scholarly journals Mathematical model of growth of two purelines of Padjadjaran female quail aged 0 to 6 weeks

2017 ◽  
Vol 42 (2) ◽  
pp. 66
Author(s):  
A. Anang ◽  
H. Indrijani ◽  
E. Sujana
Keyword(s):  
Growth Models ◽  
Gompertz Model ◽  
High Accuracy ◽  
Coefficient Of Determination ◽  
Standard Errors ◽  
Black Line ◽  
Female Quail ◽  
Best Fit ◽  
Black Color ◽  
Brown Color

A research was conducted at Quail Breeding Centre of Padjadjaran University.  A hundred quails of female black and brown color of each line was observed from hatch to age of six weeks. Four growth models were compared: Gompertz, Logistic, Richards, and MMF. The best fit was measured with Coefficient of determination (R2) and standard error of prediction (se). The results showed that all observed models have high accuracy with R2 ranging from 0.9950 to 0.9988 for black color, and 0.9984 to 0.9992 for brown color respectively. Standard errors of prediction (SE) ranged from 1.99 g to 4.01 g for black, and from 1.92 g to 2.52 g for brown, respectively. Gompertz model was more favorable with R2 and SE of 0.9988 and 1.99 g for black, and 0.9991 and 1.92 g for brown, respectively. Age at inflection, maximum average daily gains and weights at inflection were 4.18 week, 27.87 g and 100.23 g for black line and 3.38 week, 25.05 g and 75.34 g for brown line, respectively.

Prediction of dry matter accumulation in bitter vetch

2017 ◽  
Author(s):  
Ufuk Karadavut ◽  
Adil Bakoglu ◽  
Halit Tutar ◽  
Kagan Kokten ◽  
Hava Seyma Yilmaz
Keyword(s):  
Growth Models ◽  
Block Design ◽  
Coefficient Of Determination ◽  
Dry Matter Accumulation ◽  
Randomized Block Design ◽  
Bitter Vetch ◽  
Best Fitting ◽  
Local Genotypes ◽  
Best Fit ◽  
Different Sources

This study was carried out in Bingol province on eastern Anatolian Region between 2013 and 2015. In this study, we obtained 14 bitter vetch genotypes from different sources. The experiment was carried our in three replications in randomized block design. Each plant was weekly measured for 6 weeks starting from germination. For each plant, plant height, fresh and dry stem weight, fresh and dry leaf weights were determined. Logistic, Richards and Weibull growth models were fitted to describe the growth pattern of the genotypes. The best fitting model criteria used were coefficient of determination and mean squared. Richards’s growth model was found to best fit the data for most of the genotypes. Logistic model was the worst fit. In Turkey, climate and soil properties have very large variations. For this, local genotypes showed large variation according to plating areas. YEREL LICE genotype showed more stable and it is the height identified all growth models than other local genotypes. However, IFVE 2923 SEL and IFVE 2977 SEL 2802 these genotypes gave positive results in different environmental conditions.

scholarly journals Age, growth, and maturity of the whitebrow skate, Bathyraja minispinosa, from the eastern Bering Sea

2011 ◽  
Vol 68 (7) ◽  
pp. 1426-1434 ◽  
Author(s):  
Shaara M. Ainsley ◽  
David A. Ebert ◽  
Gregor M. Cailliet
Keyword(s):  
Bering Sea ◽  
Growth Models ◽  
Gompertz Model ◽  
Parameter Estimates ◽  
Population Declines ◽  
Age At Maturity ◽  
Von Bertalanffy Model ◽  
Eastern Bering Sea ◽  
Best Fit ◽  
The Bering Sea

