Towards understanding the type and function of indigenous goats: input for genetic improvement and conservation programme

Assefa, Tesfamichael; Alemayehu, Kefyalew; Tesema, Zeleke

doi:10.1080/09712119.2023.2254368

Cited by 2 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…G oats 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.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Lendrawati,

Afriani,

Ratni

2024

AAVS

View full text Add to dashboard Cite

This study aimed to determine the optimal model for predicting the body weight of adult female Kacang goats based on certain body measurements and to investigate correlation and regression. This study used 91 heads of Kacang Does collected from Talawi village from 2021-2022. The body weight (BW) data was regressed and associated with body dimensions (body length = BL, chest girth = GH and shoulder height = SH) using the SPSS program. The Pearson correlation (r) between body weight and measurements was calculated and the degree of fit of the models was assessed using the coefficient of determination (R 2 ), Adj R 2 and root mean squared error (RMSE). Body weight had a highly significant (P< 0.01) correlation with BL (r = 0.723), CG (r = 0.814), and SH (r = 0.549). The optimal estimation of body weight was achieved through a blend of chest circumference and body length, as indicated by the regression model: BW = -15.705 + 0.133BL + 0.457CG.0.457CG with the highest r (0.822), R 2 (0.676) and adjusted R 2 (0.668) and the lowest RMSE (13.427). These findings suggested that chest girth and body length can be used as predictors for body weight of adult female Kacang goats in rural areas. The findings could help farmers in adult female Kacang goat breeding by estimating body weight from body measurements.

show abstract

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Lendrawati,

Afriani,

Ratni

2024

AAVS

View full text Add to dashboard Cite

show abstract

Phenotypic characterization of Nguni goats in four agro-ecological zones of Limpopo province, South Africa

Mathapo,

Mugwabana,

Tyasi

2024

PLoS ONE

View full text Add to dashboard Cite

The study was conducted to phenotypically characterize Nguni goats from four agro-ecological zones of Limpopo province, South Africa. A total of 426 goats were sampled from four agro-ecological zones. The quantitative traits that were studied for phenotypic characterization using Analysis of Variance (ANOVA) were heart girth (HG), body length (BL), withers height (WH), sternum height (SH), rump height (RH), rump length (RL), rump width (RW), cannon circumference (CC), testicular length (TL) and scrotal circumference (SC) while qualitative traits were coat colour pattern and type, back profile, ear orientation, presence of horn, horn shape and orientation. The study further looked at the structural indices of the goats. The findings indicated that the agro-ecological zones significantly affected (P<0.05) the quantitative traits of Nguni goats. Female goats from arid zone had higher (P<0.05) BW, HG, BL, WH, RH, and CC with mean values of 35.76±0.92, 73.89±0.63, 66.26±0.62, 63.40±0.56, 64.71±0.44 and 8.07±0.06, respectively as compared to the other zones. Male goats from arid zone had higher (P<0.05) BW, HG, BL, RW, TL and SC with mean values of 37.20±2.29, 78.75±1.44, 70.95±1.57, 16.83±0.38, 15.50±0.50 and 31.00±0.00, respectively as compared to other zones. In terms of qualitative traits, the goats were characterized by higher proportion of patchy coat colour pattern (62.7%), brown dominant colour type (42.6%), straight back profile (46.6%), and semi-pendulous ear orientation (65.4%). The goats had horns (100%), curved horn shape (71.6%) and backward horn orientation (89.4%). Though the agro-ecological zone had non-significant influence (P>0.05) on the qualitative traits. Findings of structural indices on dactyl-thoracic, transversal pelvic, longitudinal pelvic and proportionality indicated that the Nguni goats can be matched as light medium meat type. In conclusion, the variation in morphometric traits of Nguni goats and knowing their structural and functional indices can assist in their conservation and genetic improvement. There was no difference in the qualitative traits of the goats in four agro-ecological zones. Studies needed to be conducted on genetic characterization using genetic markers to integrate the information from morphological traits.

show abstract

Towards understanding the type and function of indigenous goats: input for genetic improvement and conservation programme

Cited by 2 publications

References 17 publications

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

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

Phenotypic characterization of Nguni goats in four agro-ecological zones of Limpopo province, South Africa

Contact Info

Product

Resources

About