scholarly journals Regression model analysis for prediction of body weight from body measurements in female Batur sheep of Banjarnegara District, Indonesia

2021 ◽  
Vol 22 (7) ◽  
Author(s):  
Alek Ibrahim ◽  
Wayan Tunas Artama ◽  
I Gede Suparta Budisatria ◽  
Ridwan Yuniawan ◽  
Bayu Andri Atmoko ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Model ◽  
Akaike Information Criterion ◽  
Computer Software ◽  
Correlation Coefficients ◽  
Information Criterion ◽  
Model Analysis ◽  
The Body ◽  
Body Measurements ◽  
Central Java

Abstract. Ibrahim A, Artama WT, Budisatria IGS, Yuniawan R, Atmoko BA, Widayanti R. 2021. Regression model analysis for prediction of body weight from body measurements in female Batur sheep of Banjarnegara District, Indonesia. Biodiversitas 22: 2723-2730. Bodyweight is an important aspect of livestock management. The present study was undertaken to estimate correlation coefficients between biometric traits and identify best predictor of body weight in female Batur sheep from body measurements. Data on body weight and body measurements (body length: BL, chest girth: CG and withers height: WH) were collected from 73 female Batur sheep in Batur Village, Banjarnegara District, Central Java Province, Indonesia. Batur sheep were grouped into 3 categories based on their age, namely groups <1.5 years, 1.5-2.5 years and >2.5 years. The data were analyzed using simple, multiple, and automatic linear regression methods using the SPSS computer software version 25 platform. The correlation coefficient, coefficient determination, adjusted coefficient determination, residual standard error, Akaike information criterion, Bayesian information criterion, and Akaike information criterion corrected were used to determine the best regression formula for the prediction of BW. The average BW (kg), BL (cm), CG (cm), and WH (cm) of 49.27, 63.11, 91.41, and 56.82, respectively was observed in the present study. The correlation coefficients of 0.433, 0.866, and 0.369 for BW with BL, CG, and WH were observed in the present study. The best prediction of BW using two predictors (BL and GC) was BW =-56.522 + 0.509BL + 0.843CG, followed by using three predictors (BL, CG, and WH) was BW =-57.897+ 0.505BL + 0.839CG + 0.034WH, and using the only one predictor (CG) was BW =-28.443 + 0.905CG. The study revealed that CG and its combination with other linear body measurements can effectively define the body weight in Batur sheep. However, the highest R2 of 0.782 was observed when CG and BL were used as predictors.

scholarly journals Morphological characterization of Arab and Oromo goats in northwestern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Oumer Sheriff ◽  
Kefyalew Alemayehu ◽  
Aynalem Haile
Keyword(s):  
Body Weight ◽  
Coat Color ◽  
Strong Association ◽  
Correlation Coefficients ◽  
Field Research ◽  
Morphological Characterization ◽  
The Body ◽  
Regression Equations ◽  
Body Measurements ◽  
Chest Girth

Abstract Background An exploratory field research was conducted in northwestern Ethiopia, to characterize the morphological features of Arab and Oromo goat populations as an input to design community-based breeding programs. Ten qualitative and nine quantitative traits were considered from 747 randomly selected goats. All data collected during the study period were analyzed using R statistical software. Results Plain white coat color was predominantly observed in Arab goats (33.72%) while plain brown (deep and light) coat color was the most frequent in Oromo goats (27.81%). The morphometric measurements indicated that Oromo goats have significantly higher body weight and linear body measurements than Arab goats. Positive, strong and highly significant correlations were obtained between body weight and most of the body measurements in both goat populations. The highest correlation coefficients of chest girth with body weight for Arab (r  =  0.95) and Oromo (r  =  0.92) goat populations demonstrated a strong association between these variables. Live body weight could be predicted with regression equations of y  =  − 33.65  +  0.89  ×  for Arab goats (R2  =  90) and y  =  − 37.55  +  0.94  ×  for Oromo goats (R2  =  85), where y and x are body weight and chest girth, respectively, in these goat types. Conclusions The morphological variations obtained in this study could be complemented by performance data and molecular characterization using DNA markers to guide the overall goat conservation and formulation of appropriate breeding and selection strategies.

