Does the age of milk affect its mid-infrared spectrum and predictions?

Milk of dairy species commonly undergo standardized official analyses, these that may require chemical preservation and transportation to a certified laboratory. In this context, storage duration is an important factor that can potential affect both milk chemical analyses and its mid-infrared spectrum. We analysed milk samples at different time points/ages to assess repeatability and reproducibility of mid-infrared predicted traits (e.g., fat and protein). Using spectral data, we also evaluated the ability of spectroscopy coupled with chemometrics to discriminate samples according to their age. Although the main components of milk remained consistently reproducible across age (days), changes in the spectrum due to sample aging and deterioration of the matrix were detectable. Using a discriminant analysis, we achieved a classification accuracy of 77% in validation. Predicting milk age using mid-infrared spectra is feasible, allowing for sample monitoring within circuits where maximum reliability is needed, e.g., bulk or individual milk samples for legal/official use or payment systems.

Effects of different temperature-humidity indexes on milk traits of Holstein cows: A 10-year retrospective study.

Test-day records (n = 723,091) collected between 2012 and 2021 from 43,015 Holstein cows at 157 farms located in northern Italy were used to study the effects of heat load on milk production and composition a posteriori. The data consisted of milk yield (kg/d), traditional gross composition traits, somatic cell score (SCS), differential somatic cell count (%), milk ß-hydroxybutyrate (BHB, mmol/L), milk urea (mg/dL), and milk fatty acid composition (g/100 g of milk). Test-day records were then associated with their relative temperature-humidity indexes (THI) calculated using historical environmental data registered by weather stations. Indexes were created using either yearly or summer THI data. The yearly indexes included the average daily THI (adTHI) and the maximum daily THI (mdTHI) measured throughout the whole year, and the summer indexes focused on 3 mo only (June-August) and included the average daily summer THI (adTHIs), the maximum daily summer THI (mdTHIs), and the average daily THI of the hottest 4 h of the day (adTHI4h; 1200-1600 h). All indexes had significant effects on the majority of milk traits analyzed, with, in particular, adTHI and mdTHI being highly significant in explaining the variation of all traits. Milk yield started to decline at a higher THI compared with protein and fat content. The reduction in fat ceased in the elevated THI experienced during the summer months, as demonstrated by adTHIs, mdTHIs, and adTHI4h. The cows had a tendency for increased BHB concentration with elevated THI, suggesting a greater risk of negative energy balance in presence of heat stress. Furthermore, the concentration of the de novo fatty acids C14:0 and C16:0 was reduced in higher THI, reflecting altered mammary gland activity upon elevated heat load and stress. Milk SCS tended to increase with higher adTHIs, mdTHIs, and adTHI4h. The use of yearly indexes is recommended when investigating the effects of heat load on milk composition, whereas summer indexes are suggested when investigating traits influenced by extreme conditions, such as SCS and milk yield. With global temperatures expected to further rise in the upcoming decades, early and easy identification of cows or herds suffering from heat stress, such as through changes in milk composition, is crucial for timely intervention. Adapting measures to mitigate such effects of elevated THI on milk yield and composition is a necessity for the dairy industry to prevent detrimental impacts on dairy production.

Genetic and genomic evaluation of age at first calving in Italian Holsteins.

