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      Tucumã Oil Shifted Ruminal Fermentation, Reducing Methane Production and Altering the Microbiome but Decreased Substrate Digestibility Within a RUSITEC Fed a Mixed Hay – Concentrate Diet

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          Abstract

          Tucumã oil is sourced from the fruit pulp of the tucumã tree and contains high concentrations of unsaturated fatty acids and carotenoids. Due to these properties it may have the potential to decrease enteric methane (CH 4) from ruminants when included in the diet. The objective of this study was to determine the effect of oil mechanically extracted from the fruit pulp of tucumã on fermentation characteristics, CH 4 production and the microbial community using the rumen stimulation technique. Treatments consisted of a control diet (forage:concentrate; 70:30), and tucumã oil included at 0.5 or 1.0% (v/v). Addition of tucumã oil linearly decreased ( P < 0.01) dry matter disappearance. Total gas (mL/d) and carbon dioxide (CO 2) production (mL/d, mL/g DM) were unaffected ( P ≥ 0.36) to increasing addition of tucumã oil where 0.5% (v/v) of Tucumã oil numerically increased both variables. Acetate and butyrate percentages of total VFA were linearly decreased ( P ≤ 0.01) and propionate and valerate percentages of total VFA were linearly increased ( P < 0.01) by increasing concentrations of tucumã oil added to the substrate. The ratio of acetate to propionate was linearly decreased ( P < 0.01) with increasing concentration of tucumã oil. Methane production (mL/d) was linearly decreased ( P = 0.04) with increasing addition of tucumã oil to the substrate. Tucumã oil reduced the bacterial richness and diversity when included at 1.0% (v/v) in both solid- and liquid- associated microbes. The abundance of the genera Fibrobacter and Rikenellaceae RC9 gut group were decreased and Pyramidobacter, Megasphaera, Anaerovibrio, and Selenomonas were enriched by the addition of 1.0% tucumã oil. In conclusion, tucumã oil resulted in the favorable shift in fermentation products away from acetate toward propionate, decreasing the production of CH 4 when tucumã oil was included at 1.0% (v/v), however, substrate digestibility was also inhibited. The rumen microbiota was also altered by the addition of tucumã oil.

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          Methane emissions from cattle.

          Increasing atmospheric concentrations of methane have led scientists to examine its sources of origin. Ruminant livestock can produce 250 to 500 L of methane per day. This level of production results in estimates of the contribution by cattle to global warming that may occur in the next 50 to 100 yr to be a little less than 2%. Many factors influence methane emissions from cattle and include the following: level of feed intake, type of carbohydrate in the diet, feed processing, addition of lipids or ionophores to the diet, and alterations in the ruminal microflora. Manipulation of these factors can reduce methane emissions from cattle. Many techniques exist to quantify methane emissions from individual or groups of animals. Enclosure techniques are precise but require trained animals and may limit animal movement. Isotopic and nonisotopic tracer techniques may also be used effectively. Prediction equations based on fermentation balance or feed characteristics have been used to estimate methane production. These equations are useful, but the assumptions and conditions that must be met for each equation limit their ability to accurately predict methane production. Methane production from groups of animals can be measured by mass balance, micrometeorological, or tracer methods. These techniques can measure methane emissions from animals in either indoor or outdoor enclosures. Use of these techniques and knowledge of the factors that impact methane production can result in the development of mitigation strategies to reduce methane losses by cattle. Implementation of these strategies should result in enhanced animal productivity and decreased contributions by cattle to the atmospheric methane budget.
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            Small sample inference for fixed effects from restricted maximum likelihood.

            Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings. The statistic uses an adjusted estimator of the covariance matrix that has reduced small sample bias. This approach has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact, namely for Hotelling T2 type statistics and for analysis of variance F-ratios. The performance of the modified statistics is assessed through simulation studies of four different REML analyses and the methods are illustrated using three examples.
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              Board-invited review: Recent advances in biohydrogenation of unsaturated fatty acids within the rumen microbial ecosystem.

              Recent advances in chromatographic identification of CLA isomers, combined with interest in their possible properties in promoting human health (e.g., cancer prevention, decreased atherosclerosis, improved immune response) and animal performance (e.g., body composition, regulation of milk fat synthesis, milk production), has renewed interest in biohydrogenation and its regulation in the rumen. Conventional pathways of biohydrogenation traditionally ignored minor fatty acid intermediates, which led to the persistence of oversimplified pathways over the decades. Recent work is now being directed toward accounting for all possible trans-18:1 and CLA products formed, including the discovery of novel bioactive intermediates. Modern microbial genetics and molecular phylogenetic techniques for identifying and classifying microorganisms by their small-subunit rRNA gene sequences have advanced knowledge of the role and contribution of specific microbial species in the process of biohydrogenation. With new insights into the pathways of biohydrogenation now available, several attempts have been made at modeling the pathway to predict ruminal flows of unsaturated fatty acids and biohydrogenation intermediates across a range of ruminal conditions. After a brief historical account of major past accomplishments documenting biohydrogenation, this review summarizes recent advances in 4 major areas of biohydrogenation: the microorganisms involved, identification of intermediates, the biochemistry of key enzymes, and the development and testing of mathematical models to predict biohydrogenation outcomes.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 July 2018
                2018
                : 9
                : 1647
                Affiliations
                [1] 1Animal Science Graduate Course, Veterinary Medicine Institute, Federal University of Pará , Belém, Brazil
                [2] 2School of Life and Environmental Sciences, Faculty of Science, The University of Sydney , Sydney, NSW, Australia
                [3] 3Lacombe Research and Development Centre, Agriculture and Agri-Food Canada , Lacombe, AB, Canada
                [4] 4Institute of Physiology, University of Veterinary Medicine , Hanover, Germany
                [5] 5Embrapa Dairy Cattle , Juiz de Fora, Brazil
                Author notes

                Edited by: Emilio M. Ungerfeld, Instituto de Investigaciones Agropecuarias (INIA), Chile

                Reviewed by: Biswarup Sen, Tianjin University, China; Secundino Lopez, Universidad de León, Spain

                *Correspondence: Alexandre V. Chaves, alex.chaves@ 123456sydney.edu.au

                This article was submitted to Systems Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2018.01647
                6071481
                30093888
                dced5355-cba8-4227-abb3-ca2954292781
                Copyright © 2018 Ramos, Terry, Holman, Breves, Pereira, Silva and Chaves.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 April 2018
                : 02 July 2018
                Page count
                Figures: 4, Tables: 4, Equations: 0, References: 58, Pages: 11, Words: 0
                Funding
                Funded by: Alexander von Humboldt-Stiftung 10.13039/100005156
                Funded by: Universidade Federal do Pará 10.13039/501100007382
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 10.13039/501100002322
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                oil supplementation,cattle,amazonia,rumen stimulation technique,rumen microbiome

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