scholarly journals Morphological characterization of Arab and Oromo goats in northwestern Ethiopia: implications for community-based breeding programs

2020 ◽  
Author(s):  
Oumer Sheriff ◽  
Kefyalew Alemayehu ◽  
Aynalem Haile
Keyword(s):  
Body Weight ◽  
Coat Color ◽  
Strong Association ◽  
Correlation Coefficients ◽  
Field Research ◽  
The Body ◽  
Regression Equations ◽  
Body Measurements ◽  
Breeding Programs ◽  
Chest Girth

Abstract Background: An exploratory field research was conducted in Northwestern Ethiopia, to characterize the morphological features of Arab and Oromo goat populations as a first step to design breeding programs. Ten qualitative and nine quantitative traits were considered from 747 randomly selected goats. All data collected during the study period were analyzed using R statistical software, version 3.5.2, 2018. Results: Plain white coat color was predominantly observed in Arab goats (33.72%) while plain brown (deep and light) coat color was the most frequent in Oromo goats (27.81%). The morphometric measurements indicated that Oromo goats have significantly (P < 0.001) higher body weight and linear body measurements than Arab goats. Positive, strong and highly significant (P < 0.001) correlations were obtained between body weight and most of the body measurements in both goat populations. The highest correlation coefficients of chest girth with body weight for Arab (r = 0.95) and Oromo (r = 0.92) goat populations demonstrated a strong association between these variables. Live body weight could be predicted with regression equations of y = -33.65 + 0.89x for Arab goats (R2 = 90) and y = -37.55 + 0.94x for Oromo goats (R2 = 85), where y and x are body weight and chest girth, respectively, in these goat types. Conclusions: The morphological variations obtained in this study could be complemented by performance data and molecular characterization using DNA markers to guide the overall goat conservation and formulation of appropriate breeding and selection strategies.

scholarly journals Short Communication: Prediction of body weight based on body measurements in female Saburai goat

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
AKHMAD DAKHLAN ◽  
MUHAMMAD DIMA IQBAL HAMDANI ◽  
DELSI RUSITAIMI PUTRI ◽  
SULASTRI SULASTRI ◽  
ARIF QISTHON
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Regression Model ◽  
Short Communication ◽  
Linear Regression Analysis ◽  
Information Criterion ◽  
Multiple Linear Regression Analysis ◽  
Regression Equation ◽  
Body Measurements ◽  
Chest Girth

Abstract. Dakhlan A, Hamdani MDI, Putri DR, Sulastri, Qisthon A. 2021. Short Communication: Prediction of body weight based on body measurements in female Saburai goats. Biodiversitas 22: 1391-1396. Saburai goat is a new composite breed in Lampung Province with little information on its performance. This research aimed to predict body weight based on body measurements, namely body length (BL), chest girth (CG), and shoulder height (SH) in female Saburai goats. This study used 42 female Saburai goats aged 3-4 years. The method used in this study was a survey, namely all-female Saburai goats aged 3-4 years were used for this research. The data obtained were analyzed using correlation and simple and multiple linear regression analysis using R program. Coefficient determination (R2), adjusted R2, residual standard error (RSE), Akaike information criterion (AIC), Bayesian information criterion (BIC), and stepwise regression analysis were used to find the best and most parsimonious regression model to predict BW based on body measurements. The results showed that BL, CG, and SH were positively and significantly correlated with BW of female Saburai goats with correlation coefficients of 0.858, 0.956 and 0.862, respectively. Chest girth was the best predictor for BW if using single predictor with regression equation of Ŷ = -31.17 + 0.93X2. However, combination of BL and CG was the best and most parsimonious regression model in predicting BW of female Saburai goat with regression equation of Ŷ = -36.09 + 0.31X1 + 0.72X2 with R2 = 0.941, adjusted R2 = 0.938, RSE = 2.842, AIC = 216.73 and BIC = 223.78. In conclusion, all body measurements in this study (particularly combination of BL and CG) could be used as predictor for BW with high accuracy of prediction. The result of this study suggested that CG and BL could be as indirect criteria to improve BW of female Saburai goats.

