scholarly journals Stool and ruminal microbiome components associated with methane emission and feed efficiency in Nelore beef cattle.

2021 ◽  
Author(s):  
Bruno G.N. Andrade ◽  
Haithem Afli ◽  
Flavia A. Bressani ◽  
Rafael R. C. Cuadrat ◽  
Priscila S. N. de Oliveira ◽  
...  
Keyword(s):  
Methane Emission ◽  
Feed Efficiency ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Mixed Linear Models ◽  
Human Welfare ◽  
Feed Composition ◽  
Fecal Microbiome ◽  
Treatment Groups ◽  
The Impact

Abstract Background: The impact of extreme changes in weather patterns in the economy and human welfare are some of the biggest challenges that our civilization is facing. From the anthropogenic activities that contribute to climate change, reducing the impact of farming activities is a priority, since it is responsible for up to 18% of greenhouse gases linked to such activities. To this end, we tested if the ruminal and fecal microbiome components of 52 Brazilian Nelore bulls, belonging to two treatment groups based on the feed intervention, conventional and by-products based diet, could be used in the future as biomarkers for methane emission and feed efficiency in bovine.Results: We identified a total of 5,693 Amplicon Sequence Variants (ASVs) in the Nelore bulls microbiomes. Differential abundance (DA) analysis with the ANCOM approach identified 30 bacterial and 15 archaea ASVs as DA among treatment groups. Association analysis using Maaslin2 and Mixed Linear Models indicated that bacterial ASVs are linked to the residual methane emission (RCH4) and Residual Feed Intake (RFI) phenotypes, contributing to the host’s phenotypic variation, suggesting their potential as targets for interventions and/or biomarkers.Conclusion: Feed composition induced significant differences in abundance and richness of ruminal and fecal microbial populations. The diet based on industrial byproducts applied to our treatment groups influenced the microbiome diversity of bacteria and archaea, but not of protozoa. Different ASVs were associated with RCH4 emission and RFI in both ruminal and fecal microbiomes. While ruminal ASVs are expected to directly influence RCH4 emission and RFI, the relation of fecal taxa, such as Alistipes and Rikenellaceae (gut group RC9), with these traits might also be associated with host health due to their link to anti-inflammatory compounds, and these have the potential to be used as accessible biomarkers for these complex phenotypes.

scholarly journals Fecal and Ruminal Microbiome Components Associated With Methane Emission in Beef Cattle.

2020 ◽  
Author(s):  
Bruno G.N. Andrade ◽  
Haithem Afli ◽  
Flavia A. Bressani ◽  
Rafael R. C. Cuadrat ◽  
Priscila S. N. de Oliveira ◽  
...  
Keyword(s):  
Treatment Group ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Dietary Treatment ◽  
Mixed Linear Models ◽  
Feed Composition ◽  
Treatment Groups ◽  
Weather Patterns ◽  
Group B ◽  
The Impact

Abstract Background: The impact of extreme changes in weather patterns in the economy and humanity welfare are some of the biggest challenges that our civilization is facing. From the anthropogenic activities that contribute to climate change, reducing the impact of farming activities is a priority, since its responsible for up to 18% of greenhouse gases linked to such activities. To this end, we tested if the ruminal and fecal microbiomes components of 52 Brazilian Nelore bulls, belonging to two experimental groups based on the feed intervention, conventional (A) and byproducts based diet (B), could be used as biomarkers for methane (CH4) emission.Results: We identified a total of 5,693 Amplicon Sequence Variants (ASVs) in the Nelore bulls microbiomes from the experimental group B. Statistical analysis showed that the microbiome populations were significantly different among treatment groups. Differential abundance (DA) analysis with the ANCOM approach identified 30 bacterial and 15 archaea ASVs as DA among treatment groups. Random forest models, using either bacteria or archaea ASVs as predictors, were able to predict the treatment group with high accuracy (r2>0.85). Association analysis using Mixed Linear Models indicate that bacterial and archaea ASVs are linked to the CH4 emission phenotype, of which the most prominent were the ruminal ASV 40 and fecal ASV 35. These ASVs contributed to a 9.7% increase and 7.3% decrease of the variation in CH4 emission, respectively, which indicated their potential as targets for feed interventions and/or biomarkers.Conclusion: The feed composition induced significant differences in abundance and richness of ruminal and fecal microbial populations. The dietary treatment based on industrial byproducts applied had an impact on the microbiome diversity of bacteria and archaea, but not on protozoa. Microbiome components (ASVs) of bacteria and archaea can be successfully used to predict the treatment group, thus giving support to the hypothesis that the feed intervention modulate microbiome abundance and diversity. Microbiome components were associated with CH4 emission in both microbiomes. Therefore, both ruminal and fecal ASVs can be used as biomarkers for methane production and emission.

