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: 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.

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

The 2 major subvariants of β-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 β-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.

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.

Genome-wide analysis reveals the patterns of genetic diversity and population structure of 8 Italian local chicken breeds

The aim of this study was to conduct a genome-wide comparative analysis of 8 local Italian chicken breeds (Ermellinata di Rovigo, Millefiori di Lonigo [PML], Polverara Bianca, Polverara Nera, Padovana, Pepoi [PPP], Robusta Lionata, and Robusta Maculata), all under a conservation plan, to understand their genetic diversity and population structure. A total of 152 animals were analyzed using the Affymetrix Axiom 600 K Chicken Genotyping Array. The levels of genetic diversity were highest and lowest in PML and PPP, respectively. The results of genomic inbreeding based on runs of homozygosity (ROH; FROH) showed marked differences among breeds and ranged from 0.161 (PML) to 0.478 (PPP). Furthermore, in all breeds, short ROH (<4 Mb in length) were more frequent than long segments. Patterns of genetic differentiation, model-based clustering, and neighbor networks showed that most breeds formed nonoverlapping clusters and were clearly separate populations. The 2 Polverara breeds shared a similar genetic background and showed the lowest genetic differentiation in comparison with purebred lines; the local populations showed separated groups. PPP and PML were closer to the group of the purebred broiler lines (BRSA, BRSB, BRDA, and BRDB). Six genomic regions are presented as hotspots of autozygosity among the Italian chicken breeds, with candidate genes involved in multiple morphological phenotypes as breast muscle, muscle dry matter content, and body weight. This study is the first exhaustive genome-wide analysis of the diversity of these Italian local chickens from Veneto region. We conclude that breeds have conserved authentic genetic patterns. The results are of significant importance because they will help design and implement conservation strategies. In fact, the conservation of these breeds may also have positive impacts on the local economy, niche traditional markets, and offering a source of high-quality products to consumers. In this context, genomic information may play a crucial role in the management of local breeds.

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 (IOD_P). The data set comprised 33,776 test-day records with IOD_P from 4,072 cows. Data of IOD_P 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 IOD_P decreased with parities and was the lowest in early lactation. Heritability of IOD_P 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 IOD_P 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 IOD_P as an indicator trait of milk iodine content by improving reference data and estimating genetic correlation between predicted and measured values.

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.

Genome-wide assessment of diversity and differentiation between original and modern Brown cattle populations

Identifying genomic regions involved in the differences between breeds can provide information on genes that are under the influence of both artificial and natural selection. The aim of this study was to assess the genetic diversity and differentiation among four different Brown cattle populations (two original vs. two modern populations) and to characterize the distribution of runs of homozygosity (ROH) islands using the Illumina Bovine SNP50 BeadChip genotyping data. After quality control, 34 735 SNPs and 106 animals were retained for the analyses. Larger heterogeneity was highlighted for the original populations. Patterns of genetic differentiation, multidimensional scaling, and the neighboring joining tree distinguished the modern from the original populations. The F_ST -outlier identified several genes putatively involved in the genetic differentiation between the two groups, such as stature and growth, behavior, and adaptability to local environments. The ROH islands within both the original and the modern populations overlapped with QTL associated with relevant traits. In modern Brown (Brown Swiss and Italian Brown), ROH islands harbored candidate genes associated with milk production traits, in evident agreement with the artificial selection conducted to improve this trait in these populations. In original Brown (Original Braunvieh and Braunvieh), we identified candidate genes related with fat deposition, confirming that breeding strategies for the original Brown populations aimed to produce dual-purpose animals. Our study highlighted the presence of several genomic regions that vary between Brown populations, in line with their different breeding histories.

A survey on sensor systems used in Italian dairy farms and comparison between performances of similar herds equipped or not equipped with sensors

Sensor systems (SS) were developed over the last few decades to help dairy farmers manage their herds. Such systems can provide both data and alerts to several productive, behavioral, and physiological indicators on individual cows. Currently, there is still a lack of knowledge on both the proportion of dairy farms that invested in SS and type of SS installed. Additionally, it is still unclear whether the performances of herds equipped with SS differ from those of similar herds managed without any technological aid. Therefore, the aims of this study were (1) to provide an insight into SS spread among Italian dairy farms and (2) to analyze the performances of similar herds equipped or not equipped with SS. To reach the former goal, a large survey was carried out on 964 dairy farms in the northeast of Italy. Farmers were interviewed by the technicians of the regional breeders association to collect information on the type of SS installed on farms and the main parameters recorded. Overall, 42% of the surveyed farms had at least 1 SS, and most of them (72%) reared more than 50 cows. Sensors for measuring individual cow milk yield were the most prevalent type installed (39% of the surveyed farms), whereas only 15% of farms had SS for estrus detection. More sophisticated parameters, such as rumination, were automatically monitored in less than 5% of the farms. To reach the latter goal of the study, a subset of 100 Holstein dairy farms with similar characteristics was selected: half of them were equipped with SS for monitoring at least individual milk yield and estrus, and the other half were managed without any SS. Average herd productive and reproductive data from official test days over 3 yr were analyzed. The outcomes of the comparison showed that farms with SS had higher mature-equivalent milk production. Further clustering analysis of the same 100 farms partitioned them into 3 clusters based on herd productive and reproductive data. Results of the Chi-squared test showed that the proportion of farms equipped with SS was greater in the cluster with the best performance (e.g., higher milk yield and shorter calving interval). However, the presence of a few farms equipped with SS in the least productive cluster for the same parameters pointed out that although the installation of SS may support farmers in time- and labor-saving or in data recording, it is not a guarantee of better herd performance.

