We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Investigation of Egg External Quality Characteristics of Linda Geese with Data Mining Methods.
- Authors
YONAR, Harun; ARSLAN, Emre; KIRIKÇI, Kemal
- 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.
- Subjects
EGG quality; GEESE; DATA mining; K-means clustering; COMPUTER algorithms
- Publication
Manas Journal of Agriculture Veterinary & Life Sciences, 2022, Vol 12, Issue 2, p115
- ISSN
1694-7932
- Publication type
Article
- DOI
10.53518/mjavl.1198225