Fleece rot in Merino sheep. 1. The heritability of fleece rot in unselected flocks of medium-wool Peppin Merinos

1984 ◽  
Vol 35 (3) ◽  
pp. 423 ◽  
Author(s):  
BJ McGuirk ◽  
KD Atkins
Keyword(s):  
Agricultural Research ◽  
Heritability Estimate ◽  
Visual Assessment ◽  
Research Centre ◽  
Data Sets ◽  
Data Set ◽  
Merino Sheep ◽  
Two Measures ◽  
Heritability Estimates ◽  
Birth Type

Fleece rot was observed on hogget ewes and rams in unselected medium-wool Peppin Merino flocks over a 15-year period at Trangie Agricultural Research Centre, N.S.W. Each sheep was given a score of from 0 (no fleece rot) to 5 (very severe fleece rot) following a subjective visual assessment along the backline prior to shearing. Data were analysed as two measures of susceptibility to fleece rot: a score as defined above; and incidence, where fleece rot was treated as an all-or-none trait. The average incidence of fleece rot over 23 flock x year combinations was 36%, but this varied widely, from 8 to 90%. Other environmental factors (sex, birth type and age of dam) generally had small and non-significant effects on fleece rot. After adjusting for significant environmental effects, the half-sib heritability estimates for sires:with at least three progeny were 0.36 (�0.07) for score and 0.23 (�0.07) for incidence. Separate anaiyses were conducted for flock x year data sets of low, intermediate and high incidences. The highest heritability estimate for incidence was, as expectedly theoretically, obtained in the data set of intermediate incidence. Offspring-dam heritability estimates ( � s.e.) for fleece rot score and incidence were respectively 0.21 (� 0 0 5 ) and 0.14(�0.04). Corresponding offspring-sire estimates for score and incidence were 0.20 (�0.06) and 0.17 (�0.05). It is concluded that a realistic estimate of the heritability of the underlying liability to fleece rat is of the order of 40%.

Genetic evaluation of production traits between and within flocks of Merino sheep. II. Component traits of the Hogget fleece

1993 ◽  
Vol 44 (7) ◽  
pp. 1523 ◽  
Author(s):  
SI Mortimer ◽  
KD Atkins
Keyword(s):  
Agricultural Research ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Matter Content ◽  
Research Centre ◽  
Production Traits ◽  
Merino Sheep ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Fleece Weight

Components of the fleece and wool quality traits were measured or assessed on Merino hogget ewes in an unselected multiple-bloodline flock over a 7-year period at Trangie Agricultural Research Centre, N.S.W. The traits recorded were face cover score (FC), leg cover score (LC), neck fold score (NF), body fold score (BF), wax content (W), suint content (S), vegetable matter content (VM), dust penetration (D), follicle density (N) and follicle ratio (RA). Genetic differences within and between flocks of Merino sheep were examined for the traits, and estimates of heritability and within-flock genetic and phenotypic correlations and between-flock genetic correlations among the traits were obtained. Genetic and phenotypic correlations were also estimated between these traits and the major wool production traits: greasy fleece weight (GFW), clean fleece weight (CFW), fibre diameter (FD), body weight (BWT) and staple length (SL). Significant strain. flock within strain and flock effects were wresent for all traits. The influence of environmental effects (birth-rearing type, age at measurement and age of dam) on the traits was estimated, with the birth-rearing type being significant and the largest effect for most traits. Paternal half-sib heritability estimates were 0.44� 0.06 for FC, 0.35� 0.06 for LC, 0.24�0.05 for NF, 0.23�0.05 for BF, 0.38�0.07 for W, 0.42�0.07 for S, 0.06�0.04 for VM, 0.22�0.06 for D, 0.20� 0.07 for N and 0.21�0.07 for RA. Estimates of within-flock phenotypic and genetic correlations were in broad agreement with available published estimates. The implications of the results for Merino breeding programs are discussed.

Pedigree analysis of selected lines of Merino sheep. 1. Inbreeding

2002 ◽  
Vol 53 (7) ◽  
pp. 771
Author(s):  
E. Safari ◽  
J. W. James
Keyword(s):  
Confidence Interval ◽  
Agricultural Research ◽  
Pedigree Analysis ◽  
Early Years ◽  
Research Centre ◽  
Mass Selection ◽  
Pedigree Data ◽  
Selected Lines ◽  
Merino Sheep ◽  
Inbreeding Coefficients