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.

Estimation of maximum thermo-hygrometric index thresholds affecting milk production in Italian Brown Swiss cattle

It is known that heat stress affects dairy cow performance in multiple ways: physiological, behavioral, reproductive, and productive. The aim of the present study was to determine if a threshold of temperature-humidity index (THI) exists for multiple milk production traits (milk yield, fat-corrected milk, protein and fat yield and percentage, energy-corrected milk, cheese production, and cheese yield) in Italian Brown Swiss dairy cows from the period 15 d before the day of the Italian Breeders Association test-day sampling. A 10-yr data set (2009-2018) containing 202,776 test-day records of 23,296 Brown Swiss cows was matched with the maximum THI. In all parities considered, no THI thresholds were observed for milk yield in Brown Swiss. In contrast, a THI threshold of 75 was identified for fat-corrected milk. No THI threshold was found for fat percentage, but fat yield showed the highest THI thresholds in cows of first and second parity. Protein yield and cheese production were affected by heat stress with average THI threshold of 74. The THI thresholds identified indicate that the Brown Swiss breed has higher thermal tolerance versus literature values reported for Holstein cows. As THI rises, Brown Swiss cows tend to produce the same volume of milk, but with a decreasing quality with regard to components. Further study is necessary to estimate the genetic component of heat tolerance, in Brown Swiss cattle, considering that the correct estimation of THI thresholds represents the first step to identify components that could be included in selection procedures.

Genetic relationships of lactose and freezing point with minerals and coagulation traits predicted from milk mid-infrared spectra in Holstein cows

The aim of the present study was to assess the relationships of lactose percentage (LP), lactose yield (LY), and freezing point (FRP) with minerals and coagulation properties predicted from mid-infrared spectra in bovine milk. To achieve this purpose, we analyzed 54,263 test-day records of 4,297 Holstein cows to compute (co)variance components with a linear repeatability animal model. Parity, stage of lactation, season of calving, and herd-test-date were included as fixed effects in the model, and additive genetic animal, within- and across-lactation permanent environment, and residual were included as random effects. Lactose percentage was more heritable (0.405 ± 0.027) than LY (0.121 ± 0.021) and FRP (0.132 ± 0.014). Heritabilities (± standard error) of predicted milk minerals varied from 0.375 ± 0.027 for Na to 0.531 ± 0.028 for P, and those of milk coagulation properties ranged from 0.348 ± 0.052 for rennet coagulation time to 0.430 ± 0.026 for curd firming time. Lactose percentage showed favorable (negative) genetic correlations with milk somatic cell score (SCS) and FRP, and it was almost uncorrelated with casein-related minerals (Ca and P) and coagulation properties. Moreover, LP was strongly correlated with Na (-0.783 ± 0.022), a mineral known to increase in the presence of intramammary infection (IMI) and high somatic cell count. Indeed, Na is the main osmotic replacer of lactose in mastitic milk when the blood-milk barrier is altered during IMI. Being strongly associated with milk yield, LY did not favorably correlate with coagulation properties, likely because of the negative correlation of this trait with protein and casein percentages. Milk FRP presented moderate and null genetic associations with Na and SCS, respectively. Results of the present study suggest that the moderate heritability of LP and its genetic correlations with IMI-related traits (Na and SCS) could be exploited for genetic selection against mastitis. Moreover, selection for LP would not impair milk coagulation characteristics or Ca and P content, which are important for cheesemaking.

