932 resultados para Dairy plants.


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A constructed wetland at Greenmount College, Co. Antrim, N. Ireland was built in 2004 to study the treatment of ‘dirty water’ effluent from the Greenmount dairy unit. The effluent has a mean BOD5 of c.1000 mg/L and contains milking parlour wash-water and runoff from silage clamps and yard areas lightly contaminated with cattle manure. The nominal water retention time of this wetland is 100 days. The primary purposes of the wetland are to eliminate organic pollution and eutrophication risk from nitrogen and phosphorus compounds. However the wetland should also effectively remove any zoonotic pathogens present in manure and milk. Accordingly, a 12-month microbiological survey of water in the five ponds of the wetland commenced in August 2007. The aims of the survey are to determine changes, as effluent passes through the wetland system, in a broad range of indicator organisms (faecal coliforms, Escherichia coli, Enterococcus faecalis and Clostridium perfringens) and the occurrence of several pathogens - Salmonella, Campylobacter, Cryptosporidium and Mycobacterium avium subsp. paratuberculosis (Map). The highest indicator organism counts - E. coli and faecal coliforms, 103-104 CFU/ml - are observed in pond 1, and a significant reduction (1-3 log10) in all indicator organisms occurs as water passes through the wetland from pond 1 to pond 5. Hence the wetland is efficient at reducing levels of indicator organisms in the dairy effluent. Salmonella and Campylobacter spp. are being detected intermittently in all the ponds, whilst Cryptosporidium and Map have yet to be detected, and so the ability of the wetland to reduce/eliminate specific pathogens is less clear at present.

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Aim: We used a combination of modelling and genetic approaches to investigate whether Pinguicula grandiflora and Saxifraga spathularis, two species that exhibit disjunct Lusitanian distributions, may have persisted through the Last Glacial Maximum (LGM, c. 21 ka) in separate northern and southern refugia.

Location: Northern and eastern Spain and south-western Ireland.

Methods: Palaeodistribution modelling using maxent was used to identify putative refugial areas for both species at the LGM, as well as to estimate their distributions during the Last Interglacial (LIG, c. 120 ka). Phylogeographical analysis of samples from across both species' ranges was carried out using one chloroplast and three nuclear loci for each species.

Results: The palaeodistribution models identified very limited suitable habitat for either species during the LIG, followed by expansion during the LGM. A single, large refugium across northern Spain and southern France was postulated for P. grandiflora. Two suitable regions were identified for S. spathularis: one in northern Spain, corresponding to the eastern part of the species' present-day distribution in Iberia, and the other on the continental shelf off the west coast of Brittany, south of the limit of the British–Irish ice sheet. Phylogeographical analyses indicated extremely reduced levels of genetic diversity in Irish populations of P. grandiflora relative to those in mainland Europe, but comparable levels of diversity between Irish and mainland European populations of S. spathularis, including the occurrence of private hapotypes in both regions.

Main conclusions: Modelling and phylogeographical analyses indicate that P. grandiflora persisted through the LGM in a southern refugium, and achieved its current Irish distribution via northward dispersal after the retreat of the ice sheets. Although the results for S. spathularis are more equivocal, a similar recolonization scenario also seems the most likely explanation for the species' current distribution.

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Background: The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates. Methodology/Principal Findings: We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC- curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data. Conclusions/Significance: These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies. © 2014 Tsairidou et al.

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Background

The human microbiome plays a significant role in maintaining normal physiology. Changes in its composition have been associated with bowel disease, metabolic disorders and atherosclerosis. Sequences of microbial origin have been observed within small RNA sequencing data obtained from blood samples. The aim of this study was to characterise the microbiome from which these sequences are derived.

Results


Abundant non-human small RNA sequences were identified in plasma and plasma exosomal samples. Assembly of these short sequences into longer contigs was the pivotal novel step in ascertaining their origin by BLAST searches. Most reads mapped to rRNA sequences. The taxonomic profiles of the microbes detected were very consistent between individuals but distinct from microbiomes reported at other sites. The majority of bacterial reads were from the phylum Proteobacteria, whilst for 5 of 6 individuals over 90% of the more abundant fungal reads were from the phylum Ascomycota; of these over 90% were from the order Hypocreales. Many contigs were from plants, presumably of dietary origin.  In addition, extremely abundant small RNAs derived from human Y RNAs were detected.

Conclusions

A characteristic profile of a subset of the human microbiome can be obtained by sequencing small RNAs present in the blood. The source and functions of these molecules remain to be determined, but the specific profiles are likely to reflect health status. The potential to provide biomarkers of diet and for the diagnosis and prognosis of human disease is immense.

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The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

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The invasive aquatic plant species Elodea nuttallii could pose a considerable risk to European freshwater ecosystems based on its current distribution, rate of spread and potential for high biomass. However, little research has been conducted on the impacts of this species on native biota. This study takes an ecosystem-wide approach and examines the impact of E. nuttallii on selected physicochemical parameters (dissolved oxygen and pH), algae, invertebrate and macrophyte communities. Elodea nuttallii had small but significant impacts on plant, invertebrate and algal species. The richness of algal periphyton was lower on E. nuttallii than on native macrophytes. The taxonomic composition of invertebrate communities associated with E. nuttallii differed from that associated with similar native plant species, but did not differ in terms of total biomass or species richness. Macrophyte species richness and total cover were positively correlated with percentage cover of E. nuttallii. Not all macrophyte species responded in the same way to E. nuttallii invasion; cover of the low-growing species, Elodea canadensis and charophytes were negatively correlated with E. nuttallii cover, whilst floating-rooted plants were positively correlated with E. nuttallii cover. All observed differences in the macrophyte community were small relative to other factors such as nutrient levels, inter-annual variation and differences between sites. Despite this, the observed negative association between E. nuttallii and charophytes is a key concern due to the rarity and endangered status of many charophyte species.