scholarly journals Nonlinear modeling growth body weight of Mangalarga Marchador horses

2017 ◽  
Vol 47 (4) ◽  
Author(s):  
Felipe Amorim Caetano Souza ◽  
Tales Jesus Fernandes ◽  
Raquel Silva de Moura ◽  
Sarah Laguna Conceição Meirelles ◽  
Rafaela Aparecida Ribeiro ◽  
...  
Keyword(s):  
Body Weight ◽  
Linear Models ◽  
Nonlinear Modeling ◽  
Growth Curves ◽  
Live Weight ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Cross Sectional ◽  
Adult Body Weight ◽  
The Cross

ABSTRACT: The analysis of the growth and development of various species has been done using the growth curves of the specific animal based on non-linear models. The objective of the current study was to evaluate the fit of the Brody, Gompertz, Logistic and von Bertalanffy models to the cross-sectional data of the live weight of the MangalargaMarchador horses to identify the best model and make accurate predictions regarding the growth and maturity in the males and females of this breed. The study involved recording the weight of 214 horses, of which 94 were males and 120 were non-pregnant females, between 6 and 153 months of age. The parameters of the model were estimated by employing the method of least squares, using the iteratively regularized Gauss-Newton method and the R software package. Comparison of the models was done based on the following criteria: coefficient of determination (R²); Residual Standard Deviation (RSD); corrected Akaike Information Criterion (AICc). The estimated weight of the adult horses by the models ranged between 431kg and 439kg for males and between 416kg and 420kg for females. The growth curves were studied using the cross-sectional data collection method. For males the von Bertalanffymodel was found to be the most effective in expressing growth, while in females the Brody model was more suitable. The MangalargaMarchador females achieve adult body weight earlier than the males.

scholarly journals Choice of non-linear models to determine the growth curve of meat-type quail

2021 ◽  
Vol 51 (2) ◽  
Author(s):  
Marta Jeidjane Borges Ribeiro ◽  
Fabyano Fonseca Silva ◽  
Maíse dos Santos Macário ◽  
José Aparecido Santos de Jesus ◽  
Claudson Oliveira Brito ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Linear Models ◽  
Growth Curves ◽  
Information Criterion ◽  
Metabolizable Energy ◽  
Coefficient Of Determination ◽  
Parameter Estimates ◽  
Coturnix Coturnix ◽  
Non Linear ◽  
Meat Type

ABSTRACT: The objective of this study was to compare non-linear models fitted to the growth curves of quail to determine which model best describes their growth and check the similarity between models by analyzing parameter estimates.Weight and age data of meat-type European quail (Coturnix coturnix coturnix) of three lines were used, from an experiment in a 2 × 4 factorial arrangement in a completely randomized design, consisting of two metabolizable energy levels, four crude protein levels and six replicates. The non-linear Brody, Von Bertalanffy, Richards, Logistic and Gompertz models were used. To choose the best model, the Adjusted Coefficient of Determination, Convergence Rate, Residual Mean Square, Durbin-Watson Test, Akaike Information Criterion and Bayesian Information Criterion were applied as goodness-of-fit indicators. Cluster analysis was performed to check the similarity between models based on the mean parameter estimates. Among the studied models, Richards’ was the most suitable to describe the growth curves. The Logistic and Richards models were considered similar in the analysis with no distinction of lines as well as in the analyses of Lines 1, 2 and 3.

scholarly journals The Trp64Arg Polymorphism of the β3-Adrenergic Receptor Gene Is Not Associated with Body Weight or Body Mass Index in Japanese: A Longitudinal Analysis

2003 ◽  
Vol 88 (12) ◽  
pp. 5914-5920 ◽  
Author(s):  
Yumi Matsushita ◽  
Tetsuji Yokoyama ◽  
Nobuo Yoshiike ◽  
Yasuhiro Matsumura ◽  
Chigusa Date ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Weight ◽  
Energy Intake ◽  
Body Mass ◽  
Longitudinal Analysis ◽  
Adrenergic Receptor ◽  
Cross Sectional ◽  
Genotype Frequencies ◽  
The Cross

