scholarly journals Growth characteristics of noiler chickens as determined by nonlinear algorithms

2021 ◽  
Vol 48 (5) ◽  
pp. 12-19
Author(s):  
J. Adamu ◽  
A. Y. Shuaibu ◽  
A. O. Raji
Keyword(s):  
Goodness Of Fit ◽  
Growth Models ◽  
Growth Patterns ◽  
Growth Characteristics ◽  
Coefficient Of Determination ◽  
Logistic Growth ◽  
Mathematical Function ◽  
Morphometric Traits ◽  
Male And Female ◽  
Males And Females

The assessment of growth characteristics of noilers chickens as determined by non- linear algorithms will provide the best mathematical function in the growth of male and female noilers chickens This study sought to determine the adequacy of two mathematical functions for modeling growth characteristics of male and female Noiler® chickens. Body weights and morphometric traits of 200 Noiler chickens were measured bimonthly for 20 weeks and the data obtained fitted to the Gompertz and Logistic growth models using the nonlinear regression. The results showed significant (P<0.05) difference between males and females only at 16, 18 and 20 weeks of age, with values of 2316.2 vs 2121.9 g, 2624.3 vs 2378.1 g, and 3002.7 vs 2718.7g, respectively. There were no discernable differences between males and females for most body measurements except body length which was longer in the latter than former from 14 weeks of age. The asymptomatic weight (A) of the models revealed that Gompertz model had higher values for both male and female Noilers than the Logistic for body weight and all morphometric traits. The reverse was observed with the scale parameter 2 (B) and relative growth rate (C) for all traits. The coefficient of determination (R ) values for both models (male and female) were generally high (>80%) indicating a good fit for the data. The other goodness of fit criteria; Akaike Information Criterion (AIC) and standard deviation (SD) were lower for the Gompertz compared to Logistic for both male and female. Thus, the study revealed that the Gompertz was the better model for explaining the growth patterns of both male and female Noiler chickens.     L'évaluation des caractéristiques de croissance des poulets de Noilers tels que déterminées par des algorithmes non linéaires fournira la meilleure fonction mathématique de la croissance des poulets de Noilers masculins et féminins. Cette étude a cherché à déterminer l'adéquation de deux fonctions mathématiques pour la modélisation des caractéristiques de croissance des poulets mâles et femelles Noiler. Les poids corporels et les traits morphométriques de 200 poulets nilaques ont été mesurés bimenshly pendant 20 semaines et les données obtenues dans les modèles de Gompertz et croissance logistiques utilisant la régression non linéaire. Les résultats ont montré une différence significative (p <0,05) entre les mâles et les femmes seulement à 16, 18 et 20 semaines, avec des valeurs de 2316,2 vs 2121,9 g, 2624.3 contre 2378,1 g et 3002,7 vs 2718.7g, respectivement. Il n'y avait pas de  différences discernables entre les hommes et les femmes pour la plupart des mesures du corps, à l'exception de la longueur du corps, ce qui était plus long que l'ancien de 14 semaines. Le poids asymptomatique (A) des modèles a révélé que le modèle de Gompertz avait des valeurs plus élevées pour les noilers mâles et femelles que la logistique pour le poids corporel et tous les traits morphométriques. L'inverse a été observé avec le paramètre d'échelle (B) et le taux de croissance relative (C) pour tous les traits. Le coefficient de valeurs de détermination (R ) pour les deux modèles (hommes et femmes) était généralement élevé (> 80%) indiquant un bon ajustement pour les données. L'autre bonté des critères d'ajustement; Le critère d'information Akaike (CIA) et l'écart type (ET) étaient plus bas pour le Gompertz par rapport à la logistique pour les hommes et les femmes. Ainsi, l'étude a révélé que le Gompertz était le meilleur modèle d'explication des schémas de croissance des poulets mâles et femelles Noilers. 

scholarly journals Prediction of mono and multiphasic growth parameters of broilers (Short Communication)

2010 ◽  
Vol 53 (1) ◽  
pp. 101-107
Author(s):  
M. Mendeş
Keyword(s):  
Goodness Of Fit ◽  
Short Communication ◽  
Growth Parameters ◽  
Growth Models ◽  
Growth Function ◽  
Logistic Growth ◽  
Model Parameters ◽  
Male And Female ◽  
Body Weights ◽  
Males And Females

Abstract. The main objective of this study was to predict mono and multiphasic growth model parameters of broilers. For this purpose daily body weights-age data of 106 male and female chickens reared under different stocking densities (GR1=11 birds/m2 , GR2=17 birds/m2 and GR3=25 birds/m2) were used. Results of mono and multiphasic (diphasic and triphasic) growth curve analyses showed that defining the growth of birds using multiphasic growth models instead of monophasic growth models, displays more detailed and reliable results. Based on goodness-of-fit criteria, lead to the choice of a triphasic logistic growth function for GR1 and GR2, and diphasic function for GR3 males and females.

