Minimum resources for phenotyping morphological traits of maize (Zea mays L.) genetic resources

2008 ◽  
Vol 6 (3) ◽  
pp. 195-200 ◽  
Author(s):  
Rodomiro Ortiz ◽  
José Crossa ◽  
Ricardo Sevilla
Keyword(s):  
Phenotypic Variation ◽  
Variance Components ◽  
Maximum Likelihood Method ◽  
Zea Mays L ◽  
Plant Traits ◽  
Reproductive Traits ◽  
Likelihood Method ◽  
Vegetative Traits ◽  
Highland Maize ◽  
Northern Peru

The aim of this research was to use variance components to calculate total phenotypic variation for 12 vegetative and reproductive maize traits. A set of 59 accessions, belonging to nine Peruvian highland maize races, were grown at two consecutive planting seasons in 2 years at one inter-Andean site in northern Peru. The trial data provided a means for calculating the variance components using the restricted maximum-likelihood method. The variance components were assumed to be stable while the number of environments and replications varied to simulate phenotypic variation for each trait. The least number of environments and replications, which does not affect the precision of phenotyping, was selected for assessing each trait. Tabulated data provide the number of environments and replications that can be used as a reference for Peruvian highland trials to assess quantitative variation in plant and reproductive traits. The results suggest that fewer environments and replications are needed for reproductive than for plant traits because the former show higher heritability than vegetative traits.

scholarly journals EFFECT OF FIXED FACTORS AND ESTIMATION OF GENETIC PARAMETERS OF GROWTH TRAITS FOR MOUNTAIN KIDS

2019 ◽  
Vol 50 (6) ◽  
Author(s):  
Hermiz & Baper
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Maximum Likelihood Method ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Likelihood Method ◽  
Phenotypic Correlations ◽  
Body Weights ◽  
Genetic And Phenotypic Correlations

Body weights at birth (469), weaning (394) and at six month of age (358) for kids utilized in this study were raised at private project in Duhok governorate, Iraq during two kidding season (2016-2017) and (2017-2018). GLM within SAS programme was used to analyze the data which include the fixed effects (age of doe, year and season of kidding, sex of kid and type of birth, regression on doe weight at kidding, and the regression of later weights of kids on earlier weights) influencing the studied traits. Restricted Maximum Likelihood Method was used to estimate repeatability, heritability, genetic and phenotypic correlations after adjusting the records for fixed effects. Variance components of random effects were tested for positive definite. Overall mean of weights at birth (BWT), weaning (WWT) and 6 month of age (WT6M) were 2.92, 15.32 and 24.45 kg, respectively. Differences among groups of age of doe in all studied traits were not significant, while year of kidding and sex of kid affect all traits significantly (p<0.01). Season of kidding affect BWT and WWT significantly (P<0.01). Single born kids were heavier (P<0.01) than twins in BWT only. Regression of BWT on doe weight at kidding (0.033 kg/kg) was significant (P<0.01), while the regressions of WWT and WT6M were not significant. The regression coefficients of WWT on BWT (1.906 kg/kg) and of WT6M on WWT (0.835 kg/kg) were highly significant (P<0.01). Repeatability estimates for BWT, WWT and WT6M were 0.47, 0.45 and 0.35, respectively; on the same order the estimates of heritability were 0.41, 0.61 and 0.79. Genetic correlations between BWT with each of WWT (0.45) and WT6M (0.55), and between WWT and WT6M (0.68) were highly significant. All phenotypic correlations between each pair of body weights were higher than genetic correlations and ranged between 0.48 and 0.73.

scholarly journals New Quality-Range-Setting Method Based on Between- and Within-Batch Variability for Biosimilarity Assessment

2021 ◽  
Vol 14 (6) ◽  
pp. 527
Author(s):  
Alexis Oliva ◽  
Matías Llabrés
Keyword(s):  
Quality Control ◽  
Variance Components ◽  
Maximum Likelihood Method ◽  
Drug Product ◽  
Statistical Quality Control ◽  
Likelihood Method ◽  
Reference Drug ◽  
Statistical Quality ◽  
Manufacture Process ◽  
Intended Use

