Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
Use of Multivariate Adaptive Regression Splines, Classification Trees and ROC Curve in Diagnosis of Subclinical Mastitis in Dairy Cattle
Journal of the Hellenic Veterinary Medical Society · Ocak 2022
YÖKSİS Kayıtları
Use of Multivariate Adaptive Regression Splines, Classification Trees and ROC Curve in Diagnosis of Subclinical Mastitis in Dairy Cattle
JOURNAL OF THE HELLENIC VETERINARY MEDICAL SOCIETY · 2022 SCI-Expanded
PROFESÖR İBRAHİM AYTEKİN →
Makale Bilgileri
DergiJournal of the Hellenic Veterinary Medical Society
Yayın TarihiOcak 2022
Cilt / Sayfa73 · 3817-3826
Scopus ID2-s2.0-85129649865
Erişim🔓 Açık Erişim
Özet
Subclinical mastitis is one of the most significant diseases that cause economic losses in dairy cattle farming. This research was conducted on 112 heads of Holstein Friesian dairy cattle to reveal the relationship between subclinical mastitis and milk composition and milk quality.In the study, CMT (California Mastitis Test) and CSCC (Classified Somatic Cell Count) used in the diagnosis of subclinical mastitis were used as a binary response variable i.e. healthy and unhealthy. Potential predictors included here were lactation number, days in milk (DIM), darkness-lightness ranges between 0=black and 100=white (L*), green-red ranges between - a*=-60 and a*=+60 (a*), blue-yellow ranges between -b*=-60 and b*=+60 (b*), redness-yellowness (Hue°), vividness-dullness (Chroma), milk fat, milk protein, lactose, milk freezing point, solid non-fat SNF, density, solids, pH, and electrical conductivity. Classification and Regression Tree (CART), Chi-Squared Automatic Interaction Detection (CHAID), Exhaustive Chi-Squared Automatic Interaction Detection (Ex-CHAID), Quick, Unbiased, Efficient, Statistical Tree (QUEST), and multivariate adaptive regression splines (MARS) were used as data mining algorithms that help to make an accurate decision about detecting influential factors increasing the risk of subclinical mastitis. In conclusion, better classification performances of CART and MARS data mining algorithms were determined compared with those of the remaining algorithms to correctly discriminate between healthy and unhealthy cows.
Yazarlar (3)
1
Altay Yasin
ORCID: 0000-0003-4049-8301
2
Ibrahim Aytekin
3
Ecevit Eyduran
Anahtar Kelimeler
Classification trees
CMT
CSCC
MARS algorithm
Milk quality
Subclinical Mastitis
Kurumlar
Eskişehir Osmangazi Üniversitesi
Eskisehir Turkey
Iğdır Üniversitesi
Igdir Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
2
Atıf
3
Yazar
6
Anahtar Kelime