Average Growth Curve Research Articles

Growth performance of yearling F1 progeny of different crossbred beef cattle

Bangladesh has a great demand of beef but it has been facing demand and supply mismatches due to insufficient production and supply of beef, low carcass yield of native cattle and recent no-cattle export policy of a long bordered neighboring country. Thus, the present work was undertaken with an objective to develop market beef cattle of average >150 Kg carcass weight by 24 months with an average FCR of <6.50 under on farm feeding and management condition. Aiming at developing breeding bulls the native dams of BCB-1 (BLRI Cattle Breed 1) were inseminated with the imported frozen semen of Brahman, Simmental, Charolais and Limousin. The crossbred progeny of different assorted F1 genotypes were being selected and their production and breeding performance were evaluated and compared with BCB-1. All pregnant (> 6 months of gestation period) cows were in pre-natal care, and all calves were raised in a single plane of nutrition and management. All crossbred progeny performed better than BCB-1 in terms of live weights and average daily gains. Among the crossbreds, Charolais×BCB-1 had the highest (p<0.001) birth weight (27.5±1.52 kg) followed by Brahman×BCB-1 (24.1±1.23), Simmental×BCB-1 (21.9±1.78), Limousin×BCB-1 (19.8±1.39) and BCB-1×BCB-1 (18.4±1.09), and the genotypes differences were highly significant (p<0.001). In average growth curve, Simmental cross grew faster followed by Charolais, Limousin, Brahman crosses and purebred BCB-1. The genotype×environment interaction was only observed in birth weight. Purebred BCB-1 had the lowest daily DM intake and showed the lowest FCR in all ages compare to other crosses. Calf scour and alopecia occurred in all genotypes. In this breeding program, calf mortality was found as 5.26%. Simmental×BCB-1 is performing as the best among the five genotypes in terms of growth up to 12 month of age.Bang. J. Anim. Sci. 2017. 46 (2): 82-87

Sum Scores in Twin Growth Curve Models: Practicality Versus Bias.

To study behavioral or psychiatric phenotypes, multiple indices of the behavior or disorder are often collected that are thought to best reflect the phenotype. Combining these items into a single score (e.g. a sum score) is a simple and practical approach for modeling such data, but this simplicity can come at a cost in longitudinal studies, where the relevance of individual items often changes as a function of age. Such changes violate the assumptions of longitudinal measurement invariance (MI), and this violation has the potential to obfuscate the interpretation of the results of latent growth models fit to sum scores. The objectives of this study are (1) to investigate the extent to which violations of longitudinal MI lead to bias in parameter estimates of the average growth curve trajectory, and (2) whether absence of MI affects estimates of the heritability of these growth curve parameters. To this end, we analytically derive the bias in the estimated means and variances of the latent growth factors fit to sum scores when the assumption of longitudinal MI is violated. This bias is further quantified via Monte Carlo simulation, and is illustrated in an empirical analysis of aggression in children aged 3-12years. These analyses show that measurement non-invariance across age can indeed bias growth curve mean and variance estimates, and our quantification of this bias permits researchers to weigh the costs of using a simple sum score in longitudinal studies. Simulation results indicate that the genetic variance decomposition of growth factors is, however, not biased due to measurement non-invariance across age, provided the phenotype is measurement invariant across birth-order and zygosity in twins.

Isotope geochemistry of Mississippi Valley Type stratabound F-Ba-(Pb-Zn) ores of Hammam Zriba (Province of Zaghouan, NE Tunisia)