Abstract Ainsley, S. M., Ebert, D. A., and Cailliet, G. M. 2011. Age, growth, and maturity of the whitebrow skate, Bathyraja minispinosa, from the eastern Bering Sea. – ICES Journal of Marine Science, 68: 1426–1434. Skates are a common bycatch in groundfish fisheries in the Bering Sea; however, their life-history characteristics are not well known. The study is the first to investigate the age, growth, and age at maturity of Bathyraja minispinosa. Ages were estimated using sectioned vertebrae and several growth models were compared. The Gompertz model was the best fit and no significant differences were detected between sexes for any model. The maximum age estimated was 37 years, and parameter estimates generated from the three-parameter von Bertalanffy model were k = 0.02 year−1 and L∞ = 146.9 cm total length (TL). Males reached their size at 50% maturity larger than females (70.1 and 67.4 cm, respectively), but no significant differences in the estimated size or age at maturity were found. Whereas B. minispinosa is smaller than many skate species in the eastern Bering Sea, it has a considerably longer estimated lifespan, indicating that size may not be a reliable method of estimating the vulnerability of a rajid species to population declines in the eastern North Pacific.

scholarly journals Selecting the best growth model for elasmobranches

2015 ◽  
Author(s):  
Kwang-Ming Liu ◽  
Chiao-Bin Wu ◽  
Shoou-Jeng Joung ◽  
Wen-Pei Tsai
Keyword(s):  
Growth Model ◽  
Growth Models ◽  
Stock Assessment ◽  
Gompertz Model ◽  
Information Criterion ◽  
Age And Growth ◽  
Deep Waters ◽  
Extended Longevity ◽  
Best Fit ◽  
Two Parameter

Age and growth information is essential for accurate stock assessment of fish, and growth model selection may influence the result of stock assessment. Previous descriptions of the age and growth of elasmobranches relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life-history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranches. This study attempts to improve the accuracy of age estimates by testing four growth models—the VBGM, two-parameter VBGM, Robertson (Logistic) and Gompertz models—to fit observed and simulated length-at-age data for 37 species of elasmobranches. The best growth model was selected based on corrected Akaike’s Information Criterion (AICc), the AICc difference, and the AICc weight. The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ > 100 cm TL, 0.05 < k < 0.15 yr-1), such as pelagic sharks. For fast-growing small sharks (L∞ < 100 cm TL, kr or kg > 0.2 yr-1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model, while all the species best fit by the Gompertz model are skates and rays.

Application of non-linear mixed models for modelling the quail growth curve for meat and laying

2018 ◽  
Vol 156 (10) ◽  
pp. 1216-1221 ◽  
Author(s):  
H. B. Santos ◽  
D. A. Vieira ◽  
L. P. Souza ◽  
A. L. Santos ◽  
F. R. Santos ◽  
...  
Keyword(s):  
Growth Rate ◽  
Growth Curve ◽  
Mixed Models ◽  
Gompertz Model ◽  
Average Growth ◽  
Relative Growth ◽  
Female Quail ◽  
Absolute Growth ◽  
Growth Profiles ◽  
Best Fit

AbstractThe objective of the current paper was to apply mixed models to adjust the growth curve of quail lines for meat and laying hens and present the rates of instantaneous, relative and absolute growth. A database was used with birth weight records up to the 148th day of female quail of the lines for meat and posture. The models evaluated were Brody, Von Bertalanffy, Logistic and Gompertz and the types of residues were constant, combined, proportional and exponential. The Gompertz model with the combined residue presented the best fit. Both strains present a high correlation between the parameters asymptotic weight (A) and average growth rate (k). The two strains presented a different growth profile. However, growth rates allow greater discernment of growth profiles. The meat line presented a higher growth rate (6.95 g/day) than the lineage for laying (3.65 g/day). The relative growth rate was higher for lineage for laying (0.15%) in relation to the lineage for meat (0.13%). The inflection point of both lines is on the first third of the growth curve (up to 15 days). All results suggest that changes in management or nutrition could optimize quail production.

Modelling and comparison of growth of the silver-lip pearl oyster Pinctada maxima (Jameson) (Mollusca : Pteriidae) cultured in West Papua, Indonesia

2008 ◽  
Vol 59 (1) ◽  
pp. 22 ◽  
Author(s):  
Anne M. Lee ◽  
Ashley J. Williams ◽  
Paul C. Southgate
Keyword(s):  
Growth Models ◽  
Logistic Models ◽  
High Growth ◽  
Growth Function ◽  
Pearl Oyster ◽  
High Growth Rate ◽  
Coefficient Of Determination ◽  
West Papua ◽  
Pinctada Maxima ◽  
Best Fit