Abstract The β3-adrenergic receptor (ADRB3) is expressed mainly in visceral adipose tissue and is thought to contribute to lipolysis and the delivery of free fatty acids to the portal vein. Although many studies have examined the relationship between the Trp64Arg mutation of ADRB3 and obesity, the results have been inconsistent. We examined the cross-sectional relationship of ADRB3 variants with indexes of obesity, and their longitudinal changes over 10 yr, in men and women, aged 40–69 yr, who were randomly selected from the Japanese rural population. The study considered both dietary energy intake and physical activity levels. Among the 746 participants, the genotype frequencies of the Trp64Trp, Trp64Arg, and Arg64Arg variants were 483, 224, and 39, respectively. The cross-sectional analysis showed no significant differences in height, weight, body mass index, blood pressure, serum total and high density lipoprotein cholesterols, and hemoglobin A1c among the genotype groups even after adjustments for gender, age, smoking, alcohol drinking, physical activity, and energy intake. No significant differences in the weight changes between the genotype groups were evident in the longitudinal analysis. We conclude that the Trp64Arg mutation of ADRB3 has little or no influence on either body weight or body mass index in the general Japanese population.

Factors governing the shape of the growth curve of body weight and the age at slaughter of Suffolk × Welsh lambs

1966 ◽  
Vol 8 (3) ◽  
pp. 435-444 ◽  
Author(s):  
J. S. Broadbent ◽  
J. H. Watson
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Growth Curve ◽  
Compensatory Growth ◽  
Marked Effect ◽  
Growth Curves ◽  
Live Weight ◽  
Linear Component ◽  
Slaughter Weight ◽  
Birth Type

Curves of growth in live-weight, from birth to 16 weeks of age, of 362 Suffolk × Welsh lambs were analysed for the effect of sex, birth type, sire and test centre environment and related to variation in age at slaughter.The relative pre-natal disadvantages of twin lambs resulted in their curves of growth differing from those of single-born animals, particularly in males. Test centre environment exerted a marked effect in such cases. At one centre, male twins showed marked compensatory growth.Differences in growth existed between the 14 sire progeny groups. As the linear component of the growth curves decreased, the quadratic values became increasingly negative. Deceleration of growth was most marked in slowest growing progeny groups and this was accentuated by a poor test centre environment.These factors combined to influence age at slaughter, which was also related to birth weight of the lamb. Lambs at the best test centre reached slaughter weight 10 and 16 days earlier than lambs at the two remaining centres. Sires produced differences in age at slaughter of 10 to 14 days, within centres.

scholarly journals Mathematical models to describe the growth curves of white-egg layers

2018 ◽  
Vol 39 (3) ◽  
pp. 1327
Author(s):  
Cleber Franklin Santos de Oliveira ◽  
João Marcos Novais Tavares ◽  
Gerusa Da Silva Salles Corrêa ◽  
Bruno Serpa Vieira ◽  
Silvana Alves Pedrozo Vitalino Barbosa ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Mean Squared Error ◽  
Computer Software ◽  
Logistic Models ◽  
Growth Curves ◽  
Gompertz Model ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Population Densities

The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.

scholarly journals Method to generate growth and degrowth models obtained from differential equations applied to agrarian sciences

2018 ◽  
Vol 39 (6) ◽  
pp. 2659 ◽  
Author(s):  
André Luiz Pinto dos Santos ◽  
Guilherme Rocha Moreira ◽  
Cicero Carlos Ramos de Brito ◽  
Frank Gomes-Silva ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Differential Equations ◽  
Goodness Of Fit ◽  
Least Squares Method ◽  
Growth Curves ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
Marquardt Algorithm ◽  
Maturation Rate ◽  
Biological Interpretation

This study aims to propose a method to generate growth and degrowth models using differential equations as well as to present a model based on the method proposed, compare it with the classic linear mathematical models Logistic, Von Bertalanffy, Brody, Gompertz, and Richards, and identify the one that best represents the mean growth curve. To that end, data on Undefined Breed (UB) goats and Santa Inês sheep from the works of Cavalcante et al. (2013) and Sarmento et al. (2006a), respectively, were used. Goodness-of-fit was measured using residual mean squares (RMS), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute deviation (MAD), and adjusted coefficient of determination . The models’ parameters (?, weight at adulthood; ?, an integration constant; ?, shape parameter with no biological interpretation; k, maturation rate; and m, inflection point) were estimated by the least squares method using Levenberg-Marquardt algorithm on the software IBM SPSS Statistics 1.0. It was observed that the proposed model was superior to the others to study the growth curves of goats and sheep according to the methodology and conditions under which the present study was carried out.