Age at first calving (AFC) represents the nonproductive period of ∼2 yr in Holstein cows, and thus, it has a relevant effect on the cost of rearing replacements in the dairy herd. In the present study, we aimed to evaluate genetic and genomic aspects of AFC in the Italian Holstein population. Data of 4,206,218 heifers with first calving between 1996 and 2020 were used. Age at first calving averaged 26.09 ± 3.07 mo and decreased across years. Heritability was estimated using a linear animal model which included the fixed effects of herd-year-season of birth and classes of gestation length, and the random animal additive genetic effect fitted to a pedigree-based relationship matrix. The EBV and genomically EBV (GEBV) were obtained, and they were standardized to mean 100 and standard deviation 5, where animals above the mean are those contributing to reduce AFC. Heritability estimates of AFC ranged from 0.031 to 0.045. The trend of sires' GEBV was favorable and indicated a reduced AFC across years. Approximate genetic correlations between GEBV of AFC and GEBV of other economically important traits were calculated on a subset of genotyped females born after 2015. Moderate favorable associations of AFC with production traits (0.39-0.51), udder depth (0.40), interval from first to last insemination in heifer (-0.43), and longevity (0.34) were assessed. Overall, the greatest lifetime productive performances and most favorable days open in first lactation were observed when heifers calved at 22 to 23 mo. In contrast, progeny of sires with GEBV of AFC above the mean yielded more milk, fat, and protein in first lactation, and had shorter days open than progeny of sires with GEBV of AFC below the mean. Results suggested that breeding strategies to improve AFC should be pursued, also considering genetic correlations between AFC and traits which are already part of the Italian Holstein breeding objective. The inclusion of AFC in an aggregate index is expected to contribute to enhance farm income.

Effectiveness of mid-infrared spectroscopy for the prediction of cow milk metabolites.

Proton nuclear magnetic resonance (1H NMR) spectroscopy is acknowledged as one of the most powerful analytical methods with cross-cutting applications in dairy foods. To date, the use of 1H NMR spectroscopy for the collection of milk metabolic profile is hindered by costly and time-consuming sample preparation and analysis. The present study aimed at evaluating the accuracy of mid-infrared spectroscopy (MIRS) as a rapid method for the prediction of cow milk metabolites determined through 1H NMR spectroscopy. Bulk milk (n = 72) and individual milk samples (n = 482) were analyzed through one-dimensional 1H NMR spectroscopy and MIRS. Nuclear magnetic resonance spectroscopy identified 35 milk metabolites, which were quantified in terms of relative abundance, and MIRS prediction models were developed on the same 35 milk metabolites, using partial least squares regression analysis. The best MIRS prediction models were developed for galactose-1-phosphate, glycerophosphocholine, orotate, choline, galactose, lecithin, glutamate, and lactose, with coefficient of determination in external validation from 0.58 to 0.85, and ratio of performance to deviation in external validation from 1.50 to 2.64. The remaining 27 metabolites were poorly predicted. This study represents a first attempt to predict milk metabolome. Further research is needed to specifically address whether developed prediction models may find practical application in the dairy sector, with particular regard to the screening of dairy cows' metabolic status, the quality control of dairy foods, and the identification of processed milk or incorrectly stored milk.

Invited review: Bovine colostrum, a promising ingredient for humans and animals-Properties, processing technologies, and uses.

Mammalian colostrum, known as "liquid gold," is considered a valuable source of essential nutrients, growth factors, probiotics, prebiotics, antibodies, and other bioactive compounds. Precisely for this reason, bovine colostrum (BC) is an emerging ingredient for the feed, food, and pharmaceutical industries, being nowadays commercially available in a variety of forms in several countries. Moreover, quite a large number of functional foods and supplements for athletes, human medicines, pet nutrition plans, and complementary feed for some livestock categories, such as piglets and calves, contain BC. The amount of BC yielded by a cow after calving represents approximately 0.5% of the yearly output in dairy breeds. For its nutritional properties and low availability, BC is characterized by a greater market value and an increasing demand compared with other by-products of the dairy sector. However, information regarding the market size of BC for the food and pharmaceutical industries, as well as future developments and perspectives, is scarcely available in the scientific literature. This lack can be attributed to industrial secrecy as well as to the relatively small scale of the BC business when compared with other dairy products, which makes the BC market limited, specific, and intended for a restricted audience. From a legal perspective, regulations assign BC to the large family of milk-derived powders; thus, collecting specific production data, as well as import-export trend information, is not straightforward and can result in unprecise estimates. Given that the interest in BC is increasing in different fields, it is important to have an overview of the production steps and of pros and cons of this emerging ingredient. The present narrative review discloses why BC has started to be considered a product rather than a by-product of the dairy industry. Moreover, the present document aims to summarize the existing methodologies used to assess BC quality in terms of immunoglobulin concentration, the different applications of BC in the industry, and the BC processing technologies. Finally, a panoramic view of the current international market is provided for the first time for this dairy product.

