Leveraging milk mid-infrared spectroscopy to authenticate animal welfare, farming practices, and dairy systems of Parmigiano Reggiano cheese.

Increasing consumer concerns underscore the importance of verifying the practices and origins of food, especially certified premium products. The aim of this study was to evaluate the ability of Fourier-transform mid-infrared (FT-MIR) spectroscopy to authenticate animal welfare parameters, farming practices, and dairy systems. Data on farm characteristics were obtained from the Parmigiano Reggiano Consortium in northern Italy.

Mind the Step: An Artificial Intelligence-Based Monitoring Platform for Animal Welfare.

We present an artificial intelligence (AI)-enhanced monitoring framework designed to assist personnel in evaluating and maintaining animal welfare using a modular architecture. This framework integrates multiple deep learning models to automatically compute metrics relevant to assessing animal well-being. Using deep learning for AI-based vision adapted from industrial applications and human behavioral analysis, the framework includes modules for markerless animal identification and health status assessment (e.

Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: insights for enhancing breeding programs and herd management.

Fertility is a crucial aspect of dairy herd efficiency and sustainability. Among factors influencing fertility in dairy cattle, metabolic stress and systemic inflammation of animals are of main relevance, especially in the postpartum stage when ovarian activity begins and cows are inseminated. Our study aimed to infer the associations between milk infrared-predicted blood biomarkers of stress resilience and fertility traits, namely the interval from calving to first service (iCF), days open (DO), and the pregnancy rate at first service (PRF) in a multi-breed population of 89,097 dairy cows.

Structural equation models to infer relationships between energy-related blood metabolites and milk daily energy output in Holstein cows.

During lactation, high-yielding cows experience metabolic disturbances due to milk production. Metabolic monitoring offers valuable insights into how cows manage these challenges throughout the lactation period, making it a topic of considerable interest to breeders. In this study, we used Bayesian networks to uncover potential dependencies among various energy-related blood metabolites, i.

Infrared spectroscopy coupled with machine learning algorithms for predicting the detailed milk mineral profile in dairy cattle.

Milk minerals are not only essential components for human health, but they can be informative for milk quality and cow's health. Herein, we investigated the feasibility of Fourier Transformed mid Infrared (FTIR) spectroscopy for the prediction of a detailed panel of 17 macro, trace, and environmental elements in bovine milk, using partial least squares regression (PLS) and machine learning approaches. The automatic machine learning significantly outperformed the PLS regression in terms of prediction performances of the mineral elements.

Unraveling metabolic stress response in dairy cows: Genetic control of plasma biomarkers throughout lactation and the transition period.

Breeding animals able to effectively respond to stress could be a long-term, sustainable, and affordable strategy to improve resilience and welfare in livestock systems. In the present study, the concentrations of 29 plasma biomarkers were used as candidate endophenotypes for metabolic stress response in single-SNP, gene- and haplotype-based GWAS using 739 healthy lactating Italian Holstein cows and 88,271 variants. Significant genetic associations were found in all the 3 GWAS approaches for plasma γ-glutamyl transferase concentration on BTA17, for paraoxonase on BTA4, and for alkaline phosphatase and zinc on BTA2.

Combining genetic markers, on-farm information and infrared data for the in-line prediction of blood biomarkers of metabolic disorders in Holstein cattle.

Background: Various blood metabolites are known to be useful indicators of health status in dairy cattle, but their routine assessment is time-consuming, expensive, and stressful for the cows at the herd level. Thus, we evaluated the effectiveness of combining in-line near infrared (NIR) milk spectra with on-farm (days in milk [DIM] and parity) and genetic markers for predicting blood metabolites in Holstein cattle. Data were obtained from 388 Holstein cows from a farm with an AfiLab system.

Review of equations to predict methane emissions in dairy cows from milk fatty acid profiles and their application to commercial dairy farms.

Greenhouse gas emission from the activities of all productive sectors is currently a topic of foremost importance. The major contributors in the livestock sector are ruminants, especially dairy cows. This study aimed to evaluate and compare 21 equations for predicting enteric methane emissions (EME) developed on the basis of milk traits and fatty acid profiles, which were selected from 46 retrieved through a literature review.

Characterization of dry-cured ham microbiota at 12 months of seasoning obtained from different rearing strategies using 16S rRNA profiling.

In this study, we investigated the microbiota of 72 Italian ham samples collected after 12 months of seasoning. The hams were elaborated from pigs fed different rearing methods, including the traditional restricted medium protein diet chosen as control (C group); restrictive low protein diet (LP group); two ad libitum high-protein diet groups (HP9M group: slaughter at 9 months of age; HP170 group: slaughter at 170 kg). A multi-amplicon 16S metabarcoding approach was used, and a total of 2845 Amplicon Sequence Variants were obtained from the 72 ham samples.

