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    An application of bootstrap technique in animal science: Egg yolk color sample
    (KAFKAS UNIV, VETERINER FAKULTESI DERGISI, 2015) Narinç, Doğan; Aygün, Ali; Küçükönder, Hande; Aksoy, Tülin; Gürcan, Eser Kemal
    In this study, it was aimed to introduce the Bootstrap technique and to reveal the relationship between measurements of yolk color fan grades and digital colorimeter that is used for determining the yellow color of egg by utilizing this technique. For this purpose, a total of 1350 samples of 15 color grades of Roche yolk color fan and L* (lightness), a* (redness), b* (yellowness) values in the same samples were compared. The means, standard errors and confidence intervals for each color parameters of fan grades have been demonstrated by the Bootstrap technique. The grades of Roche yolk color fan in terms of L* values have been divided into 10 groups (P < 0.01), while only divided into 9 groups in terms of b* values (P < 0.01). According to the means of Redness (a*), all of the Roche yolk color fan grades (15 grades) have been determined as independent from each other (P < 0.01). With the Bootstrap method, the standard error values of means were decreased by 42.03%, 35.38% and 30.24%, respectively, and the confidence intervals were narrowed by the ratio of 42.03%, 35.38% and 30.24%, respectively. The results of the study were compared with the results of the study that was conducted by using Roche yolk color fan which is cheaper but less reliable and by using digital colorimeter method which is expensive but reliable.
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    Comparison of Resampling and Bayesian Approaches in Variance Component Estimation of a Hierarchical Univariate Mixed Effect Model
    (Selçuk Üniversitesi, 2020) Narinç, Doğan; Öksüz Narinç, Nihan
    The purpose of the study is to investigate the relative performance of two estimation procedures, a semi-frequentist estimation technique (via a Bootstrapped the restricted maximum likelihood: Bootstrap-REML) and Bayesian method (via a Gibbs sampler), for estimation of variance components of a two level hierarchical linear mixed model. For this purpose one variable named X was generated using R simulation with the structure of two level nested designs which showed Gaussian distribution. The variable X contains 10000 data, with an average of 0 and variances of 100 and. For this data, five different scenarios were created according to the rate of variance components and analyzes were carried out. All of the estimations and definitions of autocorrelation, changes of the total variance and estimation biases were performed for the posterior distributions and bootstrapped parameter distributions of all the scenarios. In general, the results obtained with both methods are close to each other, although the bias of the results obtained with the Gibbs sampling method was found less and autocorrelation was not found for Gibbs sampling estimates. In conclusion, according to the results of this study, it is not possible to say that using the Bootstrap-REML estimator under Gaussian distribution and balanced data is a good alternative to Bayesian Gibbs sampler.Perhaps different results may be obtained from another study using unbalanced data, non-normally distributed data and high sample sizes.
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    Japanese quail meat quality: Characteristics, heritabilities, and genetic correlations with some slaughter traits
    (POULTRY SCIENCE ASSOC INC, 2013) Narinç, Doğan; Aksoy, Tülin; Karaman, Emre; Aygün, Ali; Fırat, Mehmet Ziya; Uslu, Mustafa Kemal
    The aim of this study was to evaluate the genetic parameters of several breast meat quality traits and their genetic relationships with some slaughter traits [BW, breast yield (BRY), and abdominal fat yield (AFY)]. In total, 1,093 pedigreed quail were slaughtered at 35 d of age to measure BRY, AFY, and breast meat quality traits [ultimate pH (pHU), Commission Internationale d'Eclairage color parameters (L*, lightness; a*, redness; and b*, yellowness), thawing and cooking loss (TL and CL, respectively), and Warner-Bratzler shear value (WB)]. The average pHU, L*, a*, and b* were determined to be 5.94, 43.09, 19.24, and 7.74, respectively. In addition, a very high WB average (7.75 kg) indicated the firmness of breast meat. High heritabilities were estimated for BW, BRY, and AFY (0.51, 0.49, and 0.35). Genetic correlations of BW between BRY and AFY were found to be high (0.32 and 0.58). On the other hand, the moderate negative relationship between BRY and AFY (-0.24) implies that selection for breast yield should not increase abdominal fat. The pHU was found to be the most heritable trait (0.64), whereas the other meat quality traits showed heritabilities in the range of 0.39 to 0.48. Contrary to chickens, the genetic correlation between pHU and L* was low. The pHU exhibited a negative and high correlation with BW and AFY, whereas L* showed a positive but smaller relationship with these traits. Moreover, pHU exhibited high negative correlations (-0.43 and -0.62) with TL and WB, whereas L* showed a moderate relationship (0.24) with CL. This genetic study confirmed that the multi-trait selection could be used to improve meat quality traits. Further, the ultimate pH of breast meat is a relevant selection criterion due to its strong relationships with either water-holding capacity and texture or low abdominal fatness.