Udder health-related traits in cow milk: phenotypic variability and effect on milk yield and composition.

The milk differential somatic cell count (DSCC) has been proposed in recent years as a mean by which to better monitor the udder health status (UHS) in dairy cows. Milk DSCC is the amount of polymorphonuclear neutrophils and lymphocytes contributing to the total somatic cell count (SCC) and can be determined on a routine basis in individual milk samples subjected to official analysis. In the present study, 522 865 milk test-day records of 77 143 cows were scrutinised to identify factors affecting the variability of both DSCC and SCC in Holstein Friesian, Jersey, Simmental and Rendena cows through linear mixed models. The fixed effects were breed, parity, lactation stage, sampling season, and all the first-order interactions of breed. Cow and herd-test-date were considered as random. Subsequently, four UHS groups were created (1: SCC ≤ 200 000 cells/mL and DSCC ≤ 65%; 2: SCC ≤ 200 000 cells/mL and DSCC > 65%; 3: SCC > 200 000 cells/mL and DSCC > 65%; 4: SCC > 200 000 cells/mL and DSCC ≤ 65%) to compare milk yield and quality. Milk SCS and DSCC differed across lactation, parity, sampling season and breed. In particular, Simmental cows had the lowest SCC and Jersey the lowest DSCC. Depending on the breed, UHS affected daily milk yield and composition to a different extent. The UHS group 4, i.e. the one grouping test-day records with high SCC and low DSCC, presented the lowest estimate of milk yield and lactose content no matter the breeds. Our findings support that udder health-related traits (SCS and DSCC) are useful information to improve udder health at individual cow and herd levels. Moreover, the combination of SCS and DSCC is useful to monitor milk yield and composition.

How heat stress conditions affect milk yield, composition, and price in Italian Holstein herds.

An edited data set of 700 bulk and 46,338 test-day records collected between 2019 and 2021 in 42 Holstein-dominated farms in the Veneto Region (North of Italy) was available for the present study. Information on protein, fat and lactose content, somatic cell count, and somatic cell score was available in bulk milk as well as individual test-day records, whereas urea concentration (mg/dL), differential somatic cell count (%), and milk yield (kg/d) were available for test-day records only. Milk features were merged with meteorological data retrieved from 8 weather stations located maximum 10 km from the farms. The daily and weekly temperature-humidity index (THI; wTHI) and maximum daily (MTHI) and weekly temperature-humidity index were associated with each record to evaluate the effect of heat stress conditions on milk-related traits through linear mixed models. Least squares means were estimated to evaluate the effect of THI and, separately, of MTHI on milk characteristics correcting for conventional systematic factors. Overall, heat stress conditions lowered the quality of both bulk milk and test-day records, with fat and protein content being greatly reduced, and somatic cell score and differential somatic cell count augmented. Milk yield was not affected by either THI or MTHI in this data set, but the effect of elevated THI and MTHI was in general stronger on test-day records than on bulk milk. Farm-level economic losses of reduced milk quality rather than reduced yield as consequence of elevated THI or MTHI was estimated to be between $23.57 and $43.98 per farmer per day, which is of comparable magnitude to losses resulting from reduced production. Furthermore, MTHI was found to be a more accurate indicator of heat stress experienced by a cow, explaining more variability of traits compared with THI. The negative effect of heat stress conditions on quality traits commences at lower THI/MTHI values compared with milk yield. Thus, a progressive farmers' income loss due to climatic changes is already a reality and it is mainly due to deterioration of milk quality rather than quantity in the studied area.

Invited review: Iodine level in dairy products-A feed-to-fork overview.