Analytical biosimilarity assessment relies on two implicit conditions. First, the analytical method must meet a set of requirements known as fit for intended use related to trueness and precision. Second, the manufacture of the reference drug product must be under statistical quality control; i.e., the between-batch variability is not larger than the expected within-batch variability. In addition, the quality range (QR) method is based on one sample per batch to avoid biased standard deviations in unbalanced studies. This, together with the small number of reference drug product batches, leads to highly variable QR bounds. In this paper, we propose to set the QR bounds from variance components estimated using a two-level nested linear model, accounting for between- and within-batch variances of the reference drug product. In this way, the standard deviation used to set QR is equal to the square root of the sum of between-batch variance plus the within-batch variance estimated by the maximum likelihood method. The process of this method, which we call QRML, is as follows. First, the condition of statistical quality control of the manufacture process is tested. Second, confidence intervals for QR bounds lead to an analysis of the reliability of the biosimilarity assessment. Third, after analyzing the molecular weight and dimer content of seven batches of a commercial bevacizumab drug product, we concluded that the QRML method was more reliable than QR.

Heritability of some meat quality traits in ducks

2016 ◽  
Vol 12 (4) ◽  
pp. 9-17 ◽  
Author(s):  
Magdalena Graczyk ◽  
Ewa Gornowicz ◽  
Sebastian Mucha ◽  
Mirosław Lisowski ◽  
Bartosz Grajewski ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Meat Quality ◽  
Variance Components ◽  
Maximum Likelihood Method ◽  
Computer Software ◽  
Likelihood Method ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Pekin Ducks ◽  
General Appearance

The aim of the study was to estimate the heritability coefficients of fourteen meat quality traits in ducks. The study was conducted on 387 individuals of an F2 cross of Polish and French Pekin ducks. The following traits were examined in the breast (BM) and leg (LM) muscles: electrical conductivity at 15 minutes post-slaughter (BMEC15 and LMEC15), pH at 24 hours post-slaughter (BMpH24 and LMpH24), thermal drip (TDBM and TDLM) and lightness (L*) (LBM and LLM). Additionally, sensory traits were evaluated in the raw breast (BM) and leg (LM) muscles: colour (CRMB and CRLM), odour (ORBM and ORLM) and general appearance (GARBM and GARLM). Estimators of the variance components were obtained by the Restricted Maximum Likelihood method, using ASReml computer software. In general, varied heritability estimates were obtained: 0.01 (BMEC15), 0.16 (LMEC15), 0.01 (BMpH24), 0.06 (LMpH24), 0.07 (TDBM), 0.06 (TDLM), 0.08 (LBM), 0.07 (LLM), 0.08 (CRBM), 0.73 (CRLM), 0.11 (ORBM), 0.92 (ORLM), 0.24 (GARBM), and 0.40 (GARLM).

scholarly journals Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders

2020 ◽  
Author(s):  
Muhammad Ammar Malik ◽  
Tom Michoel
Keyword(s):  
Gene Expression ◽  
Maximum Likelihood ◽  
Latent Variables ◽  
Variance Components ◽  
Maximum Likelihood Method ◽  
Likelihood Function ◽  
Restricted Maximum Likelihood ◽  
Likelihood Method ◽  
Confounding Factors ◽  
Gradient Based

AbstractLinear mixed modelling is a popular approach for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors are known, estimating simultaneously the contribution of known and latent variance components in linear mixed models is a challenge that has so far relied on numerical gradient-based optimizers to maximize the likelihood function. This is unsatisfactory because the resulting solution is poorly characterized and the efficiency of the method may be suboptimal. Here we prove analytically that maximumlikelihood latent variables can always be chosen orthogonal to the known confounding factors, in other words, that maximum-likelihood latent variables explain sample covariances not already explained by known factors. Based on this result we propose a restricted maximum-likelihood method which estimates the latent variables by maximizing the likelihood on the restricted subspace orthogonal to the known confounding factors, and show that this reduces to probabilistic PCA on that subspace. The method then estimates the variance-covariance parameters by maximizing the remaining terms in the likelihood function given the latent variables, using a newly derived analytic solution for this problem. Compared to gradient-based optimizers, our method attains equal or higher likelihood values, can be computed using standard matrix operations, results in latent factors that don’t overlap with any known factors, and has a runtime reduced by several orders of magnitude. We anticipate that the restricted maximum-likelihood method will facilitate the application of linear mixed modelling strategies for learning latent variance components to much larger gene expression datasets than currently possible.

