Atıf İçin Kopyala
Balcı Z., Yabanova İ.
Sakarya University Journal of Science, cilt.26, sa.3, ss.579-589, 2022 (Hakemli Dergi)
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Yayın Türü:
Makale / Tam Makale
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Cilt numarası:
26
Sayı:
3
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Basım Tarihi:
2022
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Doi Numarası:
10.16984/saufenbilder.848213
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Dergi Adı:
Sakarya University Journal of Science
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Derginin Tarandığı İndeksler:
Academic Search Premier, Business Source Elite, Business Source Premier, EBSCO Education Source, TR DİZİN (ULAKBİM)
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Sayfa Sayıları:
ss.579-589
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Van Yüzüncü Yıl Üniversitesi Adresli:
Evet
Özet
Although the egg is a cheap food source, it is one of the valuable nutritional sources for people because of its rich nutritional values. It is also among the most consumed foods in daily nutrition. With the increase in egg production, it is very difficult to collect them with the human power in the egg production farms, to classify them according to their weights and to separate the defective (dirty and broken) eggs. Therefore, the mechanization has become a necessity in large capacity production farms. Cracks and fractures may occur in the egg shell as a result of exposure to external factors such as the transportation of eggs. The cracks or fractures that are formed leave the egg vulnerable to disease-causing micro-organisms. Before the egg sorting and packing, the broken and cracked eggs must be separated. This process is commonly carried out with manpower. However, it is very difficult to obtain the necessary efficiency from this process based on manpower. In this study, egg crack detection was performed by using Support Vector Machines (SVM) and Artificial Neural Network (ANN). As a result of the applied methods, crack detection process accuracy values were 0.99 for ANN and 1 for SVM. In addition, the program was developed in LABVIEW environment to detect cracks in real time.