The Hammam Zriba F-Ba-(Zn-Pb) ore deposit in the Province of Zaghouan in north-eastern Tunisia is hosted in the shallow dipping unconformity between green marls with chalky biomicritic limestones of Campanian age and Uppermost Jurassic carbonates. The mineralization consists mainly of fluorite and barite with minor sphalerite and galena. Calcite is the main gangue mineral. Two types of Zn-Pb sulfides can be distinguished according to the geometry of the orebodies, i.e., lenticular or stratiform ores, intra-karstic fillings. Sulfur isotope compositions (δ34S) of barite range from 14.7 to 17.2‰, indicating that sulfur was derived from Triassic evaporites and the higher ones (19–25.7‰) are due to reservoir effect associated with thermo-chemical sulfate reduction (TSR) or bacterial sulfate reduction (BSR) under conditions of restricted sulfate supply. δ34S of galena and sphalerite in lenticluar and intra-karstic orebodies range from −13.8 to 2.1‰, and could be explained by multiple sources of reduced sulfur: Triassic evaporites, diagenetic primary sulfides as well as sulfur from organic matter. Both TSR and BSR as potential contributors of sulfur are needed for sulfide precipitation. Lead isotope compositions of galena exhibit very similar: 206Pb/204Pb (18.858–18.876), 207Pb/204Pb (15.667–15.684), and 208Pb/204Pb (38.680–38.747) ratios, and plot between the upper crust and orogene average growth curves, reflecting involvement of a mixing and subsequent homogenization of Pb isotopic compositions of different source Pb reservoirs. The underlying Paleozoic basement rocks were the plausible source of metals. The economic ore (fluorite F1) mineralization was formed during the Eocene-Miocene compressional phase. During this deformation phase, deep-seated basinal brines have been circulated as hydrothermal fluids that have interacted with the Paleozoic rocks, thereby leaching metals, and have been channelized through subsidiary faults associated with the major regional NE–SW-trending deep-seated Zaghouan-Ressas fault. Hydrothermal fluids then migrated to the site of deposition where they got mixed with shallow, cooler, metal-depleted, TSR- and BSR-derived sulfur-rich fluids, which triggered the precipitation of the ores.

Regularized quantile regression for SNP marker estimation of pig growth curves

BackgroundGenomic growth curves are generally defined only in terms of population mean; an alternative approach that has not yet been exploited in genomic analyses of growth curves is the Quantile Regression (QR). This methodology allows for the estimation of marker effects at different levels of the variable of interest. We aimed to propose and evaluate a regularized quantile regression for SNP marker effect estimation of pig growth curves, as well as to identify the chromosome regions of the most relevant markers and to estimate the genetic individual weight trajectory over time (genomic growth curve) under different quantiles (levels).ResultsThe regularized quantile regression (RQR) enabled the discovery, at different levels of interest (quantiles), of the most relevant markers allowing for the identification of QTL regions. We found the same relevant markers simultaneously affecting different growth curve parameters (mature weight and maturity rate): two (ALGA0096701 and ALGA0029483) for RQR(0.2), one (ALGA0096701) for RQR(0.5), and one (ALGA0003761) for RQR(0.8). Three average genomic growth curves were obtained and the behavior was explained by the curve in quantile 0.2, which differed from the others.ConclusionsRQR allowed for the construction of genomic growth curves, which is the key to identifying and selecting the most desirable animals for breeding purposes. Furthermore, the proposed model enabled us to find, at different levels of interest (quantiles), the most relevant markers for each trait (growth curve parameter estimates) and their respective chromosomal positions (identification of new QTL regions for growth curves in pigs). These markers can be exploited under the context of marker assisted selection while aiming to change the shape of pig growth curves.

