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.

Predicting methane emissions of individual grazing dairy cows from spectral analyses of their milk samples.

Data on the enteric methane emissions of individual cows are useful not just in assisting management decisions and calculating herd inventories but also as inputs for animal genetic evaluations. Data generation for many animal characteristics, including enteric methane emissions, can be expensive and time consuming, so being able to extract as much information as possible from available samples or data sources is worthy of investigation. The objective of the present study was to attempt to predict individual cow methane emissions from the information contained within milk samples, specifically the spectrum of light transmittance across different wavelengths of the mid-infrared (MIR) region of the electromagnetic spectrum.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows.

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation.

Estimation of body condition score change in dairy cows in a seasonal calving pasture-based system using routinely available milk mid-infrared spectra and machine learning techniques.

Body condition score (BCS) is a subjective estimate of body reserves in cows. Body condition score and its change in early lactation have been associated with cow fertility and health. The aim of the present study was to estimate change in BCS (ΔBCS) using mid-infrared spectra of the milk, with a particular focus on estimating ΔBCS in cows losing BCS at the fastest rate (i.

The globalizability of temporal discounting.

Economic inequality is associated with preferences for smaller, immediate gains over larger, delayed ones. Such temporal discounting may feed into rising global inequality, yet it is unclear whether it is a function of choice preferences or norms, or rather the absence of sufficient resources for immediate needs. It is also not clear whether these reflect true differences in choice patterns between income groups.

Breeding for improved protein fractions and free amino acids concentration in bovine milk.

Considerable resources are required to routinely measure detailed milk compositional traits. Hence, an insufficient volume of phenotypic data can hinder genetic progress in these traits within dairy cow breeding programmes. The objective of the present study was to quantify the opportunities for breeding for improved milk protein and free amino acid (FAA) composition by exploiting mid-infrared spectroscopy (MIRS) predictions routinely recorded from milk samples.

Internal teat sealants alone or in combination with antibiotics at dry-off - the effect on udder health in dairy cows in five commercial herds.

In the dairy industry, the dry period has been identified as an area for potential reduction in antibiotic use, as part of a one health approach to preserve antibiotic medicines for human health. The objective of this study was to assess the impact of dry cow treatment on somatic cell count (SCC), intramammary infection (IMI) and milk yield on five commercial Irish dairy herds. A total of 842 cows across five spring calving dairy herds with a monthly bulk tank SCC of < 200 000 cells/mL were recruited for this study.

Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits.

Including all available data when developing equations to relate midinfrared spectra to a phenotype may be suboptimal for poorly represented spectra. Here, an alternative local changepoint approach was developed to predict six milk technological traits from midinfrared spectra. Neighbours were objectively identified for each predictand as those most similar to the predictand using the Mahalanobis distances between the spectral principal components, and subsequently used in partial least square regression (PLSR) analyses.

Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods.

Numerous statistical machine learning methods suitable for application to highly correlated features, as those that exist for spectral data, could potentially improve prediction performance over the commonly used partial least squares approach. Milk samples from 622 individual cows with known detailed protein composition and technological trait data accompanied by mid-infrared spectra were available to assess the predictive ability of different regression and classification algorithms. The regression-based approaches were partial least squares regression (PLSR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO), elastic net, principal component regression, projection pursuit regression, spike and slab regression, random forests, boosting decision trees, neural networks (NN), and a post-hoc approach of model averaging (MA).

A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra.

Lactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an interest in quantifying this biomolecule routinely.

Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid-infrared spectra.

Background: A robust proxy for estimating methane (CH ) emissions of individual dairy cows would be valuable especially for selective breeding. This study aimed to improve the robustness and accuracy of prediction models that estimate daily CH emissions from milk Fourier transform mid-infrared (FT-MIR) spectra by (i) increasing the reference dataset and (ii) adjusting for routinely recorded phenotypic information. Prediction equations for CH were developed using a combined dataset including daily CH measurements (n = 1089; g d ) collected using the SF tracer technique (n = 513) and measurements using respiration chambers (RC, n = 576).

Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis.

The objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactating grazing dairy cows. A data set comprising 1,074 records of DMI from 457 cows was available for analysis. Linear regression and partial least squares regression were used to develop the equations using the following variables: (1) milk yield (MY), fat percentage, protein percentage, body weight (BW), stage of lactation (SOL), and parity (benchmark equation); (2) MIRS wavelengths; (3) MIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (4) NIRS wavelengths; (5) NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (6) MIRS and NIRS wavelengths; and (7) MIRS wavelengths, NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity.

How herd best linear unbiased estimates affect the progress achievable from gains in additive and nonadditive genetic merit.

Sustainable dairy cow performance relies on coevolution in the development of breeding and management strategies. Tailoring breeding programs to herd performance metrics facilitates improved responses to breeding decisions. Although herd-level raw metrics on performance are useful, implicitly included within such statistics is the mean herd genetic merit.

