Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle

ABSTRACT: Numerous prediction equations have been developed based on mid-infrared (MIR) spectra, and some could be potentially used as biomarkers of heat stress. However, practical experience shows that confusion can easily occur between the effect of heat stress and other effects, such as lactation...

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Main Authors: Pauline Lemal, Clément Grelet, Frédéric Dehareng, Hélène Soyeurt, Martine Schroyen, Nicolas Gengler
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Journal of Dairy Science
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Online Access:http://www.sciencedirect.com/science/article/pii/S0022030224012657
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author Pauline Lemal
Clément Grelet
Frédéric Dehareng
Hélène Soyeurt
Martine Schroyen
Nicolas Gengler
author_facet Pauline Lemal
Clément Grelet
Frédéric Dehareng
Hélène Soyeurt
Martine Schroyen
Nicolas Gengler
author_sort Pauline Lemal
collection DOAJ
description ABSTRACT: Numerous prediction equations have been developed based on mid-infrared (MIR) spectra, and some could be potentially used as biomarkers of heat stress. However, practical experience shows that confusion can easily occur between the effect of heat stress and other effects, such as lactation stage or feeding variation over the year. On this basis, the objective of this study was to identify potential milk components predicted by MIR as biomarkers of heat stress based on a 2-step approach allowing correction for those effects. The first step consisted in the estimation of residuals from test-day random regression models on DIM to remove systematic lactation stage effects. These models also contained, among others, general (i.e., month of production) or specific (i.e., herd × test-day) fixed effects related to feeding and management. During the second step, means and variances of residuals by temperature-humidity index (THI) classes were studied. The models were applied to 611,063 records from 97,042 primiparous Holstein cows from 2015 to 2022 in the south of Belgium. The MIR-predicted milk components with the highest deviations from the mean with increasing THI were protein percentage, casein concentration, magnesium concentration, and (to a lesser extent) PUFA concentration. Concerning residual variances, the highest heteroscedasticity with THI was obtained for milk MIR MUFA, C18:1 cis-9, and citrate concentrations. Conversely, a relative homoscedasticity of variance with increasing THI was observed for several milk MIR components including protein percentage and casein concentration. Based on the criteria of the good biomarkers guidelines, milk protein percentage seems to be the most promising trait of this study, followed by Mg concentration. However, in the context of genetic evaluation, which requires variability, milk MIR MUFA, C18:1 cis-9, or citrate concentration variations, if they are heritable, could be of great interest. Finally, an increase in milk MIR citrate concentration variance could be an early warning for the detection of heat stress in the frame of DHI.
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spelling doaj-art-d83dff02aea94208b6b99be33d84fa832025-01-23T05:25:12ZengElsevierJournal of Dairy Science0022-03022025-02-01108217141729Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattlePauline Lemal0Clément Grelet1Frédéric Dehareng2Hélène Soyeurt3Martine Schroyen4Nicolas Gengler5University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium; Corresponding authorWalloon Agricultural Research Center (CRA-W), 5030 Gembloux, BelgiumWalloon Agricultural Research Center (CRA-W), 5030 Gembloux, BelgiumUniversity of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, BelgiumUniversity of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, BelgiumUniversity of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, BelgiumABSTRACT: Numerous prediction equations have been developed based on mid-infrared (MIR) spectra, and some could be potentially used as biomarkers of heat stress. However, practical experience shows that confusion can easily occur between the effect of heat stress and other effects, such as lactation stage or feeding variation over the year. On this basis, the objective of this study was to identify potential milk components predicted by MIR as biomarkers of heat stress based on a 2-step approach allowing correction for those effects. The first step consisted in the estimation of residuals from test-day random regression models on DIM to remove systematic lactation stage effects. These models also contained, among others, general (i.e., month of production) or specific (i.e., herd × test-day) fixed effects related to feeding and management. During the second step, means and variances of residuals by temperature-humidity index (THI) classes were studied. The models were applied to 611,063 records from 97,042 primiparous Holstein cows from 2015 to 2022 in the south of Belgium. The MIR-predicted milk components with the highest deviations from the mean with increasing THI were protein percentage, casein concentration, magnesium concentration, and (to a lesser extent) PUFA concentration. Concerning residual variances, the highest heteroscedasticity with THI was obtained for milk MIR MUFA, C18:1 cis-9, and citrate concentrations. Conversely, a relative homoscedasticity of variance with increasing THI was observed for several milk MIR components including protein percentage and casein concentration. Based on the criteria of the good biomarkers guidelines, milk protein percentage seems to be the most promising trait of this study, followed by Mg concentration. However, in the context of genetic evaluation, which requires variability, milk MIR MUFA, C18:1 cis-9, or citrate concentration variations, if they are heritable, could be of great interest. Finally, an increase in milk MIR citrate concentration variance could be an early warning for the detection of heat stress in the frame of DHI.http://www.sciencedirect.com/science/article/pii/S0022030224012657heat stressbiomarkersresidualsMIR traits
spellingShingle Pauline Lemal
Clément Grelet
Frédéric Dehareng
Hélène Soyeurt
Martine Schroyen
Nicolas Gengler
Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
Journal of Dairy Science
heat stress
biomarkers
residuals
MIR traits
title Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
title_full Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
title_fullStr Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
title_full_unstemmed Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
title_short Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle
title_sort residual analysis for the identification of potential mid infrared derived biomarkers of heat stress in dairy cattle
topic heat stress
biomarkers
residuals
MIR traits
url http://www.sciencedirect.com/science/article/pii/S0022030224012657
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