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Developing a growth curve model in Malabari goats

Sunitha Thomas

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22 January 2025
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A study was conducted to determine the growth curve for live weight in Malabari goats and to select the appropriate model to predict their growth. Data on body weight, body length, chest girth and height at withers of 1064 Malabari goats were recorded from birth to one year of age at monthly interval for the period 2014 - 2017 from the six field centres of ICAR-AICRP on goat improvement (Malabari), located at across Kerala state, India. Data were also recorded at University Goat and Sheep Farm, Thrissur, Kerala (Kerala Veterinary and Animal Sciences University) for the period 2017-2018.Effect of non-genetic factors like type of birth, sex, season, age of the dam and centre of study was corrected using least square analysis. The average daily gain (ADG) during the pre and post weaning period was determined. Five non-linear models were tested to fit the growth curve parameters of these goats. The coefficient of determination (R 2 ),Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Predicted Error (MAPE) were used as the criteria to determine the best fit model. As per the results, Gompertz model was found to be the best fit model to predict their growth.

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$109.00
Ships in 3-5 business days
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Developing a growth curve model in Malabari goats

$109.00

Description

A study was conducted to determine the growth curve for live weight in Malabari goats and to select the appropriate model to predict their growth. Data on body weight, body length, chest girth and height at withers of 1064 Malabari goats were recorded from birth to one year of age at monthly interval for the period 2014 - 2017 from the six field centres of ICAR-AICRP on goat improvement (Malabari), located at across Kerala state, India. Data were also recorded at University Goat and Sheep Farm, Thrissur, Kerala (Kerala Veterinary and Animal Sciences University) for the period 2017-2018.Effect of non-genetic factors like type of birth, sex, season, age of the dam and centre of study was corrected using least square analysis. The average daily gain (ADG) during the pre and post weaning period was determined. Five non-linear models were tested to fit the growth curve parameters of these goats. The coefficient of determination (R 2 ),Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Predicted Error (MAPE) were used as the criteria to determine the best fit model. As per the results, Gompertz model was found to be the best fit model to predict their growth.

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