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Predicting The Body Weight Of Indigenous Goat Breeds From Morphological Measurements Using The Classification And Regression Tree (Cart) Data Mining Algorithm
(Institute for Animal Husbandry, Belgrade-Zemun, 2023) Oyebanjo, M.O.
Classification and regression tree (CART) is a tree-based data mining algorithm that develops a model to predict an outcome. This study purposed to create a model to predict the body weight (BWT) of Red Sokoto (RS), Sahel (SH), and West African Dwarf (WAD) goats using morphological measurements (such as body length, BL; head girth, HG; head width, HDW; face length, FAL; height at wither, HTW; rump length, RL; shoulder width, SW; rump width, RW; and rump height, RH). In total, 600 goats were used for this study (200 each of RS, SH, and WAD goats). Pearson’s Moment Correlation was used to evaluate the degree of association between BWT and each morphological measurement. Concomitantly, CART analysis was performed to estimate which independent variable (morphological measurements) played a considerable role in the BWT (dependent variable) prediction. In RS and WAD goats, a positive and statistically significant (p < 0.0001) correlation was observed between BWT and each morphological measurement. However, in SH goats, both positive and negative statistically significant correlations were observed between BWT and morphological measurements. The CART analysis indicated that in RS and WAD goats, HG played a considerable role in BWT prediction, while, in SH goats, BL was considered the most critical independent variable in BWT prediction. Therefore, this study suggests that HG can be used as a prognostic index for BWT estimation in Red Sokoto and West African Dwarf, while BL can be used for Sahel goats. The SAS codes used are available via a GitHub repository (https://github.com/Soullevram/CART).
Factor analysis and body dimensions of the Japanese quail (Coturnix Coturnix Japonica)
(2023) Osaiyuwu, O.H.; Idahor, K.O.; Akintan, A.A.
Morphometric variation can be effectively measured within and between populations and used as a basis for characterization of different livestock types. The study was aimed at contributing to the characterization process of the Japanese quail (mottled brown and white) through quantitative assessment. Zoometrical data on body weight and 11 body measurement were taken on 747 mottled brown quail and 272 white quail from six different farms around Ibadan in the Southwest Nigeria. Descriptive statistics showed that average body weight of Japanese quail reared in Southwest Nigeria were 158.72±2.03, 157.24±1.31, 140.6 ±1.39, and 136.27±2.7g for mottled brown female, brown male, white female and white male, respectively. Sexual dimorphism was observed in all the traits with higher values recorded for the females. Significant correlation (P<0.001) was observed between body weight and body measurements. The best correlation was obtained between body weight and thigh length r = 0.76 and 0.70 for mottled brown quail and white respectively. Factor solution from the principal component analysis, with varimax rotation of the transformation matrix showed three factors were identified in each of the genetic group (total variance of first principal component = 27.86, 30.16, 31.88 and 38.85 for mottled brown male, mottled female, white male, white female quail, respectively). In the two strains of Japanese quail, PC1 had the largest share of the total variance and correlated highly with body weight, breast length, wing length, thigh length and shank length. The PC1 could be used to describe the generalised form of quail. PC2 was orthogonal to PC1 and loaded heavily on breast girth and neck length. Data was also subjected to linear and stepwise regression. More reliable prediction was obtained from stepwise regression, R² was highest with breast girth R²=0.71 and breast length R²=0.81 for brown and white quail, respectively. The weight of Japanese quail is linearly related to body measurements. The high, positive correlation between body weight and zoometric body measurements indicates that these easily measured parts can be used as criteria for assessment and selection of body weight.
Analysis of Growth Models of Japanese Quails (Coturnix Coturnix japonica) in Nigeria
(2017) Olaniyan, A.A.; Akinyemi, M.O.; Osaiyuwu, O.H.; Salako, A.E
This study, aimed at comparing the growth curve parameters and determining the best non linear model for Japanese quails was conducted at the Department of Animal Science, University of Ibadan, Ibadan. Two hundred and thirty-five (235) Japanese quails were purchased at day old from a reputable hatchery in Ibadan and reared in cages, after two weeks of brooding on deep litter. Body weights (g) were taken weekly from hatch till the birds were 25 weeks old. The average of the weekly body weights was fitted to four non-linear models, namely Gompertz, Logistic, Brody and Von Bertalanffy to define the growth pattern and examine the existence of differences in the growth pattern described by the models. Models were compared using Coefficients of determination (R2), Mean square error (MSE), size of Residual standard deviation (RSD), Akaike’s information criteria (AIC) and Percentage forecast error. The R2 values were high for all models: 0.980, 0.979, 0.973 and 0.973 for Von Bertalanffy, Gompertz, Logistic and Brody, respectively. The Mean square error and Akaike’s information criteria values were 65.744 and 107.449; 64.685 and 107.043; 51.363 and 101.277; 49.731 and 100.470 for the Logistic, Brody, Gompertz and Von Bertalanffy models, respectively. Residual standard deviations were 8.979, 8.539, 7.847 and 7.832 with corresponding Percentage forecast error (PCFE) values of 16.315, 11.523, 12.948 and 13.687 for the Brody, Logistic, Gompertz and Von Bertalanffy models respectively. The Von Bertalanffy model was the most suitable for explaining the growth of the Japanese quails based on these goodness of fit criteria: The highest R2 (0.980), lowest Mean square error (49.731), Residual standard deviation (7.832) and Akaike’s information criteria (100.470)

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