scholarly journals Mathematical models to describe the growth curves of Vietnamese Ri chicken

2023 ◽  
Vol 83 ◽  
Author(s):  
T. H. Nguyen ◽  
C. X. Nguyen ◽  
M. Q. Luu ◽  
A. T. Nguyen ◽  
D. H. Bui ◽  
...  
Keyword(s):  
Growth Curve ◽  
Model Comparison ◽  
Growth Parameters ◽  
Growth Models ◽  
Growth Curves ◽  
Information Criterion ◽  
Chicken Breed ◽  
Richards Model ◽  
Genetics And Genomics ◽  
Backyard Chicken

Abstract Ri chicken is the most popular backyard chicken breed in Vietnam, but little is known about the growth curve of this breed. This study compared the performances of models with three parameters (Gompertz, Brody, and Logistic) and models containing four parameters (Richards, Bridges, and Janoschek) for describing the growth of Ri chicken. The bodyweight of Ri chicken was recorded weekly from week 1 to week 19. Growth models were fitted using minpack.lm package in R software and Akaike’s information criterion (AIC), Bayesian information criterion (BIC), and root mean square error (RMSE) were used for model comparison. Based on these criteria, the models having four parameters showed better performance than the ones with three parameters, and the Richards model was the best one for males and females. The lowest and highest value of asymmetric weights (α) were obtained by Bridges and Brody models for each of sexes, respectively. Age and weight estimated by the Richard model were 8.46 and 7.51 weeks and 696.88 and 487.58 g for males and for females, respectively. Differences in the growth curves were observed between males and female chicken. Overall, the results suggested using the Richards model for describing the growth curve of Ri chickens. Further studies on the genetics and genomics of the obtained growth parameters are required before using them for the genetic improvement of Ri chickens.

scholarly journals The Standard Deviation Structure as a New Approach to Growth Analysis in Weight and Length Data of Farmed Lutjanus guttatus

Fishes ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 60
Author(s):  
Sergio G. Castillo-Vargasmachuca ◽  
Eugenio Alberto Aragón-Noriega ◽  
Guillermo Rodríguez-Domínguez ◽  
Leonardo Martínez-Cárdenas ◽  
Eulalio Arámbul-Muñoz ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Growth Parameters ◽  
Growth Models ◽  
Growth Curves ◽  
Gompertz Model ◽  
Information Criterion ◽  
Weight Growth ◽  
Length Data ◽  
Size At Age ◽  
The Right

In the present study, size-at-age data (length and weight) of marine cage-reared spotted rose snapper Lutjanus guttatus were analyzed under four different variance assumptions (observed, constant, depensatory, and compensatory variances) to analyze the robustness of selecting the right standard deviation structure to parametrize the von Bertalanffy, Logistic, and Gompertz models. The selection of the best model and variance criteria was obtained based on the Bayesian information criterion (BIC). According to the BIC results, the observed variance in the present study was the best way to parametrize the three abovementioned growth models, and the Gompertz model best represented the length and weight growth curves. Based on these results, using the observed error structure to calculate the growth parameters in multi-model inference analyses is recommended.

scholarly journals Evaluation of Growth Curve Models for Body Weight in American Mink

Animals ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 22
Author(s):  
Duy Ngoc Do ◽  
Younes Miar
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Model Comparison ◽  
American Mink ◽  
Growth Curves ◽  
Information Criterion ◽  
Selection Response ◽  
Growth Curve Models ◽  
Body Weights ◽  
Males And Females

Modelling the growth curves of animals is important for optimizing the management and efficiency of animal production; however, little is known about the growth curves in American mink (Neovison vison). The study evaluated the performances of four three-parameter (Logistic, Gompertz, von Bertalanffy, and Brody), four four-parameter (Richards, Weibull, Bridges, and Janoscheck) and two polynomial models for describing the growth curves in mink. Body weights were collected from the third week of life to the week 31 in 738 black mink (373 males and 365 females). Models were fitted using the nls and nlsLM functions in stats and minpack.lm packages in R software, respectively. The Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) were used for model comparison. Based on these criteria, Logistic and Richards were the best models for males and females, respectively. Four-parameter models had better performance compared to the other models except for Logistic model. The estimated maximum weight and mature growth rate varied among the models and differed between males and females. The results indicated that males and females had different growth curves as males grew faster and reached to the maximum body weight later compared to females. Further studies on genetic parameters and selection response for growth curve parameters are required for development of selection programs based on the shape of growth curves in mink.