The theme of iodine in the dairy sector is of particular interest due to the involvement and the interconnection of several stakeholders along the dairy food chain. Iodine plays a fundamental role in animal nutrition and physiology, and in cattle it is an essential micronutrient during lactation and for fetal development and the calf's growth. Its correct use in food supplementation is crucial to guarantee the animal's recommended daily requirement to avoid excess intake and long-term toxicity. Milk iodine is fundamental for public health, being one of the major sources of iodine in Mediterranean and Western diets. Public authorities and the scientific community have made great efforts to address how and to what extent different drivers may affect milk iodine concentration. The scientific literature concurs that the amount of iodine administered through animal feed and mineral supplements is the most important factor affecting its concentration in milk of most common dairy species. Additionally, farming practices related to milking (e.g., use of iodized teat sanitizers), herd management (e.g., pasture vs. confinement), and other environmental factors (e.g., seasonality) have been identified as sources of variation of milk iodine concentration. Overall, the aim of this review is to provide a multilevel overview on the mechanisms that contribute to the iodine concentration of milk and dairy products.

Genetic and nongenetic variation of heifer fertility in Italian Holstein cattle.

Excellent fertility performance is important to maximize farmers' profit and to reduce the number of culled animals. Although female fertility of adult cows has been included in Italian Holstein breeding objectives since 2009, little has been done to quantify genetic variation of heifer fertility characteristics so far. The aim of the present study was to estimate genetic parameters of 4 fertility traits in nulliparous Italian Holstein heifers and to develop an aggregate selection index to improve heifer fertility. Data were retrieved from the national fertility database and included information on insemination, calving, and pregnancy diagnosis dates. The investigated phenotypes (mean ± standard deviation) were age at first insemination (AFI, mo; 17.25 ± 2.89), nonreturn rate at 56 d from the first insemination (NRR56, binary; 0.78 ± 0.41), conception rate at first insemination (CR, binary; 0.61 ± 0.49), and interval from first to last insemination (IFL, d; 26.09 ± 51.85). Genetic parameters were estimated using a 4-trait animal model that included the following fixed effects: herd-year of birth and month of birth for AFI, and herd-year-season of birth and month-year of insemination for IFL, NRR56, and CR; the animal additive genetic effect (fitted to the pedigree-based relationship matrix) was considered as a random term. An aggregate index was developed from the estimated additive genetic (co)variance matrix by considering CR as the breeding goal and AFI, NRR56, and IFL as selection criteria. Heritability estimates from average covariance matrices ranged from 0.012 (CR) to 0.015 (IFL), with the exception of AFI (0.071). Conception rate at first insemination was strongly correlated with both IFL (-0.730) and NRR56 (0.668), and weakly to AFI (-0.065), and the relative emphasis placed on each selection criteria in the aggregate index was 10%, 47%, and 43% for AFI, IFL, and NRR56, respectively. The results of the present study suggest that heifer fertility should be considered as an additional trait in the breeding objectives of Italian Holstein.

Grazing affects metabolic pattern of individual cow milk.

Effective traceability tools able to characterize milk from pasture are important to safeguard low-input farming systems, niche dairy products, and local traditions. The aims of the present study were to investigate the ability of proton nuclear magnetic resonance (1H NMR) spectroscopy to discriminate between milk produced from cows before and after the beginning of the grazing season, and to assess the effects of grazing on milk metabolites. The research trial involved a single alpine holding with 72 lactating cows. Individual milks were repeatedly sampled from the same animals before (i.e., d -3 and -1) and after (i.e., d 2, 3, 7, 10, and 14) the onset of the grazing period. One-dimensional 1H NMR spectra of milk extracts were collected through a Bruker spectrometer. Random forest discriminant analysis was applied to 1H NMR spectra to predict the period of collection for each sample. Data concerning the relative abundance of milk metabolites were analyzed through a linear mixed model, which included the fixed effects of period of sampling, cow breed, stage of lactation, and parity, and the random effect of cow nested within breed. The random forest model exhibited great accuracy (93.1%) in discriminating between samples collected on d -3, -1, 2, and 3 and those collected on d 7, 10, and 14. Univariate analysis performed on the 40 detected metabolites highlighted that milk samples from pasture had lower levels of 14 compounds (with fumarate being the most depressed metabolite) and greater levels of 15 compounds (with methanol and hippurate being the most elevated metabolites). Results indicate that milk 1H NMR spectra are promising to identify milk produced in different conditions. Also, our study highlights that grazing is associated with significant changes of milk metabolic profile, suggesting the potential use of several metabolites as indicators of farm management.