Introducing a sinusoidal equation to describe lactation curves for cumulative milk yield and composition in Holstein cows

2020 ◽  
Vol 87 (2) ◽  
pp. 220-225
Author(s):  
Navid Ghavi Hossein-Zadeh ◽  
Hassan Darmani Kuhi ◽  
James France ◽  
Secundino López
Keyword(s):  
Linear Model ◽  
Milk Yield ◽  
Milk Fat ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Production Traits ◽  
Lactation Curve

AbstractThe aim of the work reported here was to investigate the appropriateness of a sinusoidal function by applying it to model the cumulative lactation curves for milk yield and composition in primiparous Holstein cows, and to compare it with three conventional growth models (linear, Richards and Morgan). Data used in this study were 911 144 test-day records for milk, fat and protein yields, which were recorded on 834 dairy herds from 2000 to 2011 by the Animal Breeding Centre and Promotion of Animal Products of Iran. Each function was fitted to the test-day production records using appropriate procedures in SAS (PROC REG for the linear model and PROC NLIN for the Richards, Morgan and sinusoidal equations) and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination $\lpar {R_{{\rm adj}}^2 } \rpar $, root mean square error (RMSE), Akaike's information criterion (AIC) and the Bayesian information criterion (BIC). $R_{{\rm adj}}^2 $ values were generally high (>0.999), implying suitable fits to the data, and showed little differences among the models for cumulative yields. The sinusoidal equation provided the lowest values of RMSE, AIC and BIC, and therefore the best fit to the lactation curve for cumulative milk, fat and protein yields. The linear model gave the poorest fit to the cumulative lactation curve for all production traits. The current results show that classical growth functions can be fitted accurately to cumulative lactation curves for production traits, but the new sinusoidal equation introduced herein, by providing best goodness of fit, can be considered a useful alternative to conventional models in dairy research.

Growth patterns of two widely distributed freshwater turtles and a comparison of common methods used to estimate age

2002 ◽  
Vol 50 (5) ◽  
pp. 477 ◽  
Author(s):  
Ricky-John Spencer
Keyword(s):  
Growth Models ◽  
Sympatric Species ◽  
Growth Patterns ◽  
Juvenile Stage ◽  
Age And Growth ◽  
Logistic Growth ◽  
Freshwater Turtles ◽  
Dietary Shift ◽  
Demographic Models ◽  
Murray River

Turtles are long lived and demographic models requiring estimates of age, growth, fecundity and survival are central for management. Most studies that estimate age and growth of freshwater turtles use annuli as an index of age without estimating its error and very few studies that use growth models include many juveniles, where growth is often large and variable. In this paper, I compare the reliability of growth annuli and common models in determining age and growth of two widely distributed turtles in Australia. Most turtles are carnivorous during the juvenile stage but many species shift to a lower-quality omnivorous diet prior to maturing. Patterns of growth are often characterised by this dietary shift and I compared the growth of a common omnivorous turtle (Emydura macquarii) and a vulnerable sympatric species that is an obligate carnivore (Chelodina expansa). Mark–recapture programs were established in three lagoons on the Murray River. In total, 1218 hatchling E. macquarii were released into two of the lagoons and growth annuli were found to be unreliable in estimating their age by Year 2. The von Bertalanffy and logistic growth models can reliably estimate age of both male and female E. macquarii and C. expansa respectively. Growth is extremely rapid during the juvenile stage of E. macquarii, but is highly variable in C. expansa, with rapid growth occurring only beyond three years of age. Hence growth models fail to predict age when juveniles are excluded from the analyses. Female E. macquarii delay maturity until 9–12 years of age because clutch size is positively related to body size and they can produce only one large clutch per year. Female C.�expansa mature later (at ~14 years) than female E. macquarii and both species are sexually dimorphic, as males mature earlier at smaller sizes than females. Common growth models describe the growth of two widely distributed freshwater turtles, but different patterns of growth and age at maturity relate to quality of diet and reproduction.

scholarly journals Coherent Mortality Forecasting for the Algerian Population

2021 ◽  
Vol 87 (3-4) ◽  
pp. 209-231
Author(s):  
Farid Flici
Keyword(s):  
Goodness Of Fit ◽  
Population Projections ◽  
Female Mortality ◽  
Male And Female ◽  
Mortality Forecasting ◽  
Algerian Population ◽  
Males And Females

