Growth modeling of dairy heifers in Québec based on random regression

2012 ◽  
Vol 92 (1) ◽  
pp. 33-47 ◽  
Author(s):  
R. I. Cue ◽  
D. Pietersma ◽  
D. Lefebvre ◽  
R. Lacroix ◽  
K. Wade ◽  
...  
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Growth Modeling ◽  
The Body ◽  
Random Regression ◽  
Individual Growth ◽  
Residual Variance ◽  
Brown Swiss ◽  
Dairy Heifers ◽  
Height Data

Cue, R. I., Pietersma, D., Lefebvre, D., Lacroix, R., Wade, K., Pellerin, D., de Passillé, A-M. and Rushen, J. 2012. Growth modeling of dairy heifers in Québec based on random regression. Can. J. Anim. Sci. 92: 33–47. A total of 144 006 weight (calculated from tape girth measurements) and height data records from Québec dairy heifers were analyzed using random regression to estimate growth curve parameters of Ayrshires, Brown Swiss and Holstein animals to permit prediction of individual heifer growth from 0 to 32 mo. There were, on average, 5.15 records per heifer (minimum 3 records, maximum 25 records). The body weight data were analyzed using linear and quadratic fixed and random regressions, with a power-of-the-mean (POM) function to model the residual variance. The POM was 1.2 for Holstein and Ayrshire and slightly less than 1 for Brown Swiss. Estimated body weight at 24 mo was 507, 564, 624 kg, for Ayrshires, Brown Swiss and Holstein, respectively. The height data were analyzed with a Brody, monomolecular non-linear growth curve model. Mature height was estimated to be 148 cm in both Holstein and Ayrshires, and 150 cm in Brown Swiss. Random regression models were shown to be able to predict individual growth, and can be incorporated in decision-support tools to help producers reducing the average age at first calving.

scholarly journals Effect of body weight of goats and lactation order on the growth rate of kids in the suckling period

2011 ◽  
Vol 27 (3) ◽  
pp. 1193-1200 ◽  
Author(s):  
M. Zujovic ◽  
N. Memisi ◽  
V. Bogdanovic ◽  
Z. Tomic ◽  
N. Maksimovic ◽  
...  
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Milk Yield ◽  
Growth Traits ◽  
Statistical Significance ◽  
The Body ◽  
Individual Growth ◽  
Positive Sign ◽  
Suckling Period ◽  
Final Body Weight

The paper presents results of investigation of milk yield by lactation, by order, and mother's body weight on growth rate of kids of the domestic Balkan goat. Daily weight gains of 376 single kids (168 male and 208 female), in three monthly intervals, and their final body weight at 90 days of age were established. Variability of analyzed traits was presented using descriptive statistics parameters, and differences of growth traits for weight gain of kids resulting from the effect of milk yield of female goats by order of lactation were investigated by single analysis of variance. The effect of independent variables, mothers' milk yield and body weight, on body weight of kids was tested using multiple regression analysis. During the entire suckling period, established average values for kids body weight differed significantly (P<0.001), increasing from the 1st toward later lactations. At 90 days of age the lowest values were established in kids from the youngest mothers (11.86 kg), while for kids of mothers in the fourth or later lactations these values were higher (13.93 kg). Coefficients of determination indicate that the variability percentage for individual growth traits of kids was in the 0.08 - 0.17 interval, indicating its significance. Both "b" coefficients (b1 and b2) are positive and statistically highly significant, except for coefficient b2 in the analysis of body weight of kids at birth. The positive sign and high statistical significance indicate a pronounced effect of mother's milk yield and body weight on the body weight of kids up to 90 days of age.

Growth-Rates of the Bandicoot Isoodon-Macrourus and the Brushtail Possum Trichosurus-Vulpecula

1993 ◽  
Vol 41 (2) ◽  
pp. 141 ◽  
Author(s):  
RT Gemmell ◽  
JK Hendrikz
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Growth Curve ◽  
Growth Rates ◽  
Post Partum ◽  
Quadratic Equation ◽  
The Body ◽  
Brushtail Possum ◽  
Trichosurus Vulpecula ◽  
Iterative Analysis

