scholarly journals Breeding Low Emitting Ruminants: Predicting Methane from Microbes

Proceedings ◽  
2020 ◽  
Vol 36 (1) ◽  
pp. 177
Author(s):  
Suzanne J. Rowe ◽  
Melanie Hess ◽  
Larissa Zetouni ◽  
Sharon Hickey ◽  
Rudiger Brauning ◽  
...  
Keyword(s):  
Energy Source ◽  
Low Cost ◽  
Genotyping By Sequencing ◽  
Methane Emissions ◽  
Mitigation Strategies ◽  
Microbial Fermentation ◽  
Global Access ◽  
Research Alliance ◽  
Microbial Dna ◽  
Ruminant Livestock

The greatest source of global anthropogenic methane (CH4) emissions is from ruminant livestock. Multiple mitigation strategies in livestock are currently being explored. Of these breeding for lower CH4 emitting ruminants has the advantage of being permanent and cumulative and universally applicable to all classes of livestock. Here, we show that methane emissions can be predicted by the complex community of microbiota sampled from rumens enabling evaluation of systems and individuals. Furthermore, there is evidence that the microbial community is controlled not only be the feed substrate but also by the host itself and that selecting hosts that favour a microbial fermentation with lowered methane emissions changes the energy source to the animal, and in turn both rumen physiology and body composition. Current methods for obtaining microbial DNA and subsequent sequencing of an animal’s microbiome, however, are too expensive to implement in commercial selection programs. A methodology that offers fast, low-cost, high throughput profiling of rumen microbiomes using Genotyping-by-sequencing (GBS) has been developed using an unbiased reference free approach to group microbiota. To date, this has been applied to over 4000 sheep samples and validated in cattle. Results show that microbial profiles are heritable and correlated with methane emissions and feed intake. This research is part of a flagship program funded by the global research alliance to disseminate global access to technologies that lower greenhouse gas emissions in ruminant livestock.

scholarly journals Burkholderia thailandensis E264 as a promising safe rhamnolipids’ producer towards a sustainable valorization of grape marcs and olive mill pomace

2021 ◽  
Author(s):  
Alif Chebbi ◽  
Massimiliano Tazzari ◽  
Cristiana Rizzi ◽  
Franco Hernan Gomez Tovar ◽  
Sara Villa ◽  
...  
Keyword(s):  
Energy Source ◽  
Olive Oil ◽  
Low Cost ◽  
Carbon Sources ◽  
Burkholderia Thailandensis ◽  
Rhamnolipid Production ◽  
Key Points ◽  
Wide Range ◽  
Long Chain ◽  
Olive Mill

Abstract Within the circular economy framework, our study aims to assess the rhamnolipid production from winery and olive oil residues as low-cost carbon sources by nonpathogenic strains. After evaluating various agricultural residues from those two sectors, Burkholderia thailandensis E264 was found to use the raw soluble fraction of nonfermented (white) grape marcs (NF), as the sole carbon and energy source, and simultaneously, reducing the surface tension to around 35 mN/m. Interestingly, this strain showed a rhamnolipid production up to 1070 mg/L (13.37 mg/g of NF), with a higher purity, on those grape marcs, predominately Rha-Rha C14-C14, in MSM medium. On olive oil residues, the rhamnolipid yield of using olive mill pomace (OMP) at 2% (w/v) was around 300 mg/L (15 mg/g of OMP) with a similar CMC of 500 mg/L. To the best of our knowledge, our study indicated for the first time that a nonpathogenic bacterium is able to produce long-chain rhamnolipids in MSM medium supplemented with winery residues, as sole carbon and energy source. Key points • Winery and olive oil residues are used for producing long-chain rhamnolipids (RLs). • Both higher RL yields and purity were obtained on nonfermented grape marcs as substrates. • Long-chain RLs revealed stabilities over a wide range of pH, temperatures, and salinities

scholarly journals PSII-17 Program Chair Poster Pick: Effect of ruminal protozoa on methane emissions in ruminants – a meta-analysis

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 397-398
Author(s):  
Xiaoxia Dai ◽  
Kenneth Kalscheur ◽  
Pekka Huhtanen ◽  
Antonio Faciola
Keyword(s):  
Dairy Cows ◽  
Meta Analysis ◽  
Random Effect ◽  
Negative Relationship ◽  
Small Ruminants ◽  
Methane Emissions ◽  
Mitigation Strategies ◽  
Positive Relationships ◽  
Ruminal Fermentation ◽  
The Relationship