Mortality forecasting is much needed for population projections and actuarial calculations. Forecasting mortality of males and females in an independent way leads in most of cases to some incoherence regarding the expected male-female mortality evolution. To avoid a possible unrealistic convergence/divergence in this sense, a coherent mortality forecasting is required. In this paper, we compare the performance of two coherent models, namely the model of Li and Lee (2005) and that of Hyndman et al. (2013) on forecasting male and female mortality of the Algerian population. Results show that the first model provides better goodness-of-fit but less coherence compared to the second one.

scholarly journals Age and growth of hilsa shad, Tenualosa ilisha (Hamilton, 1822) of the river Tentulia in Bangladesh

2015 ◽  
Vol 3 (1) ◽  
pp. 227 ◽  
Author(s):  
Rajaul Karim ◽  
Krishna Chandra Roy ◽  
Purobi Rani Roy ◽  
Zoarder Faruque Ahmed
Keyword(s):  
Growth Models ◽  
Age And Growth ◽  
Coefficient Of Determination ◽  
Von Bertalanffy ◽  
Length Frequency ◽  
Male And Female ◽  
Total Length ◽  
Growth Equations ◽  
Tenualosa Ilisha ◽  
Length Frequency Data

This study was carried out on age and growth of hilsa shad, Tenualosa ilisha in river Tentulia in Bhola district using monthly samples from January to December 2009 by checking annual rings or growth checks on hard parts. Age and growth of T. ilisha got progressed by direct fit of length frequency data both to standard and to modified von Bertalanffy growth models with ELEFAN I procedure where the predicted maximum total length were (TL∞) 41.88 cm for male and 52.40 cm for female. Powell-Wetherall procedure gave an initial asymptotic total length (TL∞) for both male and female 40.42 cm, 50.61 cm respectively. The values of Z/K were 3.362 for male and 2.626 for female. The growth co-efficient (K) was obtained as 1.40 year-1 for male and 1.00 year-1 for female. The von Bertalanffy growth equations in terms of body weight (BW) for both male and female were BWt=799.26[1-exp{-1.40(t+0.002)}]3 and BWt=1717.82[1-exp{-0.99(t+0.013)}]3 respectively. The length-weight relationship for both sexes were BW=0.0101 TL 3.02 for male and BW=0.0086 TL 3.08 for female. The value of coefficient of determination (R2) was estimated for both male and female species were 0.969 and 0.968.

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 Investigation of the growth patterns of non-functioning pituitary macroadenomas using volumetric assessments on serial MRI investigations

2016 ◽  
Vol 20 (1) ◽  
Author(s):  
Jaco Pieterse ◽  
Coert S. De Vries ◽  
Susanna F. Otto
Keyword(s):  
Growth Curve ◽  
Exponential Growth ◽  
Tumour Growth ◽  
Growth Models ◽  
Mass Effect ◽  
Growth Patterns ◽  
Logistic Growth ◽  
Serial Mri ◽  
Pituitary Macroadenomas

Background: Benign non-functioning pituitary macroadenomas (NFMA) often cause mass effect on the optic chiasm necessitating transsphenoidal surgery to prevent blindness.However, surgery is complicated and there is a high tumour recurrence rate. Currently, very little is known about the natural (and residual post-surgical) growth patterns of these NFMA. Conflicting data describe decreased growth to exponential growth over various time periods.Due to lack of information on growth dynamics of these NFMA, suitable follow-up imaging protocols have not been described to date.Objective: To determine if NFMA grow or stay quiescent over a time period using serial MRI investigations and a stereo logical method to determine tumour volume. In addition, to evaluate if NFMA adhere to a certain growth pattern or grow at random.Method: Thirteen patients with NFMA had serial MRI investigations over a 73-month period at the Universitas Academic Hospital. Six of the selected patients had undergone previous surgery, while seven patients had received no medical or surgical intervention. By using astereological method, tumour volumes were calculated and plotted over time to demonstrate growth curves. The data were then fitted to tumour growth models already described in literature in order to obtain the best fit by calculating the r2 value.Results: Positive tumour growth was demonstrated in all cases. Tumour growth patterns of nine patients best fitted the exponential growth curve while the growth patterns of three patients best fitted the logistic growth curve. The remaining patient demonstrated a linear growth pattern.Conclusion: A specific growth model best described tumour growth observed in non-surgical and surgical cases. If follow-up imaging confirms positive growth, future growth can be predicted by extrapolation. This information can then be used to determine the relevant follow-up-imaging interval in each individual patient.

scholarly journals Growth And Reproduction Of Mulloway Fish (Argyrosomus japonicus) In Estuary Area, Merauke Regency

