Comparison of the mid-infrared spectra and prediction equations developed from morning and evening milk samples from twice-a-day milked dairy cows.

Mid-infrared spectroscopy is a technology used globally for quantifying the concentration of fat, protein, lactose and other constituents in the milk samples of both individual animals and bulk tank milk. Differences in the milk components and yield of cows are known to exist between morning and evening milk; nonetheless, differences in the spectra originating from the same cow from morning and evening milkings have never been investigated. Data was obtained from 2,602 dairy cows from 7 research farms in Ireland.

Unveiling the fitness of Saccharomyces cerevisiae strains for lignocellulosic bioethanol: a genomic exploration through fermentation stress tests.

Lignocellulosic biomass holds significant promise as a substrate for bioethanol production, yet the financial viability of lignocellulosic fermentation poses challenges. The pre-treatment step needed for lignocellulosic substrates generates inhibitors that impede Saccharomyces cerevisiae growth, affecting the fermentation process and overall yield. In modern sugarcane-to-ethanol plants, a rapid succession of yeast strains occurs, with dominant strains prevailing.

Transferability across countries of equations developed using milk mid-infrared spectroscopy to estimate daily body condition score change in dairy cows.

Routine milk samples are commonly subjected to spectroscopic analysis within the mid-infrared (MIR) region of the electromagnetic spectrum to estimate macro-constituents of milk such as fat, protein, lactose, and urea content. These spectra, however, can also be used to predict other traits, such as daily BCS change (ΔBCS). The objective of the present study was to assess the transferability across countries of equations for predicting daily ΔBCS that were developed using milk MIR data collected in Ireland and in Canada.

Rapid selection of milk mid-infrared spectra for creating a dairy cow population world representative spectral database.

The advantage of employing mid-infrared spectrometry for milk analysis in breeding lies in its ability to quickly generate millions of records. However, these records may be biased if the calibration process does not account for their spectral variability when constructing the predictive model. Therefore, this study introduces a novel method for developing a world representative spectral database (WRSD) to reduce the risks of spectral extrapolation when predicting dairy traits in new samples.

Using milk mid-infrared spectroscopy to estimate cow-level nitrogen efficiency metrics.

Minimizing pollution from the dairy sector is paramount; one potential cause of such pollution is excess nitrogen. Nitrogen pollution contributes to a deterioration in water quality as well as an increase in both eutrophication and greenhouse gases. It is therefore essential to minimize the loss of nitrogen from the sector, including excretion from the cow.