scholarly journals Describing the growth curve of local turkey using non-linear models

2018 ◽  
pp. 7104-7107
Author(s):  
Aureliano Juárez-Caratachea ◽  
Iván Delgado-Hurtado ◽  
Ernestina Gutiérrez-Vázquez ◽  
Guillermo Salas-Razo ◽  
Ruy Ortiz-Rodríguez ◽  
...  
Keyword(s):  
Growth Curve ◽  
Visual Analysis ◽  
Linear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Von Bertalanffy ◽  
Commercial Feed ◽  
Non Linear ◽  
Best Fitting ◽  
Multiple Determination

Objective. Determine the best non-linear model to fit the growth curve of local turkeys managed under confinement in Michoacan, Mexico. Material and methods. Twenty-four and 43 female and male turkeys, reared under commercial conditions were given commercial feed. Birds were weighed weekly from hatch to 29 weeks of age. The Gompertz, Brody, Richards, von Bertalanffy and Logistic models were chosen to describe the age-weight relationship. Results. The best fitting model was selected based on the multiple determination coefficient (R2), the Akaike information criterion (AIC) and visual analysis of the observed and predicted curves. In both female and male, von Bertalanffy was the best model. The highest estimates of parameter A (mature weight) for both females and males were obtained with the von Bertalanffy model followed by the Gompertz and Logistic. The estimates of A were higher for males than for females. The highest estimates of parameter k (rate of maturity) for both females and males were, in decreasing order, for the Logistic, Gompertz, and von Bertalanffy models. k values for female turkeys was higher than for males. The age at the point of inflection (TI) and body weight at the age of point of inflection (WI) varied with the model used. The largest values of TI and WI corresponded to the Logistic model. Between sexes, the largest TI and WI values corresponded to males. Conclusions. The best models to describe turkey growth was the von Bertalanffy because it present the highest R2 and lowest AIC values.

scholarly journals Non-linear growth models for bullfrog tadpoles

2012 ◽  
Vol 36 (4) ◽  
pp. 454-462 ◽  
Author(s):  
Cleber Fernando Menegasso Mansano ◽  
Marta Verardino De Stéfani ◽  
Marcelo Maia Pereira ◽  
Beatrice Ingrid Macente
Keyword(s):  
Growth Rate ◽  
Weight Gain ◽  
Linear Models ◽  
Logistic Models ◽  
Biological Data ◽  
Von Bertalanffy ◽  
Initial Weight ◽  
Absolute Deviation ◽  
Total Length ◽  
Non Linear

Describing animal growth rate using non-linear models allows a detailed evaluation of growth behavior. Four non-linear models were used to fit weight gain and total length data of bullfrog (Lithobates catesbeianus) tadpoles, as follows: Gompertz, Y = A exp (-exp (-b (t-T))); Von Bertalanffy, Y = A (1 - K exp (-B t))³; Logistic, Y = A (1+ K exp (-B t))-1 and Brody, Y=A (1 - K exp (-B t)). We used 3,240 tadpoles, with average initial weight 0.044 g and average total length 12.79 mm, stage 25 Gosner. The measurements were conducted every ten days on 10% of the animals in every tank. The criteria used to select the model that best described the growth curve were: Residual Mean Square (RMS); determination coefficient (R²); residual graphical analysis; residual mean absolute deviation (MAD). Brody mathematical model was not a good fit for weight gain and total length, while Von Bertalanffy model underestimated tadpole initial weight, thus showing the difficulty of mathematical models to describe biological data at this growth stage. However, the Gompertz and Logistic models were considered to be an adequate fitting to describe growth rate and total length of bullfrog tadpoles in captivity.