Alternative somatic cell count traits exploitable in genetic selection for mastitis resistance in Italian Holsteins

The aim of the present study was to characterize alternative somatic cell count (SCC) traits that could be exploited in genetic selection for mastitis resistance. Data were from 66,407 first-parity Holsteins in 404 herds. Novel SCC traits included average somatic cell score (SCS, log-transformation of SCC) in early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), the presence of at least one test-day (TD) SCC >400,000 cells/mL in the lactation, and the ratio of number of TD SCC >400,000 cells/mL to total number of TD in the lactation. Novel traits and lactation-mean SCS (SCS_LM) were analyzed using linear mixed or logistic regression models, including month of calving, year of calving, number of TD, and milk yield as fixed effects, and herd and residual as random terms. A multitrait linear animal model was applied to a random subset of 152 herds (n = 22,695 cows) to assess heritability of and genetic correlations between SCC traits. Alternative SCC traits were affected by the environmental factors included in the model; in particular, results suggested a seasonal effect and a tendency toward an improvement of the udder health status in the last years. Association was also found between novel SCC traits and milk production. Alternative SCC traits exhibited coefficients of additive genetic variation that were similar to or larger than that of traditional SCS_LM. Heritability of novel SCC traits was smaller than heritability of SCS_LM (0.126 ± 0.014), ranging from 0.044 ± 0.008 (SCS_SD) to 0.087 ± 0.010 (SCS_150). Genetic correlations between SCC traits ranged from 0.217 ± 0.096 (SCS_150 and SCS_SD) to 0.969 ± 0.010 (SCS_LM and SCS_150). Alternative SCC traits exhibited additive genetic variation that is potentially exploitable in breeding programs of Italian Holstein population to improve resistance to mastitis.

Technical note: Development and validation of an HPLC method for the quantification of tocopherols in different types of commercial cow milk

In the present study, a methanol-fluorescence-based HPLC method was validated for its use to quantify α-tocopherol and γ-tocopherol in raw milk, whole UHT milk, partially skimmed UHT milk, whole pasteurized milk, and partially skimmed pasteurized milk. Repeatability and reproducibility, calculated as relative standard deviation of 10 measurements within the same day and 30 measurements across 3 d, respectively, were always below 5% for both tocopherols concentrations and retention times. Recovery was assessed through 3 spiking levels and it ranged from 89 to 107%. The method was able to detect the expected declines in tocopherols in milk exposed to UHT or skimming treatments. Vitamin E, calculated as the sum of α-tocopherol and γ-tocopherol, was similar in whole pasteurized and raw milk, averaging 1.57 and 1.56 mg/L, respectively, followed by whole UHT (1.33 mg/L), partially skimmed pasteurized (0.77 mg/L), and partially skimmed UHT milk (0.61 mg/L).

Development and validation of a novel SNP panel for the genetic characterization of Italian chicken breeds by next-generation sequencing discovery and array genotyping

The aim of this study was to compare the intra and inter genetic variability and population structure of 7 indigenous chicken breeds of the Veneto region, through a novel panel of 64 SNP, each located in an exonic region and mostly on different chromosomes. A total of 753 blood samples from 7 local chicken breeds (Ermellinata di Rovigo, Millefiori di Lonigo, Polverara, Pepòi, Robusta Lionata, Robusta Maculata, and Padovana) was collected and analyzed. Two strains of Polverara (Nera and Bianca) and Padovana (Dorata and Camosciata) were included in the study. The observed heterozygosity ranged from 0.124 (Pèpoi) to 0.244 (Ermellinata di Rovigo), and the expected heterozygosity varied from 0.132 (Millefiori di Lonigo) to 0.300 (Ermellinata di Rovigo). Global FIS results (0.114) indicated a low-medium inbreeding effect, with values ranging from 0.008 (Millefiori di Lonigo) to 0.223 (Ermellinata di Rovigo). Pairwise FST values (0.167) for all populations ranged from 0.020 (Polverara Nera and Polverara Bianca) to 0.193 (Robusta Lionata and Polverara Nera), indicating that the studied breeds were genetically highly differentiated. The software STRUCTURE was used to detect the presence of population substructures, and the most probable number of clusters (K) of the 10 chicken populations was at K = 8. The affiliation was successful in all Veneto chicken breeds. The present SNP marker results, compared with previous data obtained using microsatellites, provided a reliable estimate of genetic diversity within and between the studied breeds, and demonstrated the utility of the proposed panel as a rapid, efficient, and cost-effective tool for periodical monitoring of the genetic variability among poultry populations. In addition, the present SNP panel could represent a resource for a systematic approach with relevant impact on breeding program decisions and could turn out to be a reliable tool for genetic traceability of indigenous chicken meat. Adoption of a periodical monitoring system of genetic diversity is a fundamental tool in conservation actions and should increase the value of typical and niche products.