A commonly used approach to quantifying growth is to fit mathematical models to length-at-age data. Growth of the silver-lip pearl oysters, Pinctada maxima, cultured at a commercial pearl farm in West Papua, Indonesia was expressed mathematically by fitting five growth models (Gompertz, Richards, Logistic, Special von Bertalanffy Growth Function (VBGF) and General VBGF) to length-at-age data. The criteria used to determine the best fit model were a low mean residual sum of squares (MRSS), high coefficient of determination (r2) and low deviation of the asymptotic length (L∞) from the maximum length (Lmax). Using these criteria, the models were ranked accordingly: Special VBGF; General VBGF; Gompertz; Richards and Logistic models. The Special VBGF yielded the best fit (L∞ = 168.38 mm; K = 0.930 year–1; t0 = 0.126; MRSS = 208.64; r2 = 0.802; Deviation of L∞ from Lmax = 37.52 mm) and, accordingly, was used to model the growth of oysters cultured at three sites and two depths within the farm. Likelihood ratio tests were used to compare growth of oysters cultured at these sites and depths. Based on L∞ and K values, favourable sites and depths could be determined that optimised growth requirements for the various stages of P. maxima culture. Sites with high K and L∞ values were preferred sites for culturing juvenile oysters before pearl production, when high growth rate is essential to produce large numbers of oysters in the shortest time possible. In addition, high L∞ may facilitate implantation of larger nuclei conducive to the production of larger, more valuable pearls. Conversely, sites with low K values were preferred sites for weakening P. maxima before pearl ‘seeding’, a process undertaken to minimise nucleus rejection after seeding.

scholarly journals Selecting the best growth model for elasmobranches

2015 ◽  
Author(s):  
Kwang-Ming Liu ◽  
Chiao-Bin Wu ◽  
Shoou-Jeng Joung ◽  
Wen-Pei Tsai
Keyword(s):  
Growth Model ◽  
Growth Models ◽  
Stock Assessment ◽  
Gompertz Model ◽  
Information Criterion ◽  
Age And Growth ◽  
Deep Waters ◽  
Extended Longevity ◽  
Best Fit ◽  
Two Parameter

Age and growth information is essential for accurate stock assessment of fish, and growth model selection may influence the result of stock assessment. Previous descriptions of the age and growth of elasmobranches relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life-history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranches. This study attempts to improve the accuracy of age estimates by testing four growth models—the VBGM, two-parameter VBGM, Robertson (Logistic) and Gompertz models—to fit observed and simulated length-at-age data for 37 species of elasmobranches. The best growth model was selected based on corrected Akaike’s Information Criterion (AICc), the AICc difference, and the AICc weight. The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ > 100 cm TL, 0.05 < k < 0.15 yr-1), such as pelagic sharks. For fast-growing small sharks (L∞ < 100 cm TL, kr or kg > 0.2 yr-1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model, while all the species best fit by the Gompertz model are skates and rays.

Development and evaluation of trans-Amadi groundwater parameters: The integration of finite element techniques

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Finite Element ◽  
Polynomial Regression ◽  
Nitrate Concentration ◽  
Strong Relationship ◽  
Total Iron ◽  
Coefficient Of Determination ◽  
Port Harcourt ◽  
Polynomial Expression ◽  
The Relationship ◽  
Best Fit

Mathematical model was developed and evaluated to monitor and predict the groundwater characteristics of Trans-amadi region in Port Harcourt City. In this research three major components were considered such as chloride, total iron and nitrate concentration as well as the polynomial expression on the behavious on the concentration of each component was determined in terms of the equation of the best fit as well as the square root of the curve. The relationship between nitrate and distance traveled by Nitrate concentration by the model is given as Pc = 0.003x2 - 0.451x + 14.91with coefficient of determination, R² = 0.947, Chloride given as Pc = 0.000x2 - 0.071x + 2.343, R² = 0.951while that of Total Iron is given as Pc = 2E-05x2 - 0.003x + 0.110, R² = 0.930. All these show a strong relationship as established by Polynomial Regression Model. The finite element techniques are found useful in monitoring, predicting and simulating groundwater characteristics of Trans-amadi as well as the prediction on the variation on the parameters of groundwater with variation in time.