Four pairs of selection lines of Merino sheep consisting of 100 ewes and 5 rams were established at the Trangie Agricultural Research Centre in 1951. Each line was selected (mass selection) for the appropriate character and direction (Plus or Minus) for a period of 18 years (5 generations). The characters subjected to selection were clean fleece weight, crimp frequency, weaning weight, and skin folds. The average inbreeding coefficients calculated from the pedigree data of the those selected lines ranged from 3.79% in the Fleece Plus line to 9.09% in the Folds Plus line, corresponding to average annual inbreeding rates of 0.211% and 0.505%, respectively. Generally, there were similar fluctuating patterns in the means of inbreeding coefficients across years, with higher variation in the early years, and different rates of inbreeding in different flocks. The only exception was the Fleece Plus flock with a trend to increased variation across years, higher fluctuations in average inbreeding coefficient in final years, and inbreeding, which was not located in the 95% confidence interval of the inbreeding in flocks simulated for an infinitesimal model. Although the Folds Plus line showed inbreeding within the 95% confidence interval of simulation inbreeding, it was located at the higher end of the confidence interval, due to natural selection. Excellent agreement was found between the simulated flocks inbreeding (6.54%) and predicted inbreeding from an adaptation of the formula of JA Woolliams, NR Wray, and R Thompson (1993) (6.44%).

scholarly journals SASRAD: An hourly-timestep solar radiation database for South Africa

2009 ◽  
Vol 20 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Daniel Ciolkosz
Keyword(s):  
South Africa ◽  
Solar Radiation ◽  
South African ◽  
Agricultural Research ◽  
Data Sets ◽  
Correction Algorithm ◽  
The South ◽  
Data Set ◽  
Agricultural Research Council ◽  
Range Correction

A methodology is presented for the correction and filling of solar radiation data at sites within South Africa, with the aim of creating a continuous, hourly-timestep dataset for multiple locations. Data from twenty sites, collected by the Agricultural Research Council, are analysed with regard to the amount of data requiring offset or multiplier adjustment, as well as the amount of bad data. A range correction algorithm is implemented based on the 90th percentile (10% exceedance) hourly irradiance, as a function of site latitude and elevation. The resulting, corrected data set is given the title: South African Solar Radiation Database (SASRAD). Comparisons are made with two other solar radiation datasets, the South African Atlas of Agrohydrology and Climatology, and a limited set of older historical data from the South African Weather Service (SAWS). Results indicate that the SASRAD dataset matches well with other datasets, with major discrepancies apparently due to problems with the other data sets, rather than the SASRAD data. The Coefficient of Multiple Determination (R2) between the Atlas and SASRAD for monthly radiation is 0.927, and the mean error between three of the SASRAD sites and the corresponding SAWS data is 1.1 MJ m-2 d-1. The fraction of data requiring correction varied from 11% to 100%, depending on the site. The range correction algorithm was successful at correcting data that had been subject to incorrect calibration, and did not remove annual trends in mean radiation levels.

Pedigree analysis of selected lines of Merino sheep. 2. Gene contributions

2002 ◽  
Vol 53 (8) ◽  
pp. 955
Author(s):  
E. Safari ◽  
J. W. James
Keyword(s):  
Agricultural Research ◽  
Pedigree Analysis ◽  
Consistent Pattern ◽  
Research Centre ◽  
Mass Selection ◽  
Selected Lines ◽  
Male And Female ◽  
Merino Sheep ◽  
Coefficients Of Variation ◽  
Standard Deviations

Four pairs of selection lines of Merino sheep consisting of 100 ewes and 5 rams were established at the Trangie Agricultural Research centre in 1951. Each line was selected (mass selection) for the appropriate character and direction (Plus or Minus) for a period of 18 years (5 generations). Pedigree analysis of these selected lines in terms of gene contributions revealed different patterns in means and standard deviations of gene contributions of male and female founders. Female founders showed a consistent pattern in all of the selected lines, with an increasing trend for the first 5-6 years in both parameters, and then stabilised. Fleece Plus showed the smallest variation, with an average coefficient of variation of 163%, whereas Folds Plus showed the highest variation with 213%. In the mean contributions, male founders showed a declining pattern for the first 5-6 years and finally stabilised. In the standard deviations, Weight and Folds flocks showed an increasing pattern in the first 1-2 years, whereas Fleece and Crimp flocks showed a declining pattern for the first 3-6 years before stabilising. Male founders showed smaller variation in mean contribution than female founders. In the Weight and Folds flocks, coefficients of variation were in the range of 55-88%, whereas in the Fleece and Crimp flocks they ranged from 98% to 156%. On average, 71% of genes were contributed by female founders and 29% by male founders. A good agreement (>90%) was found between observed and estimated inbreeding from Wray and Thompson (1990) expression in all flocks except Weight Plus and Fleece Minus lines. Effective numbers of male, female, and both male and female founders showed a consistent pattern of early fluctuation, with a trend towards increasing, and eventually stabilised in all the lines. Fleece Plus and Folds Plus lines showed the smallest and highest effective numbers for male, female, and both male and female founders, respectively, which is consistent with the pattern of observed inbreeding. During the first and second year there was a major reduction in the effective number of female founders, which is an indication of marked decrease in the genetic variability at the beginning.