Although the bandicoot Isoodon macrourus and the brushtail possum Trichosurus vulpecula give birth to similar-size young, about 200 mg, the pouch young of the bandicoot grow more quickly than those of the possum. The bandicoot is weaned at 59 days when the body weight is between 90 and 250 g. A young possum weighs about 20 g at Day 60 and between 780 and 1031 g when weaned at Day 170-180 post partum. The body weight of both species has been described previously as a continuous curve expressed by a quadratic equation. In this study, instead of assuming the growth curve to be continuous, the growth curve has been expressed as two components. The growth rates of both species were similar from birth until Day 12 post partum; the bandicoot then had a faster growth rate. The results from iterative analysis indicated a change in growth rate at Day 30 (data for Days 31 and 32 were missing) and Day 96 post partum for the bandicoot and possum, respectively. Thus, both marsupials showed a change in growth rate as hair appeared, eyes opened and the young first left the pouch.

scholarly journals Konstruktion von Indizes mit Restriktionen in Random Regression Modellen zur Veränderung der Wachstumskurve

2007 ◽  
Vol 50 (6) ◽  
pp. 619-627
Author(s):  
N. Mielenz ◽  
L. Schüler
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Regression Models ◽  
Test Period ◽  
Regression Coefficients ◽  
Random Regression ◽  
Breeding Value ◽  
Time Interval ◽  
Final Body Weight ◽  
Index Construction

Abstract. Title of the paper: Index construction with restrictions in random regression models to change the pattern of the growth curve Random regression models provide estimated breeding values (EBV) for the complete growth curve for any target age. The animal-specific curves can be described as the weighted sum of continuous covariates with random regression coefficients. By using the covariance matrix K of the additive genetic regression coefficients the response to index selection can be calculated for any age or time of the test period. In this study selection indexes with equality restrictions based on the eigenvectors of matrix K were used to modify the growth curve of the population. In order to demonstrate the index construction a matrix K was used, estimated from repeated measurements for body weight of bulls by using Legendre polynomials as covariates. Indexes for high and low growth rate until age at the reflection point were derived subject to the restriction of zero gain for initial and final body weight. Selection strategies for improving body weight at the end of the test period while holding the daily gain in a certain time interval on a desired level were compared. By using so-called "restrictive economic values", an aggregate breeding value for body weight was derived from EBV for individual growth curve.

scholarly journals Kajian Penggunaan Aplikasi Android Sebagai Platform Untuk Menghitung Indeks Massa Tubuh (IMT)

2020 ◽  
Vol 1 (1) ◽  
pp. 15-20
Author(s):  
Lathifah Hanum ◽  
Dwiny Meidelfi ◽  
Aldo Erianda
Keyword(s):  
Image Processing ◽  
Body Weight ◽  
Health Risks ◽  
Processing Method ◽  
The Body ◽  
Measurement Tool ◽  
External Device ◽  
Image Processing Method ◽  
Daily Diet ◽  
Height Data

Body Mass Index or BMI is an indicator used to measure body weight whether classified as ideal or not. A person's BMI determines by comparing body weight and height which then predicts the standard body value category from the results of renewal. BMI is often used as a measurement tool for the body in carrying out daily diet programs. However, BMI is also often used as a reference for health risks, as a determinant of coronary heart disease or as a measurement tool for diets for people with diabetes mellitus. Using a smartphone that continues to increase over time can be used for ease in calculating a person's BMI. With various methods of making existing systems, such as manual, Bluetooth Low Energy (BLE) or image processing. The manual method requires weight and height data input which is not necessarily the same every time. While BLE requires an external device other than a smartphone to calculate weight and height. From the studies conducted, the image processing method is the most effective. The image processing method takes the data needed to calculate the BMI through the inputted image without the need to manually input data or use an external device other than a smartphone.  

scholarly journals Shifting body weight-fecundity relationship in a capital breeder: maternal effects on egg numbers of the autumnal moth under field conditions

2008 ◽  
Vol 99 (1) ◽  
pp. 73-81 ◽  
Author(s):  
A. Heisswolf ◽  
T. Klemola ◽  
T. Andersson ◽  
K. Ruohomäki
Keyword(s):  
Body Weight ◽  
Body Size ◽  
The Body ◽  
Residual Variance ◽  
Data Set ◽  
Potential Fecundity ◽  
Autumnal Moth ◽  
Egg Number ◽  
Pupal Mass ◽  
Parent Generation

AbstractIn the literature, various environmental factors are described as being capable of influencing the reproductive output of insect females irrespective of their body size. Still, female body size or weight is widely used as a proxy for fecundity. In the present study, a seven-year data set on the autumnal moth, Epirrita autumnata (Borkhausen) (Lepidoptera: Geometridae), was used to analyze whether the body weight-fecundity relationship in this capital breeding, cyclic forest defoliating lepidopteran is constant across years. Ambient temperature conditions and density of conspecifics during larval development, the length of the pupal period, as well as moth densities in the parent generation were examined as factors capable of modifying the body weight-fecundity relationship. While the regression slope of potential fecundity (total egg numbers per female) on pupal mass was constant across years, the mean total egg number per given body weight (the regression intercept) was significantly different between years. This residual variance in egg numbers after controlling for the effect of pupal mass was best explained by the pooled geometrid density (autumnal and winter moths) in the parent generation. The total egg number per given body weight decreased with increasing density of geometrid moths in the parent generation. Thus, maternal density effects on offspring fecundity were found in this system. Their rather weak nature suggests, however, that this maternal effect alone does not have the potential of causing cyclic population dynamics in the autumnal moth.

