Prediction of postpartum performances of transition Zebu (Bos indicus) cows using receiver operating characteristics analysis

Abstract

Receiver Operating Characteristics (ROC) analysis is a popular method to discriminate between the two conditions of tested animals. In this study, we estimated accuracy and threshold values of metabolic (Dry matter Intake; DMI and Body Condition Score: BCS, NEFA and BHBA) and immune indicators (Haptoglobin: Hp, Serum Amyloid A: SAA, IL-6, TNF-a, IL-1b, and IL-8) during transition period (–21, –14, –7, 0, +3, +7, +14 and +21 days) to predict the high yielding (HY) and pregnant Deoni cows. ROC analysis revealed that SAA (–21 d), IL-6 (–21 and –7 d), BCS (–7 d) and BHBA (–7 d) during pre-partum period, differentiated HY from low or medium yielder (LY/MY) cows with moderate to excellent accuracy (AUC >0.8). During postpartum period, IL-6 (+7 d), TNF-a (+21 d), DMI (+21 d), NEFA (+14 d and +21 d) and BHBA (+21 d) levels had moderate to excellent accuracy to differentiate HY from LY or MY cows. IL-6 (–14 d and –7 d), TNF-a (–14 d) and DMI (–21 d; above 2 kg/100 kg BW) during pre-partum period while, SAA (+3 d and +7 d), IL-6 (+3 and +21 d) and TNF-a (+7 and +21 d) during postpartum period were significantly predicted the pregnant cows with moderate to excellent accuracy. Altogether, it is concluded that SAA, IL-6 and TNF-a levels had higher accuracy in discrimination of HY and pregnant cows from LY or MY and non-pregnant cows, respectively. Therefore, their corresponding threshold values could be used for predicting HY and pregnant Zebu (Deoni) cows.