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.

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.

PSI-B-28 Breed effect on weight gain of broilers

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 229-229
Author(s):  
Sodiq Oladipo ◽  
Khadeejah Kareem-Ibrahim ◽  
Olatunji T Abanikannda
Keyword(s):  
Weight Gain ◽  
Linear Models ◽  
Poultry Production ◽  
Initial Weight ◽  
Southwestern Nigeria ◽  
The People ◽  
Commercial Broiler ◽  
Similar Weight ◽  
The Difference ◽  
Weight Table

Abstract Poultry production as an aspect of livestock production is important to the biological needs, economic and social development of the people in any nation. Broiler birds are specifically bred for rapid growth to attain mature body size within 7–10 weeks depending on the strain, sex and management. This study was carried out in the humid tropics of Southwestern Nigeria. The experimental units were derived from four commercial broiler breeds namely Arbor Acre, Cobb, Marshall and Ross. Each breed had 76 chicks totaling 304 across the four breeds. On arrival, each chick was tagged by breed and identification number, and the initial weight of the chicks were recorded. Each of the breeds were thereafter randomly selected and randomly assigned to four experimental plots as replicates of the same treatment. The broiler birds were reared for 10 weeks and their weight taken and recorded at weekly intervals. All statistical analyses were conducted using boxplot, descriptive statistic and general linear models of Minitab® 16. After exploratory analysis to check for normality and outliers, a total of 217 birds were used in the final analyses. Except for the Marshall breed that had a highly significantly (P < 0.01) lower weight at hatching, other breeds had fairly similar weight (Table 1). However, there was no statistical (P > 0.05) difference in mean initial weight across the four replicates. While breed alone accounted for 37.81% of the total variation in initial weight, it only accounted for 30.07% of the difference in weight gain. The effect of breed on weight gain was only significant (P < 0.01) in Marshall, while the other three breeds were not statistically different (P >0.05). It can be deduced from this study that performance in terms of weight gain of most of the commercially available breeds in Nigeria are similar with the exception of Marshall.

scholarly journals The assessment of efficient representation of drug features using deep learning for drug repositioning

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Mahroo Moridi ◽  
Marzieh Ghadirinia ◽  
Ali Sharifi-Zarchi ◽  
Fatemeh Zare-Mirakabad
Keyword(s):  
Deep Learning ◽  
Linear Models ◽  
De Novo ◽  
Drug Repositioning ◽  
Linear Method ◽  
Cost Effective ◽  
Biological Data ◽  
Non Linear ◽  
Disease Associations ◽  
Efficient Representation

Abstract Background De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly used in cases with a limited number of candidate pairs of drugs and diseases. In other words, they are not scalable to a large number of drugs and diseases. Most of the in-silico methods mainly focus on linear approaches while non-linear models are still scarce for new indication predictions. Therefore, applying non-linear computational approaches can offer an opportunity to predict possible drug repositioning candidates. Results In this study, we present a non-linear method for drug repositioning. We extract four drug features and two disease features to find the semantic relations between drugs and diseases. We utilize deep learning to extract an efficient representation for each feature. These representations reduce the dimension and heterogeneity of biological data. Then, we assess the performance of different combinations of drug features to introduce a pipeline for drug repositioning. In the available database, there are different numbers of known drug-disease associations corresponding to each combination of drug features. Our assessment shows that as the numbers of drug features increase, the numbers of available drugs decrease. Thus, the proposed method with large numbers of drug features is as accurate as small numbers. Conclusion Our pipeline predicts new indications for existing drugs systematically, in a more cost-effective way and shorter timeline. We assess the pipeline to discover the potential drug-disease associations based on cross-validation experiments and some clinical trial studies.

scholarly journals Insulin-like growth factor-I and analogues increase growth in artificially-reared neonatal pigs

2002 ◽  
Vol 87 (6) ◽  
pp. 587-593 ◽  
Author(s):  
Frank R. Dunshea ◽  
Chung S. Chung ◽  
Phil C. Owens ◽  
John F. Ballard ◽  
Paul E. Walton
Keyword(s):  
Growth Rate ◽  
Growth Factors ◽  
Weight Gain ◽  
Milk Intake ◽  
Daily Weight Gain ◽  
Initial Weight ◽  
Increase Growth Rate ◽  
Neonatal Pigs ◽  
Igf I ◽  
Ad Libitum

