scholarly journals Repeatability of gaseous measurements across consecutive days in sheep using Portable accumulation chambers

2021 ◽  
Author(s):  
E O’ Connor ◽  
F M McGovern ◽  
D T Byrne ◽  
T M Boland ◽  
E Dunne ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Small Ruminants ◽  
Prediction Equation ◽  
Gaseous Emissions ◽  
Time Points ◽  
Ewe Lambs ◽  
Carbon Dioxide Co2 ◽  
High Level

Abstract Portable accumulation chambers (PAC) enable gaseous emissions from small ruminants to be measured over a 50 min period, to date however, the repeatability of consecutive days of measurement in the PAC has not been investigated. The objectives of this study were to investigate: 1) the repeatability of consecutive days of gaseous measurements in the PAC, 2) the number of days required to achieve precise gaseous measurements, and 3) to develop a prediction equation for gaseous emissions in sheep. A total of 48 ewe lambs (c. 10 to 11 mo of age) were randomly divided into four measurement groups each day, for 17 consecutive days. Gaseous measurements were conducted between 0800 h and 1200 h daily. Animals were removed from perennial ryegrass silage for at least 1 h before measurements in the PAC and animals were assigned randomly to each of the 12 chambers. Methane (CH4; ppm) concentration, oxygen (O2; percentage) and carbon dioxide (CO2; percentage) were measured at 3 time points (0, 25, and 50 min after entry of the first animal into the first chamber). To quantify the effect of animal and day variation on gaseous emissions, between-animal, between-day and error variances were calculated for each gaseous measurement using a linear mixed model. The number of days required to gain a certain precision (defined as the 95% confidence interval (CI) range) for each gaseous measurement was also calculated. For all 3 gases the between-day variance (39% to 40%) accounted for a larger proportion of total variance compared to between-animal variance, while the repeatability of 17 consecutive days of measurement was 0.36, 0.31 and 0.23 for CH4, CO2 and O2, respectively. Correlations between consecutive days of measurement were strong for all 3 gases; the strongest correlation between d 1 and the remaining days for CH4, CO2 and O2 was 0.71 (d 1 and d 6), 0.77 (d 1 and d 2) and 0.83 (d 1 and d 5), respectively. A high level of precision was achieved when gaseous measurements from PAC were taken over 3 consecutive days. The prediction equation over-estimated gaseous production for all 3 gases: the correlations between actual and predicted gaseous output ranged from 0.67 to 0.71, with the r 2 ranging from 0.45 to 0.71. Results from this study will aid the refinement of the protocol for the measurement of gaseous emissions in sheep using the PAC.

scholarly journals Investigation of intra-day variability of gaseous measurements in sheep using Portable accumulation chambers 1

2021 ◽  
Author(s):  
E O’ Connor ◽  
N McHugh ◽  
T M Boland ◽  
E Dunne ◽  
F M McGovern
Keyword(s):  
Small Ruminants ◽  
Live Weight ◽  
Optimal Time ◽  
Body Volume ◽  
Gaseous Emissions ◽  
O2 Consumption ◽  
Time Points ◽  
Ch4 Production ◽  
Measurement Protocol ◽  
Carbon Dioxide Co2

Abstract Portable accumulation chambers (PAC) enable short term spot measurements of gaseous emissions including methane (CH4), carbon dioxide (CO2) and oxygen (O2) consumption from small ruminants. To date the differences in morning and evening gaseous measurements in the PAC have not been investigated. The objectives of this study were to investigate: 1) the optimal measurement time in the PAC, 2) the appropriate method of accounting for the animal’s size when calculating the animal’s gaseous output, and 3) the intra-day variability of gaseous measurements. A total of 12 ewe lambs (c. 10 to 11 months of age) were randomly selected each day from a cohort of 48 animals over nine consecutive days. Methane emissions from the 12 lambs were measured in 12 PAC during two measurement runs daily, AM (8 to 10 h) and PM (14 to 16 h). Animals were removed from Perennial ryegrass silage for at least 1 hour prior to measurements in the PAC and animals were assigned randomly to each of the 12 chambers. Methane (ppm) concentration, O2 and CO2 percentage were measured at 5 time points (T1 = 0.0 min, T2 = 12.5 min, T3 = 25.0 min, T4 = 37.5 min and T5 = 50.0 min from entry of the first animal into the first chamber) using an Eagle 2 monitor. The correlation between time points T5-T1 (i.e. 50 min minus 0 min after entry of the animal to the chamber) and T4-T1 was 0.95, 0.92 and 0.77 for CH4, O2 and CO2, respectively (P<0.01). The correlation between CH4 and CO2 output and O2 consumption, calculated with live-weight and with body volume was 0.99 (P<0.001). The correlation between the PAC measurement recorded on the same animal in the AM and PM measurement runs was 0.73. Factors associated with CH4 production included: day and time of measurement, the live-weight of the animal and the hourly relative humidity. Results from this study suggest that the optimal time for measuring an animal’s gaseous output in the PAC is 50 min, that live-weight should be used in the calculation of gaseous output from an animal and that the measurement of an animal’s gaseous emissions in either the AM or PM does not impact on the ranking of animals when gaseous emissions are measured using the feeding and measurement protocol outlined in the present study.