Characterization of the genetic polymorphism linked to the ß-casein A1/A2 alleles using different molecular and biochemical methods.

The 2 major subvariants of ß-casein (A1 and A2), coded by CSN2 gene, have received great interest in the last decade both from the scientific community and the dairy sector due to their influence on milk quality. The consumption of the A1 variant, compared with the A2 variant, has a potential negative effect on human health after its digestion but, at the same time, its presence improves the milk technological properties. The aim of the present study was to compare the best method in terms of time required, costs, and technical engagement for the identification of ß-casein A1 and A2 variants (homozygous and heterozygous animals) in milk to offer a reliable service for large-scale screening studies. Two allele-specific PCR procedures, namely RFLP-PCR and amplification refractory mutation system (ARMS-PCR), and one biochemical technique (HPLC) were evaluated and validated through sequencing. Manual and automated DNA extraction protocols from milk somatic cells were also compared. Automated DNA extraction provided better yield and purity. Chromatographic analysis was the most informative and the cheapest method but unsuitable for large-scale studies due to lengthy procedures (45 min per sample). Both allele-specific PCR techniques proved to be fast and reliable for differentiating between A1 and A2 variants but more expensive than HPLC analysis. Specifically, RFLP-PCR was the most expensive and labor-demanding among the evaluated techniques, whereas ARMS-PCR was the fastest while also requiring less technical expertise. Overall, automated extraction of DNA from milk matrix combined with ARMS-PCR is the most suitable technique to provide genetic characterization of the CSN2 gene on a large scale.

Effects of preservative, storage time, and temperature of analysis on detailed milk protein composition determined by reversed-phase high-performance liquid chromatography.

Milk preservative and freezing are used as strategies to prevent microbial growth and milk degradation, especially when immediate analytical processing is not feasible. The effects of the addition of preservative and freezing procedures have been investigated mainly in relation to milk gross chemical composition predicted through mid-infrared spectroscopy. This study aimed to determine whether different preservatives (i.e., no preservative, hydrogen peroxide, Bronopol, and Azidiol), freezing times (i.e., 0, 7, and 30 d), and temperatures of analysis (i.e., 5 and 21°C) influence the composition of milk protein fractions determined through reversed-phase HPLC. Bulk milk samples for the analysis of protein profile were collected from 5 commercial dairy farms. Data were analyzed with a linear mixed model, which included type of preservative, time of storage, temperature of analysis, and the interaction between type of preservative and time of storage as fixed effects, with the farm and the residual as random effects. Samples with no preservative had the greatest amount of all protein fractions, whereas Bronopol-preserved milk had the lowest amount. Increasing storage time under freezing conditions had a nonlinear detrimental effect on milk protein fractions. The temperature of analysis significantly contributed to the variation of κ-casein, ß-casein, αS1-casein, ß-lactoglobulin, and α-lactalbumin fractions. The z-scores were calculated to evaluate the similarity between detailed protein profile of fresh milk without preservative analyzed at 5°C and detailed protein profile of milk treated according to the tested conditions. Overall results suggested a good agreement between different analytical conditions. Still, short storage time under freezing conditions is recommended to avoid degradation of milk protein fractions and consequent analytical underestimation.

Nuclear magnetic resonance spectroscopy to investigate the association between milk metabolites and udder quarter health status in dairy cows.

Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

Effectiveness of visible - Near infrared spectroscopy coupled with simulated annealing partial least squares analysis to predict immunoglobulins G, A, and M concentration in bovine colostrum.

