Meat

Summary

Meat is animal flesh that is eaten as food. Humans have hunted, farmed, and scavenged animals for meat since prehistoric times. The establishment of settlements in the Neolithic Revolution allowed the domestication of animals such as chickens, sheep, rabbits, pigs, and cattle. This eventually led to their use in meat production on an industrial scale in slaughterhouses. Meat is mainly composed of water, protein, and fat. It is edible raw but is normally eaten after it has been cooked and seasoned or processed in a variety of ways. Unprocessed meat will spoil or rot within hours or days as a result of infection with, and decomposition by, bacteria and fungi. Meat is important to the food industry, economies, and cultures around the world. There are nonetheless people who choose to not eat meat (vegetarians) or any animal products (vegans), for reasons such as taste preferences, ethics, environmental concerns, health concerns or religious dietary rules. Terminology The wo

Official source

https://en.wikipedia.org/wiki/Meat

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Chemical profiling of manure: toward source inference in environmental fraud cases?

Luiz Felippe De Alencastro, Nicolas Estoppey, William Lacour, Adrien Schopfer

With 6% of Europe's freshwater resources, Switzerland is often considered the ‘water tower of Europe’. Over 8 millions residents rely on more than 57’600 farms to provide meat, milk, or eggs, with 1.58 million cattle, 1.58 million swine or 9.39 million poultry. Livestock farming produce the manure, which is a mixture of urine, faeces and infrastructure washing water. Manure is stockpiled in over 100’000 pits in Switzerland (total capacity of 18 million m3), and then used as fertilizer. When manure enters aquatic environment, such pollution could be responsible of major health risks, contaminating drinkable water sources, or ecological disasters with the death of biota, including fishes. This kind of accident occurs frequently, and authors are in many cases not found by environmental law enforcement. This study aimed at exploring the possibilities of chemical markers to differentiate manures, with the purpose of estimating whether it would be possible to perform source inference in manure pollution cases in a chemical profiling approach. An exploratory market research was first conducted to understand practices of farming chemicals use, including antibiotics and detergents, in order to select potential chemical markers. Manure samples were analysed using ASE-SPE-UPLC-MS/MS (Accelerated Solvent Extraction – Solid Phase Extration – Ultra Performance Liquid Chromatography - tandem Mass Spectrometry) to detect 17 selected chemical markers with Multiple Reaction Monitoring mode: 11 antibiotics (benzylpenicillin, cloxacillin, colistin, danofloxacin, enrofloxacin, neomycin, sufadoxin, sulfaguanidin, sulfamethoxazol, tetracycline and trimetroprim), 1 vermifuge (flubadenzol), 2 local anesthetics (lidocaine and procain), 1 detergent (dodecylbenzenesulfonic acid) and 2 manure/faecal chemical markers (skatole and indole). Analysis in scan mode, extraction of several m/z and statistical testing (PCA and hierarchical cluster analysis) permitted to differentiate manure from cattle and pig farms, and some markers may also be useful to identify a farm among others. Finally, analysis of few specimens collected during pollution events showed that some chemical markers can be found in the water. The results of this study suggest that the applied methodology could allow to identify some types of pollution (including faecal pollution such as manure or wastewater treatment plant malfunctioning), and may help to achieve source inference in environmental fraud cases.

2015

Background: Diet is widely recognized as one of the main modifiable drivers of gut microbiota variability, and its influence on microbiota composition is an active area of investigation. Objective: The present work aimed to explore the associations between usual diet and gut microbiota composition in a large sample of healthy French adults. Methods: Gut microbiota composition was established through sequencing of the 16S rRNA gene in stool samples from 862 healthy French adults of the Milieu Interieur study. Usual dietary consumptions were determined through the administration of a food-frequency questionnaire. The associations between dietary variables and alpha- and beta-diversity indexes and relative taxa abundances were tested using Spearman correlations, permutational ANOVAs, and multivariate analyses with linear models, respectively. Results: Foods generally considered as healthy (raw fruits, fish) were positively associated with alpha-diversity, whereas food items for which a limited consumption is generally recommended (fried products, sodas or sugary drinks, fatty sweet products, processed meats, ready-cooked meals, and desserts) were negatively associated with alpha-diversity. Fruits, fried products, ready-cooked meals, and cheese contributed to shifts within microbiota composition (beta-diversity). Our results also highlighted a number of associations between various food group intakes and abundances of specific phyla, genera, and species. For instance, the consumption of cheese was negatively associated with Akkermansia muciniphila abundance. Conclusions: This large-scale population-based study supports that the usual consumption of certain food items is associated with several gut microbial features, and extends the mechanistic arguments linking Western diet to an altered microbiota composition. These results provide new insights into the understanding of complex diet-gut microbiota relations, and their implications for host health deserve further investigation because altered microbiota diversity was consistently linked to increased risk of several health outcomes. This trial was registered at clinicaltrials.gov as NCT01699893.