scholarly journals Use of factor scores in multiple regression analysis for estimation of body weight by certain body measurements in Romanov Lambs

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7434 ◽  
Author(s):  
Yalcin Tahtali
Keyword(s):  
Factor Analysis ◽  
Body Weight ◽  
Regression Model ◽  
Multiple Regression ◽  
Prediction Equation ◽  
Multiple Regression Model ◽  
The Body ◽  
Body Measurements ◽  
Factor Scores ◽  
Two Factors

The study investigates the solution of the multicollinearity between certain body measurements of Romanov lambs and prediction of the body weight of Romanov lambs using the thus calculated factor analysis scores and a multiple regression model. For this purpose, the body measurements (wither height (WH), croup height (CH), body length (BL), chest depth (CD), chest circumference (CC), chest width behind shoulders (CWS) and head length (HL)) and body weight (BW) of 6-month-old 50 Romanov lambs born in 2015 were used. The factor analysis scores were used to obtain the prediction equation for the relationship between the investigated traits. The analysis results showed that there was a multicollinearity between the wither and croup height traits used in the prediction equation. Moreover, the results revealed that the variables for the body measurements can be represented by two factors. These factors explained 50.89% and 22.86% of the total variance, respectively. The multicollinearity between the independent variables was eliminated with the use of the factor scores obtained with the factor analysis in the multiple regression model, and thus it was observed that better results can be obtained by using the factor analysis scores in the prediction of the body weight of 6-month-old Romanov lambs.

scholarly journals Phenotypic Correlation of Body Weight and Linear Body Measurements in Muscovy (Cairinia Moschata) and Mallard (Anas Platyrhynchos) Ducks

2020 ◽  
pp. 13-17
Author(s):  
Ologbose F. I. ◽  
Mbara S. W.
Keyword(s):  
Body Weight ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Selection Index ◽  
Body Height ◽  
Correlation Coefficients ◽  
The Body ◽  
Phenotypic Correlation ◽  
Body Measurements ◽  
Linear Body

Data on body weight and linear body measurements (LBMs) namely body height (BH), body length (BL), breast circumference (BC), thigh length (TL), bill length (BiL), wing length (WL) and shank length (SL) were taken from 120 ducks (i. e. 60 Muscovy and 60 Mallard ducks) at 4 and 8 weeks of age were analysed to obtain the phenotypic correlation between LBMs and body weight. The value of the pearson’s linear correlation coefficient to determine the level of relationship between the body weight and linear body measurement. This ranged from 0.488 (SL) – 0.996 (BH) and (0.729 (SL) – 0.996 (Bil) in Muscovy and Mallard duck at week 4 respectively. While, at week 8, the value of the pearson’s linear correlation coefficient ranges from 0.126 (Bil) – 0.960 (BL) and 0.735(BC) – 0.978 (BH) respectively. This positive and mostly significantly phenotypic relationship between the body weight and linear body measurements indicates that an improvement in one trait could leads to an improvement in the other. Correlation coefficients indicate the strength of a linear relation between traits and thus provide useful information about the traits involved for the purpose of breeding and improvement plan. This shows that favourable relationships exist among traits that have higher correlation coefficients, it further explains that such traits could be collectively included in the selection index to achieve positive phenotypic progress.

scholarly journals Prediction of grasscutters (Thryonomis swinderianus) body weight from linear body measurements

2021 ◽  
Vol 41 (1) ◽  
pp. 264-271
Author(s):  
A. J. Henry ◽  
S. N. Ibe ◽  
B. O. Asuquo
Keyword(s):  
Body Weight ◽  
Body Length ◽  
Goodness Of Fit ◽  
Correlation Coefficients ◽  
Tail Length ◽  
Experimental Period ◽  
The Body ◽  
Coefficient Of Determination ◽  
Body Measurements ◽  
Linear Body