Modelagem do crescimento de Cryptomeria japonica por análise de tronco parcial

Este trabalho objetivou avaliar o padrão de crescimento bem com descrever a distribuição probabilística do incremento corrente anual em diâmetro de Cryptomeria japonica (L.F.) D. Don. em povoamento instalado no município de Rio Negro, PR. Foram amostradas 20 árvores em um plantio com 34 anos de idade e espaçamento 3 m x 2 m. Foram coletados discos a 1,3 m do solo (DAP) para a realização da análise de tronco parcial de cada árvore. A série de crescimento em diâmetro sem casca obtida foi utilizada para gerar as curvas de crescimento acumulado médio para a variável DAP (cm), de incremento médio anual (IMA) e incremento corrente anual (ICA). A partir dos dados de ICA, avaliou-se a distribuição de frequência desses por meio de funções de densidade de probabilidade (fdp’s). O ICA do DAP foi de 0,78 cm ano-1 e a idade de encontro das curvas de ICA e IMA ocorreu entre o 7° e o 8° ano. Identificou-se que cerca de 43% dos incrementos da espécie concentram-se até 0,5 cm. Os resultados obtidos são úteis para a definição de estratégias para o manejo da espécie em regiões semelhantes ao local de estudo, definindo-se, por exemplo, idades de intervenção silvicultural, como o desbaste.

Growth curve of Repartida goats reared in the Caatinga region, Brazil

This work aimed to determine which non-linear model (Brody, Gompertz, logistic, von Bertalanffy or Richards) best represents the average growth curve of goats, in addition to evaluating the effect of the environment. The weight data of 40 Repartida goats reared in the Brazil Caatinga were included in this study. Weight data was collected every 30 days from birth until 270 days of age. The parameters of the models (A, mature body weight; B, constant of integration; k, maturation rate; m, inflection point) were estimated using the NLIN procedure of SAS. The logistic model showed a slightly higher average fit in comparison to the other models. The absolute growth rate suggests that the maximum growth rate was reached early. The effect of the contemporary groups was significant (P < 0.05), but only for the estimated k parameter. The estimated correlation between the A and k parameters was significant and negative, indicating a lower probability of a high body weight in adulthood. Goats of the Repartida ecotype are characterized by their high birth weight and low weight at maturity, which combined with the nutritional deficit, suggests that these animals have adapted to the adverse conditions of the Brazilian Caatinga region.

Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep.

Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied.

Comparação de modelos não lineares para descrever o crescimento de fêmeas leiteiras mêstiças taurino x zebu no Nordeste do Brasil

Objetivou-se comparar as funções matemáticas de Brody (BD), Von Bertalanffy (VB), Logístico (LG) e Gompertz (GP), identificar a que melhor descreve o crescimento, estimar componentes da curva (peso assintótico: a; índice de maturidade: k) e caracterizar o formato (ponto de inflexão: PI; taxa de crescimento instantâneo: TCI) da curva média de crescimento de fêmeas mestiças (Bos taurus x Bos indicus) em sistema de produção semi-extensivo. Foram utilizados 537 registros de pesagens realizadas em intervalos de 30 dias durante o período de 2010 a 2012, pertencentes a três propriedades. Os valores de a e k foram, respectivamente, 1.982 kg e 0,000286 kg/dia para BD; 550,50 kg e 0,00232 kg/dia para VB; 405,20 kg e 0,006374 kg/dia para LG e 479,70 kg e 0,00353 kg/dia para GP. Baseado nos critérios estatísticos observou-se que os modelos VB, BD e LG apresentaram os maiores (>0,74) coeficientes de determinação ajustados (Ra²), e menor valor do resíduo foi encontrado no modelo GP (4.918,38), indicando que todos os modelos se adequaram estatisticamente aos dados observados. Para os critérios de interpretação biológica, os modelos VB (8,48 meses) e LG (9,4 meses) apresentaram PI mais próximos do observado, o modelo VB (12,04-0,535 kg/mês) foi o único capaz de descrever a TCI, e os demais modelos subestimaram o incremento de peso corporal. O modelo de VB apresentou o melhor ajuste aos dados de crescimento de fêmeas mestiças com alta variabilidade genética em sistema semi-extensivo.

Transitional modeling of experimental longitudinal data with missing values

Longitudinal categorical data are often collected using an experimental design where the interest is in the differential development of the treatment group compared to the control group. Such differential development is often assessed based on average growth curves but can also be based on transitions. For longitudinal multinomial data we describe a transitional methodology for the statistical analysis based on a distance model. Such a distance approach has two advantages compared to a multinomial regression model: (1) sparse data can be handled more efficiently; (2) a graphical representation of the model can be made to enhance interpretation. Within this approach it is possible to jointly model the observations and missing values by adding a new category to the response variable representing the missingness condition. This approach is investigated in a Monte Carlo simulation study. The results show this is a promising way to deal with missing data, although the mechanism is not yet completely understood in all cases. Finally, an empirical example is presented where the advantages of the modeling procedure are highlighted.