OXFORD UNIV PRESS2019

Multimedia and food chain modelling of toxics for comparative risk and life cycle impact assessment

Ralph Rosenbaum

The overall goal of this dissertation is to contribute to the development of best available practice in environmental multimedia fate and multipathway exposure modelling for human health and ecosystem impacts, addressing several important aspects. Environmental multimedia models relate environmental emissions to impacts (or risk factors) combining multimedia fate and multipathway exposure estimates with effect assessment data. Many organic chemicals formed in combustion and released to air as well as organic chemicals released to air, water, and soil from industrial activities enter humans primarily through food – in particular through meat and dairy products. Therefore, food chain modelling is of utmost importance for human exposure assessment. Model comparison and quantification of uncertainties of model results are vital for their correct interpretation. This leads to the following questions: How would a model framework be structured favouring flexibility, transparency, comparability, interpretability, without limiting the capabilities of the model parts? How can carry-over modelling of chemical biotransfer into biota such as meat or milk be improved considering limited data availability and high uncertainties? How can environmental multimedia multipathway models be compared in a systematic and detailed way, and what are important sources of differences? How to identify important sources of uncertainty in a model result, including regression models used for estimation and when modelling large sets of chemicals? In order to answer that, the following specific goals are addressed: Develop a consistent matrix algebra framework for multimedia fate, multipathway exposure and toxicity effects models. Review existing biotransfer models for chemical transfer into meat and milk and develop, compare and evaluate an improved carry-over model for meat and milk. Compare selected multimedia fate, multipathway exposure and toxicity effects models on the level of final characterisation factors as well as for intermediate results. Develop and test approaches to assess the uncertainty of model results accounting for regression model uncertainty and main parameters contributing to overall uncertainty. Chapter 1 puts this dissertation into its context and introduces multimedia fate, multipathway exposure and human health and ecosystem effects modelling with a focus on the food chain exposure in the frame of comparative risk and Life Cycle Impact Assessment. Chapter 2 presents a framework for multimedia multipathway models entirely based on matrix algebra. When assessing human health or ecosystem impacts of chemicals several calculation steps need to be addressed. We suggest a matrix algebra framework which includes the fate, exposure, effect, and damage assessment for human health and ecosystems, also applicable to spatial modelling. Special emphasis is laid upon interpretation of the physical meaning of different elements within the matrices. Chapter 3 describes the development, comparison and evaluation of an improved carry-over model for chemical transfer into meat and milk. The objective of this study is to increase the reliability and transparency of chemical biotransfer modelling into meat and milk and explicitly confront the uncertainties in exposure assessments of chemicals that require such estimates. To address this we developed a dynamic three compartment cow model (called CKow), able to distinguish lactating and non-lactating cows, to more accurately track the transport of a chemical into meat fat and milk within the cow. Using the CKow model as base model we derived a simplified model proposing an improved, less uncertain regression model to predict COR for meat and milk based on Kow. Chapter 4 is a detailed comparison of four characterisation methods used in LCIA. The main objective was to investigate whether or not the models' results agree with each other in terms of ranking as well as in absolute values and identify where differences come from. A comparison of characterisation factors and intermediate results of IMPACT 2002, CalTOX, USES-LCA, and EDIP97 has been performed for generic organic compounds. The comparison procedure was undertaken in three tiers: 1) comparison of available published factors, 2) calculated factors based on the harmonised chemical test set and 3) an in depth comparison revealing differences of the models on the level of processes and algorithms. Chapter 5 explores possibilities to estimate the uncertainty of results from multimedia fate and multipathway exposure models and to account for regression model uncertainty. Quantification and communication of uncertainties related to model results is vital for their correct interpretation and use. We explore and compare approaches to identify and quantify main sources of uncertainty, enabling to focus the data acquisition for the uncertainty assessment, especially when modelling large sets of chemicals. Chapter 6 presents general conclusions, wrapping up the achievements of this dissertation and answering the scientific questions raised above.

EPFL2006