Passage rate of solids and fluids in the digestive tract of buffaloes, cattle and sheep: selection of non-linear model

1997 ◽  
Vol 64 (1) ◽  
pp. 63-69 ◽  
Author(s):  
A. Amici ◽  
S. Bartocci ◽  
S. Terramoccia ◽  
F. Martillotti
Keyword(s):  
Linear Models ◽  
Latin Square ◽  
Sums Of Squares ◽  
Passage Rate ◽  
Significant Difference ◽  
Age Dependent ◽  
Non Linear ◽  
Best Fitting ◽  
Kinetics Of ◽  
Selection Of

AbstractFive mathematical models were compared to select the most satisfactory model to describe digesta kinetics of solids and fluids in the gastrointestinal tract of buffaloes (Mediterranean bulls), cattle (Friesian bulls) and sheep (Delle Langhe rams) given food at maintenance level, according to a Latin-square arrangement for four consecutive periods of 21 days. Chromium mordanted alfalfa hay and cobalt-ethylenediamine tetraacetic acid were used as nonabsorbable markers and were administered through the rumen cannula in a single dose. Four different isonitrogenous diets (N × 6·25 = 140 g/kg dry matter) with different concentrate:forage ratios (12·5:87·5, 25:75, 37·5:62·5, 50:50) were used.Faecal chromium and cobalt concentration curves were fitted with five non-linear models: three gamma (G2, G3, G4) age-dependent one-compartment, one gamma age-dependent/age-independent two-compartment (G2G1) and one multicompartment (MC).Wilcoxon tests on residual sums of squares of the different models for solids showed that MC and G4 gave a better fit than G2G1, G2, G3 for all the data and within the species. The comparison of MC v. G4 did not show any significant difference (P > 0·05) for all the data computed together or within each species. Nevertheless, MC had a higher number of curves with lower residual sums of squares in comparison with G4 and was also able to produce estimates of digesta kinetics in the second compartment.The cobalt excretion curves for fluids, considering all the data, and only within sheep, showed G4 as the best fitting model. When G4 was compared with other models no significant differences were recorded either for cattle: G4 v. G2 (F = 0·6645), G4 v. G2G1 (P = 0·0620) and for buffalo: G4 v. G2 (P = 0·1575), G4 v.G3(P = 0·0796) and G4 v. G2G1 (P = 0·1641).It is concluded that the multicompartment model (MC) and G4 model were the best fits for solids and for fluids respectively.

scholarly journals Estimation of growth curve parameters in Mehraban sheep using different non-linear models

Genetika ◽  
2020 ◽  
Vol 52 (2) ◽  
pp. 815-823
Author(s):  
Meysam Latifi ◽  
Mehdi Bohlouli
Keyword(s):  
Growth Curve ◽  
Linear Models ◽  
Non Linear

scholarly journals Nonlinear models in the height description of the Rhino sunflower cultivar

2022 ◽  
Vol 52 (3) ◽  
Author(s):  
Anderson Chuquel Mello ◽  
Marcos Toebe ◽  
Rafael Rodrigues de Souza ◽  
João Antônio Paraginski ◽  
Junior Carvalho Somavilla ◽  
...  
Keyword(s):  
Growth Curve ◽  
Critical Points ◽  
Nonlinear Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Maximum Acceleration ◽  
Inflection Points ◽  
Best Fitting ◽  
Microsoft Office

ABSTRACT: Sunflower produces achenes and oil of good quality, besides serving for production of silage, forage and biodiesel. Growth modeling allows knowing the growth pattern of the crop and optimizing the management. The research characterized the growth of the Rhino sunflower cultivar using the Logistic and Gompertz models and to make considerations regarding management based on critical points. The data used come from three uniformity trials with the Rhino confectionery sunflower cultivar carried out in the experimental area of the Federal University of Santa Maria - Campus Frederico Westphalen in the 2019/2020 agricultural harvest. In the first, second and third trials 14, 12 and 10 weekly height evaluations were performed on 10 plants, respectively. The data were adjusted for the thermal time accumulated. The parameters were estimated by ordinary least square’s method using the Gauss-Newton algorithm. The fitting quality of the models to the data was measured by the adjusted coefficient of determination, Akaike information criterion, Bayesian information criterion, and through intrinsic and parametric nonlinearity. The inflection points (IP), maximum acceleration (MAP), maximum deceleration (MDP) and asymptotic deceleration (ADP) were determined. Statistical analyses were performed with Microsoft Office Excel® and R software. The models satisfactorily described the height growth curve of sunflower, providing parameters with practical interpretations. The Logistics model has the best fitting quality, being the most suitable for characterizing the growth curve. The estimated critical points provide important information for crop management. Weeds must be controlled until the MAP. Covered fertilizer applications must be carried out between the MAP and IP range. ADP is an indicator of maturity, after reaching this point, the plants can be harvested for the production of silage without loss of volume and quality.