Visible - near infrared spectroscopy coupled with variable selection using simulated annealing PLS regression was tested to predict immunoglobulin fractions (g/L) of bovine colostrum, namely IgG, IgA and IgM. Immunoglobulins were quantified in 678 samples using the gold standard radial immunodiffusion. Samples were divided in calibration (50%) and validation (50%) datasets. Maximum number of selected variables were limited to 200 and root mean squared error in cross validation (RMSECV) was used as loss function. Performance of the final model developed using the calibration dataset was assessed on the validation dataset. Overall, simulated annealing PLS improved validation RMSECV compared to ordinary PLS regression by 3% to 17%. The present study demonstrated the effectiveness of the calibration model for accurate quantification of IgG, the most abundant immunoglobulin of bovine colostrum (RMSECV = 13.28 g/L; R2 = 0.83). These outcomes could be useful to assess colostrum quality intended for animal and human usage.

Variation of immunoglobulins G, A, and M and bovine serum albumin concentration in Holstein cow colostrum.

Immunoglobulins G (IgG), A (IgA), and M (IgM) represent 70-80% of total proteins in cattle colostrum and are essential for the passive transfer of antibodies from the dam to the calf. Considering the practical difficulties of colostrum sample collection and the high cost of analysis, non-genetic sources of variation of the three immunoglobulins fractions have been scarcely studied together on a large scale in dairy cows. In the present study, IgG, IgA, IgM, and bovine serum albumin (BSA) were determined in colostrum samples of Holstein cows through bovine-specific radial immunodiffusion kits; such phenotypes allowed to investigate the effects of parity, herd, and calving season, and interactions. Only the first colostrum was considered in the present study, as the calf was separated from the dam immediately after birth and was not allowed to suckle. The average of IgG (n = 676), IgA (n = 573), IgM (n = 658), total immunoglobulins (n = 525), and BSA (n = 614) was 91.31, 4.20, 105.99, 5.05, and 2.47 g/L, respectively, and all traits positively correlated to each other. Overall, the immunoglobulins were less concentrated in colostrum of first- and second-parity cows than later-parity cows. These findings suggest that colostrum quality, based on Ig, is overall greater in cows that experienced more than two lactations, likely due to a greater experience of the immune system and to a wider immune heritage compared to younger cows. As regards the effect of calving season, the concentration of all Ig tended to be generally greater in colostrum sampled from August to November. Moreover, there were differences in IgG, IgA, and IgM concentration among the nine herds involved. Future studies will investigate the relationships of these traits with yield, and gross and detailed composition of bovine colostrum and will consider their genetic background to evaluate potential selection strategies to improve colostrum quality.

Short communication: Iodine content in bovine milk is lowly heritable and shows limited genetic variation.

Milk and dairy products are considered important sources of iodine in several countries. Despite this, there is a paucity of studies that have investigated sources of variation of milk iodine, especially on a large scale. So far, it is not clear if milk iodine content could be increased through breeding in dairy cattle. Recently, a mid-infrared spectroscopy prediction model has been developed for an indirect quantification of iodine content in cow milk, as it is a faster and less expensive method that allows the prediction at population level. The model has coefficient of determination and ratio of performance to deviation in external validation of 0.57 and 1.44, respectively, and it was used in the present study to predict the iodine content from historical milk spectral data to investigate phenotypic and genetic aspects in the Italian Holstein cattle. Based on the accuracy of the model, the prediction was interpreted as proxy for the real milk iodine concentration (IODP). The data set comprised 33,776 test-day records with IODP from 4,072 cows. Data of IODP were transformed through natural logarithm to achieve a normal distribution. The effect of parity, lactation stage, and month of sampling were investigated, and genetic parameters were estimated using a test-day repeatability animal model. Milk IODP decreased with parities and was the lowest in early lactation. Heritability of IODP was low (0.025) and it was positively genetically correlated with milk yield and negatively with fat content. Results suggested that it would be challenging to directly improve this trait through breeding strategies in dairy cattle, because IODP is mainly affected by temporary environmental factors and thus, cannot be easily improved through genetics. Although preliminary, findings of this study suggest that it would be more convenient to develop feeding and management strategies to drive milk iodine level than to put efforts and resources into breeding strategies. Further studies should validate IODP as an indicator trait of milk iodine content by improving reference data and estimating genetic correlation between predicted and measured values.

