Comparison and estimation of the growth curve models of Hanwoo steer (Bos taurus coreanae)

2018 ◽  
Author(s):  
Hu-Rak Park ◽  
Seung-Hoon Eum ◽  
Seung-Hee Roh ◽  
Jakyeom Seo ◽  
Seong-Keun Cho ◽  
...  
Keyword(s):  
Body Weight ◽  
Logistic Model ◽  
Bos Taurus ◽  
Growth Models ◽  
Logistic Models ◽  
Regression Equations ◽  
Von Bertalanffy ◽  
Growth Data ◽  
Growth Ratio ◽  
Mean Square Errors

The present study was conducted to estimate and compare the three types of growth models in Hanwoo steer (Bos aurus coreanae). The Gompertz, Von Bertalanffy, and Logistic nonlinear models were used. A total of 2,239 Hanwoo steers (Bos taurus coreanae) from 6 months to 24 months old (2003 to 2014) and 8,916 growth data from the Hanwoo improvement Center were used to estimate the growth model which included three parameters. These parameters were A, mature body weight; b, growth ratio; and k, intrinsic growth rate. Regression equations using the Gompertz, Von Bertalanffy, and Logistic models were calculated as respectively. The mean square errors (MSEs) for each model were 1945.9, 1958.7, and 1935.0, respectively. The equation using the Logistic model showed the lowest value among three models. The estimated birth weights from the Gompertz, Von Bertalanffy, and Logistic models were 50.35 kg, 36.94 kg, and 74.13 kg, respectively. Furthermore, the estimated mature weights from the Gompertz, Von Bertalanffy, and Logistic models were 919.0 kg, 1043.3 kg, and 770.0 kg, respectively. In addition, the estimated age and body weight at inflection from the Gompertz, Von Bertalanffy, and Logistic models were 349.0 days and 338.1 kg, 317.9 days and 308.2 kg, and 397.8 days and 385.0 kg, respectively. Based on the results, we concluded that the regression equation using the Logistic model was the most appropriate among the growth models for measuring data. However, further studies would be needed in order to obtain more accurate parameters using a much wider period of data from birth to shipping age.

scholarly journals Modelagem otimizada de indicadores biológicos de qualidade da água

Revista DAE ◽  
2019 ◽  
Vol 221 (68) ◽  
pp. 131-141
Author(s):  
Gabriel da Costa Cantos Jerônimo ◽  
Luiz Felipe Ramos Turci ◽  
Paulo Augusto Zaitune Pamplin ◽  
Patrícia Neves Mendes
Keyword(s):  
Population Growth ◽  
Logistic Model ◽  
Growth Models ◽  
Lemna Minor ◽  
Growth Data ◽  
Model Quality ◽  
Nonlinear Growth ◽  
Statistical Indicators ◽  
Selection Of

Resumo 27/06/2018 DOI: https://doi.org/10.36659 /dae.2020.011 Turci, L. F. R Pamplin, P. A. Z https://orcid.org/0000-0001-7516-0963 https://orcid.org/0000-0001-7318-9121 O estudo de plantas aquáticas (macrófitas) é importante, uma vez que essas plantas apresentam potencial de utilização em estudos de ecotoxicologia, como bioindicadores no tratamento de águas residuárias. A mode- lagem criteriosa do crescimento dessas plantas, especificamente a Lemna minor, é útil na determinação das condições de otimização dessas aplicações; assim, deseja-se sempre obter o modelo que melhor represente a dinâmica de crescimento populacional da planta em estudo. Neste trabalho, apresenta-se uma metodologia de ajuste e seleção de modelos de crescimento não lineares com base em indicadores estatísticos que servem como avaliadores de qualidade dos modelos. Para ilustrar o uso da metodologia, foi feito o cultivo de Lemna minor em meio Steinberg e foram ajustados três modelos aos dados médios de crescimento de suas frondes, selecionando o modelo Logístico como o melhor. Palavras-chave: Modelo de crescimento populacional. Avaliadores de qualidade. Lemna minor. Abstract The study of aquatic plants (macrophytes) is important since such plants present a potential utilization in ecotoxi- cology as bioindicators, as well in wastewater treatment. The criterious growth modelling of such plants, specifically Lemna minor, is useful for the determination of the optimal conditions of mentionedin applications - so one always looks for the best model that represents the dynamic of population growth of the plant in study. This work presents a methodology of adjustment and selection of nonlinear growth models based on statistical indicators, which work as quality evaluators for the models. To illustrate this methodology, Lemna minor was grown in Steinberg environ- ment, and three models were fitted to the fronds growth data, the Logistic model was selected as the best model. Keywords: Population growth model. Quality evaluators. Lemna minor.

scholarly journals Growth Patterns of birds, dinosaurs and reptiles: Are differences real or apparent?