Exogenous insulin-like growth factor (IGF)-I has been shown to increase growth rate in neonatal pigs while an analogue of IGF-I, long arginine (LR3) IGF-I, has been shown to be more potent than IGF-I in the rat. Therefore, two studies were conducted to determine whether IGF-I and LR3IGF-I increase growth in the artificially-reared neonatal pig. Expt 1 involved forty-two (2 kg initial weight) pigs infused with either control, IGF-I (2, 4 or 8 μg/h) or LR3IGF-I (2, 4 or 8 μg/h) infusions for 8 d. Pigs were weighed and then offered 1·7 MJ (gross energy) milk replacer/kg0·75 per d. Expt 2 involved eighteen pigs (2 kg initial weight) treated with control saline, IGF-I (8 μg/h) or LR3IGF-I (8 μg/h) infusions. After 9 d an additional pump was inserted to increase the infusion rates of each of the growth factors (16 μg/h) for a further 9 d. Cows' milk was provided ad libitum. In Expt 1 there was no overall effect of growth factors on daily weight gain or slaughter weight. However, milk intake was greater in pigs infused with growth factors (909 v. 867 g/d, P=0·027), with an apparently greater milk intake by the pigs infused with IGF-I compared with LR3IGF-I (920 v. 898 g/d, P=0·12). Infusion of LR3IGF-I decreased plasma IGF-I concentrations, but had no effect on plasma IGF-II concentrations. In Expt 2, neither IGF-I nor LR3IGF-I infusion had any effect upon daily weight gain over the first 9 d of the study. However, over the second 9 d of the study, daily weight gain was increased in LR3IGF-I-infused pigs (457 v. 386 g/d, P<0·01), but not in pigs infused with IGF-I (413 v. 386 g/d, P=0·15). Milk intake was not different during the first 9 d of the study but was significantly greater in pigs infused with growth factors over the second half of the study (3407 v. 2905 g/d, P<0·01). Plasma IGF-binding protein-3 concentrations were highly correlated (R=0·85) with average daily gain over the 3 d preceding blood sampling. In conclusion, exogenous IGF-I and particularly LR3IGF-I can increase growth rate and milk intake in artificially-reared pigs fed ad libitum but not in limit-fed piglets.

scholarly journals EVALUATION OF NON-LINEAR TAPER EQUATIONS FOR PREDICTING THE DIAMETER OF EUCALYPTUS TREES

2018 ◽  
Vol 42 (1) ◽  
Author(s):  
Guilherme Silverio Aquino de Souza ◽  
Diogo Nepomuceno Cosenza ◽  
Ana Carolina da Silva Cardoso Araújo ◽  
Lucas Veiga Ayres Pimenta ◽  
Ramon Barreto Souza ◽  
...  
Keyword(s):  
Variable Exponent ◽  
Linear Models ◽  
Mean Squared Error ◽  
Graphical Analysis ◽  
Statistical Validation ◽  
Absolute Deviation ◽  
Stem Taper ◽  
Non Linear ◽  
Identity Test ◽  
Taper Equations

ABSTRACT This study aims to evaluate non-linear stem taper models for predicting the pre-commercial diameter of eucalyptus trees and to analyze the effect of genotype on stem taper. The treatments comprise three different genotypes of Eucalyptus sp. in a 3 × 3 m plantation spacing. Seventy sample trees aged 10 years were felled for each treatment. The outside bark diameter measurements were taken at 0.5 m; 1.0 m; 1.5 m; 2.0 m, and then at intervals of 2.0 m till the top of the stem. Four non-linear models were evaluated, namely, the sigmoid model of Garay (1979), the variable exponent model of Kozak (1988), the segmented model of Max and Burkhart (1976), and the compatible model of Demaerschalk (1972). The performance of the models was assessed using the following statistical validation methods: correlation coefficient, standard error of estimate, mean bias, bias variance, root mean squared error, and mean absolute deviation. Graphical analysis of residues was used to evaluate the accuracy and precision of the estimates. Compared with other models, the variable exponent model of Kozak (1988) best described the stem profile, and predicted the total volume of the trees. The identity test showed that the stem profile is affected by the genotype.