scholarly journals Fecal and Ruminal Microbiome Components Associated With Methane Emission in Beef Cattle.

2020 ◽  
Author(s):  
Bruno G.N. Andrade ◽  
Haithem Afli ◽  
Flavia A. Bressani ◽  
Rafael R. C. Cuadrat ◽  
Priscila S. N. de Oliveira ◽  
...  
Keyword(s):  
Treatment Group ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Dietary Treatment ◽  
Mixed Linear Models ◽  
Feed Composition ◽  
Treatment Groups ◽  
Weather Patterns ◽  
Group B ◽  
The Impact

Abstract Background: The impact of extreme changes in weather patterns in the economy and humanity welfare are some of the biggest challenges that our civilization is facing. From the anthropogenic activities that contribute to climate change, reducing the impact of farming activities is a priority, since its responsible for up to 18% of greenhouse gases linked to such activities. To this end, we tested if the ruminal and fecal microbiomes components of 52 Brazilian Nelore bulls, belonging to two experimental groups based on the feed intervention, conventional (A) and byproducts based diet (B), could be used as biomarkers for methane (CH4) emission.Results: We identified a total of 5,693 Amplicon Sequence Variants (ASVs) in the Nelore bulls microbiomes from the experimental group B. Statistical analysis showed that the microbiome populations were significantly different among treatment groups. Differential abundance (DA) analysis with the ANCOM approach identified 30 bacterial and 15 archaea ASVs as DA among treatment groups. Random forest models, using either bacteria or archaea ASVs as predictors, were able to predict the treatment group with high accuracy (r2>0.85). Association analysis using Mixed Linear Models indicate that bacterial and archaea ASVs are linked to the CH4 emission phenotype, of which the most prominent were the ruminal ASV 40 and fecal ASV 35. These ASVs contributed to a 9.7% increase and 7.3% decrease of the variation in CH4 emission, respectively, which indicated their potential as targets for feed interventions and/or biomarkers.Conclusion: The feed composition induced significant differences in abundance and richness of ruminal and fecal microbial populations. The dietary treatment based on industrial byproducts applied had an impact on the microbiome diversity of bacteria and archaea, but not on protozoa. Microbiome components (ASVs) of bacteria and archaea can be successfully used to predict the treatment group, thus giving support to the hypothesis that the feed intervention modulate microbiome abundance and diversity. Microbiome components were associated with CH4 emission in both microbiomes. Therefore, both ruminal and fecal ASVs can be used as biomarkers for methane production and emission.

scholarly journals Application of Mixed Linear Models in the Analysis of Road Surface Features

2015 ◽  
Vol 54 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Jurgita Židanavičiūtė ◽  
Audrius Vaitkus
Keyword(s):  
Linear Models ◽  
Road Surface ◽  
Linear Regression Models ◽  
Mixed Linear Models ◽  
Time Intervals ◽  
Surface Strength ◽  
The Road ◽  
Unequally Spaced ◽  
Units Of Analysis ◽  
The Impact

The data were collected by researchers at the Road Research Institute, in a study investigating the impact of differentfactors on road surface strength. In this statistical analysis, we apply linear mixed models (LMMs) to clustered longitudinal data, inwhich the units of analysis (points in the road) are nested within clusters (sample of four different road segments), and repeatedmeasures of road strength in these different points are collected over time with unequally spaced time intervals. The data arebalanced – each cluster has the same number of units, which are measured at the same number of time points. Because of correlateddata and different clusters in which data could be correlated, linear regression models are not appropriate here, and therefore linearmixed models are applied.