scholarly journals Phenomics data processing: A plot-level model for repeated measurements to extract the timing of key stages and quantities at defined time points

2021 ◽  
Author(s):  
Lukas Roth ◽  
María Xosé Rodríguez-Álvarez ◽  
Fred van Eeuwijk ◽  
Hans-Peter Piepho ◽  
Andreas Hund
Keyword(s):  
Time Series ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Measurement Techniques ◽  
Repeated Measurements ◽  
Canopy Height ◽  
Time Points ◽  
Percentile Method ◽  
Third Stage ◽  
Level Model

Decision-making in breeding increasingly depends on the ability to capture and predict crop responses to changing environmental factors. Advances in crop modeling as well as high-throughput field phenotyping (HTFP) hold promise to provide such insights. Processing HTFP data is an interdisciplinary task that requires broad knowledge on experimental design, measurement techniques, feature extraction, dynamic trait modeling, and prediction of genotypic values using statistical models. To get an overview of sources of variations in HTFP, we develop a general plot-level model for repeated measurements. Based on this model, we propose a seamless stage-wise process that allows to carry on estimated means and variances from stage to stage and approximates the gold standard of a single-stage analysis. The process builds on the extraction of three intermediate trait categories; (1) timing of key stages, (2) quantities at defined time points or periods, and (3) dose-response curves. In a first stage, these intermediate traits are extracted from low-level traits' time series (e.g., canopy height) using P-splines and the quarter of maximum elongation rate method (QMER), as well as final height percentiles. In a second and third stage, extracted traits are further processed using a stage-wise linear mixed model analysis. Using a wheat canopy growth simulation to generate canopy height time series, we demonstrate the suitability of the stage-wise process for traits of the first two above-mentioned categories. Results indicate that, for the first stage, the P-spline/QMER method was more robust than the percentile method. In the subsequent two-stage linear mixed model processing, weighting the second and third stage with error variance estimates from the previous stages improved the root mean squared error. We conclude that processing phenomics data in stages represents a feasible approach if using appropriate weighting through all stages. P-splines in combination with the QMER method are suitable tools to extract timing of key stages and quantities at defined time points from HTFP data.

scholarly journals Genetic Variants in the Genes of the Stress Hormone Signalling Pathway and Depressive Symptoms during and after Pregnancy

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Michael Schneider ◽  
Anne Engel ◽  
Peter A. Fasching ◽  
Lothar Häberle ◽  
Elisabeth B. Binder ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Pregnant Women ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Depression Scale ◽  
Fixed Time ◽  
Nucleotide Polymorphisms ◽  
Stress Hormone ◽  
Time Points ◽  
Over Time

Purpose. The aim of this study was to investigate whether single nucleotide polymorphisms (SNPs) in genes of the stress hormone signaling pathway, specificallyFKBP5,NR3C1, andCRHR1, are associated with depressive symptoms during and after pregnancy.Methods. The Franconian Maternal Health Evaluation Study (FRAMES) recruited healthy pregnant women prospectively for the assessment of maternal and fetal health including the assessment of depressiveness. The German version of the 10-item Edinburgh Postnatal Depression Scale (EPDS) was completed at three time points in this prospective cohort study. Visit 1 was at study entry in the third trimester of the pregnancy, visit 2 was shortly after birth, and visit 3 was 6–8 months after birth. Germline DNA was collected from 361 pregnant women. Nine SNPs in the above mentioned genes were genotyped. After construction of haplotypes for each gene, a multifactorial linear mixed model was performed to analyse the depression values over time.Results. EPDS values were within expected ranges and comparable to previously published studies. Neither did the depression scores differ for comparisons among haplotypes at fixed time points nor did the change over time differ among haplotypes for the examined genes. No haplotype showed significant associations with depressive symptoms severity during pregnancy or the postpartum period.Conclusion. The analysed candidate haplotypes inFKBP5,NR3C1, andCRHR1did not show an association with depression scores as assessed by EPDS in this cohort of healthy unselected pregnant women.