scholarly journals A Study on the Feasibility of Anaerobic Co-Digestion of Raw Cheese Whey with Coffee Pulp Residues

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3611
Author(s):  
Sandra Gonzalez-Piedra ◽  
Héctor Hernández-García ◽  
Juan M. Perez-Morales ◽  
Laura Acosta-Domínguez ◽  
Juan-Rodrigo Bastidas-Oyanedel ◽  
...  
Keyword(s):  
Methane Production ◽  
Kinetic Models ◽  
Cheese Whey ◽  
Maximum Yield ◽  
Gompertz Model ◽  
Coffee Pulp ◽  
The One ◽  
The Cost ◽  
Best Fit ◽  
Cheese Production

In this paper, a study on the feasibility of the treatment of raw cheese whey by anaerobic co-digestion using coffee pulp residues as a co-substrate is presented. It considers raw whey generated in artisanal cheese markers, which is generally not treated, thus causing environmental pollution problems. An experimental design was carried out evaluating the effect of pH and the substrate ratio on methane production at 35 °C (i.e., mesophilic conditions). The interaction of the parameters on the co-substrate degradation and the methane production was analyzed using a response surface analysis. Furthermore, two kinetic models were proposed (first order and modified Gompertz models) to determine the dynamic profiles of methane yield. The results show that co-digestion of the raw whey is favored at pH = 6, reaching a maximum yield of 71.54 mLCH4 gVSrem−1 (31.5% VS removed) for raw cheese whey and coffee pulp ratio of 1 gVSwhey gVSCoffe−1. The proposed kinetic models successfully fit the experimental methane production data, the Gompertz model being the one that showed the best fit. Then, the results show that anaerobic co-digestion can be used to reduce the environmental impact of raw whey. Likewise, the methane obtained can be integrated into the cheese production process, which could contribute to reducing the cost per energy consumption.

scholarly journals Drying kinetics of ‘babassu’ mesocarp

2017 ◽  
Vol 21 (10) ◽  
pp. 709-714 ◽  
Author(s):  
Jhonatas C. Rosa ◽  
Andreza P. Mendonça ◽  
Angélica dos S. Oliveira ◽  
Sylviane B. Ribeiro ◽  
Andréia do R. Batista ◽  
...  
Keyword(s):  
Experimental Data ◽  
Water Content ◽  
Animal Feed ◽  
Coefficient Of Determination ◽  
Residual Distribution ◽  
Solar Dryer ◽  
Error Standard Deviation ◽  
Forced Air ◽  
Final Water Content ◽  
Best Fit

ABSTRACT ‘Babassu’ mesocarp flour has been used by the pharmaceutical, human food and animal feed industries. However, there is lack of standardization in the production, as well as absence of information on the management of the product’s quality. Thus, the objective of this study was to dry the ‘babassu’ mesocarp in forced-air oven and solar dryer, adjust different mathematical models to the experimental data, as well as to quantify the levels of proteins and crude fiber of the produced flour. The criteria for the adjustment were the coefficient of determination, magnitude of the mean relative error, standard deviation of estimate and the residual distribution trend. Drying in the shortest time occurred in oven at 60 °C (370 min), leading to water content of 4.62%, while in the solar dryer the final water content was 8.07% in 6 days. The mathematical model Two Terms showed the best fit to the experimental data for oven drying and the Midilli model showed the best fit in solar dryer. There was an increase in protein content with the drying in solar dryer and oven at 40, 50 and 60 °C (1.36, 1.33, 1.15 and 1.37%, respectively) in relation to fresh mesocarp (0.88%). Drying in both oven and solar dryer promoted increase of protein in the flour.

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans

2017 ◽  
Vol 81 (2) ◽  
pp. 308-315 ◽  
Author(s):  
Vijay K. Juneja ◽  
Abhinav Mishra ◽  
Abani K. Pradhan
Keyword(s):  
Bacillus Cereus ◽  
Growth Rates ◽  
Linear Models ◽  
Growth Models ◽  
Maximum Growth ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Three Phase ◽  
Primary Model

ABSTRACT Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol–egg yolk–polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between −0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

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