2019International Journal of Current Microbiology and Applied SciencesOpen access

Prediction of Body Weight based on Body Measurements in Crossbred Cattle

J. Patel Ashwini

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Abstract

The study was undertaken to develop linear regression equations for prediction of body weights of HF crossbred cattle based on body measurements. The study was carried out on 506 HF crossbred cattle of Livestock Research Station, AAU, Anand; Sarsa Heifer Farm – Amul Dairy, Anand; Ode Semen Station – Amul Dairy, Anand. All the data were grouped age wise. Females were grouped into 0-6 M, 6-12 M, 1-2 Y, 2-4 Y, 4-6 Y and ˃6 Y age groups. Simple and multiple linear regression models were formulated using step wise method using SPSS 21.0 software. Linear regression models were fitted with BW as the dependent variable and body measurements; body length (BL), height at wither (HW), height at hip (HH), heart girth (HG), chest depth (CD) and width of hip (WH) as the independent variables to obtain the relationship between BW and body measurements. High coefficient of determination values were observed in simple linear regression using HG alone as an independent variable in most of the age groups of HF crossbred cattle. Likewise, multiple regression equations having high coefficient of determination (R2) value for each age groups were also developed. The present study showed that heart girth measurement can be used to predict the live body weight HF crossbred cattle age groups wise.

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The study was undertaken to develop linear regression equations for prediction of body weights of HF crossbred cattle based on body measurements. The study was carried out on 506 HF crossbred cattle of Livestock Research Station, AAU, Anand; Sarsa Heifer Farm – Amul Dairy, Anand; Ode Semen Station – Amul Dairy, Anand. All the data were grouped age wise. Females were grouped into 0-6 M, 6-12 M, 1-2 Y, 2-4 Y, 4-6 Y and ˃6 Y age groups. Simple and multiple linear regression models were formulated using step wise method using SPSS 21.0 software. Linear regression models were fitted with BW as the dependent variable and body measurements; body length (BL), height at wither (HW), height at hip (HH), heart girth (HG), chest depth (CD) and width of hip (WH) as the independent variables to obtain the relationship between BW and body measurements. High coefficient of determination values were observed in simple linear regression using HG alone as an independent variable in most of the age groups of HF crossbred cattle. Likewise, multiple regression equations having high coefficient of determination (R2) value for each age groups were also developed. The present study showed that heart girth measurement can be used to predict the live body weight HF crossbred cattle age groups wise.

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Available abstract

The study was undertaken to develop linear regression equations for prediction of body weights of HF crossbred cattle based on body measurements. The study was carried out on 506 HF crossbred cattle of Livestock Research Station, AAU, Anand; Sarsa Heifer Farm – Amul Dairy, Anand; Ode Semen Station – Amul Dairy, Anand. All the data were grouped age wise. Females were grouped into 0-6 M, 6-12 M, 1-2 Y, 2-4 Y, 4-6 Y and ˃6 Y age groups. Simple and multiple linear regression models were formulated using step wise method using SPSS 21.0 software. Linear regression models were fitted with BW as the dependent variable and body measurements; body length (BL), height at wither (HW), height at hip (HH), heart girth (HG), chest depth (CD) and width of hip (WH) as the independent variables to obtain the relationship between BW and body measurements. High coefficient of determination values were observed in simple linear regression using HG alone as an independent variable in most of the age groups of HF crossbred cattle. Likewise, multiple regression equations having high coefficient of determination (R2) value for each age groups were also developed. The present study showed that heart girth measurement can be used to predict the live body weight HF crossbred cattle age groups wise.

Key concepts: Crossbreed, Body weight, Animal science, Biology, Endocrinology

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