Effect of using internal teat sealant with or without antibiotic therapy at dry-off on subsequent somatic cell count and milk production.

The objective of this study was to assess the effect of treating cows with teat sealant only compared with antibiotic plus teat sealant at drying off on weekly somatic cell count, potential intramammary infection, and milk production across the entire subsequent lactation. In 3 research herds in the south of Ireland, cows with SCC that did not exceed 200,000 cells/mL in the previous lactation (LowSCC) were randomly assigned to 1 of 2 treatments at drying off: internal teat sealant alone (ITS) or antibiotic plus teat sealant (AB+ITS). Cows with SCC that exceeded 200,000 cells/mL in the previous lactation were treated with AB+ITS and included in the analyses as a separate group (HighSCC).

Milk production of Holstein-Friesian cows of divergent Economic Breeding Index evaluated under seasonal pasture-based management.

The objective of this study was to validate the effect of genetic improvement using the Irish genetic merit index, the Economic Breeding Index (EBI), on total lactation performance and lactation profiles for milk yield, milk solids yield (fat plus protein; kg), and milk fat, protein, and lactose content within 3 pasture-based feeding treatments (FT) and to investigate whether an interaction exists between genetic group (GG) of Holstein-Friesian and pasture-based FT. The 2 GG were (1) extremely high EBI representative of the top 5% nationally (referred to as the elite group) and (2) representative of the national average EBI (referred to as the NA group). Cows from each GG were randomly allocated each year to 1 of 3 pasture-based FT: control, lower grass allowance, and high concentrate.

Genetics of bull semen characteristics in a multi-breed cattle population.

Little is known of the genetic variability in semen quality traits in cattle and their inter-relationships. The objective of the present study was to estimate genetic parameters for a range of semen quality measures. The data consisted of 35,573 ejaculates from 787 artificial insemination bulls of 16 breeds.

Milk mid-infrared spectral data as a tool to predict feed intake in lactating Norwegian Red dairy cows.

Mid-infrared (MIR) spectroscopy of milk was used to predict dry matter intake (DMI) and net energy intake (NEI) in 160 lactating Norwegian Red dairy cows. A total of 857 observations were used in leave-one-out cross-validation and external validation to develop and validate prediction equations using 5 different models. Predictions were performed using (multiple) linear regression, partial least squares (PLS) regression, or best linear unbiased prediction (BLUP) methods.

Characteristics of feed efficiency within and across lactation in dairy cows and the effect of genetic selection.

The objective of the present study was to investigate the phenotypic inter- and intra-relationships within and among alternative feed efficiency metrics across different stages of lactation and parities; the expected effect of genetic selection for feed efficiency on the resulting phenotypic lactation profiles was also quantified. A total of 8,199 net energy intake (NE) test-day records from 2,505 lactations on 1,290 cows were used. Derived efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models.

Genetic and nongenetic factors associated with milk color in dairy cows.

Milk color is one of the sensory properties that can influence consumer choice of one product over another and it influences the quality of processed dairy products. This study aims to quantify the cow-level genetic and nongenetic factors associated with bovine milk color traits. A total of 136,807 spectra from Irish commercial and research herds (with multiple breeds and crosses) were used.

Cow and environmental factors associated with protein fractions and free amino acids predicted using mid-infrared spectroscopy in bovine milk.

The objective of the present study was to identify the factors associated with both the protein composition and free amino acid (FAA) composition of bovine milk predicted using mid-infrared spectroscopy. Milk samples were available from 7 research herds and 69 commercial herds. The spectral data from the research herds comprised 94,286 separate morning and evening milk samples; the spectral data from the commercial herds comprised 40,260 milk samples representing a composite sample of both the morning and evening milkings.

Processing characteristics of dairy cow milk are moderately heritable.

Milk processing attributes represent a group of milk quality traits that are important to the dairy industry to inform product portfolio. However, because of the resources required to routinely measure such quality traits, precise genetic parameter estimates from a large population of animals are lacking for these traits. Milk processing characteristics considered in the present study-rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and milk pH-were all estimated using mid-infrared spectroscopy prediction equations.

Genetics of alternative definitions of feed efficiency in grazing lactating dairy cows.

The objective of the present study was to estimate genetic parameters across lactation for measures of energy balance (EB) and a range of feed efficiency variables as well as to quantify the genetic inter-relationships between them. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,481 lactations from 1,274 Holstein-Friesian cows. A total of 8,134 individual feed intake measurements were used.

The distribution of runs of homozygosity and selection signatures in six commercial meat sheep breeds.

Domestication and the subsequent selection of animals for either economic or morphological features can leave a variety of imprints on the genome of a population. Genomic regions subjected to high selective pressures often show reduced genetic diversity and frequent runs of homozygosity (ROH). Therefore, the objective of the present study was to use 42,182 autosomal SNPs to identify genomic regions in 3,191 sheep from six commercial breeds subjected to selection pressure and to quantify the genetic diversity within each breed using ROH.