A study was conducted to investigate the relationship between linear body measurements (LBMs) and body weights of grasscutters at 2, 4 and 6 weeks of age. Simple linear correlation procedure was used to establish the strength of linear relationships and associations between the different linear body measurements with body weight. These parameters were also subjected to step-wise regression analysis. The goodness of fit (R2) was tested to determine the contribution of each independent variable measured to the prediction of the dependent variable, the body weight of grasscutters at different ages of 2, 4,6, 8, 10, 12, 14, 16, 18 and 20 weeks. One hundred and thirty-nine (139) juvenile grasscutters obtained from 24 parents comprising of 18 does and 6 bucks were used for the study. Experimental animals were raised under a mixed feeding regime throughout the experimental period of 20 weeks. The linear body measurements assessed are head length (HL), body length (BL), heart girth (HG), ear length (EL) and tail length (TL). Correlation coefficients (r) between body measurements and weights were generally positive and significant (p < 0.01) at 2 weeks, demonstrating strong relationships between variables. At 4 weeks, correlation coefficients ranged from 0.013 to 0.829 whereas at 6 weeks values ranged from -0.230 to 0.859. Coefficient of determination (R2) varied from 0.926 to 0.997, 0.965 to 0.989 and 0.930 to 0.991 at 2, 4 and 6 weeks, respectively The positive correlation coefficients observed for body length and heart girth shows that these parameters can be improved upon for grasscutters raised under intensive management. Results from this study further revealed that body weight of grasscutters can be estimated under field condition using the ear,head, body lengths and heart girth in the absence of a weighing balance.

PENGEMBANGAN TANAMAN RAMI (Boehmeria nivea L. Gaud) DAN PEMANFAATAN LIMBAH DAUN RAMI UNTUK PENGGEMUKKAN DOMBA WONOSOBO

2018 ◽  
Vol 16 (2) ◽  
pp. 201-210
Author(s):  
Muryanto Muryanto ◽  
Pita Sudrajad ◽  
Amrih Prasetyo
Keyword(s):  
Body Weight ◽  
Weight Gain ◽  
Plant Development ◽  
Body Weight Gain ◽  
Survey Methods ◽  
The Body ◽  
Boehmeria Nivea ◽  
Central Java ◽  
Potential Capacity ◽  
The Given

The aim of the study was to determine the development of ramie plants (Boehmeria nivea L. Gaud) and the effect of using ramie leaves on feed on the body weight gain of Wonosobo Sheep (Dombos). Research on the development of ramie plants using survey methods in the area of ramie plant development in Wonosobo Regency. While the research on the use of ramie leaves for fattening was carried out in Butuh Village, Kalikajar District, Wonosobo Regency in 2018. 21 male Dombos were divided into 3 feed treatments with forage proportions of 70%, 50% and 30 ramie leaves respectively. %. The results showed that currently ramie plants were being developed in Wonosobo Regency by CV. Ramindo Berkah Persada Sejahtera in Gandok Village, Kalikajar District, Wonosobo Regency, Central Java. Until now the area of the crop has reached 13 ha. Of this area will produce ramie leaves 195,000 kg / year. If one sheep needs 4 kg of ramie / tail / day leaves, then the potential capacity of sheep is 135 heads / year, if the given one is 50% then the Jurnal Litbang Provinsi Jawa Tengah, Volume 16 202 Nomor 2 – Desember 2018potential capacity is 270 heads / year and if it is reduced again to 25% of ramie leaves then the potential capacity 440 heads / year. The use of ramie leaves as a feed for Wonosobo Sheep fattening can be given as much as 30% in fresh form.

