using sensor technologies requires prior testing under varying conditions because behaviors can differ significantly, such as between grazing and confined cows. This study aimed to validate several sensor systems for classifying rumination and lying behaviors in cows on pasture under different environmental conditions, compare the sensors’ performance at different time resolutions, and evaluate a correction algorithm for rumination data. Ten Simmental dairy cows were monitored on pasture, each simultaneously equipped with an ear-tag accelerometer (ET), two different leg-mounted accelerometers (LMs), and a noseband sensor (NB). Indirect visual observations using drone-recorded video footage served as the gold standard for validation. The concordance correlation coefficient (CCC) for rumination time was very high for both the ET and NB (0.91–0.96) at a 10 min time resolution. Applying the correction algorithm to 1 min data improved the CCC for the NB from 0.68 to 0.89. For lying time, the CCC was moderate for the ET (0.55) but nearly perfect for both LMs (0.99). In conclusion, both sensors evaluated for classifying rumination are suitable for cows on pasture. We recommend using a correction algorithm for 1 min NB data. For the measurement of lying time, the LMs significantly outperformed the ET.

Calf management is important for the development, health, and welfare of the animals. In this follow-up study, we evaluated calf management practices on dairy farms in Austria using an online questionnaire in 2021 and 2022. We tested the hypothesis that farmers changed calf management on their farm within these 10 years. The total amount of analyzable surveys in 2022 was 2,314. All variables changed significantly between years. Therefore, farms were chosen randomly by controlling for confounding changes in herd size (number of dairy cows), farm type (conventional vs. organic), and type of cows' barn (free stall vs. tied up). From 2012 to 2022, the median number of cows per farm increased from 20 (interquartile range (IQR) 13 to 30) to 22 (IQR 13 to 35), and the percentage of organic-producing farms increased from 23.9% (2012) to 30.6% (2022). The number of farms offering colostrum within 4 h after birth increased from 83.7% to 87.2%. This change was significant when subsampling was performed. The quantity of first colostrum offered to the newborns was mainly 2 to 4 L (69%), with an increased percentage of farms offering less than 2 L (13.3% vs. 18.3%). The percentage of farms testing colostrum quality using an objective method (hydrometer, Brix refractometer, outflow funnel) increased significantly by 4.9-fold and was 9.4% in 2022. On most farms (88.8% and 86.6% in 2012 and 2022), calves were housed individually after birth. A higher percentage stated to group calves at an earlier age than in 2012. In both years, mainly whole milk was fed (85.1% vs. 86.3%). The number of farms where non-salable/waste milk was fed to calves decreased significantly from 84.0 to 74.1%. Milk allowance increased non-significantly. Subsampling revealed that the age at weaning increased significantly between years. The most important health problem in calves was diarrhea (in 59.8% of the farms over 10% of the calves and in 27.4% over 25%), followed by respiratory tract disease (in 39.8% of farms over 10% of the calves and on 16.4% over 25%). Compared with 2012, in 2022, a significantly higher percentage of farmers stated that they had a calf diarrhea incidence of >10% (39.8% vs. 59.8%). In our study, weak points regarding calf management on farms were not offering enough first colostrum, missing testing for colostrum quality, not housing calves socially in the first weeks post natum, and feeding restricted amounts of milk. The median mortality rate of 3% (IQR 1 to 5) and increasing diarrhea incidence also show that calf management practices need improvement. Thus, it is still an open question of how to get farmers motivated to implement changes in their management in accordance with science-based recommendations.

Climate change is a worldwide problem that is manifested in livestock farming with a decrease in animal health and welfare and economic losses due to heat stress. Therefore, a precise and continuous recording of the barn climate is essential to be able to implement actions at a certain threshold. The aim of this study was to evaluate a logger for temperature and humidity (Kestrel Drop D2) marketed for on-farm use in comparison to various other temperature/humidity data loggers under field conditions. Four different sensors were used and placed in different settings in cattle barns to correlate temperature and humidity measurements. Data were recorded for over a year in total. The data were very highly correlated. Furthermore, the area under the curve for the evaluated logger in comparison to the other ones was 0.99 to 1.0, using a temperature–humidity index cut-off of 72, often set to define heat stress. In conclusion, the evaluated logger performed equally well as the other used devices. For on-farm use, it is suitable.

Pasture management is an important topic for dairy farms with grazing systems. Herbage mass (HM) is a key measure, and estimations of HM content in pastures allow for informed decisions in pasture management. A common method of estimating the HM content in pastures requires manually collected grass samples, which are subjected to laboratory analysis to determine the dry matter (DM) content. However, in recent years, new methods have emerged that generate digital data and aim to expedite, facilitate and improve the measurement of HM. This study aimed to evaluate the accuracy of a rising plate meter (RPM) tool in a practical setting to estimate HM in Austrian pastures. With this study, we also attempted to answer whether the tool is ready for use by farmers with its default settings. This study was conducted on the teaching and research farm of the University of Veterinary Medicine in Vienna, Austria. Data were collected from May to October 2021 in five different pastures. To evaluate the accuracy of the RPM tool, grass samples were collected and dried in an oven to extract their DM and calculate the HM. The HM obtained from the grass samples was used as the gold standard for this study. In total, 3796 RPM measurements and 203 grass samples yielding 49 measurement points were used for the evaluation of the RPM tool. Despite the differences in pasture composition, the averaged HM from the RPM tool showed a strong correlation with the gold standard (R² = 0.73, r_p = 0.86, RMSE = 517.86, CV = 33.67%). However, the results may not be good enough to justify the use of the tool, because simulations in economic studies suggest that the error of prediction should be lower than 15%. Furthermore, in some pastures, the RPM obtained poor results, indicating an additional need for pasture-specific calibrations, which complicates the use of the RPM tool.