scholarly journals Evaluation of non-linear models to describe development and fertility of codling moth at constant temperatures

2017 ◽  
Vol 20 (1) ◽  
pp. 3 ◽  
Author(s):  
H. Ranjbar Aghdam ◽  
Y. Fathipour ◽  
D. C. Kontodimas
Keyword(s):  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Developmental Rate ◽  
Codling Moth ◽  
Coefficient Of Determination ◽  
Temperature Threshold ◽  
Optimum Temperature ◽  
Non Linear ◽  
Lower Temperature

Developmental rate of immature stages and age-specific fertility of females of codling moth at constant temperatures was modeled using non-linear models. The equations of Enkegaard, Analytis, and Bieri 1 and 2 were evaluated based on the value of adjusted R2 (R2adj) and Akaike information criterion (AIC) besides coefficient of determination (R2) and residual sum of squares (RSS). All models have goodness of fit to data especially for development [R2, R2adj, RSS and AIC ranged 0.9673-0.9917, 0.8601-0.9861, 0.08-6.7x10-4 and (-75.29) – (-46.26) respectively]. Optimum temperature (Topt) and upper threshold (Tmax) were calculated accurately (Topt and Tmax ranged 29.9-31.2oC and 35.9-36.7oC) by all models. Lower temperature threshold (Tmin) was calculated accurately by Bieri-1 model (9,9-10,8oC) whereas Analytis model (7,0-8,4oC) underestimated it. As far as fertility is concerned the respective values were better fitted near the optimum temperature (in 30oC) [R2 ,R2adj, RSS and AIC ranged 0,6966-0,7744, 0,5756-0,6455, 2,44-3,33 x10-4 and (-9,15)-7,15 respectively].

scholarly journals Proposals of non-linear models to adjust in vitro gas production at different incubation times in cassava genotypes

2021 ◽  
Vol 43 ◽  
pp. e22
Author(s):  
André Luiz Pinto dos Santos ◽  
Frank Sinatra Gomes da Silva ◽  
Guilherme Rocha Moreira ◽  
Cícero Carlos Ramos de Brito ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Logistic Models ◽  
Information Criterion ◽  
Gas Production ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
In Vitro Gas Production ◽  
The One

The present study aimed to propose new two-compartment models from the combination of the Gompertz, Logistic and Von Bertalanffy models and to identify between Gompertz and Logistic models, in their uni and two-compartiment versions, the one that presents the highest quality of fit to cumulative gas production curves of five cassava genotypes: Brasília, Engana Ladrão, Dourada, Gema de Ovo e Amansa Burro. The gas production readings were 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 hours after the start of the in vitro fermentation process. The estimation of the parameters for the models was made by the least squares method through the Gauss-Newton iterative process. The selection of the best model to describe the gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion and Bayesian information criterion. Among the adjusted models, the proposed models were the best to describe the accumulation of gases over time according to the methodology and conditions under which this study was developed.

scholarly journals Evaluation of Non-linear Models to Predict Potential Milk Yield of Beef Cows According to Parity Order Under Grazing

2021 ◽  
Vol 8 ◽  
Author(s):  
Matheus Fellipe de Lana Ferreira ◽  
Luciana Navajas Rennó ◽  
Isabela Iria Rodrigues ◽  
Sebastião de Campos Valadares Filho ◽  
Luiz Fernando Costa e Silva ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Linear Models ◽  
Nonlinear Models ◽  
Information Criterion ◽  
Beef Cows ◽  
Total Solids ◽  
Lactation Curve ◽  
Non Linear ◽  
Milking Machine