A powerful phenotype for gene-finding studies derived from trajectory analyses of symptoms of anxiety and depression between age seven and 18.

To investigate the utility of longitudinal data in genetic analyses of symptoms of anxiety and depression, we assessed individual differences between age 7 and 18 using growth mixture models, and investigated the genetic and non-genetic factors contributing to the trajectories. Mothers of 7,706 girl and 7,418 boy twins from the Netherlands Twin Register rated the anxious depression scale (SxAnxDep) of the Child Behavior Check List (CBCL) at age 7, 10, and 12 years. Two thousand seven hundred and six girl and 1,856 boy twins completed the Youth Self Report (YSR) at age 14, 16, and 18. While individual trajectories varied considerably, these differences were largely idiosyncratic and could not be grouped into separate latent classes with class-specific average growth curves. The intercept, which reflects the individuals' baseline level of SxAnxDep across time, explained 55-58% of the total phenotypic variance. The slope factor, which captures a common average trend over time, did not explain variance in the phenotype. This finding also underlines the high level of idiosyncrasy of trajectories that lack a common longitudinal structure. The analyses of twin data showed that the random intercept factor of SxAnxDep during childhood and during adolescence is considerably more heritable than the observations at any single age, namely between 60% and 84%. One explanation is that different factors contribute to the level of symptoms of anxiety and depression at any given time point, including temporary events and emotions. When considering baseline stability, these temporary influences average out, with the result of a more reliable and more heritable phenotype. © 2015 Wiley Periodicals, Inc.

Abstract P085: Infant Weight and Length Trajectories Have Different Impacts on Body Composition at Age 3

Introduction: Rapid infant weight gain has been linked with higher childhood body mass index (BMI) and risk of obesity. However, because BMI cannot distinguish lean from fat mass, the role of infant weight or length trajectories on childhood body composition is unclear. Hypothesis: This study aimed to evaluate how specific aspects of infant growth trajectories are associated with fat mass, lean mass and % body fat at age 3. Methods: Total 323 children age 3 y (46% female, 20% African-American) had body composition measured by dual-energy x-ray absorptiometry, and weight and length measurements from birth to age 2 y from pediatrician growth charts. Growth trajectories were characterized using the SuperImposition by Translation And Rotation (SITAR) model. This technique estimates an average growth curve with random effects that allow individual growth curves to shift up or down (size), shift right or left on the age axis (tempo) or rotate to steepen/flatten the growth curve (velocity). Tempo did not improve model fit so was excluded. Size and velocity parameters for weight and length trajectories were regressed against fat mass (FM), lean mass (LM) and % body fat measurements at age 3. Results: On average, girls had higher FM (3.9 vs. 3.4 kg) and lower LM (8.8 vs. 9.5 kg) than boys. Adjusting for sex, LM at age 3 was significantly higher with greater weight velocity and with longer length size between ages 0-2 (Table), but were not related to length velocity or weight size. Adjusting for sex, higher FM was seen for those with higher weight size between ages 0-2, but was not related to either weight or length velocities. Percent body fat at age 3 was associated with both larger weight size and shorter length size between 0-2 years of age, but not with either growth velocities. Conclusions: Weight and length size and velocity differ in their impact on children’s body composition by age 3. This study suggests that faster early weight gain (higher weight velocity) and longer lengths but not higher overall weight may lead to leaner body composition by age 3.