scholarly journals 101 Evaluation of Growth Curve Functions for predicted weight in small holder crossbred dairy cattle in Tanzania

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 79-80
Author(s):  
Chinyere Ekine ◽  
Raphael Mrode ◽  
Edwin Oyieng ◽  
Daniel Komwihangilo ◽  
Gilbert Msuta ◽  
...  
Keyword(s):  
Growth Curve ◽  
Model Comparison ◽  
Predictive Ability ◽  
Nonlinear Least Squares ◽  
Information Criterion ◽  
Dairy Farms ◽  
Exponential Model ◽  
Males And Females ◽  
Small Holder ◽  
Two Parameter

Abstract Modelling the growth curve of animals provides information on growth characteristics and is important for optimizing management in different livestock systems. This study evaluated the growth curves of crossbred calves from birth to 30 months of age in small holder dairy farms in Tanzania using a two parameter (exponential), four different three parameters (Logistic, von Bertalanffy, Brody, Gompertz), and three polynomial functions. Predicted weights based on heart girth measurements of 623 male and 846 female calves born between 2016 and 2019 used in this study were from the African Dairy Genetic Gains (ADGG) project in selected milk sheds in Tanzania, namely Tanga, Kilimanjaro, Arusha, Iringa, Njomba and Mbeya. Each function was fitted separately to weight measurement of males and females adjusted for the effect of ward and season of birth using the nonlinear least squares (nls) functions in R statistical software. The Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) were used for model comparison. Based on these criteria, all three polynomial and four parameter functions performed better and did not differ enough from each other in both males and females compared to the two-parameter exponential model. Predicted weight varied among the models and differed between males and females. The highest estimated weight was observed in the Brody model for both males (278.09 kg) and females (264.10 kg). Lowest estimated weight was observed in the exponential model. Estimated growth rate varied among models. For males, it ranged from 0.04 kg-0.08 kg and for females, from 0.05 kg-0.09 kg in the Brody model and logistic model respectively. Predictive ability across all fitted curves was low, ranging from 25% to approximately 29%. This could be due to the huge range of breed compositions in the evaluated crossbred calves which characterizes small holder dairy farms in this system and different levels of farm management.

scholarly journals Age estimation and the best growth model selection of the tentacled blenny Parablennius tentacularis (Brünnich, 1768) in the southeastern Black Sea

2021 ◽  
Vol 38 (2) ◽  
pp. 229-236
Author(s):  
Ayşe Van ◽  
Aysun Gümüş ◽  
Melek Özpiçak ◽  
Serdar Süer
Keyword(s):  
Growth Model ◽  
Black Sea ◽  
Growth Parameters ◽  
Growth Models ◽  
Information Criterion ◽  
Current Data ◽  
Logistic Growth ◽  
Data Set ◽  
Frequency Distributions ◽  
Selection Of

By the study's coverage, 522 individuals of tentacled blenny (Parablennius tentacularis (Brünnich, 1768)), were caught with the bottom trawl operations (commercial fisheries and scientific field surveys) between May 2010 and March 2012 from the southeastern Black Sea. The size distribution range of the sample varied between 4.8-10.8 cm. The difference between sex length (K-S test, Z=3.729, P=0.000) and weight frequency distributions (K-S test, Z=3.605, P=0.000) was found to be statistically significant. The length-weight relationship models were defined as isometric with W = 0.009L3.034 in male individuals and positive allometric with W = 0.006L3.226 in female individuals. Otolith and vertebra samples were compared for the selection of the most accurate hard structure that can be used to determine the age. Otolith was chosen as the most suitable hard structure. The current data set was used to predict the best growth model. For this purpose, the growth parameters were estimated with the widely used von Bertalanffy, Gompertz and Logistic growth functions. Akaike's Information Criterion (AIC), Lmak./L∞ ratio, and R2 criteria were used to select the most accurate growth models established through these functions. Model averaged parameters were calculated with multi-model inference (MMI): L'∞ = 15.091 cm, S.E. (L'∞) = 3.966, K'= 0.232 year-1, S.E. (K') = 0.122.

