2019, Cilt 35, Sayı 3, Sayfa(lar) 152-157 |
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Prediction of the length and width of quail eggs using linear regression analysis |
Sema Alaşahan^{1}, Betül Dağoğlu Hark^{2}, Ömer Eltas^{3} |
^{1}Hatay Mustafa Kemal University, Faculty of Veterinary Medicine, Department of Animal Science, Hatay, Turkey ^{2}Firat University, Scholl of Medicine, Department of Biostatistics and Medical Informatics, Elazig, Turkey ^{3}Ataturk University, Faculty of Veterinary Medicine, Department of Biometry, Erzurum, Turkey |
Keywords: Coturnix japonica, egg weight, equations, egg length and width |
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Aim: This study was aimed at establishing regression equations
for the estimation of egg length and egg width values
using egg weight values in quail eggs, and at determining the
error rate of the regression equations established.
Materials and Methods: Quail eggs were collected twice, between June and August to be used for the establishment of equations, and between September and October to be used for the assessment of the accuracy of the equations established. The numeric measurements of the eggs are presented as means and standard deviations. Results: Equations were established for the estimation of the dependent egg length and egg width variables using the independent egg weight variable with linear regression analysis. It was determined that equations (1) and (2) established for the estimation of egg length and egg width, respectively, both performed very well. The R² value was 0.99 for both equations, which demonstrated that the egg weight variable had a share of 99% in describing the total change in the egg length and egg width variables. The mean difference between the regression equation established in this study for the estimation of egg length and the Rahn and Paganelli (1988) equation was found to be statistically insignificant (P=0.939). Conclusion: In result, the regression equation established in this study for the estimation of quail egg width was ascertained to perform better than the Rahn and Paganelli (1988) equation, and the mean difference between these two equations was statistically significant. |
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