GHG emissions during the storage of rough pig slurry and the fractions obtained by mechanical separation

2008 ◽  
Vol 48 (2) ◽  
pp. 93 ◽  
Author(s):  
E. Dinuccio ◽  
P. Balsari ◽  
W. Berg
Keyword(s):  
Carbon Dioxide ◽  
Solid Fraction ◽  
Ghg Emissions ◽  
Pig Slurry ◽  
Gaseous Emissions ◽  
Ghg Emission ◽  
Photoacoustic Detection ◽  
Dynamic Chamber ◽  
Mechanical Separation ◽  
Carbon Dioxide Co2

Emissions of methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and ammonia (NH3) during the storage of rough pig slurry and the fractions (solid and liquid) obtained by mechanical separation were investigated in a laboratory-scale study. Manures were stored for a period of 30 days in open vessels (1500 cm3 capacity) within a climate-controlled room which was kept at 25 ± 0.2°C. Gaseous emissions were determined with the dynamic chamber method by infrared photoacoustic detection. The main GHG emission from the liquid manures was CH4. CH4 losses from both liquid and solid fractions together were 3% higher than from the rough slurry. CO2 losses from both liquid and solid fractions together increased by 10% compared with rough pig slurry. Appreciable N2O fluxes were only measured from the solid fraction. Combining the losses during the storage of both liquid and solid fraction, they resulted in reduced NH3 emissions compared with the storage of the rough pig slurry. Evidence from the present study suggests that mechanical separation of pig slurry has the potential to increase up to 25% the emission of CO2-equivalents to the atmosphere during the storage of the separated fractions if compared with the rough slurry.

scholarly journals Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

2021 ◽  
Author(s):  
Yuhua Chen ◽  
Hainan Wu ◽  
Wenguo Yang ◽  
Wei Zhao ◽  
Chunfa Tong
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Block Design ◽  
Tree Height ◽  
Genome Wide Association ◽  
Hybrid Population ◽  
Time Points ◽  
Genome Wide ◽  
Randomized Complete Block Design ◽  
Traditional Breeding

Abstract With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated to ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F1 hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated to the tree height under the p-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but 2 chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore demonstrated that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.

scholarly journals Rate of Progression in Activity and Participation Outcomes in Exercisers with Parkinson’s Disease: A Five-Year Prospective Longitudinal Study

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Stephanie A. Miller ◽  
Mindy Mayol ◽  
Elizabeth S. Moore ◽  
Audra Heron ◽  
Victoria Nicholos ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Longitudinal Study ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Long Term Effects ◽  
Prospective Longitudinal Study ◽  
Time Points ◽  
Balance Functions ◽  
Prospective Longitudinal

Background. Rates of progression of motor symptoms and physical performance show declines between 2% and 7% annually in community samples with Parkinson’s disease (PD). However, the effects of ongoing exercise behaviors on progression rates have not been considered. Objective. The primary purpose of this prospective, longitudinal study was to examine the annual rates of progression in activity and participation measures over five years in community-based exercisers with PD. Methods. A cohort of 55 regular exercisers with idiopathic PD was assessed at baseline and 1, 2, and 5 years. Regular exercise was defined as scores of 4-5 on the Stages for Readiness to Exercise Scale and a self-reported average of at least 60 minutes of exercise/week within six months of each testing session. Unadjusted and adjusted annual progression rates for activity and participation measures were calculated with a standardized equation of change from baseline. A linear mixed model with covariates of age at PD diagnosis and PD subtype was used to determine adjusted change scores. Results. Annual progression rates for unadjusted and adjusted variables were similar, and none exceeded 1.7% across time points for this group of exercisers with PD. Older age at PD diagnosis significantly contributed to faster progression of walking and balance functions. A nonlinear trajectory of the PD progression was demonstrated across most activity and participation outcomes. Conclusions. Annual progression rates demonstrated by this sample of exercisers were lower than those previously reported for motor decline in general samples with PD. Assessing activity and participation outcomes longitudinally at interim time points was important for understanding the trajectory of change over time. The lower rates of progression in this study warrant further investigation into the long-term effects of exercise in PD.

scholarly journals VALIDATION OF ANALYTICAL METHOD FOR DETERMINATION OF HIGH LEVEL CARBON DIOXIDE (CO2) IN NITROGEN GAS (N2) MATRIX USING GAS CHROMATOGRAPHY THERMAL CONDUCTIVITY DETECTOR

