scholarly journals Non-linear prediction model for egg production of quails the tropics with methionine supplementation

2021 ◽  
Vol 902 (1) ◽  
pp. 012019
Author(s):  
A Masykur ◽  
E Purwanti ◽  
N Widyas ◽  
S Prastowo ◽  
A Ratriyanto
Keyword(s):  
Logistic Model ◽  
Egg Production ◽  
Linear Prediction ◽  
Coefficient Of Determination ◽  
Diet Modification ◽  
Methionine Supplementation ◽  
Production Curve ◽  
Production Pattern ◽  
The Tropics ◽  
Linear Prediction Model

Abstract This study aimed to predict the egg production of quails receiving methionine supplementation. Two hundred and four quails were divided into two treatment diets, and six replicates with 17 quails each. The treatment diets were control (P0) and 0.12% methionine supplementation (P1). Egg production data were collected for eleven weeks, and a T-test was performed. Next, the data was plotted to get the actual egg production curve. We used a logistic regression model to predict the egg production pattern and calculated the model’s fitness with the coefficient of determination (R2). The results showed that methionine supplementation increased egg production by 9.43% (p<0.01). Based on the actual production curve, the increase in initial production to peak production of P1 was slower than P0, but P1 had a higher egg production than P0. The logistic model predicts that peak production of P1 was higher than P0 (62.74% vs. 56.79%), although the production rate of P1 was lower than P0 (0.21 vs. 0.36). In addition, the accuracy of both P0 and P1 models was 0.88 and 0.92, respectively. Thus, the logistic model can predict quail egg production in the tropics due to diet modification with high accuracy.

scholarly journals Application of logistic model to predict egg production pattern of quails given a low-energy diet supplemented with methionine

2021 ◽  
Vol 902 (1) ◽  
pp. 012017
Author(s):  
L A Pradista ◽  
M Veronica ◽  
N Widyas ◽  
S Prastowo ◽  
A Ratriyanto
Keyword(s):  
Treatment Period ◽  
Logistic Model ◽  
Egg Production ◽  
Low Energy ◽  
Energy Utilization ◽  
Production Data ◽  
Adaptation Period ◽  
Methionine Supplementation ◽  
Production Pattern ◽  
Low Energy Diet

Abstract Tropical countries such as Indonesia face high temperatures, which impact the energy utilization in poultry. This study aims to predict the egg production pattern of quail supplemented with methionine in a low-energy diet. In total, 204 laying quails were divided into two treatments: Control (T0) and 0.12% methionine supplementation (T1). After three weeks adaptation period, daily egg production data were collected for two periods of four weeks each (treatment period week 4-11). The t-test was applied to analyze the egg production data. Egg production patterns were predicted using logistic regression. The egg production pattern of T1 showed a significant increase compared to T0 during the treatment period (p<0.01) and overall period (p<0.01). Peak production from T0 and T1 was 59.14% vs. 66.82%, with a production rate of 0.22 vs. 0.18 and prediction accuracy of 91% vs. 86%, respectively. In conclusion, methionine supplementation to a low-energy diet increased egg production of quails.

scholarly journals Fitness of logistics model for predicting quails egg production reared in a tropical environment with dietary betaine supplementation

2021 ◽  
Vol 902 (1) ◽  
pp. 012020
Author(s):  
A Masykur ◽  
A N Azizah ◽  
N Widyas ◽  
S Prastowo ◽  
A Ratriyanto
Keyword(s):  
Logistic Model ◽  
Egg Production ◽  
Tropical Environment ◽  
Coefficient Of Determination ◽  
Production Data ◽  
Methyl Group ◽  
Organic Osmolyte ◽  
Production Curve ◽  
Dietary Treatments ◽  
Betaine Supplementation

Abstract Betaine is a methyl group donor and organic osmolyte, optimizing quail’s performance, particularly in a tropical environment. This study determined the fitness of the logistic model to predict the quail egg production with dietary betaine supplementation. Two hundred and four quails were divided into two dietary treatments, and six replicates with 17 quails each. The treatment diets were control (CTR) and 0.12% betaine supplementation (BET). Egg production data were collected for eleven weeks, and a T-test was performed. Next, the data is plotted to get the actual egg production curve. The fit of the logistic model is calculated according to the coefficient of determination (R2). Quail that received betaine supplementation produced more eggs than control (P<0.05). The actual egg production curve shows the effect of betaine supplementation seen after the fourth week. The logistic model predicts CTR to reach peak production faster than BET but to have lower peak production than BET (56.63% vs. 63.56%). Prediction of egg production both CTR and BET showed high accuracy with a relatively high R2 (0.88; CTR and 0.87; BET). Thus, the logistic model accurately predicted quails egg production reared in a tropical environment with betaine supplementation.

scholarly journals A non-linear prediction model for ageing foetal and neonatal sheep reveals basic issues in early neolithic husbandry

2021 ◽  
pp. 105344
Author(s):  
Nadja Pöllath ◽  
Ricardo García-González ◽  
Sevag Kevork ◽  
Ursula Mutze ◽  
Michaela I. Zimmermann ◽  
...  
Keyword(s):  
Prediction Model ◽  
Linear Prediction ◽  
Early Neolithic ◽  
Non Linear ◽  
Linear Prediction Model

Multi-day flow forecasting using the Kalman filter

1991 ◽  
Vol 18 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Murray A. Fitch ◽  
Edward A. McBean
Keyword(s):  
Kalman Filter ◽  
Prediction Model ◽  
Linear Prediction ◽  
Measured Data ◽  
System Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Forecasting Performance ◽  
Optimal Forecasting ◽  
Linear Prediction Model

A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm.

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.

Sign in / Sign up

Export Citation Format

Share Document