scholarly journals The Impact of Different Competitive Environments on Pacing and Performance

2018 ◽  
Vol 13 (6) ◽  
pp. 701-708 ◽  
Author(s):  
Marco J. Konings ◽  
Florentina J. Hettinga
Keyword(s):  
Fixed Effects ◽  
Linear Models ◽  
Real Life ◽  
Energy Resources ◽  
Mixed Linear Models ◽  
Start Position ◽  
Available Energy ◽  
Competitive Environments ◽  
And Performance ◽  
The Impact

Purpose: In real-life competitive situations, athletes are required to continuously make decisions about how and when to invest their available energy resources. This study attempted to identify how different competitive environments invite elite short-track speed skaters to modify their pacing behavior during head-to-head competition. Methods: Lap times of elite 500-, 1000- and 1500-m short-track speed skating competitions between 2011 and 2016 (N = 34,095 races) were collected. Log-transformed lap and finishing times were analyzed with mixed linear models. The fixed effects in the model were sex, season, stage of competition, start position, competition importance, event number per tournament, number of competitors per race, altitude, and time qualification. The random effects of the model were athlete identity and the residual (within-athlete race-to-race variation). Separate analyses were performed for each event. Results: Several competitive environments, such as the number of competitors in a race (a higher number of competitors evoked most likely a faster initial pace; coefficient of variation [CV] = 1.9–9.3%), the stage of competition (likely to most likely, a slower initial pace was demonstrated in finals; CV = −1.4% to 2.0%), the possibility of time qualification (most likely a faster initial pace; CV = 2.6–5.0%), and competition importance (most likely faster races at the Olympics; CV = 1.3–3.5%), altered the pacing decisions of elite skaters in 1000- and 1500-m events. Stage of competition and start position affected 500-m pacing behavior. Conclusions: As demonstrated in this study, different competitive environments evoked modifications in pacing behavior, in particular in the initial phase of the race, emphasizing the importance of athlete–environment interactions, especially during head-to-head competitions.

scholarly journals The Gut Microbial Architecture of Efficiency Traits in the Domestic Poultry Model Species Japanese Quail (Coturnix japonica) Assessed by Mixed Linear Models

2020 ◽  
Vol 10 (7) ◽  
pp. 2553-2562 ◽  
Author(s):  
Solveig Vollmar ◽  
Robin Wellmann ◽  
Daniel Borda-Molina ◽  
Markus Rodehutscord ◽  
Amélia Camarinha-Silva ◽  
...  
Keyword(s):  
Japanese Quail ◽  
Linear Models ◽  
Microbiota Composition ◽  
Mixed Linear Models ◽  
Model Species ◽  
Narrow Sense Heritability ◽  
Association Analyses ◽  
Domestic Poultry ◽  
Calcium Utilization ◽  
The Impact

It is well known that mammals and avian gut microbiota compositions are shaped by the host genomes and affect quantitative traits. The microbial architecture describes the impact of the microbiota composition on quantitative trait variation and the number and effect distribution of microbiota features. In the present study the gut microbial architecture of feed-related traits phosphorus and calcium utilization, daily gain, feed intake and feed per gain ratio in the domestic poultry model species Japanese quail were assessed by mixed linear models. The ileum microbiota composition was characterized by 16S rRNA amplicon sequencing techniques of growing individuals. The microbiability of the traits was on a similar level as the narrow sense heritability and was highly significant except for calcium utilization. The animal microbial correlation of the traits was substantial. Microbiome-wide association analyses revealed several traits associated and highly significant microbiota features, both on the bacteria genera as well as on the operational taxonomic unit level. Most features were significant for more than one trait, which explained the high microbial correlations. It can be concluded that the traits are polymicrobial determined with some microbiota features with larger effects and many with small effects. The results are important for the development of hologenomic selection schemes for feed-related traits in avian breeding programs that are targeting the host genome and the metagenome simultaneously.

scholarly journals Effect of Climate Change on Soil Health and Implications on Food Security: A Review

