Research Article

Regression Model and Correlation Analysis to Predict Body Weight of Rural Area Female Kacang Goat Based on Body Measurement

Lendrawati*, Tinda Afriani, Eli Ratni

Department of Animal Production and Technology, Faculty of Animal Science, Universitas Andalas, Kampus Unand Limau Manis Padang, 25165, Indonesia.

Received | October 29, 2023; Accepted | December 10, 2023; Published | March 01, 2024

*Correspondence | Lendrawati, Department of Animal Production and Technology, Faculty of Animal Science, Universitas Andalas, Kampus Unand Limau Manis Padang, 25165, Indonesia; Email: len1303@yahoo.com

Citation | Lendrawati, Afriani T, Ratni E (2024). Regression model and correlation analysis to predict body weight of rural area female Kacang goat based on body measurement. Adv. Anim. Vet. Sci., 12(5):802-806.

DOI | https://dx.doi.org/10.17582/journal.aavs/2024/12.5.802.806

ISSN (Online) | 2307-8316

Copyright: 2024 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Goats are important animals, especially in the tropics region. This animal can adapt to hard climate conditions, illness tolerance, and the ability to supply a wide range of products for people (Assefa et al., 2023). The goat population in Indonesia is about 19.39 million, with a total meat production of about 63.66 tonnes and a total slaughter of goats of 1.57 million (Livestock and Animal Health Statistics, 2022).This goat is widely raised in various parts of Indonesia, dominated by indigenousand local breeds. Moreover, the Kacang goat is the largest indigenous goat in Indonesia and is used for meat production (Ilham et al., 2023; Hariyono and Endrawati, 2023). Regardless of the enormous population, the significance of resource-poor farmers, and the adaptability of diverse agroecology, the current level of productivity of the Kacang goat is low, especially in rural areas (Lendrawati and Ratni, 2023; Khalil et al., 2019). As a result, improving productivity and conservation activities are crucial for the long-term usage of these breeds.

The primary goal of Kacang goat farming is to produce meat and generate cash through the sale of live animals and their products. Meat production is related to body weight, type, body measurements, and structural indices of livestock animals (Khandoker et al., 2017). Moreover, body measures are significant factors for describing animal growth and are utilized as selection criteria for animals (Rashid et al., 2016; Habib et al., 2019; Putra and Ilham, 2019). Aziz et al. (2023) claimed that growth traits such as live body weight and body measurements such as body length, shoulder height, and chest girth were relevant in the breed selection based on the Indonesian National Standard (SNI). In addition, knowledge of goat body weight is also useful in estimating feed requirements and dosages of medicines, as well as for other management purposes (Mahieu et al., 2011; Dakhlan et al., 2020).

Weighing is the most precise approach to determining the body weight of goats. However, collecting scales in the field is difficult, especially in rural locations (Assefa et al., 2023; Sam et al., 2016). Using body measurement as a prediction of body weight can be an alternative to measuring goat body weight in this case. A previous study reported a strong relationship between body weight and morphometric measurements such as in female Etawa grade goats (Dakhlan et al., 2020), Saburai goats (Dakhlan et al., 2021), Beetal goats (Iqbal et al., 2013; Waheed et al., 2020), black Bengal goat (Habib et al., 2019).

Although live body weight can be properly determined using a scale, certain occasions and settings necessitate a more practical technique for estimating body weight. The accuracy and suitability of approaches to determining body weight from body measurement in goats varies depending on breeds, ages, sexes, and production systems.

Dakhlan et al. (2021) reported that body weight is tightly related to body measurements, and chest girth is one of the body measurements that is widely regarded as the best single predictor of body weight in Saburai goats. Furthermore, many predictive regression equations are based on these data alone or in combination with other body measurements. Currently, there is limited data available pertaining to the estimation of body weight in Kacang goats through the utilization of body measurement and the regression method. The purpose of this study was to evaluate the association between body weight and body measurements (body length, shoulder height, and chest girth), as well as to identify the best-fitted regression model for predicting body weight in adult female Kacang.

Materials and Methods

This research was carried out from August to October 2022 on small-scale farmers in Talawi District, Sawahlunto Regency, Indonesia. In this investigation, adult female Kacang goats aged 1-3 years were used. All goats used in this study were reared under semi-intensive management, allowing them to graze on the pasture throughout the day and then housed and fed in the afternoon.

The survey approach was used in this study, and data were acquired through the purposive sampling techniques of adult female Kacang goats aged 1-3 years, reared in a semi-intensive system (allowing them to graze in the pasture throughout the day and then housed and fed in the afternoon).