Effects of slaughter weight and backfat depth on trimming, curing, and deboning losses and quality traits of Italian dry-cured ham.

This study aimed at assessing the effects of two infra-vitam traits, specifically the slaughter weight (SW) and the ultrasound backfat depth (BCKF) on several post-mortem and quality traits of typical Prosciutto Veneto protected designation of origin (PDO) dry-cured ham. The trial was conducted on a population of 423 pigs fed using different strategies to generate a high variation in SW (175 ± 15.5 kg) and BCKF (23.

Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models.

Background: Metabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation.

Complementing Braden scale for pressure ulcer risk with clinical and demographic-related factors in a large cohort of hospitalized Italian patients.

Aims: To determine the prevalence, risk, and determinants of pressure ulcer risk in a large cohort of hospitalized patients.

Design: A prospective cross-sectional study with data collection in January 2023.

Methods: Registered nurses collected data from 798 patients admitted to 27 health care units of an Italian hospital.

Methylome-wide analysis of milk somatic cells upon subclinical mastitis in dairy cattle.

Better understanding of the molecular mechanisms behind bovine mastitis is fundamental for improving the management of this disease, which continues to be of major concern for the dairy industry, especially in its subclinical form. Disease severity and progression depend on numerous aspects, such as livestock genetics, and the interaction between the causative agent, the host, and the environment. In this context, epigenetic mechanisms have proven to have a role in controlling the response of the animal to inflammation.

Subclinical Mastitis from and spp. Induces Changes in Milk Peptidome in Holstein Cattle.

Early detection of bovine subclinical mastitis may improve treatment strategies and reduce the use of antibiotics. Herein, individual milk samples from Holstein cows affected by subclinical mastitis induced by and spp. were analyzed by untargeted and targeted mass spectrometry approaches to assess changes in their peptidome profiles and identify new potential biomarkers of the pathological condition.

Effect of intramammary infection and inflammation on milk protein profile assessed at the quarter level in Holstein cows.

In this study we wanted to investigate the associations between naturally occurring subclinical intramammary infection (IMI) caused by different etiological agents (i.e., Staphylococcus aureus, Streptococcus agalactiae, Streptococcus uberis, and Prototheca spp.

Serum metabolome differences associated with subclinical intramammary infection caused by Streptococcus agalactiae and Prototheca spp. in multiparous dairy cows.

Mastitis is one of the most significant diseases in dairy cows and causes several economic losses. Somatic cell count (SCC) is often used as an indirect diagnostic tool for mastitis, especially for subclinical mastitis (SCM) where no symptoms or signs can be detected. Streptococcus agalactiae is one of the main causes of contagious mastitis, and Prototheca spp.

Associations between subclinical intramammary infection and milk fatty acid profile at the quarter level in Holstein cattle.

Mastitis, especially the subclinical form, is the most common economic and health problem in dairy cows. Little is known about changes in milk fatty acid (FA) composition according to infection/inflammation status of the mammary gland. The aim of this study was to investigate the associations between naturally occurring subclinical intramammary infection (IMI) from different pathogens, i.

Observational study on the associations between milk yield, composition, and coagulation properties with blood biomarkers of health in Holstein cows.

The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits).

Novel insights into the associations between immune cell population distribution in mammary glands and milk minerals in Holstein cows.

Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns.

Associations between the detailed milk mineral profile, milk composition, and metabolic status in Holstein cows.

The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e.

Blood biochemical changes upon subclinical intramammary infection and inflammation in Holstein cattle.

The aim of this study was to investigate the associations between subclinical intramammary infection (IMI) from different pathogens combined with inflammation status and a set of blood biochemical traits including energy-related metabolites, indicators of liver function or hepatic damage, oxidative stress, inflammation, innate immunity, and mineral status in 349 lactating Holstein cows. Data were analyzed with a linear model including the following fixed class effects: days in milk, parity, herd, somatic cell count (SCC), bacteriological status (positive and negative), and the SCC × bacteriological status interaction. Several metabolites had significant associations with subclinical IMI or SCC.

Transcriptome-wide mapping of milk somatic cells upon subclinical mastitis infection in dairy cattle.

Background: Subclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows' health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp.

Impact of innovative rearing strategies for the Italian heavy pigs: Technological traits and chemical composition of dry-cured hams.

To explore the influence of 4 feeding strategies on dry-cured ham quality, 336 barrows and gilts (3 batches, 112 pigs/batch) of 90 kg body weight (BW), were divided into 4 groups and housed in 8 pens with automated feeders. In the control group (C), the pigs were fed restrictively medium-protein feeds and slaughtered at 170 kg BW (SW) and 265 d of slaughter age (SA). With the older age (OA) treatment, the pigs were restrictively fed low protein feeds and slaughtered at 170 kg SW and 278 d SA.