Modeling feed herbage proportion and modeling of the likelihood of feeding strategies focused on grazing and herbage consumption using milk Fourier-transform mid-infrared spectral analysis.
[en] Effectively evaluating and promoting pro-grazing practices necessitates the implementation of a verification system. To address this imperative, exploration of milk composition analysis as a means to assess grazing practices has garnered substantial attention. In this study, we used component predictions from milk Fourier-transform mid-infrared (FT-MIR) spectra to construct an indicator to estimate the proportion of herbage consumed by dairy cows and another indicator to validate grazing. This approach was developed and validated using 75 estimated bulk milk analyses, each associated with 3 variables related to feeding from the same day ± 3 d, totaling 526 observations. These 3 variables are based on the occupation time, harvested and conserved herbage, and other feeds from 7 farms in Luxembourg. Hierarchical clustering facilitated the effective segregation of observations into distinct groups, with one group predominantly focused on herbage and the other group on other feeds. Leveraging partial least squares discriminant analysis trained on FT-MIR predicted milk characteristics from both groups, we successfully developed an indicator-the probability of belonging to the herbage group-with a maximum accuracy of 0.93, a sensitivity of 0.94, and a specificity of 0.93 on the Luxembourg dataset. In a partial least squares regression, the cross-validation yielded results of predicting the percentage of herbage in the diet with an error of 8.77%. Notably, the indicator relied on FT-MIR predicted components expected to reflect a diet based on herbage, such as the total of C18:1 trans fatty acids and CLA. However, it also incorporated unexpected FT-MIR predicted parameters like milk acidity parameters, citrate content, and specific proteins such as lactoferrin. Finally, the developed indicators were tested on the 5,886,364 Walloon spectra collected between 2009 and 2023, as well as 23,718 Walloon spectra between 2023 and 2025 from 72 farms known to practice grazing. The annual trends were analyzed in the context of Walloon dairy production, helping to refine the selection of better indicators. These results could contribute to practical tools for monitoring and estimating days spent on pasture. Looking ahead, future research should aim to incorporate more comprehensive data, such as precise feed compositions, to further refine our understanding of the influence of specific herbage diets on milk composition and enhance the detection of associated changes.
Disciplines :
Agriculture & agronomy
Author, co-author :
Dichou, Killian ; Université de Liège - ULiège > TERRA Research Centre
Nickmilder, Charles ; Université de Liège - ULiège > Département GxABT > Echanges Eau - Sol - Plantes
Marvuglia, Antonino ; Luxembourg Institute of Science and Technology (LIST), 4362 Esch-sur-Alzette, Luxembourg
Soyeurt, Hélène ; Université de Liège - ULiège > Département GxABT > Modélisation et développement
Language :
English
Title :
Modeling feed herbage proportion and modeling of the likelihood of feeding strategies focused on grazing and herbage consumption using milk Fourier-transform mid-infrared spectral analysis.
FNR - Fonds National de la Recherche Luxembourg F.R.S.-FNRS - Fonds de la Recherche Scientifique SPW - Service Public de Wallonie
Funding number :
D65-1435; INTERFNRS/18/12987586; T.0221.19.
Funding text :
This work was supported by the Service Public de Wallonie (Namur, Belgium) with the project WALLeSmart (grant number D65-1435), as well as the FNR (Esch-sur-Alzette, Luxembourg) with the grant INTERFNRS/18/12987586 and the F.R.S-FNRS (Brussels, Belgium) with the grant T.0221.19. under the bilateral Simulating Economic and Environmental Impacts of Dairy Cattle Management Using Agent-Based Models (SIMBA) project.
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