The study involved the measurement of various variables, namely body weight (BW), body length (BL), chest girth (CG), and shoulder height (SH). Body weight was determined by weighing adult female Kacang goats using hanging scales with a capacity of 200 kg (DLE brand). The girth of the chest was assessed by applying adhesive tape around the thoracic cavity just behind the front legs. Employing a measuring rod, the length of the body (BL) was measured in a direct manner from the shoulder joint to a mass of the coccyx. Shoulder height was determined by employing a measuring stick to ascertain the distance from the most elevated point of the shoulder to the ground (Nurhayati et al., 2014; Dakhlan et al., 2020).

The data was analyzed using the SPSS version 23 platform (IBM Inc, USA). The boxplot and the Kolmogorov-Smirnov and Shapiro tests were used to determine the normality of the data distribution. The Pearson correlation coefficient was employed for the purpose of determining the correlations that exist between the variables. Simple and multiple regression models were employed to assess the association between body measurement and body weight as shown below.

a. BW = a + b1*BL

b. BW = a + b2*CG

c. BW = a + b3*SH

d. BW = a + b1*BL+ b2*CG

e. BW = a + b1*BL+ b3*SH

f. BW = a + b2*CG+ b3*SH

g. BW = a + b1*BL+ b2*CG +b3*SH

Where; BW was a live weight as a dependent variable (kg), a is a constant or intercept, b1, b2 and b3 is the regression coefficient for each independent variable (body measurements), BL are body length, CG are chest girth, and SH are shoulder height, in cm. Based on the regression model with the highest coefficient correlation (r), coefficient of determination (R2), and adjusted R2, the lowest root mean square error (RMSE) will be suggested for use in predicting the body weight of the adult female Kacang goat.

Result and Discusssion

Descriptive statistics

The body weight and body measurements of adult female Kacang goat were illustrated in Table 1 and Figure 1.

 

Table 1: Descriptive statistics of body weight and body measurements of adult female Kacang goat.

Items	n	Mean	Sd	CV	Median	Min	Max
Body weight (kg)	91	19.66	3.51	12.35	19.50	13.85	27.00
Body length (cm)	91	57.90	5.03	25.37	58.00	45.00	67.00
Chest girth (cm)	91	60.55	5.07	25.77	61.00	52.00	70.00
Shoulder height (cm)	91	50.95	5.06	25.60	50.50	42.00	63.00

 

N: number of records, Sd: standard deviation, Min: minimum, Max: maximum.

 

 

These demonstrated that the mean and median of the data were similar, indicating that the data were balanced between below and above the median, which means the data were distributed normally. The result showed that means with standard deviation for body weight, body length, chest girth, and shoulder height of adult female Kacang goats were 19.66±3.51 kg, 57.90±5.03 cm, 60.55±5.07 cm, and 50.95±5.06 cm, respectively.

Body weight is an important feature in animal productivity because it serves as an indicator of nutrition, health, breeding, and livestock selection (Ruchay et al., 2022). The data on body weight and body measurements of adult female Kacang goat were normally distributed (Figure 1). These findings found that the average of body weight of adult female Kacang goat (1-3 years in age) was 19.66± 3.51 kg with a coefficient variation of 12.94%. This result indicated that the variation of body weight of female Kacang goats in this case was low enough even though their ages were far apart (1-3 years old). The lower variation could be caused by the similarity of their environmental factor such as the management of feeding and rearing (semi-intensive rearing system).

The body weight and body measurement of female Kacang goat in this study is higher than the study reported by (Azmidaryanti et al., 2017), adult female Kacang goats that are raised semi-intensively in Riau Province have a body weight of 15.95±2.15 kg, body of length of 49.76±2.5, chest girth of 53.19±2.95 cm, and shoulder height of 47.26±2.60 cm. However, this current study is lower than those of does Kacang goat with a body weight of 27.11±4.93 kg, body length of 60.26±4.27 cm, and chest girth of 69.42±4.64 cm (Putra and Ilham, 2019). This finding was also lower than female Malaysian Kacang with body weight, body length, and chest girth was 23.65 kg, 70.5 cm, and 63.46 cm respectively (Khandoker et al., 2017). The difference in body weight and measures between this study and the previous study is assumed to be influenced by maintenance environment variables such as different feedstuff, feeding management, and temperature (Dakhlan et al,. 2020).

