ArticleFoods (Basel, Switzerland)2021
Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow's Lactation.
Article in Foods (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- - Invited Review - Application of precision livestock farming: challenges and opportunities.Animal bioscience · 2026Article
- Endocrine-metabolic regulation during the transition period in dairy cows: mechanisms, biomarkers, and emerging diagnostics for subclinical ketosis.Frontiers in endocrinology · 2026Review
- Article
- Spectral Profiling (Fourier Transform Infrared Spectroscopy) and Machine Learning for the Recognition of Milk from Different Bovine Breeds.Animals : an open access journal from MDPI · 2024Article
- Two-Channel Detecting Sensor with Signal Cross-Correlation for FTIR Instruments.Sensors (Basel, Switzerland) · 2022Article
- The Use of Multilayer Perceptron Artificial Neural Networks to Detect Dairy Cows at Risk of Ketosis.Animals : an open access journal from MDPI · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The use of technologies for measurements of health parameters of individual cows may ensure early detection of diseases and maximization of individual cow and herd potential. In the present study, dry-film Fourier transform infrared spectroscopy (FTIR) was evaluated for the purpose of detecting and quantifying milk components during cows' lactation. This was done in order to investigate if these systematic changes can be used to identify cows experiencing subclinical ketosis. The data included 2329 milk samples from 61 Norwegian Red dairy cows collected during the first 100 days in milk (DIM). The resulting FTIR spectra were used for explorative analyses of the milk composition. Principal component analysis (PCA) was used to search for systematic changes in the milk during the lactation. Partial least squares regression (PLSR) was used to predict the fatty acid (FA) composition of all milk samples and the models obtained were used to evaluate systematic changes in the predicted FA composition during the lactation. The results reveal that systematic changes related to both gross milk composition and fatty acid features can be seen throughout lactation. Differences in the predicted FA composition between cows with subclinical ketosis and normal cows, in particular C14:0 and C18:1cis9, showed that dietary energy deficits may be detected by deviations in distinct fatty acid features.
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