Diagnostic milk biomarkers for predicting the metabolic health status of dairy cattle during early lactation
S. Heirbaut; Xiaoping Jing; Barbara Stefańska; Ewa Pruszyńska‐Oszmałek; L. Buysse; P. Lutakome; M.Q. Zhang; M. Thys · 2022 · Journal of Dairy Science
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Data on metabolic profiles of blood sampled at d 3, 6, 9, and 21 in lactation from 117 lactations (99 cows) were used for unsupervised k-means clustering. Blood metabolic parameters included -hydroxybutyrate (BHB), nonesterified fatty acids, glucose, insulin-like growth factor-1 (IGF-1) and insulin. Clustering relied on the average and range of the 5 blood parameters of all 4 sampling days. The clusters were labeled as imbalanced (n = 42) and balanced (n = 72) metabolic status based on the values of the blood parameters. Various random forest models were built to predict the metabolic cluster
Abstract by S. Heirbaut; Xiaoping Jing; Barbara Stefańska; Ewa Pruszyńska‐Oszmałek; L. Buysse; P. Lutakome; M.Q. Zhang; M. Thys, Journal of Dairy Science (2022) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3168/jds.2022-22217