This study aimed to evaluate the effect of parity order on milk yield (MY) and composition over time of grazing beef cows and to evaluate non-linear models to describe the lactation curve. Thirty-six pregnant Nellore cows (12 nulliparous, 2 years; 12 primiparous, 3 years; and 12 multiparous, 4–6 years) were included in the study. With calving day assigned as day 0, milking was performed using a milking machine to estimate MY on days 7, 14, 21, 42, 63, 91, 119, 154, and 203. Dummy variable analyses were applied to estimate its effects on MY, composition (kg and percentage), afternoon/morning, and afternoon/total proportions. Since multiparous cows had higher MY than nulliparous and primiparous cows, two different groups were used for lactation curve analysis: Mult (multiparous) and Null/Prim (nulliparous and primiparous). The MY estimated by the last edition of BR-Corte (Nutrient Requirements of Zebu and Crossbred Cattle) equation was compared with the observed values from this study. Five nonlinear models proposed by Wood (WD), Jenkins & Ferrell (JF), Wilmink (WK), Henriques (HR) and Cobby & Le Du (CL) were evaluated. Models were validated using an independent dataset of multiparous and primiparous cows. The estimates for parameters a, b, and c of the CL equation were compared between groups, and the BR-Corte equation used the model identity methodology. Nulliparous and primiparous cows displayed similar MY (P > 0.05); however, multiparous cows had an average MY that is 0.70 kg/day greater than that of nulliparous and primiparous cows (P < 0.05). Milk protein and total solids were higher for multiparous cows (P < 0.05). Effect of days in milking was found for milk fat, protein, and total solids (P < 0.05). The yield of all milk components was higher for multiparous cows than for nulliparous and primiparous cows. The afternoon/morning and afternoon/total proportions of milk production were not affected by parities and days in milking (P > 0.05), with an average of 0.76 and 0.42, respectively. The BR-Corte equation did not correctly estimate the MY (P < 0.05). The equations of WD, WK, and CL had the best estimate of MY for both Mult and Null/Prim datasets. The equations had a very similar Akaike's information criterion with correction and mean square error of prediction.

scholarly journals Comparison of the parameters of the lactation curve between normal and difficult calvings in Iranian Holstein cows

2019 ◽  
Vol 17 (1) ◽  
pp. e0401
Author(s):  
Navid Ghavi Hossein-Zadeh
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Lactation Curve ◽  
Non Linear ◽  
Best Fit

To evaluate effect of dystocia on the lactation curve characteristics for milk yield and composition in Holstein cows, six non-linear models (Brody, Wood, Sikka, Nelder, Dijkstra and Rook) were fitted on 5,917,677 test day records for milk yield (MY), fat (FP) and protein (PP) percentages, fat to protein ratio (FPR) and somatic cell score (SCS) of 643,625 first lactation Holstein cows with normal calving or dystocia from 3146 herds which were collected by the Animal Breeding Center of Iran. The models were tested for goodness of fit using adjusted coefficient of determination, root means square error, Akaike’s information criterion and Bayesian information criterion. Rook model provided the best fit of the lactation curve for MY and SCS in normal and difficult calvers and dairy cows with dystocia for FP. Dijkstra model provided the best fit of the lactation curve for PP and FPR in normal and difficult calvers and dairy cows with normal calving for FP. Dairy cows with dystocia had generally lower 100-d, 200-d and 305-d cumulative milk yield compared with normal calvers. Time to the peak milk yield was observed later for difficult calvers (89 days in milk vs. 79 days in milk) with lower peak milk yield (31.45 kg vs. 31.88 kg) compared with normal calvers. Evaluation of the different non-linear models indicated that dystocia had important negative effects on milk yield and lactation curve characteristics in dairy cows and it should be reduced as much as possible in dairy herds.

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