2019 ◽  
Author(s):  
Norbert Brunner ◽  
Manfred Kühleitner ◽  
Werner-Georg Nowak ◽  
Katharina Renner-Martin ◽  
Klaus Scheicher
Keyword(s):  
Differential Equation ◽  
Growth Pattern ◽  
Broiler Chicken ◽  
Growth Models ◽  
Growth Patterns ◽  
Von Bertalanffy ◽  
Growth Data ◽  
Quantitative Studies ◽  
Best Fitting

AbstractSystematics of animals was done on their appearance or genetics. One can also ask about similarities or differences in the growth pattern. Quantitative studies of the growth of dinosaurs have made possible comparisons with modern animals, such as the discovery that dinosaurs grew in relation to their size faster than modern reptiles. However, these studies relied on only a few growth models. If these models are false, what about the conclusions? This paper fits growth data to a more comprehensive class of models, defined by the von Bertalanffy-Pütter differential equation. Applied to data about dinosaurs, reptiles and birds, the best fitting models confirmed that dinosaurs may have grown faster than alligators. However, compared to modern broiler chicken, this difference was small.

scholarly journals Description of the growth of pequi fruits by nonlinear models

2018 ◽  
Vol 40 (4) ◽  
Author(s):  
Thais Destefani Ribeiro ◽  
Ricardo Wagner Pacopahyba de Mattos ◽  
Augusto Ramalho de Morais ◽  
Joel Augusto Muniz
Keyword(s):  
Least Squares Method ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Fresh Mass ◽  
Initial Growth ◽  
Von Bertalanffy ◽  
Growth Data ◽  
Cross Sectional ◽  
Mass Data ◽  
Days After Anthesis

Abstract Pequi tree is a species native to the Brazilian cerrado, with wide geographic distribution, whose fruit is very appreciated in cooking, composing traditional dishes. In general, pequi fruit is consumed when ripe in the fresh form or in the various derived products such as oils, liqueurs, sweets, ice creams among others, involving important socioeconomic activity generating employment and income in family agriculture. The aim of this study was to evaluate the adjustment of Brody, Gompertz, Logistic and Von Bertalanffy models in the growth and development of pequi fruits based on their physical characteristics such as longitudinal and cross-sectional diameter and fresh mass obtained over time. Parameters were estimated using R software routines, using the least squares method and the Gauss-Newton iterative process. The adjustment of models was compared using the following criteria: residual standard deviation, adjusted determination coefficient and corrected Akaike information criterion. In general, data presented no correlation error structure and the Von Bertalanffy model did not fit fresh mass data. The models presented good quality in the adjustment to pequi growth data, except for the Brody model for fresh mass. The Gompertz and Logistic models were those that best described variables, and the Gompertz model was the most suitable to describe diameter and mass data. Based on the adjustment, a slow initial growth was observed up to about 20 days after anthesis; after this period, the fruit developed more rapidly up to 90 days and then presented a tendency to stability until the end of the evaluation period at 117 days after anthesis, with sigmoid curve character. Pequi fruits obtained final average value of 7.1 cm for cross-sectional diameter, 6.8 cm for longitudinal diameter and 113g for fresh mass.

scholarly journals Classical nonlinear models to describe the growth curve for Murrah buffalo breed

2012 ◽  
Vol 42 (3) ◽  
pp. 520-525 ◽  
Author(s):  
Ronyere Olegário de Araújo ◽  
Cintia Righetti Marcondes ◽  
Maria Cecília Florisbal Damé ◽  
Analía del Valle Garnero ◽  
Ricardo José Gunski ◽  
...  
Keyword(s):  
Logistic Model ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Growth Curves ◽  
Coefficient Of Determination ◽  
Von Bertalanffy ◽  
Average Deviation ◽  
Absolute Deviation ◽  
Murrah Buffalo ◽  
Deviation Coefficient