Correlation between body measurement and body weight of adult female Kacang goat

Table 2 shows the Pearson correlation between variables. The findings of this study revealed that body measurements were positively related to body weight, with chest girth (0.814) having the strongest correlation to body weight, followed that body length (0.723) and shoulder height (0.549). The correlation between body measurements was similarly positive, ranging from 0.750 to 0.822, showing that there was no multicollinearity due to less than 0.90 (Dakhlan, 2019). Pearson correlation between body weight and body measurements supports the findings in other Indonesian local breeds of goat such as Etawa Grade goats (Dakhlan et al., 2020), Batur sheep (Ibrahim et al., 2021) and Bali Cattle (Aziz et al., 2023) who found that chest girth had the highest correlation with body weight comparing to body length and shoulder height.

 

Table 2: The coefficient correlation between the variable of adult female Kacang goat.

Body weight	1.000
Body length	0.723	1.000
Chest girth	0.814	0.822	100
Shoulder height	0.549	0.750	0.814	1.000

 

Regression equation between body measurement And body weight of adult female Kacang goat

Table 2 presents the result of the regression analysis between body weight and body measurements of adult female Kacang goats, while the scatter plot and regression model are shown in Figure 1. This study found that using a single body measurement, chest girth was the best predictor of body weight, with the highest R2 (0.663), adjusted R2 (0.659), and lowest RMSE (13.689).This data showed that chest girth influenced 66.30% of body weight variation, whereas the remainder was driven by other factors. The regression model using body measurement of two predictors showed the highest R2 (0.676) and Adj R2 (0.668) and the lowest RMSE (13.421) for the regression model BW =- 15.705 + 0.133 BL + 0.457 CG, followed by R2 (0.663), Adj R2 (0.656) and RMSE (13.671) for the equation BW = - 14.650 + 0.553 CG + 0.016 SH, and R2 (0.563), Adj R2 (0.553) and RMSE (15.486) for the the equation BW = - 12.812 + 0.418 BL + 0.164 SH. Meanwhile, Stepwise regression analysis with all independent variables found that chest girth was the best predictor for body weight with Adj R2 (0.659) and RMSE (13.689). As a result, based on the highest R2, adj R2 and lowest of RMSE value, the combination of chest girth and shoulder height became the best model among the seven model regression.

 

Table 3: Simple and multiple linear regression model to estimate body weight using body measurement of female Kacang goat.

BW = - 9.381 + 0.504 BL	0.723**	0.522	0.517	16.297
BW = - 14.473 + 0.564 CG	0.814**	0.663	0.659	13.689
BW = 0.246 + 0.381 SH	0.549**	0.301	0.293	19.748
BW = - 15.705 + 0.133 BL + 0.457 CG	0.822**	0.676	0.668	13.427
BW = - 12.812 + 0.418 BL + 0.164 SH	0.750**	0.563	0.553	15.486
BW = - 14.650 + 0.553 CG + 0.016 SH	0.814**	0.663	0.656	13.671
BW =- 15..912 + 0.134 BL+ 0.445 CG+ 0.018 SH	0.822**	0.676	0.665	14.018

 

BW: body weight; BL: body length; CG: chest girth; SH: shoulder height; r: pearson correlation; R2: determination coefficient; Adj R2: adjusted R2; **: significant at level 0.01

 

 

The finding of regression models of a recent study similar to (Dakhlan et al., 2020; Ibrahim et al., 2021) that the combination of chest girth and body length was the best predictor for body weight of female goats and sheep. The best predictor of chest girth and body length for body weight may be related to the shape of the goat body, which is similar to a tube shape, with chest girth as the base area and body length as the height of the tube resulting in volume, which is body weight, so that the greater the chest girth and body length, the heavier the goat body weight (Ilham et al., 2023).

Conclusions and Recommendations

Body weight was highly associated with body length, chest girth, and shoulder height with chest girth having the highest correlation (0.814) and the best predictor for body weight (BW) of adult female Kacang goats followed by body length (0.723) and shoulder height (0.549) if using single body measurement. The fittest prediction of body weight with model regression BW = -15.705 + 0.133BL + 0.457CG had the greatest r (0.822), R2 (0.676), and adjusted R2 (0.668), as well as the lowest RMSE (13.427). These findings suggested that chest girth and body length be used as predictors for body weight of adult female Kacang goats in rural areas.

Acknowledgements

The authors thank LPPM of Andalas University for supporting to preparation of this manuscript by Scopus Camp series 5 and for Animal Science Faculty for funding this research.

Novelty Statement

This study found the best-fitted regression model for predicting the body weight of female Kacang goats in rural areas, which will help farmers with the selection process for Kacang goat breeding. It also provided information on the relationship between body weight and body measurements (body length, chest girth, and shoulder height).

Author’s Contribution

LDW: conceptualization, writing original draf, and statistical analyses, TA: methodology and supervision. ER: review and manuscript editing. All authors accepted for the final version of the manuscript.

Conflict of interest

The authors have declared no conflict of interest.

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