2018 ◽  
pp. 35
Author(s):  
Sunarni Sunarni ◽  
Modesta R Maturbongs
Keyword(s):  
Condition Factor ◽  
Growth Patterns ◽  
Fish Growth ◽  
Research Station ◽  
Maturity Level ◽  
Male And Female ◽  
Coastal City ◽  
Management Effort ◽  
Males And Females ◽  
Growth And Reproduction

Gulamah fish bioecological research (Argyrosomus japonicas) in the estuary area of the coastal city of Merauke is very important to be done as a management effort. The purpose of the research on the bioecological of Gulamah fish in the estuary area of the coastal city of Merauke is to study aspects of population dynamics and reproductive biology aspects. The study was conducted in the Estuari area of the coastal city of Merauke for 3 months in November 2017 - January 2018. The research station was determined by purposive sampling. Gulamah fish growth patterns based on long and heavy relationship data are allometric negative. fish Gulamah males and females both at station I and station II also have relatively the same condition factor. The sex ratio between male and female Gulamah fish is 1: 1. Maturity level of gonad fish Gulamah caught during the research is still at TKG 1.

scholarly journals Stochastic Evolution of Pancreatic Cancer Metastases During Logistic Clonal Expansion

2019 ◽  
pp. 1-11 ◽  
Author(s):  
Kimiyo N. Yamamoto ◽  
Lin L. Liu ◽  
Akira Nakamura ◽  
Hiroshi Haeno ◽  
Franziska Michor
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Progression ◽  
Growth Models ◽  
Treatment Strategies ◽  
Evolutionary Model ◽  
Growth Patterns ◽  
Logistic Growth ◽  
Metastatic Progression ◽  
Treatment Regimens ◽  
Analytical Approximations

Despite recent progress in diagnostic and multimodal treatment approaches, most cancer deaths are still caused by metastatic spread and the subsequent growth of tumor cells in sites distant from the primary organ. So far, few quantitative studies are available that allow for the estimation of metastatic parameters and the evaluation of alternative treatment strategies. Most computational studies have focused on situations in which the tumor cell population expands exponentially over time; however, tumors may eventually be subject to resource and space limitations so that their growth patterns deviate from exponential growth to adhere to density-dependent growth models. In this study, we developed a stochastic evolutionary model of cancer progression that considers alterations in metastasis-related genes and intercellular growth competition leading to density effects described by logistic growth. Using this stochastic model, we derived analytical approximations for the time between the initiation of tumorigenesis and diagnosis, the expected number of metastatic sites, the total number of metastatic cells, the size of the primary tumor, and survival. Furthermore, we investigated the effects of drug administration and surgical resection on these quantities and predicted outcomes for different treatment regimens. Parameter values used in the analysis were estimated from data obtained from a pancreatic cancer rapid autopsy program. Our theoretical approach allows for flexible modeling of metastatic progression dynamics.

scholarly journals Nonlinear modelling of sheep and goat populations in India

2016 ◽  
Vol 8 (4) ◽  
pp. 1766-1769
Author(s):  
Leena Dilliwar ◽  
Med Ram Verma ◽  
Yash Pal Singh ◽  
Vijay Bahadur Sharma ◽  
Sanjay Kumar ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Census Data ◽  
Growth Models ◽  
Animal Husbandry ◽  
Absolute Error ◽  
Information Criteria ◽  
Coefficient Of Determination ◽  
Sheep Population ◽  
Nonlinear Growth ◽  
Goat Population

The objective of this paper was to study the trend in population of sheep and goat populations during 1951 to 2012 in India. The data were compiled from various issues of BAHS (Basic Animal Husbandry Statistics) for the period 1951 to 2012. Different nonlinear growth models such as Parabolic/Sikka, Brody, Brody modified, Wood, Logistic and Gompertz models were fitted to the census data of sheep and goat population. The goodness of fit of the models was tested by Coefficient of determination (R2), Adjusted coefficient of determination (R2), Mean Square Error (MSE), Mean Absolute Error (MAE) and Akaike Information Criteria (AIC). The populations of sheep and goat in India during the year 1951 were 39.10 million and 47.20 million numbers respectively and reached 135.17 million and 65.06 million respectively in the year 2012. Based on the various measures of goodness of fit we observed that the Parabolic/Sikka model was the best fitted model for studying the pattern in the populations of sheep and goat in India. This model has been used to project the sheep and goat population in India during 2020, 2025 and 2030. If the present pattern of growth continued in near future then the projected sheep population will be 102.37 million numbers whereas goat population will be 151.57 million numbers in the year 2030. The present study will provide the pattern in which the changes have been observed in sheep and goat populations in India during 1951 to 2012.

Sign in / Sign up

Export Citation Format

Share Document