Abstract The effects of ruminal protozoa (RP) concentration on methane emissions from ruminants were evaluated in a meta-analysis using 67 publications reporting data from 85 in vivo experiments. Experiments included in the database reported methane emissions (g/kg DMI) and RP (log10 cells/mL) from the same group of animals. Quantitative data including diet chemical composition, ruminal fermentation, total tract digestibility, and milk production; and qualitative information including methane mitigation strategies, animal type, and methane measurement methods were also collected. The studies were conducted in dairy cows (51%), beef steers (32%) and small ruminants (32%). 70% of the studies reported a reduction in methane emissions. Supplemental lipids reduced methane emissions 95% of the time. The relationship between methane emissions and RP concentration was evaluated as a random coefficient model with the experiment as a random effect and weighted by the inverse pooled SEM squared, including the possibility of covariance between the slope and the intercept. A quadratic effect of RP concentration on methane emissions was detected: CH4= -28.8 + 12.2 × RP-0.64 × RP2. To detect potential interfering factors in the relationship, the influence of several qualitative and quantitative factors were separately tested. Acetate, butyrate, and isobutyrate molar proportions had positive relationships with methane emissions and influenced the relationship between RP concentration and methane emissions, where the presence of ruminal fermentation variables reduced the effects of RP concentration in methane emissions. Total tract digestibility of DM, OM, and CP had negative relationships while NDF digestibility had a positive relationship with methane emissions; however, they only changed the magnitude of intercept and slope of RP and RP2 for the relationship. For dairy cows, milk fat and protein concentrations had positive relationships and milk yield had a negative relationship with methane emissions and changed the magnitude of intercept and slope of RP and RP2 for the relationship.

scholarly journals Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: Impacts of COVID-19 pandemic lockdown

2020 ◽  
Author(s):  
Shibao Wang ◽  
Yun Ma ◽  
Zhongrui Wang ◽  
Lei Wang ◽  
Xuguang Chi ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Low Cost ◽  
Air Pollutant ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Urban Air ◽  
Industrial Emissions ◽  
Gis Technology ◽  
Mobile Monitoring

Abstract. The development of low-cost sensors and novel calibration algorithms provides new hints to complement conventional ground-based observation sites to evaluate the spatial and temporal distribution of pollutants on hyper-local scales (tens of meters). Here we use sensors deployed on a taxi fleet to explore the air quality in the road network of Nanjing over the course of a year (Oct. 2019–Sep. 2020). Based on GIS technology, we develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3). Through hotspots identification analysis, we find three main sources of air pollutants including traffic, industrial emissions, and cooking fumes. We find that CO and NO2 concentrations show a pattern: highways > arterial roads > secondary roads > branch roads > residential streets, reflecting traffic volume. While the O3 concentrations in these five road types are in opposite order due to the titration effect of NOx. Combined the mobile measurements and the stationary station data, we diagnose that the contribution of traffic-related emissions to CO and NO2 are 42.6 % and 26.3 %, respectively. Compared to the pre-COVID period, the concentrations of CO and NO2 during COVID-lockdown period decreased for 44.9 % and 47.1 %, respectively, and the contribution of traffic-related emissions to them both decreased by more than 50 %. With the end of the COVID-lockdown period, traffic emissions and air pollutant concentrations rebounded substantially, indicating that traffic emissions have a crucial impact on the variation of air pollutants levels in urban regions. This research demonstrates the sense power of mobile monitoring for urban air pollution, which provides detailed information for source attribution, accurate traceability, and potential mitigation strategies at urban micro-scale.

On the suitability of induction heating system for metal additive manufacturing

2020 ◽  
Vol 235 (1-2) ◽  
pp. 219-229 ◽  
Author(s):  
Gourav K Sharma ◽  
Piyush Pant ◽  
Prashant K Jain ◽  
Pavan K Kankar ◽  
Puneet Tandon
Keyword(s):  
Energy Source ◽  
Additive Manufacturing ◽  
Induction Heating ◽  
Low Cost ◽  
Three Dimensional ◽  
Experimental System ◽  
Heating System ◽  
Industrial Applications ◽  
Metallic Materials ◽  
Semi Solid

Induction heating is a non-contact-based energy source that has the potential to quickly melt the metal and become the alternate energy source that can be used for additive manufacturing. At present, induction heating is widely used in various industrial applications such as melting, preheating, heat treatment, welding, and brazing. The potential of this source has not been explored in the additive manufacturing domain. However, the use of induction heating in additive manufacturing could lead to low-cost part fabrication as compared to other energy sources such as laser or electron beam. Therefore, this study explores the feasibility of this energy source in additive manufacturing for fabricating parts of metallic materials. An experimental system has been developed by modifying an existing delta three-dimensional printer. An induction heater coil has been incorporated to extruder head for semi-solid processing of the metal alloy. In order to test the viability of the developed system, aluminium material in the filament form has been processed. Obtained results have shown that the induction heating–based energy source is capable of processing metallic materials having a melting point up to 1000° C. The continuous extrusion of the material has been achieved by controlling the extruder temperature using a proportional integral derivative–based controller and k-type thermocouple. The study also discusses various issues and challenges that occurred during the melting of metal with induction heating. The outcomes of this study may be a breakthrough in the area of metal-based additive manufacturing.