Growth performance, correlation and regression estimates of seven-chicken strains in South-Western Nigeria

2020 ◽  
Vol 45 (2) ◽  
pp. 40-48
Author(s):  
A. J. Atansuyi ◽  
U. C. Ihendu ◽  
C. A. Chineke
Keyword(s):  
Body Weight ◽  
Growth Performance ◽  
Correlation Coefficients ◽  
Tail Length ◽  
Experimental Period ◽  
The Body ◽  
Coefficient Of Determination ◽  
Indigenous Chicken ◽  
Randomized Design ◽  
Study Results

This study was conducted to determine the growth performance, correlation and regression estimates of seven-chicken strains in South-western Nigeria using a total of 300 day-old chicks. The birds were divided into seven groups based on their strain. The seven strains are Normal feather (NF), Fulani ecotype (FE), Frizzle feather (FF), naked neck (NN) and Transylvania indigenous strains while Hubbard and Marshal were meat-type exotic chickens. There were forty- five (45) unsexed day-old chicks in each strain except the Frizzle feather that were 30 in number. Completely randomized design (CRD) was used for the trial that lasted for 8 weeks. The birds were fed experimental diets ad libitum throughout the period of the study. Results showed that there were significant differences (p<0.05) in the initial and final weights of the birds. It was observed that exotic strains weighed heavier (3569.73gHB) than their indigenous counterparts (1391.11gNF). However, the Fulani ecotype weighed heaviest (1840.99g) among Nigeria indigenous strains during the experimental period. This showed that FE strains are generally heavy breed chicken and could be incorporated into a meat producing indigenous chicken if improved upon. The result of the correlation coefficients showed that a very strong, positive and highly significant (P<0.001) relationship existed between body weights and linear body measurements as most of the values are (>0.40). All the body parameter examined had significant (p<0.01) and direct relationship with the body weight. Shoulder-to-tail length (STL) had the highest coefficient of 0.98.The high correlation estimates obtained in this study could be as a result of pleiotropy, heterozygosity or linkage of genes in the birds. The three functions were highly significant (p<0.05) for all the parameters studied. This shows that the functions well described the parameters. On the basis of coefficient of determination (R ), the body weight of poultry birds at any age can be predicted most accurately with BRG using cubic function.

scholarly journals Model comparison and estimation of genetic parameters for body weight in commercial broilers

2013 ◽  
Vol 93 (1) ◽  
pp. 67-77 ◽  
Author(s):  
G. Maniatis ◽  
N. Demiris ◽  
A. Kranis ◽  
G. Banos ◽  
A. Kominakis
Keyword(s):  
Body Weight ◽  
Akaike Information Criterion ◽  
Model Evaluation ◽  
Model Comparison ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Information Criterion ◽  
Biological Properties ◽  
Genetic Covariance ◽  
Estimation Of Genetic Parameters

Maniatis, G., Demiris, N., Kranis, A., Banos, G. and Kominakis, A. 2013. Model comparison and estimation of genetic parameters for body weight in commercial broilers. Can. J. Anim. Sci. 93: 67–77. The availability of powerful computing and advances in algorithmic efficiency allow for the consideration of increasingly complex models. Consequently, the development and application of appropriate statistical procedures for model evaluation is becoming increasingly important. This paper is concerned with the application of an alternative model determination criterion (conditional Akaike Information Criterion, cAIC) in a large dataset comprising 203 323 body weights of broilers, pertaining to 7 (BW7) and 35 (BW35) days of age. Seven univariate and seven bivariate models were applied. Direct genetic, maternal genetic and maternal environmental (c2) effects were estimated via REML. The model evaluation criteria included conditional Akaike Information Criterion (cAIC), Bayesian Information Criterion (BIC) and the standard Akaike Information Criterion (henceforth marginal; mAIC). According to cAIC the best-fitting model included direct genetic, maternal genetic and c2 effects. Maternal heritabilities were low (0.10 and 0.03) compared to the direct heritabilities (0.17 and 0.21), while c2 was 0.05 and 0.04 for BW7 and BW35, respectively. BIC and mAIC favoured a model that additionally included a direct-maternal genetic covariance, resulting in highly negative direct-maternal genetic correlations (−0.47 and −0.64 for BW7 and BW35, respectively) and higher direct heritabilities (0.25 and 0.28 for BW7 and BW35, respectively). Results suggest that cAIC can select different animal models than mAIC and BIC with different biological properties.

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