Exploring potential risk factors of antimicrobial use in beef cattle.

Livestock species are major contributors to the increase of antimicrobial (AM) resistance which is a worldwide concern for both human and animal health. The over-use of AM is widely acknowledged, however, unlike pigs, poultry and dairy cattle, knowledge on potential risk factors affecting AM usage (AMU) in beef industry is limited. Hence, this study aimed to investigate the impact of farm, breed, sex and season of arrival of purchased beef cattle on AMU in Italian beef cattle. Data on 1063 batches were collected from January 2016 to April 2019 from specialised beef fattening farms located in the north of Italy. Information on breed, sex, date of arrival, performance traits and AM agents used on farm was collected, and the treatment incidence 100 (TI100) indexes per batch were calculated using the defined daily dose animal estimated according to Italian summaries of product characteristics. Factors affecting TI100 indexes were investigated using a cross-classified multilevel model. Farms largely differed in terms of AMU. Males had greater AMU than females (P < 0.001), likely due to their higher susceptibility to disease. Statistically significant differences were observed between seasons of arrival with summer and spring having lower TI100 indexes than winter and autumn (P < 0.001). Indeed, winter is commonly linked to an increase in respiratory diseases in beef cattle. Finally, the TI100it indexes tended to be different among breeds with Blonde d'Aquitaine and Limousine having greater AMU compared to the other breeds. Results of this study provided valuable information on potential risk factors of AMU in beef production which may be useful to address its reduction. For instance, the development of tailored management strategies for specific breeds, targeted approaches to improve the health of males as well as greater care towards batches purchased in winter are possible advice to implement on-farm for a more responsible AM stewardship.

Technical note: Repeatability and reproducibility of curd yield and composition in a miniaturized coagulation model.

Miniaturized coagulation (MC) models have been proposed for the evaluation of curd yield (CY) in individual milk samples of different dairy species and breeds, and for the analysis of cheese microstructure and texture. It is still unclear if MC using less than 50 mL of milk is suitable to evaluate CY and chemical composition, and if preservative added to raw milk may interfere with MC process. Therefore, this study aimed at evaluating repeatability and reproducibility of CY, curd moisture, and fat and protein content on curd dry matter (DM) from MC trials using 40 g of milk. Miniaturized coagulations were performed by 3 different operators on 3 consecutive days, using raw milk (RM) and raw milk added with preservative (RMP). Repeatability of CY, calculated as relative standard deviation on 6 miniaturized curds obtained within a day by the same operator, was below 5% for MC carried out with both RM and RMP. The Horwitz ratio, which is the ratio between measured and expected reproducibility, highlighted good reproducibility for CY from RM and fair reproducibility for CY from RMP. The same ratio highlighted lower accuracies for curd moisture and fat and protein content on curd DM, especially for MC trials carried out with RMP. The z-test was performed to evaluate the similarity between curds manufactured with RM and RMP in terms of average yield and chemical composition; z-scores did not highlight significant differences between values obtained from MC carried out with RM and RMP. It can be concluded that preservative had negligible effects on MC, giving the opportunity to extend milk physical and chemical stability, to schedule laboratory trials on longer time span, and to broaden the sample size within a batch of analyses.

Changes in milk lactose content as indicators for longevity and udder health in Holstein cows.