scholarly journals Estimation of annual compound growth rates of guava (Psidium guajava L.) fruit in Haryana using Non linear model

2019 ◽  
Vol 11 (4) ◽  
pp. 778-784
Author(s):  
Pardeep Panghal ◽  
Manoj Kumar ◽  
Sarita Rani
Keyword(s):  
Growth Rate ◽  
Linear Model ◽  
Growth Rates ◽  
Logistic Model ◽  
Linear Models ◽  
Psidium Guajava ◽  
Annual Growth Rate ◽  
Guava Fruit ◽  
Non Linear ◽  
Best Fit

Computation of growth rates plays an important role in agricultural and economic research to study growth pattern of a various commodities. Many of the research workers used the parametric approach for computation of annual growth rate but not use the concept of non-linear model.  In this paper, an attempt has been made to study growth rates of guava for three districts (Hisar, and Kurukshetra) and Haryana state as a whole using different non-linear models. The time series data on annual area and production of guava (Psidium guajava L.) in different districts of Haryana from 1990-91 to 2015-16 were collected to fit non linear models. Growth rates were computed through best fitted non-linear models. It was found that Logistic model could be best fit for computation of growth rates of area for guava fruit in Hisar and Kurukshetra district and Haryana state as a whole whereas Gompertz model was best fit for Yamunanagar district based on high R2 and least MSE and RMSE values. It was also observed that monomolecular model was best fit for production of guava fruits in Hisar and Yamunanagar district whereas Logistic model was best fit for production of guava fruit in Kurukshetra and Haryana state as a whole because of high R2 and least MSE and RMSE values. R and excel software have been used for fitting the non linear model and computation of growth rates for area and production of guava fruit for the year 1990-91 to 2015-16. None has been used the non linear model growth model for computation of annual growth rate of guava fruit for area and production of Haryana state. But in this work non linear growth model has been used for computation of growth rate instead of parametric approaches.

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 Gompertz and Logistic Models to the Productive Traits of Sunn Hemp

2017 ◽  
Vol 10 (1) ◽  
pp. 225 ◽  
Author(s):  
Cláudia Marques de Bem ◽  
Alberto Cargnelutti Filho ◽  
Gabriela Görgen Chaves ◽  
Jéssica Andiara Kleinpaul ◽  
Rafael Vieira Pezzini ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Linear Models ◽  
Growth Models ◽  
Logistic Models ◽  
Information Criteria ◽  
Percentage Error ◽  
Absolute Deviation ◽  
Fresh Matter ◽  
Sunn Hemp ◽  
Productive Traits

Studies on growth models for productive character of sunn hemp are important to know the behavior of the culture. Therefore, the objective of this research was to adjust non-linear models, Gompertz and Logistic, in the description of productive traits of sunn hemp in two sowing periods. Two uniformity trials were performed. The evaluations began on October the 29th 2014 and December the 16th 2014, totaling 94 and 76 evaluation days for periods 1 and 2, respectively. After the emergence of the seeds of sunn hemp, for first period from 7 days after sowing, and from 2 to 13 days after sowing, on each day, they were collected randomly four plants. The traits: fresh matter leaf, stem, root, shoot, and total, and dry matter leaf, stem, root, shoot, and total. For both models the confidence interval was calculated of parameters a, b and c. The adjustment quality of the Gompertz and Logistic models was verified by the determination coefficient, the Akaike information criteria, residual standard deviation, mean absolute deviation, mean absolute percentage error and mean prediction error. The Gompertz model when compared between the sowing periods through the confidence interval of the parameters, for the productive traits, differs. The same result was found for the Logistic model. The growth models of Gompertz and Logistic presented good adjustment quality.

scholarly journals Pertumbuhan rumput laut Kappaphycus alvarezii hasil kultur jaringan pada jarak tanam yang berbeda