Growth curve models for commercial pullets under severe heat stress condition

2009 ◽  
Vol 2009 ◽  
pp. 234-234
Author(s):  
J Fayazi ◽  
M R Ghorbani ◽  
M Nazari ◽  
J Momeni ◽  
A Jaferian ◽  
...  
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Heat Stress ◽  
Growth Curve ◽  
Egg Production ◽  
Harmful Effect ◽  
The Body ◽  
Basic Knowledge ◽  
Growing Period ◽  
Severe Heat Stress

The objectives of our study were to propose a growth curve and to develop a mathematical model to describe the body weight of pullet experiencing severe heat stress (42°C). Poultry producers who raise their own replacement pullets can control their pullet’s growth, condition and development. Many of the problems which occur during the early part of lay can be traced back to insufficient or improper type of body weight attained during the various stages of the growing period. In order to avoid these problems, the body weight of pullets must be controlled. Rearing conditions for pullets vary depending on environmental pressures and can affect growth rate. Without the basic knowledge of the flock grow-out, it is virtually impossible to understand and possibly solve problems which may later occur during the laying period. It must be kept in mind that once egg production begins, it is too late to solve problems resulting from growing period. The two most important criteria of pullet quality are uniformity within the flock and proper body weight at a specific age. Almost anything that adversely affects a pullet will usually be reflected in lower body weights and poorer flock uniformity. High ambient temperatures can be devastating to commercial pullet growth rate; coupled with high humidity they can have an even more harmful effect on proper and recommended body weight. Heat stress interferes with the poultry comfort and suppresses performance efficiency. In order to verify the effect of heat stress on pullet growth rate, many curve modelled, fitted and verified to proposed best one.

Effects of some factors on growth of lambs and the determination of growth curve models

2018 ◽  
Author(s):  
Ayhan Yilmaz ◽  
Ferda Karakus ◽  
Mehmet Bingöl ◽  
Baris Kaki ◽  
Gazel Ser
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Growth Models ◽  
Age Groups ◽  
Growth Curves ◽  
The Body ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Male And Female ◽  
Growth Curve Models

he aims were to identify the body weight of the several age groups in Norduz lambs and its correlations between these traits were to determine the best non-linear growth curve models for the growth performance of the Norduz sheep breed. A total of 91 male and female of Norduz lambs were evaluated under extensive system conditions. The least square means for weights at birth and at 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195 and 210 days of age periods were 4.51±0.56, 9.28±0.25, 11.14±0.29, 14.99±0.37, 18.21±0.43, 22.54±0.54, 22.33±0.25, 23.59±0.54, 25.58±0.55, 28.07±0.58, 29.45±0.60, 29.98±0.84, 32.44±0.61, 32.03±0.59 and 31.45±0.57 kg, respectively. There were differences in favor of lambs of four-year old dams at 15 days of age and also lambs born single at 90 days of age for the body weight. The effect of weight of dam at birth, 30, 45, 60 days of age was significant (P less than 0.05-P less than 0.01) and the birth weight in lambs importantly effected the weights at 15, 30, and 45 days of age. All correlations between the body weights of several age periods were significant as statistical (P less than 0.01). As for the growth models, distinguished models were compared using the coefficient of determination and mean square error for both sexes. As a result, we concluded that von Bertalanffy model were the best model in comparison with the other models for biological growth curves in Norduz male and female lambs.

scholarly journals The body weight performance of indigenous indonesian chickens in the grower phase

2021 ◽  
Vol 888 (1) ◽  
pp. 012010
Author(s):  
F Mustofa ◽  
A P Z N L Sari ◽  
E Suryanto ◽  
D Maharani ◽  
A Agus ◽  
...  
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Critical Parameter ◽  
Body Growth ◽  
The Body ◽  
Performance Data ◽  
Production Phase ◽  
Body Weights ◽  
Battery Cages

