Dry matter intake (DMI) is a key component of feed efficiency in dairy cattle. In this study, we estimated genetic parameters of DMI over the first 24 lactation weeks in 3 dairy cattle breeds: Holstein, Nordic Red, and Jersey. In total, 1,656 primiparous cows (717 Holstein, 663 Nordic Red, and 276 Jersey) from Denmark, Finland, and Sweden were studied. For each breed, variance components, heritability, and repeatability for weekly DMI were estimated in 6 consecutive periods of the first 24 lactation weeks based on a repeatability animal model. Genetic correlations for DMI between different lactation periods were estimated using bivariate models. Based on our results, Holstein and Nordic Red cows had similar DMI at the beginning of lactation, but later in lactation Holstein cows had a slightly higher DMI than Nordic Red cows. In comparison, Jersey cows had a significantly lower DMI than the other 2 breeds within the first 24 lactation weeks. Heritability estimates for DMI ranged from 0.20 to 0.40 in Holsteins, 0.25 to 0.41 in Nordic Red, and 0.17 to 0.42 in Jerseys within the first 24 lactation weeks. Genetic and phenotypic variances for DMI varied along lactation within each breed and tended to be higher in the middle of lactation than at the beginning of the lactation. High genetic correlations were noted for DMI in lactation wk 5 to 24 in all 3 breeds, whereas DMI at early lactation (lactation wk 1 to 4) tended to be genetically different from DMI in the middle of lactation. The 3 breeds in this study might differ in their genetic variances for DMI, but the differences were not statistically significant in most of the studied periods. Breed differences for the genetic variance tended to be more obvious than for heritability. The potential breed differences in genetic variation for DMI should be considered in a future study using feed intake information from multiple breeds.
Attempts to lower the environmental footprint of milk production needs a sound understanding of the genetic and nutritional basis of methane (CH4) emissions from the dairy production systems. This in turn requires accurate and reliable techniques for the measurement of CH4 output from individual cows. Many of the available measurement techniques so far are either slow, expensive, labor intensive and are unsuitable for large-scale individual animal measurements. The main objectives of this study were to examine and validate a non-invasive individual cow CH4 measurement system that is based on photoacoustic IR spectroscopy (PAS) technique implemented in a portable gas analysis equipment (F10), referred to as PAS-F10 method and to estimate the magnitude of between-animal variations in CH4 output traits. Data were collected from 115 Nordic Red cows of the Minkiö experimental dairy farm, at the Natural Resources Institute Finland (Luke). Records on continuous daily measurements of CH4, milk yield, feed intake and BW measurements over 2 years period were compiled for data analysis. The daily CH4 output was calculated using carbon dioxide as a tracer method. Estimates from the non-invasive PAS-F10 technique were then tested against open-circuit indirect respiration calorimetric chamber measurements and against estimates from other widely used prediction models. Concordance analysis was used to establish agreement between the chamber and PAS-F10 methods. A linear mixed model was used for the analysis of the large continuous data. The daily CH4 output of cows was 555 l/day and ranged from 330 to 800 l/day. Dry matter intake, level of milk production, lactation stage and diurnal variation had significant effects on daily CH4 output. Estimates of the daily CH4 output from PAS-F10 technique compared relatively well with the other techniques. The concordance correlation coefficient between combined weekly CH4 output estimates of PAS-F10 and chamber was 0.84 with lower and upper confidence limits of 0.65 and 0.93, respectively. Similarly, when chamber CH4 measurements were predicted from PAS-F10 measurements, the mean of two separate weekly PAS-F10 measurements gave the lowest prediction error variance than either of the separate weekly PAS-F10 measurements alone. This suggests that every other week PAS-F10 measurements when combined would improve the estimation of CH4 output with PAS-F10 technique. The repeatability of daily CH4 output from PAS-F10 technique ranged from 0.40 to 0.46 indicating that some between-animal variation exist in CH4 output traits.