scholarly journals PROTOTYPE DESIGN OF MICRO HYDRO USING TURBINE ARCHIMEDES SCREW FOR SIMULATION OF HIDROPOWER PRACTICAL OF ELECTRO ENGINEERING STUDENTS

2019 ◽  
Vol 3 (1) ◽  
pp. 6
Author(s):  
Antonius Ibi Weking ◽  
Yanu Prapto Sudarmojo
Keyword(s):  
Energy Source ◽  
Power Plants ◽  
Engineering Students ◽  
Low Cost ◽  
Water Pressure ◽  
Water Discharge ◽  
Small Scale ◽  
Engineering Department ◽  
Influence Of Water ◽  
Turbine Speed

Development of new and renewable energy source always developed by world researchers which one of those is energy source from water, because it’s friendly for environment and low cost. Water is one of energy source which it’s have big potential in all Indonesian territory. The main problem from microhydropower plants is a water discharge which it’s flow is not continued every year because influenced by weather season. Micro Hydro is a microhydro power plants (MHP)in a small scale. A micro hydro can be operated in a certain of time if it has a enough water supply. To knowing a right of micro hydro’s  characteristic is not easy thing to learn it. It is because a characteristic each of micro hydro’s installation location is considered specific location.               One type of micro hydro is using Archimedes Screw Turbine. Udayana University of Electrical Engineering Department in this time not have a facility for hydropower field to use this model, so a college student not yet to receive a knowledge of this. Through this research, a writer want to expand a college student’s knowledge in hydropower field with create a prototype of micro hydro with Archimedes Screw Turbine to hydropower practical in laboratory. In this research the effect of screw’s height angle conversion and effect of water pressure conversion has to be researched. In this study will discuss the influence of water pressure and slope of the altitude angle on the rotation produced by the Archimedes screw turbine so that it can be seen the voltage, current, power generated by the generator, torque and efficiency . The result of from handmade equipment for this research in angle 40­0 with biggest generator round (rpm) is 3768 (rpm) and highest power is 10.92057 watt, torque adalah 0.60 Nm dan efisiensi sebesar 14 %. The torque which resulted from water pressure 24 psi is 0,73 Nm and efficience 18,01 %. The voltage, current, and output power which resulted in generator is 85,8 Volt, 0,1963 Ampere and 16,85 Watt. For generator speed round in the pressure 24 Psi is 4582 rpm, while turbine speed round which resulted from the pressure 24 Psi is 383 rpm before coupled with generator and 222 rpm after coupled with generator.

scholarly journals Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nan Wang ◽  
Yibing Yuan ◽  
Hui Wang ◽  
Diansi Yu ◽  
Yubo Liu ◽  
...  
Keyword(s):  
First Generation ◽  
Low Cost ◽  
Genotyping By Sequencing ◽  
Restriction Enzymes ◽  
Genotyping Error ◽  
Genome Complexity ◽  
Maize Genetics ◽  
Missing Genotypes ◽  
Map Resolution ◽  
Multiplex Sequencing

Abstract Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

Low Cost System Design to Measure and Analyze of Temperature Rise Caused by 2450 MHz RF Energy in Human Phantom Model

2016 ◽  
Vol 27 ◽  
pp. 92-102 ◽  
Author(s):  
Mesud Kahriman ◽  
Ozlem Coskun ◽  
Esin Yavuz
Keyword(s):  
Energy Source ◽  
Temperature Rise ◽  
Daily Life ◽  
Low Cost ◽  
Communication Technologies ◽  
Dipole Antenna ◽  
Good Correspondence ◽  
Phantom Model ◽  
Cost System ◽  
Rf Energy

In recent years humans are more exposed to human-made fields than natural fields with developing technologies. Especially, widespread of wireless communication technologies in all areas of daily life and getting closer to sensitive organs like brain caused an increase in possible risks and worries about human health. In the study, a temperature measurement card has been designed and produced with the aim of observing the temperature rise at the phantom model generated by EM energy source. To that end, we present a study on the temperature rise of small dipole antenna (2450 MHz) that operate close to a user’s head (1, 4 and 7 cm). We found good correspondence between the temperature rise values evaluated in the phantom heads. According to the results of measure, expected temperature rise in the tissue exposed to RF energy may varies to the distance between radiated source and tissue.

Fast-GBS v2.0: an analysis toolkit for genotyping-by-sequencing data

Genome ◽  
2020 ◽  
Vol 63 (11) ◽  
pp. 577-581
Author(s):  
Davoud Torkamaneh ◽  
Jérôme Laroche ◽  
François Belzile
Keyword(s):  
Data Analysis ◽  
Missing Data ◽  
Low Cost ◽  
Genotyping By Sequencing ◽  
Data Imputation ◽  
Sequencing Data ◽  
Missing Data Imputation ◽  
Analysis Process ◽  
Computational Resources ◽  
Analysis Platform

Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.

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