2021 ◽  
pp. 38-46
Author(s):  
Wycliffe Tumwesigye ◽  
Bobe Bedadi ◽  
Johnson Atwiine
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Crop Production ◽  
Anthropogenic Activities ◽  
Soil Health ◽  
Large Contribution ◽  
Soil Water Retention ◽  
Human Welfare ◽  
Human Wellbeing ◽  
The Impact

Climate change and soil health are intertwined complex processes that affect each other. The aim of this review was to find out the impact of climate change on soil health, its implication on food security and human welfare across the globe. The study found out that soil health is affected by land use practices and several anthropogenic activities carried out on landscapes; climate change and variability. Soil health also contributes to soil water retention, crop productivity, households’ food and income security culminating into a large contribution towards achieving sustainable development goals across the globe. Soil components affect climate and climate affects soil health and human wellbeing. The review article concluded that climate change and soil health are complex and intertwined multidisciplinary processes that require multidisciplinary approaches for better understanding and improvement of crop production. Appropriate climate smart agricultural practices are recommended to enhance soil health and mitigate and adapt to the changing climate for the improved farmers’ income, food security and human wellbeing across the globe.

Modeling cetacean habitat use in an urban coastal area in southeastern Brazil

2020 ◽  
Vol 642 ◽  
pp. 227-240
Author(s):  
L Lodi ◽  
R Tardin ◽  
G Maricato
Keyword(s):  
Habitat Use ◽  
Protected Areas ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Buffer Zone ◽  
Humpback Whales ◽  
Southeastern Brazil ◽  
Major Influence ◽  
Cetacean Species ◽  
Few Data

Most studies of cetacean habitat use do not consider the influence of anthropogenic activities. We investigated the influence of environmental and anthropogenic variables on habitat use by humpback Megaptera novaeangliae and Bryde’s whales Balaenoptera brydei off the coast of the Brazilian city of Rio de Janeiro. Although there are 2 marine protected areas (MPAs) in this area, few data are available on cetacean habitat use or on the overlap of different cetacean species within these MPAs. Our aim was to evaluate the effectiveness of the MPAs and propose a buffer zone to better protect the biodiversity of the study area. We conducted systematic surveys and developed spatial eigenvector generalized linear models to characterize habitat use by the species in the study area. Habitat use by humpback whales was influenced only by depth, whereas for Bryde’s whales there was the additional influence of anthropogenic variables. For Bryde’s whales, which use the area for feeding, sea surface temperature and the distance to anchorages had a major influence on habitat use. We also showed that neither of the MPAs in the study area adequately protects the hotspots of either whale species. Most of the humpback whale grid cells with high sighting predictions were located within 2 km of the MPAs, while areas of high sighting prediction of Bryde’s whales were located up to 5 km from the MPAs, closer to beaches. Our findings provide important insights for the delimitation of protected areas and zoning of the MPAs.

Inheritance and Correlation Analysis of Main Agronomic Traits in Mungbean (Vigna radiata L.) by Mixed Linear Models

2013 ◽  
Vol 38 (4) ◽  
pp. 624-631
Author(s):  
Chang-You LIU ◽  
Bao-Jie FAN ◽  
Zhi-Min CAO ◽  
Yan WANG ◽  
Zhi-Xiao ZHANG ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Vigna Radiata ◽  
Linear Models ◽  
Agronomic Traits ◽  
Mixed Linear Models

Chemical Composition and Metal Speciation in Porewaters from the Upper Qu’Appelle River Basin, Saskatchewan

1993 ◽  
Vol 28 (1) ◽  
pp. 83-110 ◽  
Author(s):  
Richard E. Farrell ◽  
Jae E. Yang ◽  
P. Ming Huang ◽  
Wen K. Liaw
Keyword(s):  
Amino Acids ◽  
Trace Metal ◽  
River Basin ◽  
Drainage Basin ◽  
Metal Speciation ◽  
Anthropogenic Activities ◽  
High Concentration ◽  
Metal Concentrations ◽  
Carbonate Equilibria ◽  
The Impact