With the objective of to adjust nonlinear models for the growth curves for a buffaloes herd raised in floodable lands in Rio Grande do Sul state, monthly records measured from birth to two years-old of 64 males and 63 females born between 1982 and 1989 were used. The models used were: Von Bertalanffy, Brody, Gompertz and Logistic. The parameters were estimated by NLIN procedure and the criteria used to evaluate the adjustment given by the models were: asymptotic standard deviation; coefficient of determination; average absolute deviation of residues and asymptotic index. Von Bertalanffy and Brody models overestimated the male asymptotic weight (A) in 15.9 and 171.3kg, respectively, and the Gompertz and Logistic models underestimated it in 4.5 and 13.4kg, respectively. For females, the Logistic model underestimated the asymptotic weight (-2.09kg), and Gompertz, Von Bertalanffy and Brody overestimated this parameter in 8.04, 17.7, and 280.33kg, respectively. The biggest average deviation was estimated by Brody model for both sexes, characterizing the biggest index. Considering the criteria, it is recommended the Gompertz and Logistic models for adjust females and males Murrah buffaloes breed growth curves.

scholarly journals Growth Models for Lettuce Cultivars Growing in Spring

2019 ◽  
Vol 11 (6) ◽  
pp. 147
Author(s):  
Fernanda Carini ◽  
Alberto Cargnelutti Filho ◽  
Cirineu Tolfo Bandeira ◽  
Ismael Mario Marcio Neu ◽  
Rafael Vieira Pezzini ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Critical Points ◽  
Logistic Model ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Logistic Models ◽  
Thermal Sum ◽  
Beginning Of Flowering

The objectives of this study were to adjust the Gompertz and logistic models to fit the fresh and dry matters of leaves and fresh and dry matters of shoots of four lettuce cultivars and indicate the model that best describes the growth in spring. Cultivars Ceres, Gloriosa, Grandes Lagos, and Rubinela were grown in protected environment and in soilless system, in the spring of 2016 and 2017. Seven days after transplantation, fresh and dry leaf matters and fresh and dry shoot matters were weighed every four days until beginning of flowering. The Gompertz and logistic models were adjusted as a function of accumulated thermal sum. The parameters of the Gompertz and logistic models and their confidence intervals were estimated, the assumptions of the models were verified, the goodness-of-fit measures and critical points were calculated, and the parametric and intrinsic nonlinearities quantified. The logistic and Gompertz growth models fitted well to fresh and dry leaf and shoot matters of cultivars Ceres, Gloriosa, Grandes Lagos, and Rubinela, under spring conditions. The logistic model is the most suitable to describe the growth of lettuce cultivars.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals ASAS-NANP SYMPOSIUM: Applications of machine learning for livestock body weight prediction from digital images

2021 ◽  
Vol 99 (2) ◽  
Author(s):  
Zhuoyi Wang ◽  
Saeed Shadpour ◽  
Esther Chan ◽  
Vanessa Rotondo ◽  
Katharine M Wood ◽  
...  
Keyword(s):  
Machine Learning ◽  
Body Weight ◽  
Optical Sensors ◽  
Genetic Selection ◽  
Medium Size ◽  
Regression Equations ◽  
Infrared Cameras ◽  
Applications Of Machine Learning ◽  
Corrosive Environments ◽  
Partial Weight

Abstract Monitoring, recording, and predicting livestock body weight (BW) allows for timely intervention in diets and health, greater efficiency in genetic selection, and identification of optimal times to market animals because animals that have already reached the point of slaughter represent a burden for the feedlot. There are currently two main approaches (direct and indirect) to measure the BW in livestock. Direct approaches include partial-weight or full-weight industrial scales placed in designated locations on large farms that measure passively or dynamically the weight of livestock. While these devices are very accurate, their acquisition, intended purpose and operation size, repeated calibration and maintenance costs associated with their placement in high-temperature variability, and corrosive environments are significant and beyond the affordability and sustainability limits of small and medium size farms and even of commercial operators. As a more affordable alternative to direct weighing approaches, indirect approaches have been developed based on observed or inferred relationships between biometric and morphometric measurements of livestock and their BW. Initial indirect approaches involved manual measurements of animals using measuring tapes and tubes and the use of regression equations able to correlate such measurements with BW. While such approaches have good BW prediction accuracies, they are time consuming, require trained and skilled farm laborers, and can be stressful for both animals and handlers especially when repeated daily. With the concomitant advancement of contactless electro-optical sensors (e.g., 2D, 3D, infrared cameras), computer vision (CV) technologies, and artificial intelligence fields such as machine learning (ML) and deep learning (DL), 2D and 3D images have started to be used as biometric and morphometric proxies for BW estimations. This manuscript provides a review of CV-based and ML/DL-based BW prediction methods and discusses their strengths, weaknesses, and industry applicability potential.

