Phenotypic variation of dairy cows’ hematic metabolites and feasibility of non-invasive monitoring of the metabolic status in the transition period

The results indicate that all fixed effects significantly affected the hematic concentration of most of the traits. Regarding MIR, the most predictable traits were BHB, NEFA, and urea, with coefficients of determination equal to 0.57, 0.62, and 0.89, respectively. These values suggest that MIR predictions of BHB and NEFA are not sufficiently accurate for precise and punctual determination of the hematic concentration, however, still the spectrum of the milk can be exploited to identify cows at risk of negative energy balance and subclinical ketosis. Finally, the predictions can be useful for herd screening, decision-making, and genetic evaluation.

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Publication Details

Journal
Frontiers in Veterinary Science
Published
2024-11-25
DOI
https://doi.org/10.3389/fvets.2024.1437352
Citations
22
Primary Topic
Reproductive Physiology in Livestock
Type
article
Field-Weighted Citation Impact
12.49
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article

Phenotypic variation of dairy cows’ hematic metabolites and feasibility of non-invasive monitoring of the metabolic status in the transition period

Silvia Magro, Massimo De Marchi, Elena Chiarin, Angela Costa et al.
22 citations
Frontiers in Veterinary Science
Reproductive Physiology in Livestock
12.49
article

Phenotypic variation of dairy cows’ hematic metabolites and feasibility of non-invasive monitoring of the metabolic status in the transition period

Silvia Magro, Massimo De Marchi, Elena Chiarin, Angela Costa, Damiano Cavallini
article en
22 citations

Abstract

The results indicate that all fixed effects significantly affected the hematic concentration of most of the traits. Regarding MIR, the most predictable traits were BHB, NEFA, and urea, with coefficients of determination equal to 0.57, 0.62, and 0.89, respectively. These values suggest that MIR predictions of BHB and NEFA are not sufficiently accurate for precise and punctual determination of the hematic concentration, however, still the spectrum of the milk can be exploited to identify cows at risk of negative energy balance and subclinical ketosis. Finally, the predictions can be useful for herd screening, decision-making, and genetic evaluation.

Frontiers in Veterinary ScienceVol. 11
University of Padua (IT), University of Bologna (IT)
Zero hunger
Openalex Percentile: Top 1%
Reproductive Physiology in Livestock
12.49
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