The Effect of Recombinant Human Iduronate-2-Sulfatase (Idursulfase) on Growth in Young Patients with Mucopolysaccharidosis Type II

Mucopolysaccharidosis type II (MPS II; Hunter syndrome) is an X-linked, recessive, lysosomal storage disorder caused by deficiency of iduronate-2-sulfatase. Early bone involvement leads to decreased growth velocity and short stature in nearly all patients. Our analysis aimed to investigate the effects of enzyme replacement therapy (ERT) with idursulfase (Elaprase) on growth in young patients with mucopolysaccharidosis type II. Analysis of longitudinal anthropometric data of MPS II patients (group 1, n = 13) who started ERT before 6 years of age (range from 3 months to 6 years, mean 3.6 years, median 4 years) was performed and then compared with retrospective analysis of data for MPS II patients naïve to ERT (group 2, n = 50). Patients in group 1 received intravenous idursulfase at a standard dose of 0.58 mg/kg weekly for 52–288 weeks. The course of average growth curve for group 1 was very similar to growth pattern in group 2. The average value of body height in subsequent years in group 1 was a little greater than in group 2, however, the difference was not statistically significant. In studied patients with MPS II, idursulfase did not appear to alter the growth patterns.

Jackknife-corrected parametric bootstrap estimates of growth rates in bivalve mollusks using nearest living relatives

Quantitative estimates of growth rates can augment ecological and paleontological applications of body-size data. However, in contrast to body-size estimates, assessing growth rates is often time-consuming, expensive, or unattainable. Here we use an indirect approach, a jackknife-corrected parametric bootstrap, for efficient approximation of growth rates using nearest living relatives with known age–size relationships. The estimate is developed by (1) collecting a sample of published growth rates of closely related species, (2) calculating the average growth curve using those published age–size relationships, (3) resampling iteratively these empirically known growth curves to estimate the standard errors and confidence bands around the average growth curve, and (4) applying the resulting estimate of uncertainty to bracket age–size relationships of the species of interest. This approach was applied to three monophyletic families (Donacidae, Mactridae, and Semelidae) of mollusk bivalves, a group characterized by indeterministic shell growth, but widely used in ecological, paleontological, and geochemical research. The resulting indirect estimates were tested against two previously published geochemical studies and, in both cases, yielded highly congruent age estimates. In addition, a case study in applied fisheries was used to illustrate the potential of the proposed approach for augmenting aquaculture management practices. The resulting estimates of growth rates place body size data in a constrained temporal context and confidence intervals associated with resampling estimates allow for assessing the statistical uncertainty around derived temporal ranges. The indirect approach should allow for improved evaluation of diverse research questions, from sustainability of industrial shellfish harvesting to climatic interpretations of stable isotope proxies extracted from fossil skeletons.

Early life growth trajectories and future risk for overweight

Objective:Standard approaches have found that rapid growth during the first 2 years of life is a risk factor for overweight in later childhood. Our objective was to test whether growth velocity, independent of concurrent size, was associated with overweight using a nonlinear random-effects model that allows for enhanced specifications and estimations.Methods:Longitudinal data from a birth cohort in Mexico (n=586) were used to estimate growth trajectories over 0–24 months for body mass index (BMI), length and weight using the SuperImposition by Translation and Rotation (SITAR) models. The SITAR models use a nonlinear random-effects model to estimate an average growth curve for BMI, length and weight and each participant's deviation from this curve on three dimensions—size, velocity and timing of peak velocity. We used logistic regression to estimate the association between overweight status at 7–9 years and size, velocity and timing of BMI, length and weight trajectories during 0–24 months. We tested whether any association between velocity and overweight varied by relative size during 0–24 months or birth weight.Results:SITAR models explained the majority of the variance in BMI (73%), height (86%) and weight (85%) between 0–24 months. When analyzed individually, relative BMI/length/weight (size) and BMI/length/weight velocity during 0–24 months were each associated with increased odds of overweight in late childhood. Associations for timing of peak velocity varied by anthropometric measure. However, in the mutually adjusted models, only relative BMI/length/weight (size) remained statistically significant. We found no evidence that any association between velocity and overweight varied by size during 0–24 months or birth weight.Conclusions:After mutual adjustment, size during 0–24 months of life (as opposed to birth size), but not velocity or timing of peak velocity, was most consistently associated with overweight in later childhood.