scholarly journals Age and growth of franciscana dolphins, Pontoporia blainvillei (Cetacea: Pontoporiidae) incidentally caught off southern Brazil and northern Argentina

2010 ◽  
Vol 90 (8) ◽  
pp. 1493-1500 ◽  
Author(s):  
Silvina Botta ◽  
Eduardo R. Secchi ◽  
Mônica M.C. Muelbert ◽  
Daniel Danilewicz ◽  
Maria Fernanda Negri ◽  
...  
Keyword(s):  
Growth Models ◽  
Growth Curves ◽  
Small Sample ◽  
Age And Growth ◽  
Buenos Aires Province ◽  
Von Bertalanffy ◽  
Southern Brazil ◽  
Data Set ◽  
Males And Females ◽  
Pontoporia Blainvillei

Age and length data of 291 franciscana dolphins (Pontoporia blainvillei) incidentally captured on the coast of Rio Grande do Sul State (RS), southern Brazil, were used to fit growth curves using Gompertz and Von Bertalanffy growth models. A small sample of franciscanas (N = 35) from Buenos Aires Province (BA), Argentina, were used to see if there are apparent growth differences between the populations. Male and female franciscana samples from both areas were primarily (78–85%) <4 years of age. The Von Bertalanffy growth model with a data set that excluded animals <1 year of age provided the best fit to data. Based on this model, dolphins from the RS population reached asymptotic length at 136.0 cm and 158.4 cm, for males and females, respectively. No remarkable differences were observed in the growth trajectories of males and females between the RS and BA populations.

scholarly journals The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Thais Destefani Ribeiro ◽  
Taciana Villela Savian ◽  
Tales Jesus Fernandes ◽  
Joel Augusto Muniz
Keyword(s):  
Logistic Model ◽  
Least Squares Method ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Fruit Weight ◽  
Coefficient Of Determination ◽  
Pear Fruit ◽  
Asian Pear ◽  
Residual Correlations

ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.

scholarly journals Body composition and net and dietary macrominerals requirements of Nellore steers under grazing

2009 ◽  
Vol 38 (6) ◽  
pp. 1081-1087 ◽  
Author(s):  
Vitor Visintin Silva de Almeida ◽  
Augusto César de Queiroz ◽  
Robério Rodrigues Silva ◽  
Fabiano Ferreira da Silva ◽  
Aline Cardoso Oliveira ◽  
...  
Keyword(s):  
Body Weight ◽  
Reference Group ◽  
Average Daily Gain ◽  
The Body ◽  
Regression Equations ◽  
Animal Body ◽  
Randomized Design ◽  
Dietary Requirements ◽  
Mineral Mixture ◽  
Daily Gain

This experiment was carried out with the objective of determining the macrominerals (Ca, P, Mg, K and Na) requirements of Nellore steers under grazing. Twenty four Nellore steers (371 ± 14 kg of BW and 26 mo old) were used. Four steers were slaughtered at the beginning of the experiment (reference group), serving as a reference in subsequent study. The remaining 20 animals were weighed and distributed into a completely randomized design with four supplementation levels offer: 0.0 (mineral mixture - control), 0.3, 0.6 and 0.9% of BW, with five replications. The supplements, based on ground corn, soybean meal and/or urea, were previously balanced to achieve an average daily gain of 350, 650 and 850g, respectively, for the different supplementation levels offer. The contents of macrominerals retained in the animal body were determined by regression equations of the macrominerals body content logarithm in function of the empty body weight logarithm (EBW). Net macrominerals requirements for a gain of 1kg of EBW were obtained using the equation Y'= b.10ª.Xb-1, with a and b, respectively, the intercept and the regression coefficient of the prediction equations of macrominerals in the animal body contents for each macromineral considered. The concentrations of all macrominerals, in the empty body weight and gain of the empty body weight, decreased with the increase in the body weight. Total calcium and phosphorus dietary requirements are higher than those recommended in the literature.

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