Siyah Alaca Sigirlarda 305 Gunluk Sut Verimini Etkileyen Faktorlerin Path (Iz) Analizi Ile Belirlenmesi

WOS: 000349190400011A quantitative trait was affected directly or indirectly by several factors due to relationships among them. It is necessary to identified direct and indirect effects of a factor to reveal all relationships in a detailed way. In this study, total of 11647 305-day milk yield records from the 7 parities of 5047 Holstein Friesian cows were statistically evaluated for determining direct and indirect effects of parity (X1), year of calving (X2) and lactation length (X3) on 305-day milk production (Y) via path analysis. Correlations among 305 day milk yield, parity, year of calving and lactation length were calculated 0.17, 0.43, 0.54 respectively and found statistically significant ((P<0.01). The direct effects of the parity, year of calving and lactation length on 305-day milk production were found PY1=0.12, P21=0.10, P31=0.46 respectively and statistically significant (P<0.01). The indirect U effect of parity via year of calving and S effect via lactation length on 305 day milk yield were found 0.01 and 0.04, respectively. The indirect U effect of year of calving via lactation length and S effect via parity on 305 day milk yield were found 0.31 and 0.02, respectively. Moreover, the indirect U effect of lactation length via year of calving and S effect via parity were found 0.07 and 0.01, respectively and lower

Time Scale In Least Square Method

Study of dynamic equations in time scale is a new area in mathematics. Time scale tries to build a bridge between real numbers and integers. Two derivatives in time scale have been introduced and called as delta and nabla derivative. Delta derivative concept is defined as forward direction, and nabla derivative concept is defined as backward direction. Within the scope of this study, we consider the method of obtaining parameters of regression equation of integer values through time scale. Therefore, we implemented least squares method according to derivative definition of time scale and obtained coefficients related to the model. Here, there exist two coefficients originating from forward and backward jump operators relevant to the same model, which are different from each other. Occurrence of such a situation is equal to total number of values of vertical deviation between regression equations and observation values of forward and backward jump operators divided by two. We also estimated coefficients for the model using ordinary least squares method. As a result, we made an introduction to least squares method on time scale. We think that time scale theory would be a new vision in least square especially when assumptions of linear regression are violated.WoSScopu