The growth of lambs before and after birth in relation to the level of nutrition

1948 ◽  
Vol 38 (3) ◽  
pp. 243-302 ◽  
Author(s):  
L. R. Wallace
Keyword(s):  
Body Weight ◽  
Actual Body ◽  
Growth Curves ◽  
Live Weight ◽  
Constant Level ◽  
Gravid Uterus ◽  
Standard Diet ◽  
Actual Body Weight ◽  
Weight Growth ◽  
Before And After

SUMMARYIn the investigation described, we have observed a t monthly intervals throughout gestation the changes taking place in a series of similar ewes, in lamb to the same ram, and each receiving the same standard diet.In following the live-weight growth curves of the ewes it was found that on a constant level of feeding the weight gains became greater during each succeeding month of pregnancy, and at corresponding stages were larger for ditocous than for monotocous ewes. This was found to be due to the fact that, although on our diet the ewes did gain slightly in actual body weight, the main increases in live weight resulted from the growth of the gravid uterus itself, and this increases in weight far more rapidly in the later stages of gestation, and is also heavier where twins are carried.

Prediction of body weight from linear body measurements in sheep

2017 ◽  
Author(s):  
Sandeep Kumar ◽  
S. P. Dahiya ◽  
Z. S. Dahiya ◽  
C. S. Patil
Keyword(s):  
Body Weight ◽  
Genetic Correlations ◽  
Body Height ◽  
Selection Criterion ◽  
Live Weight ◽  
Tail Length ◽  
Coefficient Of Determination ◽  
Body Measurements ◽  
Linear Type ◽  
Linear Body

Measurements of body conformation in sheep are of value in judging the quantitative characteristics of meat and also helpful in developing suitable selection criterion. Data on 349 Harnali sheep for body length (BL), body height (BH), heart girth (HG), paunch girth (PG), tail length (TL), head circumference (HC), ear length (EL), ear width (EW), face length (FL) and adult body weight (ABW) were analysed to study the relationship between linear body measurements and body weight. The mixed linear model with dam’s weight at lambing as covariate was used to study the effect of non-genetic factors on body measurements and body weight. High estimates of heritability were obtained for BL, BH, HG, TL, HC, EL, EW, FL and ABW while moderate estimate was obtained for PG. The phenotypic correlations of BL, BH, HG, PG, HC and FL with ABW were positive and significant (0.32±0.04 to 0.59±0.08). The genetic correlations of HG, PG, HC and FL with ABW were 0.51±0.13, 0.42±0.19, 0.44±0.13 and 0.43±0.15, respectively. Various combinations of linear type traits to predict ABW were found to have coefficient of determination as high as 0.92. It is concluded that heart girth is the most important trait for estimation of live weight in sheep and the prediction equation is Body weight = -63.72 + 1.23 HG with R2 = 0.87.

scholarly journals The prediction of live weight of hair goats through penalized regression methods: LASSO and adaptive LASSO

2018 ◽  
Vol 61 (4) ◽  
pp. 451-458
Author(s):  
Suna Akkol
Keyword(s):  
Live Weight ◽  
Information Criterion ◽  
Penalized Regression ◽  
Adaptive Lasso ◽  
Model Complexity ◽  
Coefficient Of Determination ◽  
Explanatory Variables ◽  
Regression Methods ◽  
Bayesian Criterion ◽  
Chest Girth

Abstract. The least absolute selection and shrinkage operator (LASSO) and adaptive LASSO methods have become a popular model in the last decade, especially for data with a multicollinearity problem. This study was conducted to estimate the live weight (LW) of Hair goats from biometric measurements and to select variables in order to reduce the model complexity by using penalized regression methods: LASSO and adaptive LASSO for γ=0.5 and γ=1. The data were obtained from 132 adult goats in Honaz district of Denizli province. Age, gender, forehead width, ear length, head length, chest width, rump height, withers height, back height, chest depth, chest girth, and body length were used as explanatory variables. The adjusted coefficient of determination (Radj2), root mean square error (RMSE), Akaike's information criterion (AIC), Schwarz Bayesian criterion (SBC), and average square error (ASE) were used in order to compare the effectiveness of the methods. It was concluded that adaptive LASSO (γ=1) estimated the LW with the highest accuracy for both male (Radj2=0.9048; RMSE = 3.6250; AIC = 79.2974; SBC = 65.2633; ASE = 7.8843) and female (Radj2=0.7668; RMSE = 4.4069; AIC = 392.5405; SBC = 308.9888; ASE = 18.2193) Hair goats when all the criteria were considered.

