Comparison of linear and nonlinear models to estimate body weight of Pelibuey ewes from body measurements

Macedo, R.; Arredondo, Victalina; Segura, Carlos U. Häubi; Castillo-Zamora, Paola

doi:10.1007/s11250-020-02515-z

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…Recently, the utilization of nonlinear models for estimating LW in sheep based on body measurements has emerged as a viable alternative to the traditional reliance on simple or multiple linear models. The accuracy of the equation W 0–365 = 0.9142 exp (0.0462 CG) generated by the exponential model to estimate LW from CG in this study (Pseudo R 2 = 0.96) was higher than that shown by the equation proposed to predict the LW of Pelibuey ewes, which showed a Pseudo R 2 = 0.82 [ 14 ]. In this regard, using the exponential model, Canul-Solís et al [ 33 ] estimated the live weight of Pelibuey ewes from hip width with a similar precision to that found in the present study.…”

Section: Discussionmentioning

confidence: 84%

“…The linear prediction equation W 0–365 = −18.540 + 0.598(CG) generated using CG as the single predictor variable was more accurate than those developed for Arsi Bale lambs (R 2 = 0.68) [ 26 ], for Batur sheep (R 2 = 0.836) [ 5 ], and for Pelibuey sheep (R 2 = 0.79) [ 14 ].…”

Section: Discussionmentioning

confidence: 99%

“…These correlation estimates and prediction equations were developed with the measurements obtained in each sampling period (W 0 , W 90 , W 180 , W 270 , W 365 ) and a general one (W 0–365 ) was generated, including the totality of measurements recorded in all periods. Finally, chest girth, which was the body measurement with the highest correlation with live weight, was used to generate prediction equations using linear: Y = a + b(x) and exponential: Y = a exp (bx) models, where Y is the live weight, x is the body measurement, and a and b are parameters [ 14 ]. The models were tested for goodness of fit using the residual mean square error (MSE) and the coefficients of determination pseudo R 2 and R 2 for nonlinear and linear models, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Morphological Description and Live Weight Prediction from Body Measurements of Socorro Island Merino Lambs

Castillo

Macedo

Arredondo

et al. 2023

Animals

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The aim of this study was to describe the morphology and estimate live weight from body measurements of Socorro Island Merino lambs. A group of Socorro Island Merino lambs was recorded from birth to year for live weight, rump width, rump length, withers height, body length, cannon bone perimeter, and chest girth, width, and depth. The effect of the lamb type on body measurements and live weight was analyzed using ANOVA, Pearson’s correlation analysis was performed to estimate the relationship between body measurements and live weight, multiple linear regressions were fitted to obtain prediction equations of live weight from the body measurements and finally, chest girth was used to generate prediction equations using linear and exponential models. At birth and at year, differences were observed in body measurements, especially those related to the thoracic region, with crossbred males showing the highest values. Live weight was correlated with almost all the body measurements, with the highest coefficients observed with chest girth, chest width, and chest depth. Live weight can be accurately predicted from multiple regression equations using several body measurements, but using only chest girth (CG) as a predictor, the exponential equation W0–365 = 0.9142 exp(0.0462 CG) showed the best accuracy.

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Section: Discussionmentioning

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Morphological Description and Live Weight Prediction from Body Measurements of Socorro Island Merino Lambs

Castillo

Macedo

Arredondo

et al. 2023

Animals

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“…In the majority of these studies, linear regression has been the preferred method for deriving these prediction equations. However, a small number of authors have also investigated the application of nonlinear regression models, as evidenced by the works of Boujenane and Halhaly [2], Canul-Solis et al [13], and Macedo-Barragán et al [14], and Sultana et al [15].…”

Section: Introductionmentioning

confidence: 99%

Use of nonlinear regression in predicting body weight of female Saburai goat

Dakhlan,

Qisthon,

Wanniatie

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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This study aimed to evaluate the use of nonlinear regression in predicting body weight of female Saburai goats using body measurements. Thirty three female Saburai goat aged 1-3 years were used in this study. Body measurements including chest girth (CG), body length (BL), shoulder height (SH), hip height (HH), and hip width (HW) were regressed on body weight (BW) using nonlinear regression (exponential and polynomial regression). The prediction accuracy of nonlinear regression was compared to linear regression by evaluating their determination coefficient (R2), adjusted R2, residual standard error (RSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Correlation and regression analysis between body measurements and body weight was done with the help of the R program using nls function and “ggplot2” package. The findings indicate that among the various linear and nonlinear regression models that make use of individual body measurements, the most efficient model for forecasting the BW of female Saburai goats is the linear regression model that employs CG as the measurement. This model is followed in terms of performance by the quadratic polynomial regression model using CG and the exponential regression model using CG, as determined by the best selection criteria. However, when considering a combination of body measurements and employing stepwise regression analysis for selecting parameters, the optimal predictor for BW is identified as a combination of CG, BL, SH, and HW. Additionally, for a more simplified model that still maintains statistical significance in its coefficient regression, the most suitable regression model for predicting the BW of female Saburai goats is one that combines CG and SH. The regression equation representing this model can be expressed as Ŷ = -65.9639 + 1.0160CG + 0.4342SH.

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“…It is concluded that as an alternative to linear models, incomplete gamma and exponential models can be used to predict body weight of sheep using some body measurements (Barragan et al, 2021). Values of live weight can be estimated by taking body measurements at any stage of the fattening period (beginning, middle, end).…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of the Nonlinear Methods for Estimate Body Weight by Body Measurements on Different Sample Sizes in Morkaraman Sheeps

YAGANOGLU

2021

Preprint

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The objective of this study was to estimate body weight of Morkaraman sheeps from body measurements with nonlinear models. Selected 110 sheeps 3-5 years were scored for body weight, body length, height at wither, chest width and pump width. For determine relationships with body weight between body measurements, correlation analysis was performed. The results of the correlation analysis indicated that the highest relationship according to the all sample sizes were body weight between body length (0.95, 0.90, 0.83, 0.81). Considering all parameters included in the model, the parameter showing the highest correlation with body weight was determined as body length according to all sample sizes. the highest correlation was found in 50 sample sizes (r:0.95). According to the small sample sizes (10-20), Logistic and Saturation growth models can be used to determine the body weight by using body length, on the other hand, Incomplete gamma model is more succesful to estimate body weight when sample size is nearly 30 and 50.

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Comparison of linear and nonlinear models to estimate body weight of Pelibuey ewes from body measurements

Cited by 4 publications

References 10 publications

Morphological Description and Live Weight Prediction from Body Measurements of Socorro Island Merino Lambs

Morphological Description and Live Weight Prediction from Body Measurements of Socorro Island Merino Lambs

Use of nonlinear regression in predicting body weight of female Saburai goat

A Comparative Study of the Nonlinear Methods for Estimate Body Weight by Body Measurements on Different Sample Sizes in Morkaraman Sheeps

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