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A. Yakubu
Department of Animal Science, Faculty of Agriculture, Nasarawa State University, Keffi, Shabu-Lafia Campus, P.M.B. 135, Lafia, Nasarawa State
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences

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Modelling hatchability and mortality in muscovy ducks using automatic linear modelling and artificial neural network Yakubu, A.; Dahloum, L.; Shoyombo, A. J.; Yahaya, U. M.
Journal of the Indonesian Tropical Animal Agriculture Vol 44, No 1 (2019): March
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jitaa.44.1.65-76

Abstract

This study was embarked upon to predict hatchability and mortality rate of Muscovy ducks in Nasarawa State, Nigeria. Data were obtained from a total of 119 duck farmers. The automatic linear modelling (ALM) and artificial neural network (ANN) models were employed. The average flock size was 9.84±0.60 per household. The predicted hatchability mean values using ALM (8.66) and ANN (8.65) were similar to the observed value (8.66). The predicted mortality mean values using ALM (2.95) and ANN (3.03) were also similar to the observed value of 2.95. Experience in duck rearing, the educational status of farmers, source of foundation stock and season were the variables of importance in the prediction of hatchability using ALM and ANN models. However, primary occupation, source of foundation stock, experience in duck rearing, land holding and management system were the important variables automatically selected for the prediction of mortality. Moderate coefficients of determination (R2 = 0.422 vs 0.376) and adjusted R2 (0.417 vs 0.371) estimates were obtained for hatchability and mortality using ALM. Different patterns were obtained under the ANN models as regards the prediction of hatchability (R2= 0.573 and adjusted R2= 0.569) and mortality (R2= 0.615 and adjusted R2= 0.612). The present information may aid management decisions towards better hatchability and mortality performance in Muscovy ducks.
DETERMINATION OF PREDICTION EQUATIONS TO ESTIMATE BODY CONDITION SCORE FROM BODY SIZE AND TESTICULAR TRAITS OF YANKASA RAMS Yakubu, A.; Fakuade, O.F.; Faith, E.A.; Musa-Azara, I.S.; Agunwole, O.A.
Journal of the Indonesian Tropical Animal Agriculture Vol 38, No 2 (2013): (June)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jitaa.38.2.79-85

Abstract

The study was aimed to develop prediction models using stepwise multiple linear regressionanalysis for estimating the body condition score (BCS) from the body weight (BW), testicular length(TL), testicular diameter (TD) and scrotal circumference (SC) of indigenous Yankasa rams. Data wereobtained from 120 randomly selected rams with approximately two and half years of age, from differentextensively managed herds in Nasarawa State, Nigeria. Although pairwise phenotypic correlationsindicated strong association (P<0.01) among the measured variables, there was collinearity problembetween BW and SC as revealed by the variance inflation factors (VIF) and tolerance valves (T). TheVIT was higher than 10 (VIF = 19.45 and 16.65 for BW and SC, respectively). The Twas smaller than0.1 (T = 0.05 and 0.06 in BW and SC, respectively). BW was retained among the collinear variables, andwas singly accounted for 83.7% of the variation in BCS. However, a slight improvement was obtainedfrom the prediction of BCS from BW and TL [coefficient of determination (R2), adjusted R2 and rootmean squares error (RMSE) were 85.3%, 85.1% and 0.305, respectively]. The prediction of the BCS ofYankasa rams from BW and testicular measurements could therefore be a potential tool for sustainableproduction and improvement of small ruminants in Nigeria.
Quantifying of morphological character for Kacang goat using principal component factor analysis Lestari, D. A.; Sutopo, S.; Kurnianto, E.; Dagong, M. I. A.; Bugiwati, S. R. A.; Mamat-Hamidi, K.; Yakubu, A.; Pandupuspitasari, N. S.; Agusetyaningsih, I.; Kamila, F. T.; Setiaji, A.
Journal of the Indonesian Tropical Animal Agriculture Vol 49, No 4 (2024): December
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jitaa.49.4.316-322

Abstract

The study’s objective was to estimate the association among various linear body measurements and body weights of adult Kacang goats. The data was obtained from 209 heads of adult Kacang Goat, compressed 78 bucks and 131 ewes. The morphological evaluation was performed by measuring body weight (BW), body length (BL), chest depth (CD), chest girth (CG), chest width (CW), and withers height (WH). Factor PROCEDURE was performed to estimate the principal component. The result of factor analysis was used to determine the independent variable for linear regression analysis. BW has a favorable correlation with CG, BL, CD, CW, and WH for bucks and ewes. PC 1 accounts for 55.62% of the variation in bucks, while PC 2 accounts for an additional 18.34%. PC 1 accounts for just 0.45% of the overall variation in ewes, whereas PC 2 accounts for 0.24%. The R-squared (R2) values for bucks and ewes in the regression equation with CG as the independent variable are 0.32 and 0.41, respectively. For both bucks and ewes, the regression equation with CW as the independent variable had a higher R2 of 0.52 and 0.20, respectively. For bucks and ewes, the regression equation'sR2 values are 0.54 and 0.44, respectively, with combined CG and CW acting as independent variables. This integrated approach to analyzing body measurements in Kacang Goats provides a robust foundation for making informed decisions in goat farming.
Co-Authors A. Setiaji Agusetyaningsih, I. Bugiwati, S. R. A. Dahloum, L. E. Kurnianto E.A. Faith I.S. Musa-Azara Kamila, F. T. Lestari, D. A. M. I. A. Dagong, M. I. A. Mamat-Hamidi, K. O.A. Agunwole O.F. Fakuade Pandupuspitasari, N. S. Shoyombo, A. J. Sutopo Sutopo Yahaya, U. M.