scholarly journals Sex-Related Difference in the Association Between Child Neglect and the Accuracy of Body Weight Perception Among Chinese Primary Schoolchildren

2021 ◽  
Vol 9 ◽  
Author(s):  
Hong-jie Yu ◽  
Xiangxiang Liu ◽  
Ming-wei Liu ◽  
Min-zhe Zhang ◽  
Miaobing Zheng ◽  
...  
Keyword(s):  
Body Weight ◽  
Child Neglect ◽  
Multinomial Logistic Regression ◽  
Weight Perception ◽  
Cross Sectional ◽  
Multinomial Logistic Regression Analysis ◽  
Related Difference ◽  
Primary Schoolchildren ◽  
Body Weight Perception ◽  
The Cross

Introduction: Body weight perception (BWP) directly determines weight management behaviors. Although child neglect is a well-established risk factor for managing body weight, little is known about its association with the accuracy of BWP. This study aimed to assess the cross-sectional and longitudinal associations between child neglect and BWP accuracy in primary schoolchildren, and explore how these differ based on the sex of the child.Methods: The sample included 1,063 primary schoolchildren (557 boys and 506 girls, aged 8–10 years) from a two-wave observational study between 2018 and 2019 in Wuhan, China. Child neglect and BWP were investigated using self-administered questionnaires. The accuracy of BWP was defined by comparing the BWP and actual body weight, and it was categorized into three groups—consistent, underestimated, and overestimated. Multinomial logistic regression analysis was conducted with fitting child neglect as the independent variable and the accuracy of BWP as the dependent variable.Results: The prevalence of weight misperception was ~44% at baseline (underestimation 40%; overestimation 4%) in Chinese primary schoolchildren. In the cross-sectional analysis, children with a higher level of neglect were more likely to misperceive their body weight. Moreover, there was an apparent sex-related difference that boys who experienced a higher level of neglect significantly reported more underestimation, while girls reported more overestimation. There was no significant longitudinal association between child neglect and the change in BWP accuracy.Conclusions: This study revealed that a higher level of neglect was significantly associated with underestimated BWP in boys and overestimated BWP in girls. The mechanisms of sex-related difference and whether child neglect is involved in the change in BWP, merit further investigations.

PSIII-5 Predicting live weight using linear body measurements in growing beef calves

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 285-285
Author(s):  
Vanessa Rotondo ◽  
Dan Tulpan ◽  
Katharine M Wood ◽  
Marlene Paibomesai ◽  
Vern R Osborne
Keyword(s):  
Machine Learning ◽  
Body Weight ◽  
Linear Models ◽  
Live Weight ◽  
Body Measurements ◽  
Learning Models ◽  
Linear Measurements ◽  
Beef Calves ◽  
Machine Learning Models ◽  
Linear Body

Abstract The objective of this study is to investigate how linear body measurements relate to and can be used to predict calf body weight using linear and machine learning models. To meet these objectives, a total of 103 Angus cross calves were enrolled in the study from wk 2 - 8. Calves were weighed and linear measurements were collected weekly, such as: poll to nose, width across the eyes (WE), width across the right ear, neck length, wither height, heart girth (HG), midpiece height (MH), midpiece circumference, midpiece width (MW), midpiece depth (MD), hook height, hook width, pin height, top of pin bones width (PW), width across the ends of pin bones, nose to tail body length, the length between the withers and pins, forearm to hoof, cannon bone to hoof. These measurements were taken using a commercial soft tape measure and calipers. To assess relationships between traits and to fit a model to predict BW, data were analyzed using the Weka (The University of Waikato, New Zealand) software using both linear regression (LR) and random forest (RF) machine learning models. The models were trained using a 10-fold cross-validation approach. The automatically derived LR model used 11 traits to fit the data to weekly BW (r2 = 0.97), where the traits with the highest coefficients were HG, PW and WE. The RF model improved further the BW predictions (r2= 0.98). Additionally, sex differences were examined. Although the BW model continued to fit well (r2 0.97), some of the top linear traits differed. The results of this study suggest that linear models built on linear measurements can accurately estimate body weight in beef calves, and that machine learning can further improve the model fit.

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