Changes in milk production traits over time might be informative of the health status of cows and may contain useful information for selective breeding purposes. In particular, early indicators are useful for traits such as longevity, which become available late in the cow's life. Lactose percentage (LP) tends to decrease in the presence of udder infection and with parity. Therefore, it can be hypothesized that cows exhibiting limited changes in LP across lactations have experienced fewer udder infections in their productive life and have a higher chance to stay longer in the herd than cows with more pronounced reduction of LP across lactations. In this study, 9 descriptors of change in LP during a cow's lifetime were defined and evaluated as potential indicators for selective breeding. For the purpose of this study, test-day records of the first 44 days in milk (DIM) of each lactation were discarded, and cows were required to have at least 5 test-days/cow per lactation (≥45 DIM) over the first 3 lactations. In this study, descriptors of LP were available for 69,586 Italian Holstein cows. Changes in LP in each lactation were quantified by regressing LP on DIM; thus, ß1, ß2, and ß3 represented the changes in LP within lactations 1, 2, and 3, respectively. Changes in LP across multiple lactations were also quantified by regressing LP on DIM (with exclusion of the first 44 DIM of each lactation); briefly, ß12 was the change of LP over lactation 1 and 2, ß23 was the change of LP over lactation 2 and 3, and ß123 was the change of LP over lactation 1, 2, and 3. Alternatively, changes in the LP lactation means (Δ) were quantified between lactations 1 and 2 (Δ12), 2 and 3 (Δ23), and 1 and 3 (Δ13). For comparison, ß and Δ were also derived for milk yield (kg/d), somatic cell score, and log-transformed total somatic cells excreted daily in milk (units). Variance components and estimated breeding values (EBV) for all ß's and Δ's were estimated. In addition, EBV for bulls with at least 25 daughters were used to assess Calo's genetic correlations between descriptors of change in LP with official published EBV for functional traits. Heritabilities for ß and Δ of LP ranged from 0.06 (Δ23) to 0.20 (Δ13), and differed significantly from 0. Furthermore, LP EBV for ß and Δ were correlated with official EBV for functional longevity index, udder health index, udder score (mammary gland morphology) index, and milk persistency; Calo's genetic correlations of LP ß123 with functional longevity and udder health index were 0.52 and 0.33, respectively. Cows with a stronger reduction of LP across lactations (i.e., stronger and negative ß, and greater and positive Δ) were characterized by lower milk persistency, impaired longevity, and worse udder health and morphology than cows with smaller reduction in LP across lactations. Results highlighted that changes in milk LP have the potential to be exploited as indicators for functional traits in Italian Holstein cattle. Further research on the biological relationship between changes in LP and mastitis is recommended.

Short communication: Genetic aspects of milk urea nitrogen and new indicators of nitrogen efficiency in dairy cows.

Milk urea nitrogen (MUN), a trait routinely measured in the national milk recording system, is a useful indicator of nitrogen utilization efficiency of dairy cows, and selection for MUN and MUN-derived traits could be a valid strategy to produce better animals with regard to efficiency of nitrogen utilization. Therefore, the aim of the present study was to explore the genetic aspects of MUN and new potential indicators of nitrogen efficiency, namely ratios of protein to MUN, casein to MUN, and whey protein to MUN, in the Italian Brown Swiss population. A total of 153,175 test-day records of 10,827 cows in 500 herds were used for genetic analysis. Variance components and heritability of the investigated traits were estimated using single-trait repeatability animal models, whereas genetic and phenotypic correlations between the traits were estimated through bivariate repeatability animal models, including fixed effects of herd-test-date, stage of lactation, parity, calving year, and calving season, and the random effects of additive genetic animal, cow permanent environment, and the residual. Heritability estimates for MUN (0.20 ± 0.01) and the 3 new indicators of nitrogen utilization efficiency (0.15 ± 0.01 for protein-to-MUN and casein-to-MUN ratios, and 0.12 ± 0.01 for ratio of whey protein to MUN) suggested that additive genetic variation exists for these traits, and thus there is potential to select for greater organic nitrogen and lower inorganic nitrogen in milk. Genetic association between MUN and the 3 ratios was high (-0.87 ± 0.01) but not unity, suggesting that ratios could provide some further information beyond that provided by MUN with regard to efficiency of nitrogen utilization. Genetic trend of the investigated traits by year of birth of Brown Swiss sires showed how the selection applied in the last 30 yr has led to an increase of both quantity and quality of milk, and a decrease of somatic cell score and MUN. The inclusion of MUN in breeding programs could speed up the process of increasing organic nitrogen such as protein, which is useful for cheese-making, and reducing inorganic nitrogen (MUN) in milk.