Investigation of Egg External Quality Characteristics of Linda Geese with Data Mining Methods

Year 2022, , 115 - 121, 26.12.2022

Harun Yonar , Emre Arslan , Kemal Kırıkçı

https://doi.org/10.53518/mjavl.1198225

Abstract

In this study, the external quality characteristics of eggs belonging to Linda accidents, a poultry species, were investigated with a data mining approach. The 288 Linda goose eggs used in the study were 36 weeks old; Their width was 52.34 mm, egg length was 76.8 mm, egg weight was 120.43 g, and shape index value was 68.26. Eggs were clustered according to shape index and weight measurements using the K-means clustering algorithm, a data mining approach. Statistically significant differences were found between the clusters in width, height, shape index, and weight (p<0.05). The findings of our study showed that eggs with a low index had high- weight; eggs with a high index were low-weight eggs. According to the results of this study, it was concluded that the shape index value might be related to egg weight. More detailed inferences can be made using data mining algorithms for different poultry species.

Keywords

Linda, goose, data mining method, egg, quality

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