scholarly journals Height Growth Models for Western Larch in British Columbia

2002 ◽  
Vol 17 (2) ◽  
pp. 66-74 ◽  
Author(s):  
David Brisco ◽  
Karel Klinka ◽  
Gordon Nigh
Keyword(s):  
British Columbia ◽  
Growth Models ◽  
Growth Curves ◽  
Site Index ◽  
Height Growth ◽  
Larix Occidentalis ◽  
Local Data ◽  
Western Larch ◽  
Richards Model ◽  
Fit Statistics

Abstract British Columbia's foresters currently use height growth curves developed with data from Montana to estimate the height and productivity of western larch (Larix occidentalis). The ability of the presently used curves to accurately predict the height growth of British Columbia's larch population is unknown. The production of new curves with local data could improve our ability to predict heights and allow increasingly precise yield projections in British Columbia. Data from 105 western larch stem analysis plots were collected from across the natural range of larch in British Columbia. The measured plots were naturally established, fire-origin, even-aged, and exhibited no indications of suppression or disease. A Richards function was fit to the data from each plot and used to generate height-age and site index information. Four models were fit to the plot data: conditioned logistic, Chapman Richards, conditioned Chapman Richards, and conditioned Weibull. The Chapman Richards model had the best fit to the data, although all four models had similar fit statistics. Overall, the Chapman Richards model is slightly more accurate at estimating heights than the currently used model. West.J. Appl. For. 17(2):66–74.

scholarly journals Nonlinear mixed-effects growth models: A tutorial using 'saemix' in R

Methodology ◽  
2021 ◽  
Vol 17 (4) ◽  
pp. 250-270
Author(s):  
Peter Boedeker
Keyword(s):  
Repeated Measures ◽  
Mixed Model ◽  
Growth Parameters ◽  
Growth Models ◽  
Simulated Data ◽  
Growth Curves ◽  
Rate Of Change ◽  
Model Framework ◽  
Growth Variability ◽  
Starting Point

Modeling growth across repeated measures of individuals and evaluating predictors of growth can reveal developmental patterns and factors that affect those patterns. When growth follows a sigmoidal shape, the Logistic, Gompertz, and Richards nonlinear growth curves are plausible. These functions have parameters that specifically control the starting point, total growth, overall rate of change, and point of greatest growth. Variability in growth parameters across individuals can be explained by covariates in a mixed model framework. The purpose of this tutorial is to provide analysts a brief introduction to these growth curves and demonstrate their application. The 'saemix' package in R is used to fit models to simulated data to answer specific research questions. Enough code is provided in-text to describe how to execute the analyses with the complete code and data provided in Supplementary Materials.

scholarly journals Genetic and phenotypic parameters for body weights, harvest length, and growth curve parameters in American mink

2021 ◽  
Author(s):  
Duy Ngoc Do ◽  
Guoyu Hu ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Growth Curve ◽  
Inflection Point ◽  
Growth Parameters ◽  
American Mink ◽  
Genetic Correlations ◽  
Growth Potential ◽  
Richards Model ◽  
Body Weights ◽  
Curve Modeling ◽  
Selection For

Abstract Understanding the genetics underlying growth curve is important for selection of animals with better growth potential, but little is known about the genetics of growth curve parameters in mink. This study estimated the genetic parameters for body weights (BW), harvest length (HL) and growth parameters derived from the Richards model. For this purpose, individual BW of 1,088 mink measured seven times in three-week intervals (week 13 to week 31 of life) were used for growth curve modeling using the Richards model. The BW traits included body weight at week 13 (BW13), 16 (BW16), 19 (BW19), 22 (BW22), 25 (BW25), 28 (BW28), and 31 (BW31). Univariate analyses indicated that sex and birth-year had significant effects (P < 0.05) on BW, HL, asymptotic weight (α), growth rate at mature (k), shape parameter (m), weight at the inflection point (WIP), and age at the inflection point (AIP). In contrast, the color type had only a significant effect (P < 0.05) on BW31 and HL. Estimated heritabilities (±SE) were ranged from 0.36±0.13 (BW13) to 0.46±0.10 (BW22) for BW and were 0.51±0.09, 0.29±0.09, 0.30±0.09, 0.33±0.1, 0.44±0.10, and 0.47±0.10 for HL, α, k, m, WIP and AIP, respectively. The parameter α had non-significant (P > 0.05) genetic correlations (±SE) with k (-0.21±0.23) and m (-0.10±0.22), suggesting that changing in shape parameters (k and m) will not influence asymptotic weight (α). Strong significant (P < 0.05) phenotypic (from 0.46±0.03 to 0.60±0.03) and genetic (0.70±0.13 to 0.88±0.09) correlations were observed between HL and different BW measures. The α, AIP, and WIP parameters had significant (P < 0.05) genetic correlations, and HL indicated that selection for higher α, AIP, and WIP values would increase HL. Parameters k and m had non-significant (P > 0.05) genetic correlations with HL, indicating the change of the curve shape could not influence HL. Overall, the results suggest that growth curve parameters are heritable and can respond to genetic or genomic selection for optimizing the performance in mink.

