Diagnostic accuracy of milk components for pregnancy diagnosis in mid and late lactation cows Dijagnostička točnost sastojaka mlijeka kod dijagnostike gravidnosti u krava srednje i kasne laktacije

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Kaya U., Yazlık M. O., Özkan H., Çamdeviren B., Güngör G., Dalkıran S., ...Daha Fazla

Mljekarstvo, cilt.73, sa.3, ss.187-195, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 73 Sayı: 3
  • Basım Tarihi: 2023
  • Doi Numarası: 10.15567/mljekarstvo.2023.0305
  • Dergi Adı: Mljekarstvo
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Sayfa Sayıları: ss.187-195
  • Anahtar Kelimeler: AUC, Holstein cows, lactation, milk components, ROC analysis, SOMATIC-CELL COUNT, FREEZING-POINT, ELECTRICAL-CONDUCTIVITY, YIELD, GESTATION, TRAITS, PARITY, SEASON, STAGE, FAT
  • Ankara Üniversitesi Adresli: Evet

Özet

The aims of this study were to establish a cut-off point by evaluating the usability of the somatic cell count (SCC) and milk components (fat, fat-free dry matter (FFDM), protein, lactose, freezing point, electrical conductivity and pH) to observe the pregnancy status, and to determine the practical usage of these parameters as diagnostic biomarker of pregnancy status. In the present study, primiparous Holstein cows (n=133) were included in the mid and late lactation. Milk samples were collected in sterile tubes for SCC and milk components analysis. In each lactation period, SCC, milk yield and milk component parameters were analysed by Student’s t test according to pregnancy status. Receiver operating characteristic curves were used to determine the predictive threshold using SCC and milk component parameters to discriminate between pregnant and non-pregnant cows. SCC levels were similar for all cows in the mid and late-lactation. In the mid lactation, FFDM, protein, lactose and electrical conductivity were higher and milk yield, fat, freezing point and pH were lower in pregnant cows (p<0.05). In the late lactation, FFDM, protein, lactose and electrical conductivity were significantly higher and milk yield, fat and pH were significantly lower in pregnant cows (p<0.05). Furthermore, fat, FFDM, protein, lactose, freezing point, electrical conductivity, and pH were the best predictors for pregnancy diagnosis in mid-lactating cows with the AUC values of 0.840, 0.768, 0.780, 0.772, 0.693, 0.792, and 0.901 respectively. Furthermore, fat, FFDM, protein, lactose, electrical conductivity, and pH could be useful diagnostic tools for pregnancy determination in late lactating cows with the AUC values of 0.869, 0.684, 0.661, 0.689, 0.756, and 0.841 respectively. In conclusion, the milk components could be used as rapid, easily accessible, and inexpensive markers for the evaluation of the diagnosis of pregnancy status in primiparous Holstein cows.