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Clostridium species are known for their impact on animal and human health, but also for the spoilage of foodstuffs. Their spores contaminate milk and result in germination and gas production, the latter being particularly evident in the cheeses that suffer severe depreciation. To address this issue, the Primary Production Department of the IZSLER institute in Brescia, Italy conducts the Most Probable Number (MPN) method on bovine milk samples collected from Northern Italian dairies between 2004 and 2023. This approach leverages two semi-quantitative protocols, S2 and S3, to detect Clostridium species spore forms upon customer request. Here, we would like to present an a-posteriori analysis on the results of the S2 and S3 protocols. The goal of this study is to highlight the differences between these two methods and provide evidence of the actual decrease in Clostridium species in raw cow milk over a 20-year period. Our analysis shows that client demand for S2 has progressively decreased, while S3's has remained constant, and both protocols reveal a significant reduction in positives; furthermore, S3's greater sensitivity made it more responsive to environmental changes. This highlights the necessity of choosing the appropriate testing protocol that accounts for both regulatory standards and environmental factors. Overall, our findings underscore the importance of continued monitoring to manage Clostridium species contamination and ensure milk quality. [ABSTRACT FROM AUTHOR]

This research communication explores the value of routinely collected bulk tank milk quality data for estimating dairy cattle welfare at herd level. Selected bulk tank milk quality parameters (somatic cell count, total bacterial count, urea, protein and fat contents) recorded during the years 2014–2016 in 287 Italian dairy farms were compared with the animal welfare data of each farm. The welfare assessment data were extracted from the database of the Italian Reference Centre for Animal Welfare (CReNBA), which includes the outputs of the application of the CReNBA welfare assessment protocol for dairy cows, used at national level for on-farm controls. The statistical analysis was carried out using the correlation coefficient for Kendall's Tau ranks, in order to investigate the presence of a categoric relationship between the selected bulk tank milk quality parameters and the overall animal welfare score or the scores of the single areas A (farm management and staff training), B (housing) and C (animal-based measures). Somatic cell count, total bacterial count, urea and proteins demonstrated only a few statistically significant and very weak correlations with farm animal welfare data, while no significant correlations were obtained for milk fat content. Given the weak correlations found, the selected bulk tank milk parameters seems to be able to provide only limited information about the welfare level of the herd, thus it could be difficult to use them for drawing up a pre-screening model for identifying herds at risk of poor welfare. [ABSTRACT FROM AUTHOR]

This Research Communication investigated the potential of mid-infrared spectroscopy to predict detailed mineral composition of bovine milk. A total of 153 bulk milk samples were analysed for contents of Ca, Cl, Cu, Fe, K, Mg, Na, P and Zn. Also, soluble and colloidal fractions of Ca, Mg and P were quantified. For each milk sample the mid-infrared spectrum was captured and stored. Prediction models were developed using partial least squares regression and the accuracy of prediction was evaluated using both cross- and external validation. The proportion of variance explained by the prediction models in cross-validation ranged from 34% (Na) to 77% (total P), and it ranged from 13% (soluble Mg) to 54% (Cl-) in external validation. The ratio of the standard deviation of each trait to the standard error of prediction in external validation, which is an indicator of the practical utility of the prediction model, was low and never greater than 2. Results from the current study supported the limited usefulness of mid-infrared spectroscopy to predict minerals present in low concentration in bulk milk. For major mineral components, results from the present research did not match previous findings demonstrating the need for further studies using larger reference datasets. [ABSTRACT FROM AUTHOR]