scholarly journals Nonlinear mixed effects models for comparing growth curves for Guzerá cattle

2020 ◽  
Vol 21 ◽  
Author(s):  
Raphael Fernandes Soares ALVES ◽  
Kaléo Dias PEREIRA ◽  
Antônio Policarpo Souza CARNEIRO ◽  
Paulo Cesar EMILIANO ◽  
Paulo Luiz Souza CARNEIRO ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Growth Models ◽  
Random Effect ◽  
Growth Curves ◽  
Information Criterion ◽  
Fixed Effect ◽  
Coefficient Of Determination ◽  
Nonlinear Mixed Effects Models ◽  
Absolute Deviation ◽  
Production Region

ABSTRACT The objective of the present work was to evaluate the accuracy of the fitted Gompertz and von Bertalanffy models for male and female Guzerá cattle, respectively. Four production regions in Northeast Brazil were included in the models as a fixed effect, and the animals were included as a random effect. In addition, the coefficients of the growth models in the production regions were compared. The accuracy of the fit equations was assessed with the Akaike information criterion, Bayesian information criterion, mean absolute deviation, mean squared error, and coefficient of determination. Confidence intervals were used for comparing the production regions. The Guzerá males in the Gado-Algodão and Serra Geral da Bahia production regions were statistically equal in asymptotic weight, and the animals in the Itapetinga-Valadares and Mata-Agreste regions had equivalent maturity rates. The Guzerá females in the Itapetinga-Valadares and Serra Geral da Bahia regions had the same asymptotic weight. The maturity rates in Itapetinga-Valadares were equal to those estimated for Mata-Agreste and Serra Geral da Bahia. The inclusion of the fixed effect of the production region and the random effect of the animals in the models improved the fit quality and increased the possibility of generating growth curves for each region.

scholarly journals Individual, spatial and inter-sex variation in somatic growth: a study of Piaractus mesopotamicus (Characiformes: Serrasalmidae), a long-distance freshwater Neotropical migratory fish

2017 ◽  
Vol 15 (2) ◽  
Author(s):  
Luzia da S. Lourenço ◽  
Rosa Maria R. da Costa ◽  
Patrícia L. Rondon ◽  
Lúcia A. F. Mateus
Keyword(s):  
River Basin ◽  
Growth Parameters ◽  
Growth Models ◽  
Average Length ◽  
Somatic Growth ◽  
Information Criterion ◽  
Individual Variability ◽  
Fish Growth ◽  
Long Distance ◽  
Piaractus Mesopotamicus

ABSTRACT Growth is a fundamental biological process, driven by multiple endogenous (intra-individual) and exogenous (environmental) factors that maintain individual fitness and population stability. The current study aims to assess whether individual, spatial (headwaters and floodplains) and inter-sex variation occurs in the growth of Piaractus mesopotamicus in the Cuiabá River basin. Samples were collected monthly from July 2006 to July 2007, at two areas in the Cuiabá River basin (headwaters and floodplain). Three growth models (individuals; individuals and sex factors; individuals and areas factors) were developed and compared the fish growth parameters using Akaike information criterion (AIC). The best fit to the length-at-age data was obtained by a model that considered individual variation and sex. The theoretical maximum average length ( L∞ ) was 64.99 cm for females, and 63.23 cm for males. Females showed a growth rate (k) of 0.230 yr-1and males of 0.196 yr-1. Thus, could be concluded that individual variability and sex were the main sources of variation in P. mesopotamicus somatic growth parameters.

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.

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