2015 ◽  
Vol 12 (24) ◽  
pp. 7-16
Author(s):  
Harry BUDIMAN ◽  
Oman ZUAS
Keyword(s):  
Carbon Dioxide ◽  
Thermal Conductivity ◽  
Gas Chromatography ◽  
Limit Of Detection ◽  
Good Precision ◽  
Thermal Conductivity Detector ◽  
Limit Of Quantitation ◽  
Carbon Dioxide Co2 ◽  
High Level

High accurate result of carbon dioxide (CO2) measurement is of great importance since the result (data) is used as the foundation for decision making related to regulated monitoring program and law enforcement. In this study, therefore, method for measurement of high level of carbon dioxide (CO2) in nitrogen (N2) matrix using gas chromatography thermal conductivity detector (GC-TCD) was validated to achieve the optimum performance of the method. For this purposes, identity confirmation, selectivity, limit of detection (LoD), limit of quantitation (LoQ), repeatability, reproducibility, accuracy, and linearity of the method were evaluated. The result shows that the GC-TCD method has good precision in term of repeatability and reproducibility having values of 0.07 and 0.37%, respectively. No bias of the method can be found and an excellent linearity of the method was obtained in the range of 2 - 13.97% mol/mol. Thus, based on the result evaluation under given criteria of this study, it can be concluded that the GC-TCD method is reliable and suitable for determination of high level of CO2 in N2 matrix.

scholarly journals Social capital associated with quality of life among late adults and elderly population in the Northeast of Thailand

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 496
Author(s):  
Kitti Prachuntasen ◽  
Wongsa Laohasiriwong ◽  
Amornrat Luenam
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Social Capital ◽  
Health Services ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Monthly Income ◽  
Cross Sectional ◽  
High Level

Background: Previous studies indicated that social capital (SC) has an influence on quality of life (QOL). However, there are limited studies on how SC might associate with QOL among late adults and elderly in Thailand. Methods: This cross-sectional study was conducted among 1,148 participants who were identified by multistage random sampling from 4 provinces in the Northeast of Thailand. A self – administered questionnaire was developed and used to assess cognitive social capital (CSC), structural social capital (SSC), accessibility to health services, and socioeconomic status (SES) and QOL. The Generalized Linear Mixed Model (GLMM) was used to determine the association between SC and QOL when controlling for other covariates. Results: Only 41.03% (95%CI: 38.17 to 43.94) of the participants had good QOL. About half (50.26%) had high level of CSC, whereas only 36.15% had high level of SSC. The multivariate analysis indicated that having high levels of CSC and SSC was associated with good QOL. Other factors that were associated with having good QOL were aged <60 years old, monthly income ≥15,000 baht, adequate income, adequate physical activity, lived in the municipality, and had high level of accessibility to health services. Conclusion: Less than half of late adults and elderly had good QOL and high level of SSC. About half had high level of CSC. Both CSC and SSC had influence on QOL as well as gender, age, monthly income, financial status, physical activity, residential area, and accessibility to health services.

scholarly journals Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164898 ◽  
Author(s):  
Alfred Musekiwa ◽  
Samuel O. M. Manda ◽  
Henry G. Mwambi ◽  
Ding-Geng Chen
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Meta Analysis ◽  
Effect Sizes ◽  
General Linear ◽  
Multiple Time ◽  
Time Points ◽  
Multiple Time Points ◽  
General Linear Mixed Model

scholarly journals Carbon dioxide fumigation of Thrips tabaci in export onions

2002 ◽  
Vol 55 ◽  
pp. 303-307 ◽  
Author(s):  
B.B.C. Page ◽  
M.J. Bendall ◽  
A. Carpenter ◽  
C.W. Van_Epenhuijsen
Keyword(s):  
Carbon Dioxide ◽  
Delivery System ◽  
Elevated Carbon Dioxide ◽  
Thrips Tabaci ◽  
Control Treatment ◽  
Co2 Concentrations ◽  
Carbon Dioxide Co2 ◽  
High Level ◽  
Air Control ◽  
Chemical Pesticides

As an alternative to chemical pesticides elevated carbon dioxide atmospheres were examined as a method for controlling thrips on export onions A replicated gas delivery system was used to deliver a constant supply of various concentrations of carbon dioxide (CO2) to thripsinfested onions within sealable bags Six CO2 treatments an air control and 15 30 45 60 and 100 CO2 (all in balance air) were applied for 6 12 24 48 and 72 h Mortality was 100 at CO2 concentrations of 30 or more after at least 24 h However the control treatments also had a high level of mortality and although there were significant differences between the control treatment and the CO2 treatments these differences were not large

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