Dataset Information

Month-wise variation and prediction of bulk tank somatic cell count in Brazilian dairy herds and its impact on payment based on milk quality.

ABSTRACT: Payment programs based on milk quality (PPBMQ) are used in several countries around the world as an incentive to improve milk quality. One of the principal milk parameters used in such programs is the bulk tank somatic cell count (BTSCC). In this study, using data from an average of 37,000 farms per month in Brazil where milk was analyzed, BTSCC data were divided into different payment classes based on milk quality. Then, descriptive and graphical analyses were performed. The probability of a change to a worse payment class was calculated, future BTSCC values were predicted using time series models, and financial losses due to the failure to reach the maximum bonus for the payment based on milk quality were simulated.In Brazil, the mean BTSCC has remained high in recent years, without a tendency to improve. The probability of changing to a worse payment class was strongly affected by both the BTSCC average and BTSCC standard deviation for classes 1 and 2 (1000-200,000 and 201,000-400,000 cells/mL, respectively) and only by the BTSCC average for classes 3 and 4 (401,000-500,000 and 501,000-800,000 cells/mL, respectively). The time series models indicated that at some point in the year, farms would not remain in their current class and would accrue financial losses due to payments based on milk quality.The BTSCC for Brazilian dairy farms has not recently improved. The probability of a class change to a worse class is a metric that can aid in decision-making and stimulate farmers to improve milk quality. A time series model can be used to predict the future value of the BTSCC, making it possible to estimate financial losses and to show, moreover, that financial losses occur in all classes of the PPBMQ because the farmers do not remain in the best payment class in all months.

SUBMITTER: Busanello M

PROVIDER: S-EPMC5558750 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Project description:Microorganisms from the environment can enter the dairy supply chain at multiple stages, including production, milk collection, and processing, with potential implications for quality and safety. The ability to track these microorganisms can be greatly enhanced by the use of high-throughput DNA sequencing (HTS). Here HTS, both 16S rRNA gene amplicon and shotgun metagenomic sequencing were applied to investigate the microbiomes of fresh mid- and late-lactation milk collected from farm bulk tanks, collection tankers, milk silos, skimmed milk silos, a cream silo, and powder samples to investigate the microbial changes throughout a skim milk powder manufacturing process. 16S rRNA gene analysis established that the microbiota of raw milks from farm bulk tanks and in collection tankers were very diverse but that psychrotrophic genera associated with spoilage, Pseudomonas and Acinetobacter, were present in all samples. Upon storage within the whole-milk silo at the processing facility, the species Pseudomonas fluorescens and Acinetobacter baumannii became dominant. The skimmed milk powder generated during the mid-lactation period had a microbial composition that was very different from that of raw milk; specifically, two thermophilic genera, Thermus and Geobacillus, were enriched. In contrast, the microbiota of skimmed milk powder generated from late-lactation milk more closely resembled that of the raw milk and was dominated by spoilage-associated psychrotrophic bacteria. This study demonstrates that the dairy microbiota can differ significantly across different sampling days. More specifically, HTS can be used to trace microbial species from raw milks through processing to final powdered products.IMPORTANCE Microorganisms can enter and persist in dairy at several stages of the processing chain. Detection of microorganisms within dairy food processing is currently a time-consuming and often inaccurate process. This study provides evidence that high-throughput sequencing can be used as an effective tool to accurately identify microorganisms along the processing chain. In addition, it demonstrates that the populations of microbes change from raw milk to the end product. Routine implementation of high-throughput sequencing would elucidate the factors that influence population dynamics. This will enable a manufacturer to adopt control measures specific to each stage of processing and respond in an effective manner, which would ultimately lead to increased food safety and quality.

Project description:BackgroundThe vector-borne human viral zoonosis tick-borne encephalitis (TBE) is of growing concern in Sweden. The area where TBE is considered endemic has expanded, with an increasing geographical distribution of Ixodes ricinus as the tick vector and a rising number of reported TBE cases in humans. Efforts to map TBE risk areas have been carried out by sentinel monitoring, mainly based on individual sampling and analysis of wild and domestic animals, as well as ticks, for tick-borne encephalitis virus (TBEV). However, the interpretation of the geographical distribution has been hampered by the patchy and focal nature of TBEV occurrence. This study presents TBEV surveillance data based on antibody analysis of bulk tank milk collected from dairy herds located throughout Sweden before (May) and after (November) the vector season. A commercial TBEV antibody ELISA was modified and evaluated for use in this study.ResultsThe initial comparative TBEV antibody analysis revealed a good correlation between milk and serum antibody levels from individually sampled cows. Also, the TBEV-antibody levels for the mean-herd serum showed good comparability with TBEV antibody levels from bulk tank milk, thus indicating good predictability of seroprevalence when analysing bulk tank milk from a herd. Analyses of bulk tank milk samples collected from 616 herds in May and 560 herds in November showed a geographical distribution of TBEV seropositive herds that was largely consistent with reported human TBE cases. A few TBEV-reactive herds were also found outside known locations of human TBE cases.ConclusionSerological examination of bulk tank milk from dairy cattle herds may be a useful sentinel surveillance method to identify geographical presence of TBEV. In contrast to individual sampling this method allows a large number of animals to be monitored. TBEV seropositive herds were mainly found in coastal areas of southern Sweden similar to human TBE cases. However, some antibody-reactive herds were found outside known TBE areas at the time of the study.

Project description:Milk fat is important in terms of economic value and in its potential to provide information concerning cow diet and health. Under current milk payment schemes in Ireland farmer income is directly linked to milk fat production.A descriptive analysis of milk fat depression (MFD) as calculated from test day milk recording data across all milk recording herds from 2004 to 2014 was undertaken. A dataset of 17 million test day records was used to calculate the prevalence of MFD in Irish milk recorded herds and to create a graphical description of the major descriptive epidemiological trends in milk fat depression in time and space in Ireland. The bulk tank equivalent (BTE) for test day milk fat was calculated for each herd and for cohorts of cows within herds using the formula; BTE milk fat?=?sum test day fat kg/sum test day milk kg. Milk fat depression was defined as BTE <3.3% milk fat and BTE?>?3.2% milk protein.The annual prevalence of MFD decreased significantly over time in a linear manner until 2014. Across all years the highest prevalence of MFD occurred in April or May. The highest prevalence occurred most commonly in May, with 9.1% of herds experiencing MFD in 2014. The highest prevalence of MFD in autumn calved cohorts occurred at 181-210 days in milk whereas it occurred at days 61-90 in milk in spring calving cohorts. The stage of lactation for the most common occurrence of MFD in both the spring and autumn cohorts corresponded with the month of May. There were some notable spatial patterns regarding variations in prevalence of MFD across the country. Cohorts of cows with the highest genetic values for milk yield had the highest prevalence of MFD whereas cohorts of cows with the highest breeding values for milk fat percent had the lowest prevalence of MFD.A subpopulation of Irish herds experienced the condition of MFD. Descriptive analysis suggested spatial, temporal and animal level associations. This condition warrants further investigation.

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Month-wise variation and prediction of bulk tank somatic cell count in Brazilian dairy herds and its impact on payment based on milk quality.

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