The heritability of mental traits in humans: A proposal for a more coherent discussion

2003 ◽  
Vol 62 (1) ◽  
pp. 5-10 ◽  
Author(s):  
Manfred Velden
Keyword(s):  
Heritability Estimate ◽  
Environmental Variations ◽  
Heritability Estimates

It is proposed to simplify the debate about the heritability of mental traits in humans by concentrating on two crucial issues: Population specificity of heritability estimates and the relation of these estimates to the malleability of the trait to which they refer. It is demonstrated that due to vast differences between the environmental variations of populations there would have to be a heritability estimate for every imaginable population, and that a heritability estimate allows no predictions whatsoever about the malleability of the trait in question. It is therefore concluded that this field of research should be abandoned.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection

2018 ◽  
Vol 21 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Bakhtyar Sepehri ◽  
Nematollah Omidikia ◽  
Mohsen Kompany-Zareh ◽  
Raouf Ghavami
Keyword(s):  
Variable Selection ◽  
Predictive Power ◽  
Selection Method ◽  
Data Sets ◽  
Data Set ◽  
Comfa Model ◽  
Variable Selection Method

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Materials & Methods: Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Result & Conclusion: Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields.

Human Activity Recognition using Fourier Transform Inspired Deep Learning Combination Model

2019 ◽  
Vol 9 (1) ◽  
pp. 16-31
Author(s):  
Kyungkoo Jun
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Short Term Memory ◽  
Window Size ◽  
Sensor Data ◽  
Data Sets ◽  
Data Set ◽  
Proposed Model ◽  
Testing Data ◽  
Labeling Scheme

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.

scholarly journals An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

2019 ◽  
Vol 73 (8) ◽  
pp. 893-901
Author(s):  
Sinead J. Barton ◽  
Bryan M. Hennelly
Keyword(s):  
Cosmic Ray ◽  
Data Sets ◽  
Biological Cells ◽  
Statistical Classification ◽  
Signal To Noise ◽  
Multivariate Statistical ◽  
Data Set ◽  
Artefact Removal ◽  
Single Capture ◽  
Acquisition Method

Cosmic ray artifacts may be present in all photo-electric readout systems. In spectroscopy, they present as random unidirectional sharp spikes that distort spectra and may have an affect on post-processing, possibly affecting the results of multivariate statistical classification. A number of methods have previously been proposed to remove cosmic ray artifacts from spectra but the goal of removing the artifacts while making no other change to the underlying spectrum is challenging. One of the most successful and commonly applied methods for the removal of comic ray artifacts involves the capture of two sequential spectra that are compared in order to identify spikes. The disadvantage of this approach is that at least two recordings are necessary, which may be problematic for dynamically changing spectra, and which can reduce the signal-to-noise (S/N) ratio when compared with a single recording of equivalent duration due to the inclusion of two instances of read noise. In this paper, a cosmic ray artefact removal algorithm is proposed that works in a similar way to the double acquisition method but requires only a single capture, so long as a data set of similar spectra is available. The method employs normalized covariance in order to identify a similar spectrum in the data set, from which a direct comparison reveals the presence of cosmic ray artifacts, which are then replaced with the corresponding values from the matching spectrum. The advantage of the proposed method over the double acquisition method is investigated in the context of the S/N ratio and is applied to various data sets of Raman spectra recorded from biological cells.

Imbalanced Data Detection Kernel Method in Closed Systems

2013 ◽  
Vol 756-759 ◽  
pp. 3652-3658
Author(s):  
You Li Lu ◽  
Jun Luo
Keyword(s):  
Kernel Methods ◽  
Kernel Method ◽  
Imbalanced Data ◽  
Data Detection ◽  
Data Sets ◽  
System Call ◽  
Data Set ◽  
Imbalanced Data Sets ◽  
Lower Complexity ◽  
Closed Systems

Under the study of Kernel Methods, this paper put forward two improved algorithm which called R-SVM & I-SVDD in order to cope with the imbalanced data sets in closed systems. R-SVM used K-means algorithm clustering space samples while I-SVDD improved the performance of original SVDD by imbalanced sample training. Experiment of two sets of system call data set shows that these two algorithms are more effectively and R-SVM has a lower complexity.

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