Modeling physical growth using mixed effects models

This article demonstrates the use of mixed effects models for characterizing individual and sample average growth curves based on serial anthropometric data. These models are advancement over conventional general linear regression because they effectively handle the hierarchical nature of serial growth data. Using body weight data on 70 infants in the Born in Bradford study, we demonstrate how a mixed effects model provides a better fit than a conventional regression model. Further, we demonstrate how mixed effects models can be used to explore the influence of environmental factors on the sample average growth curve. Analyzing data from 183 infant boys (aged 3-15 months) from rural South India, we show how maternal education shapes infant growth patterns as early as within the first 6 months of life. The presented analyses highlight the utility of mixed effects models for analyzing serial growth data because they allow researchers to simultaneously predict individual curves, estimate sample average curves, and investigate the effects of environmental exposure variables.

Early life growth trajectories and future risk for overweight

Using a newly developed statistical technique, our objective was to test whether key aspects of growth trajectories between 0–24 months of age, such as size, velocity, and timing of peak velocity, were independently associated with overweight in late childhood. We used data from a birth cohort in Mexico (n=586) and the SuperImposition by Translation and Rotation (SITAR) method to estimate infant/childhood (0–24 months) growth trajectories for BMI, height, and weight. The SITAR method uses a nonlinear random‐effects model to estimate the average growth curve and each individual's deviation from this average curve on three dimensions—size, velocity, and timing of peak velocity. In separate models for each of the anthropometric measures (BMI, height, and weight), logistic regression estimated the association between overweight in late childhood and size, velocity, and timing of the BMI/height/weight trajectory. In crude models, relative BMI/height/weight (size) and BMI/height/weight velocity during 0–24 months were each associated with increased odds of overweight. In the mutually‐adjusted models, only relative BMI/height/weight (size), but not velocity, remained statistically significant. We found no evidence that the association between velocity and overweight varied by size. These results are not consistent with the hypothesis that growth velocity in infancy programs future risk for overweight.Grant Funding Source : This work was supported by pilot funds from the Berkeley Population Center NICHD R21 (HD056581).

Modeling the growth rate and lag time of different strains of Salmonella enterica and Listeria monocytogenes in ready-to-eat lettuce

The growth parameters (growth rate, μ and lag time, λ) of three different strains each of Salmonella enterica and Listeria monocytogenes in minimally processed lettuce (MPL) and their changes as a function of temperature were modeled. MPL were packed under modified atmosphere (5% O2, 15% CO2 and 80% N2), stored at 7–30 °C and samples collected at different time intervals were enumerated for S. enterica and L. monocytogenes. Growth curves and equations describing the relationship between μ and λ as a function of temperature were constructed using the DMFit Excel add-in and through linear regression, respectively. The predicted growth parameters for the pathogens observed in this study were compared to ComBase, Pathogen modeling program (PMP) and data from the literature. High R2 values (0.97 and 0.93) were observed for average growth curves of different strains of pathogens grown on MPL. Secondary models of μ and λ for both pathogens followed a linear trend with high R2 values (>0.90). Root mean square error (RMSE) showed that the models obtained are accurate and suitable for modeling the growth of S. enterica and L. monocytogenes in MP lettuce. The current study provides growth models for these foodborne pathogens that can be used in microbial risk assessment.