scholarly journals Rapid divergence in vegetative morphology of a wind-pollinated plant between populations at contrasting densities

2021 ◽  
Author(s):  
Jeanne Tonnabel ◽  
Patrice David ◽  
John Pannell
Keyword(s):  
Plant Density ◽  
Plant Traits ◽  
Pollen Dispersal ◽  
Reproductive Traits ◽  
High Density ◽  
Source Population ◽  
Sexually Dimorphic ◽  
Low Density ◽  
Potential Conflict ◽  
Vegetative Traits

Plant sexual dimorphism is thought to evolve in response to sex-specific selection associated with competition for access to mates or resources, both of which will often be density-dependent. In wind-pollinated plants in particular, vegetative traits can have an important influence on both resource acquisition and the pollen dispersal and receipt, with potential conflict between these two components of fitness. We evaluated the role of plant density in shaping plant traits by measuring evolutionary responses in experimental populations of the sexually dimorphic wind-pollinated plant Mercurialis annua. After three generations of evolution, we observed divergence between high- and low-density populations in several vegetative traits, whereas there was no divergence for reproductive traits. A reversal in the direction of sexually dimorphic traits expressed in young plants evolved in both low- and high-density populations compared to the original population (stored as seeds). Compared to the source population, males at high density evolved to be taller when young, whereas at low density young females tended to become smaller. These results demonstrate that a simple change in plant density can induce rapid, age-dependent and sex-specific evolution in the ontogeny of vegetative organs, and illustrates the power of experimental evolution for investigating plant trait evolution.

scholarly journals Phenotypic variation of flowering and vegetative morphological traits along the distribution for the endemic species Yucca capensis (Agavaceae)

2015 ◽  
Vol 93 (4) ◽  
pp. 765 ◽  
Author(s):  
Maria Clara Arteaga ◽  
Rafael Bello-Bedoy ◽  
José Luis León-de la Luz ◽  
José Delgadillo ◽  
Reymundo Dominguez
Keyword(s):  
Endemic Species ◽  
Phenotypic Variation ◽  
Abiotic Factors ◽  
Reproductive Traits ◽  
Geographic Range ◽  
Leaf Length ◽  
Stem Length ◽  
Coefficients Of Variation ◽  
Vegetative Traits ◽  
Plant Length

<p class="p1"><span class="s1">Phenotypic variation across the geographic range of a species depends upon genetic differences within and between populations as well as environmental heterogeneity. Estimating the variation in morphological and reproductive traits and determining the influence of abiotic factors on the expression of phenotype is particularly important in endemic species as a means of inferring their response to different environmental scenarios. This study analyzes the interpopulation variation in oral and vegetative traits of <em>Yucca capensis </em>Lenz and their relation to altitude and precipitation. At 2 different sites total plant length, stem length, stem circumference, rosette length, rosette diameter, leaf length and leaf width were measured and the number of plants with inflorescences and fruits was recorded. The results showed higher coefficients of variation for plant length, stem length and rosette length and lower coefficients of variation for leaf length and width. All of the vegetative traits differed significantly between sites. It was found that 31 % and 12 % of the plants produced inflorescences and fruits respectively and inflorescence production differed between sites, presenting a positive relation with average annual precipitation. This study shows that there is large phenotypic variation in vegetative traits and that levels of rainfall have a clear influence on the production of reproductive structures throughout the geographic range of the endemic species <em>Y. capensis</em>.</span></p>

scholarly journals Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders

2021 ◽  
Author(s):  
Muhammad Ammar Malik ◽  
Tom Michoel
Keyword(s):  
Gene Expression ◽  
Maximum Likelihood ◽  
Random Effects ◽  
Latent Variables ◽  
Variance Components ◽  
Maximum Likelihood Method ◽  
Likelihood Function ◽  
Restricted Maximum Likelihood ◽  
Likelihood Method ◽  
Confounding Factors

