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.
The Bergman Minimal Model enables estimation of two key indices of glucose/insulin dynamics: glucose effectiveness and insulin sensitivity. In this paper we describe MINMOD Millennium, the latest Windowsbased version of minimal model software. Extensive beta testing of MINMOD Millennium has shown that it is user-friendly, fully automatic, fast, accurate, reproducible, repeatable, and highly concordant with past versions of MINMOD. It has a simple interface, a comprehensive help system, an input file editor, a file converter, an intelligent processing kernel, and a file exporter. It provides publication-quality charts of glucose and insulin and a table of all minimal model parameters and their error estimates. In contrast to earlier versions of MINMOD and some other minimal model programs, Millennium provides identified estimates of insulin sensitivity and glucose effectiveness for almost every subject. Disciplines
A quarter of all anthropogenic methane emissions in the United States are from enteric fermentation, primarily from ruminant livestock. This study was undertaken to test the effect of a methane inhibitor, 3-nitrooxypropanol (3NOP), on enteric methane emission in lactating Holstein cows. An experiment was conducted using 48 cows in a randomized block design with a 2-wk covariate period and a 12-wk data collection period. Feed intake, milk production, and fiber digestibility were not affected by the inhibitor. Milk protein and lactose yields were increased by 3NOP. Rumen methane emission was linearly decreased by 3NOP, averaging about 30% lower than the control. Methane emission per unit of feed dry matter intake or per unit of energy-corrected milk were also about 30% less for the 3NOP-treated cows. On average, the body weight gain of 3NOP-treated cows was 80% greater than control cows during the 12-wk experiment. The experiment demonstrated that the methane inhibitor 3NOP, applied at 40 to 80 mg/kg feed dry matter, decreased methane emissions from high-producing dairy cows by 30% and increased body weight gain without negatively affecting feed intake or milk production and composition. The inhibitory effect persisted over 12 wk of treatment, thus offering an effective methane mitigation practice for the livestock industries.
Enteric methane (CH 4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.
Abstract. The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (AE0.28) · DMI (kg/day) (R 2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (AE0.008) · GEI (MJ/day) (R 2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia's national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO 2 -e reduction in calculated annual emissions from Australian cattle.
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