Abstract Body weight is a critical parameter to monitor in chickens due to its correlation with better performance during the production phase. Hence, this study aimed to present an overview of the body weight performance of indigenous Indonesian chickens in the grower phase. The study was conducted in Gunung Kidul, Yogyakarta. Data of body weight performance data of 227 Merawang, 157 Murung Panggang, and 416 KUB chickens in the grower phase were collected. These weights were measured 4 times at 6, 8, 10, and 12 weeks while rearing the chickens in battery cages in a closed house under similar management. The result showed that the Murung Panggang chickens at each age had the highest body weight and uniformity value (P<0.05), followed by Merawang and KUB. The body growth curve of the Merawang, Murung Panggang, and KUB chickens at the 6th week showed similar weights, ranging between 400-600 g. However, at the 8th, 10th, and 12th weeks, the Merawang and Murung Panggang chickens had higher body weight performance. Therefore, this study suggested that Merawang and Murung Panggang chickens may have a greater potential to attain higher final body weights.

scholarly journals Estimation of genetic parameters for body weight traits in Mazandaran native breeder hens by random regression models

Genetika ◽  
2019 ◽  
Vol 51 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Yousef Naderi
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Information Criterion ◽  
The Body ◽  
Random Regression ◽  
Likelihood Method ◽  
Primary Concern ◽  
Environmental Correlations

The primary concern of this study is to investigate appropriate random regression model for estimate genetic parameters body weight at hatch (BW1), eight (BW8), twelve (BW12) and thirty two (BW32) weeks of ages by the restricted maximum likelihood method. The body weight records set included 39872 during 16 generations of hens kept at the Mazandaran Breeding Center of Iran. Random regression were modelled using generation-hatch as a fixed effect and additive genetic and permanent environmental effects as random effects Residual variances were modeled through a step function with 1 and 3 classes. The model was considered to be the most appropriate with the highest significant log likelihood ratio test (LRT) and the lowest Akaike information criterion (AIC) and Bayesian information criterion (BIC). Heritability values increased from 0.21 for BW1, to 0.40 for BW32. Genetic correlations of body weight at different record keeping were often higher than permanent environmental correlations. Genetic correlations between pairs of body weight measures were moderate to high with a range from 0.25 to 0.97. The largest genetic correlation, as well as permanent environmental correlation, was observed between BW12and BW32. High and moderate broad sense heritability values for all studied traits shows that these traits are less influenced by residual effects which make them effectively transmitted to the progeny. Findings show that genetic improvement for body weight can be achieved by selection. The Heritability of body weight at thirty two weeks of ages and its relatively high genetic correlation with all other ages showed that it could be the most appropriate period for selection. Also, the genetic trend estimates for body weight traits showed that selection decisions made during the breeding program effectively improved the growth performance.

ANALYSES OF GROWTH CURVE PARAMETERS OF N’DAMA CATTLE RAISED IN THE HUMID TROPICS

2021 ◽  
Vol 34 (1) ◽  
pp. 1-13
Author(s):  
M. O. Ozoje ◽  
S. O. Peters ◽  
S. I. Ojikuku
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Growth Rates ◽  
Growth Traits ◽  
Negative Relationship ◽  
Growth Function ◽  
Individual Growth ◽  
Early Maturity ◽  
Relative Growth ◽  
Relative Growth Rates

Individual growth curve parameters are suitable phenotypic variable for the assessment of growth course and early maturity. This study focused on the analyses of growth curves parameters of N’Dama cows derived from the Richarads growth function. Data consist of field records of weight measurements from birth to 36 months old of 98 N’Dama cows born and raised between 1992 and 1998. The coefficient of variation was moderately high in both the curve and predicted parameters except for point of inflation (m). The estimates of heritability for maturing traits ranged from 0.18 to 0.30. While those for body weights and growth traits ranged form 0.21 to 0.47. High correlation coefficients were observed between mature weight parameter (A) and body weight at 180 days. 365days and 550days of age. A negative relationship was observed between A and maturing rate index k,(0.51) and between A and all maturing parameters associated with stages of growth (degrees of maturity and relative growth rates). Sire variation was an important source of variation (P < 0.05) for all the parameters studies except for residual means squares (RMS). Year of birth was also a significant (P < 0.05), source of variation for A, K, RMS, degrees of maturity at 180days of age and the relative growth rates at 180days and 365 of age, while age of dam significantly (P < 0.05) affected the constant of integration b, the maturing rate index k, body weight and degree of maturity at 180days of age. Season of birth affected the point of inflation (m) RMS body weight at 180day and absolute growth rate at 365days of age. The interaction between year of birth and age of dam was significant (P < 0.05), affecting only the A and the K parameters

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