Abstract Random effects models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors are known, estimating simultaneously the contribution of known and latent variance components in random effects models is a challenge that has so far relied on numerical gradient-based optimizers to maximize the likelihood function. This is unsatisfactory because the resulting solution is poorly characterized and the efficiency of the method may be suboptimal. Here we prove analytically that maximum-likelihood latent variables can always be chosen orthogonal to the known confounding factors, in other words, that maximum-likelihood latent variables explain sample covariances not already explained by known factors. Based on this result we propose a restricted maximum-likelihood method which estimates the latent variables by maximizing the likelihood on the restricted subspace orthogonal to the known confounding factors, and show that this reduces to probabilistic PCA on that subspace. The method then estimates the variance-covariance parameters by maximizing the remaining terms in the likelihood function given the latent variables, using a newly derived analytic solution for this problem. Compared to gradient-based optimizers, our method attains greater or equal likelihood values, can be computed using standard matrix operations, results in latent factors that don’t overlap with any known factors, and has a runtime reduced by several orders of magnitude. Hence the restricted maximum-likelihood method facilitates the application of random effects modelling strategies for learning latent variance components to much larger gene expression datasets than possible with current methods.

The co-responsibility of mass and environment in the formation of lenticular galaxies

2020 ◽  
Vol 15 (S359) ◽  
pp. 173-174
Author(s):  
A. Cortesi ◽  
L. Coccato ◽  
M. L. Buzzo ◽  
K. Menéndez-Delmestre ◽  
T. Goncalves ◽  
...  
Keyword(s):  
Active Galactic Nuclei ◽  
Maximum Likelihood Method ◽  
Spiral Galaxies ◽  
Galactic Nuclei ◽  
Rotation Velocity ◽  
Elliptical Galaxies ◽  
Likelihood Method ◽  
Data Set ◽  
Lenticular Galaxies ◽  
Galaxies Kinematics

AbstractWe present the latest data release of the Planetary Nebulae Spectrograph Survey (PNS) of ten lenticular galaxies and two spiral galaxies. With this data set we are able to recover the galaxies’ kinematics out to several effective radii. We use a maximum likelihood method to decompose the disk and spheroid kinematics and we compare it with the kinematics of spiral and elliptical galaxies. We build the Tully- Fisher (TF) relation for these galaxies and we compare with data from the literature and simulations. We find that the disks of lenticular galaxies are hotter than the disks of spiral galaxies at low redshifts, but still dominated by rotation velocity. The mechanism responsible for the formation of these lenticular galaxies is neither major mergers, nor a gentle quenching driven by stripping or Active Galactic Nuclei (AGN) feedback.

scholarly journals Reproductive traits and floral visitors of Aechmea distichantha plants growing in different habitats of a South American xerophytic forest

Rodriguésia ◽  
2018 ◽  
Vol 69 (2) ◽  
pp. 385-396 ◽  
Author(s):  
Rodrigo M. Freire ◽  
Ignacio M. Barberis ◽  
José L. Vesprini
Keyword(s):  
Reproductive Traits ◽  
Climatic Conditions ◽  
Similar Proportion ◽  
South American ◽  
The Sun ◽  
Carpenter Bee ◽  
Carpenter Bees ◽  
Vegetative Traits ◽  
Floral Visitors ◽  
Almost All

Abstract Aechmea distichantha, a widely-distributed facultative epiphytic bromeliad species, is present from rainforests to xerophytic forests. At its southernmost distribution (Humid Chaco) it grows in the understory and forest edges. This animal-pollinated bromeliad shows high phenotypic plasticity on its vegetative traits, but there is no information about plasticity on its reproductive traits. Infructescences from shade plants were heavier, had longer rachis, more spikelets, higher number of fruits/spikelet and higher number of seeds/fruit than those from sun plants, but they presented similar number of open flowers. The number of visitation events was similar in both habitats, but more flowers were visited in the sun than in the shade. Flowers were visited by seven species (six insects and one hummingbird). In the sun, the carpenter bee was the most frequent visitor and visited almost all flowers, whereas in the shade different species of visitors attained similar proportion of visits and number of visited flowers. Despite visitation events were similar in both habitats, plants growing in the shade set more seeds/fruit than plants growing in the sun. The higher proportion of visits accomplished by carpenter bees compared to hummingbirds is probably a consequence of the climatic conditions in the austral location of these populations.

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