Modeling of average growth curve in Santa Ines sheep using random regression models

Polynomial functions of age of different orders were evaluated in the modeling of the average growth trajectory in Santa Ines sheep in random regression models. Initially, the analyses were performed not considering the animal effect. Subsequently, the random regression analyses were performed including the random effects of the animal and its mother (genetic and permanent environment). The linear fit was lower, and the other orders were similar until near 100 days of age. The cubic function provided the closest fit of the observed averages, mainly at the end of the curve. Orders superior to this one tended to present incoherent behavior with the observed weights. The estimated direct heritabilities, considering the linear fit, were higher to those estimated by considering other functions. The changes in animal ranking based on predicted breeding values using linear fit and superior orders were small; however, the difference in magnitude of the predicted breeding values was higher, reaching values 77% higher than those obtained with the cubic function. The cubic polynomial function is efficient in describing the average growth curve.

New age (ca. 2970 Ma), mantle source composition and geodynamic constraints on the Archean Fiskenæsset anorthosite complex, SW Greenland

The Archean Fiskenæsset Complex, SW Greenland, consists of an association of ca. 550-meter-thick layered anorthosite, leucogabbro, gabbro, and ultramafic rocks (peridotite, pyroxenite, dunite, hornblendite). The complex was intruded by tonalite, trondhjemite, and granodiorite (TTG) sheets (now orthogneisses) during thrusting that was followed by several phases of isoclinal folding. The trace element systematics of the Fiskenæsset Complex and associated volcanic rocks are consistent with a supra-subduction zone geodynamic setting. The Fiskenæsset anorthosites, leucogabbros, gabbros and ultramafic rocks collectively yield an Sm–Nd errorchron age of 2973 ± 28 Ma (MSWD = 33), with an average initial ε Nd = + 3.3 ± 0.7, consistent with a long-term depleted mantle source. Regression of Pb isotope data define an age of 2945 ± 36 Ma (MSWD = 44); and the regression line intersects the average growth curve at 3036 Ma. Slightly lower Pb–Pb errorchron age is interpreted as reflecting partial disturbance of the U–Pb system in gabbros, leucogabbros and ultramafic rocks during intrusion of TTGs. Complex internal structures in zircons from orthogneisses reveal several episodes of zircon growth and recrystallization taking place between ca. 3200 and 2650 Ma. Zircon ages peak at about 3200, 3100, 3000, 2950, 2820, and 2750 Ma. The 3200–3000 Ma zircon cores are interpreted as inherited xenocrysts from older reworked crustal rocks. 2950 Ma is considered as an approximate intrusion age of sampled TTGs. The 2940–2650 Ma ages are attributed to metamorphic overgrowth and recrystallization in response to multiple tectonothermal events that affected the Fiskenæsset region. On the basis of recently published trace element data, and new Nd and Pb isotope and U–Pb zircon age data, a three-stage geodynamic model is proposed to explain the evolution of the Fiskenæsset Complex. Stage 1 represents the formation of depleted shallow mantle source > 3000 Ma (ε Nd = + 3.3 ± 0.7) for the complex. Stage 2 corresponds to the development of an intra-oceanic island arc between 3000–2950 Ma. Stage 3 is characterized by the collision of the island arc with either a passive continental margin or with an older arc between 2950–2940 Ma.

Avaliação da trajetória média de crescimento de caprinos em modelos de regressão aleatória

Polynomial functions for modeling growth curves of 946 Anglo-Nubiano goats, born from 1980 to 2005, and their effect on genetic parameter estimates were evaluated. Growth trajectories were fitted by fixed regression of weights on orthogonal polynomial of age, considering polynomials from second to seventh orders. For fixed regression, polynomial models were compared using the following criteria: mean square errors, absolute average residual error, square percent bias and goodness of fit. Akaikes information criterion, Bayesian information criterion and likelihood ratio test criteria were used to evaluate the effect of different polynomial order of fixed regression on genetic parameters estimates. An expressive improvement was found using higher order polynomials and those of fourth order were sufficient for modeling the average growth curve of goats. No influences on genetic parameter estimates were observed adopting higher than cubic order polynomial functions. The direct heritability showed an increasing pattern until 84th day of age, while the maternal one had a constant pattern for the whole period. Polynomial functions are efficient tools for modeling growth curve and polynomials of at least fourth order should be used for modeling the average growth curve of goat in random regression models.