Abstract Porewater samples from the upper Qu’Appelle River basin in Saskatchewan, Canada, were analyzed to obtain metal, inorganic ligand and amino add profiles. These data were used to compute the aqueous speciation of the metals in each porewater using the computer program GEOCHEM-PC. The porewaters were classified as slightly to moderately saline. Metal concentrations reflected both the geology of the drainage basin and the impact of anthropogenic activities. Whereas K and Na were present almost entirely as the free aquo ions, carbonate equilibria dominated the speciation of Ca. Mg and Mn (the predominant metal ligand species were of the type MCO3 (s). MCO30. and MHCO3+). Trace metal concentrations were generally within the ranges reported for non-polluted freshwater systems. Whereas the speciation of the trace metals Cr(III) and Co(II) was dominated by carbonate equilibria, Hg(II)-, Zn(II)- and Fe(II)-speciation was dominated by hydroxy-metal complexes of the type M(OH)+ and M(OH)2°. The speciation of Fe(III) was dominated by Fe(OH)3 (s). In porewaters with high chloride concentrations (> 2 mM), however, significant amounts of Hg(II) were bound as HgCl20 and HgClOH0. The aqueous speciation of Al was dominated by Al(OH)4− and Al2Si2O4(OH)6 (s). Total concentrations of dissolved free amino acids varied from 15.21 to 25.17 umole L−1. The most important metal scavenging amino acids were histidine (due to high stability constants for the metal-histidine complexes) and tryptophan (due to its relatively high concentration in the porewaters. i.e., 5.96 to 7.73 umole L−1). Secondary concentrations of various trace metal-amino add complexes were computed for all the porewaters, but metal-amino acid complexes dominated the speciation of Cu(II) in all the porewaters and Ni(II) in two of the porewaters.

Environmental impact of nutrients from nordic fish farming

1995 ◽  
Vol 31 (10) ◽  
pp. 61-71 ◽  
Author(s):  
M. Enell
Keyword(s):  
Major Part ◽  
Fish Farming ◽  
Fish Farms ◽  
Feed Composition ◽  
The North ◽  
Comprehensive Development ◽  
The Baltic ◽  
Inland Water Bodies ◽  
The Impact ◽  
Feed Coefficient

During the last 20 years there has been an interesting development of the Nordic fish farming, with regard to the feeding and farming technology and to the increase in production quantities. During the period 1974-1994 the production increased from 15,800 to about 250,000 tonnes/year. In 1974 the major part of the production was in Denmark, and in 1994 the major part was in Norway. The nutrient impact of fish farming on surrounding sea areas is mainly a function of the feed coefficient, the feed composition and metabolic processes in the fish. The comprehensive development of the feed composition and the feeding technology has resulted in reduced load of unmetabolized nutrients from fish farms, calculated per tonne fish produced. In 1974 the mean Nordic feed coefficient was 2.08 and in 1994 the coefficient was 1.25. Feed coefficients of 1.0-1.1 are now reported for Danish and Norwegian freshwater and marine fish farms. The nitrogen (N) and phosphorus (P) content of the feed has decreased, in addition the quality of the nutrient substances in the feed has changed, especially for N. The N content has decreased from 7.8 to 6.8% during the period 1974-1994 and the content of P has decreased from 1.7 to 0.7% during the same period. This development of the feed coefficient and the feed composition has resulted in a present load from a typical Nordic fish farm of 55 kg N and 4.8 kg P/t fish produced. The figures for 1974 were 132 kg N and 31 kg P/t fish produced. The Nordic fish farming production in 1994 resulted in a load of about 13,750 t N and about 1,200 t P on the actual recipients. The load from the Swedish, Finnish and Danish fish farming operations, with the Baltic Sea and the Skagerrak as the recipients, is negligible in comparison with other pollution sources. The quantities of N and P from the fish farming are equal to 0.5% of the atmospheric deposition on the sea surface and 3% of the atmospheric P load. Norwegian, Icelandic and the Faroe Islands fish farming operations are using the North Sea and the Norwegian Sea as the recipients. However, the nutrient load from single fish farms in certain coastal and inland water bodies can be significant and must be considered in the impact assessment together with other sources.

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