Abstract
Infrared spectral analysis of milk is a cheap, fast, and accurate method for analysing chemical composition of milk. Infrared light consists of many wavelengths, each carrying energy in a different wave-like motion. When a beam of infrared light passes through milk the energy of wavelengths interacts with chemical bonds of molecules present inside the milk. Energy of wavelengths can be absorbed or transmitted. Absorbance or transmittance values are transformed with a Fourier transformation, resulting in Fourier transform infrared (FT-IR) milk spectra.
FT-IR milk spectra tell us something about the molecules inside the milk, and can be used to predict milk composition. Metabolic diseases, such as ketosis, have also been predicted from milk spectra. The advantages of FT-IR milk spectral analysis make infrared milk spectra a good candidate for defining new phenotypes. These predicted phenotypes could be used for farm management or in breeding programs. Genetic studies have revealed that both a number of infrared predicted phenotypes, and FT-IR milk spectra are heritable. Heritability estimates for infrared milk spectra, however, vary across studies. Acquiring more knowledge on genetics of infrared milk spectra could help to develop more efficient methods for application of infrared milk spectra in breeding programs.
The aims of this PhD-project were, to perform a thorough genetic analysis on Fourier transform infrared milk spectra for two Danish dairy cattle populations: Danish Holstein and Danish Jersey. Secondly, infrared-prediction ability was analysed for orotic acid, followed by a genetic analysis on the infrared-predicted phenotype.
This PhD thesis includes one published paper, and two submitted manuscripts, which all make a link between FT-IR milk spectra and genetics. The first paper discusses heritability of individual wavenumbers, and genomic correlations between wavenumbers for two Danish dairy cattle breeds. Heritability varied between 0.00-0.31 for Danish Holstein, and 0.00-0.30 for Danish Jersey. Genomic correlations were moderate to strong, and a division into two groups of wavenumbers was observed. Paper II tested infrared prediction ability of orotic acid, and revealed good prediction accuracy, both within breed (0.79), and across breeds (0.65). Genetic analysis showed a link between infrared predicted orotic acid and calf health. The final paper gives insight in genes underlying infrared milk spectra, but also highlights breed differences in genetic architecture of FT-IR milk spectra.
This PhD-study has provided us with deeper knowledge of the genetic background of FT-IR milk spectra in the Danish Holstein population, and Danish Jersey population.
FT-IR milk spectra tell us something about the molecules inside the milk, and can be used to predict milk composition. Metabolic diseases, such as ketosis, have also been predicted from milk spectra. The advantages of FT-IR milk spectral analysis make infrared milk spectra a good candidate for defining new phenotypes. These predicted phenotypes could be used for farm management or in breeding programs. Genetic studies have revealed that both a number of infrared predicted phenotypes, and FT-IR milk spectra are heritable. Heritability estimates for infrared milk spectra, however, vary across studies. Acquiring more knowledge on genetics of infrared milk spectra could help to develop more efficient methods for application of infrared milk spectra in breeding programs.
The aims of this PhD-project were, to perform a thorough genetic analysis on Fourier transform infrared milk spectra for two Danish dairy cattle populations: Danish Holstein and Danish Jersey. Secondly, infrared-prediction ability was analysed for orotic acid, followed by a genetic analysis on the infrared-predicted phenotype.
This PhD thesis includes one published paper, and two submitted manuscripts, which all make a link between FT-IR milk spectra and genetics. The first paper discusses heritability of individual wavenumbers, and genomic correlations between wavenumbers for two Danish dairy cattle breeds. Heritability varied between 0.00-0.31 for Danish Holstein, and 0.00-0.30 for Danish Jersey. Genomic correlations were moderate to strong, and a division into two groups of wavenumbers was observed. Paper II tested infrared prediction ability of orotic acid, and revealed good prediction accuracy, both within breed (0.79), and across breeds (0.65). Genetic analysis showed a link between infrared predicted orotic acid and calf health. The final paper gives insight in genes underlying infrared milk spectra, but also highlights breed differences in genetic architecture of FT-IR milk spectra.
This PhD-study has provided us with deeper knowledge of the genetic background of FT-IR milk spectra in the Danish Holstein population, and Danish Jersey population.
| Originalsprog | Engelsk |
|---|
| Forlag | Århus Universitet |
|---|---|
| Antal sider | 144 |
| Status | Udgivet - apr. 2019 |