DEPIK ◽  
2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Ayuningsih Ria Sapitri ◽  
Nunik Cokrowati ◽  
Rusman .
Keyword(s):  
Growth Rate ◽  
Tissue Culture ◽  
Weight Gain ◽  
Analysis Of Variance ◽  
Kappaphycus Alvarezii ◽  
Initial Weight ◽  
Microsoft Excel ◽  
Randomized Design ◽  
Significant Difference ◽  
Completely Randomized Design

Abstract. The purpose of this study is to determine the best planting space on the growth of regenerated tissue culture Kappaphycusalvarezii. The completely randomized design (CRD) was utilized in this study, thre treatment was four different planting spaces; P1: 15cm, P2: 20 cm, P3: 25 cm, and P4: 30 cm with initial weight of 100g/hill. Every treatment has four replicates (four rafts). The data were subjected to one way of analysis of variance (ANOVA) at 5% of error levels and followed by Least Significant Difference (LSD) test. The Anova test showed that planting space gave a significant affect on weight gain and growth rate where the best planting space was 25 cm with weight gain and growth rate of 331.4 g and 4.87% perday, respectively. Keywords: K.alvarezii;space; tissue culture regenerated;growth;photosynthesis Abstrak. Tujuan penelitian ini adalah untuk menentukan jarak tanam optimum untuk pertumbuhan rumput laut Kappaphycus alvarezii hasil kultur jaringan. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) dengan 4 perlakuan menggunakan bibit hasil kultur jaringan dengan jarak tanam yang berbeda yakni P1: jarak tanam 15cm , P2: jarak tanam 20 cm, P3: jarak tanam 25 cm, dan P4: jarak tanam 30 cm dengan berat awal 100 g/rumpun, masing-masing perlakuan dengan empat kali ulangan pada 4 rakit. Data penelitian yang diperoleh, ditabulasi menggunakan Microsoft excel dan dianalisis menggunakan analisis sidik ragam (ANOVA) pada taraf kesalahan 5%, kemudian dilakukan uji lanjut dengan uji Least Significant Difference (LSD). Hasil penelitian ini menunjukkan bahwa jarak tanam berpengaruh nyata terhadap pertumbuhan rumput laut (P<0,05), dimana jarak tanam terbaik adalah 25 cm dengan pertambahan bobot 331,4 g dan laju pertumbuhan 4,87% per hari.Kata Kunci: K. alvarezii; Jarak tanam; kultur jaringan; pertumbuhan; fotosintesis

scholarly journals Romanov Kuzularının Vücut Özelliklerinin Tanımlanmasında Doğrusal ve Doğrusal Olmayan Modellerin Karşılaştırılması

2020 ◽  
Vol 8 (2) ◽  
pp. 499
Author(s):  
Yalçın Tahtalı ◽  
Ahmet Tahsin Yaldızbaş
Keyword(s):  
Body Length ◽  
Growth Curve ◽  
Linear Models ◽  
Logistic Models ◽  
Live Weight ◽  
Growth Period ◽  
Coefficient Of Determination ◽  
Linear Quadratic ◽  
Absolute Deviation ◽  
Cubic Model

In this study, the purpose of defining the development of body characteristics of 50 Romanov lambs 180. During the growth period up to the age of day, records of body characteristics such as body weight, body length, height of cidago were taken every 15 days and the parameters of the growth curves were calculated from the Linear models with the obtained data and the Linear, Quadratic and Cubic model, Non-Linear models with Gompertz, and Logistic models. The coefficient of determination (R2), mean square error (MSE) and mean absolute deviation (MAD) values were used in determining the model that best fit the growth curve. As a result of the study, the highest R2 value and the lowest HKO values were 0.992-0.591 in live weight, 0.993-0.441 in cidago height, and 0.986-1.164 in body length, respectively. The highest R2 value in all body characteristics was obtained from the cubic model. SPSS statistics program was used to determine the parameters of the growth curve model. According to the obtained data, it was determined that the most compatible model to explain the development of all body characteristics of the Romanov lambs is the Cubic model.

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