Short communication: Phenotypic characterization of total antioxidant activity of buffalo, goat, and sheep milk

Free radicals are reactive and unstable waste molecules produced by cells, responsible of damages and alteration on DNA, proteins, and fat. The daily intake of antioxidant compounds, acting against free radicals and their detrimental effects, is essential for human health. Milk contains several compounds with antioxidant activity, and the sum of their reducing potential blocking free radicals development is defined as total antioxidant activity (TAA). This novel trait has been described in literature both in individual and bulk cow milk, but there are no reports from other dairy species. Therefore, the present study aimed to investigate phenotypic variation of TAA in individual samples of buffalo (n = 105), goat (n = 112), and sheep (n = 198) milk. Total antioxidant activity was measured through a reference spectrophotometric method, and expressed as millimoles per liter of Trolox equivalents (TE). The greatest TAA was observed in sheep milk, averaging 7.78 mmol/L of TE and showing also the broadest phenotypic variation expressed as coefficient of variation (13.98%). Significantly lower TAA values were observed for buffalo (7.35 mmol/L of TE) and goat (6.80 mmol/L of TE) milk, with coefficients of variation of 8.18 and 8.47%, respectively. Total antioxidant activity exhibited weak correlations with milk yield and chemical composition. Phenotypic values of TAA presented in this study will be used to assess the ability of mid-infrared spectroscopy to predict this new trait and thus to collect data at the population level.

Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.

Environmental life cycle assessment of Italian mozzarella cheese: Hotspots and improvement opportunities

The present study investigated a cradle-to-grave life cycle assessment to estimate the environmental impacts associated with Italian mozzarella cheese consumption. The differences between mozzarella produced from raw milk and mozzarella produced from curd were studied, and differences in manufacturing processes have been emphasized in order to provide guidance for targeted improvements at this phase. Specifically, the third-largest Italian mozzarella producer was surveyed to collect site-specific manufacturing data. The Ecoinvent v3.2 database was used for secondary data, whereas SimaPro 8.1 was the modeling software. The inventory included inputs from farm activities to end of life disposal of wasted mozzarella and packaging. Additionally, plant-specific information was used to assign major inputs, such as electricity, natural gas, packaging, and chemicals to specific products; however, where disaggregated information was not provided, milk solids allocation was applied. Notably, loss of milk solids was accounted during the manufacture, moreover mozzarella waste and transport were considered during distribution, retail, and consumption phases. Feed production and animal emissions were the main drivers of raw milk production. Electricity and natural gas usage, packaging (cardboard and plastic), transport, wastewater treatment, and refrigerant loss affected the emissions from a farm gate-to-dairy plant gate perspective. Post-dairy plant gate effects were mainly determined by electricity usage for storage of mozzarella, transport of mozzarella, and waste treatment. The average emissions were 6.66 kg of CO₂ equivalents and 45.1 MJ of cumulative energy demand/kg of consumed mozzarella produced directly from raw milk, whereas mozzarella from purchased curd had larger emissions than mozzarella from raw milk due to added transport of curd from specialty manufacturing plants, as well as electricity usage from additional processes at the mozzarella plant that are required to process the curd into mozzarella. Normalization points to ecotoxicity as the impact category most significantly influenced by mozzarella consumption. From a farm gate-to-grave perspective, ecotoxicity and freshwater and marine eutrophication are the first and second largest contributors of mozzarella consumption to average European effects, respectively. To increase environmental sustainability, an improvement of efficiency for energy and packaging usage and transport activities is recommended in the post-farm gate mozzarella supply chain.

Environmental life cycle assessment of Italian mozzarella cheese: Hotspots and improvement opportunities

The present study investigated a cradle-to-grave life cycle assessment to estimate the environmental impacts associated with Italian mozzarella cheese consumption. The differences between mozzarella produced from raw milk and mozzarella produced from curd were studied, and differences in manufacturing processes have been emphasized in order to provide guidance for targeted improvements at this phase. Specifically, the third-largest Italian mozzarella producer was surveyed to collect site-specific manufacturing data. The Ecoinvent v3.2 database was used for secondary data, whereas SimaPro 8.1 was the modeling software. The inventory included inputs from farm activities to end of life disposal of wasted mozzarella and packaging. Additionally, plant-specific information was used to assign major inputs, such as electricity, natural gas, packaging, and chemicals to specific products; however, where disaggregated information was not provided, milk solids allocation was applied. Notably, loss of milk solids was accounted during the manufacture, moreover mozzarella waste and transport were considered during distribution, retail, and consumption phases. Feed production and animal emissions were the main drivers of raw milk production. Electricity and natural gas usage, packaging (cardboard and plastic), transport, wastewater treatment, and refrigerant loss affected the emissions from a farm gate-to-dairy plant gate perspective. Post-dairy plant gate effects were mainly determined by electricity usage for storage of mozzarella, transport of mozzarella, and waste treatment. The average emissions were 6.66 kg of CO₂ equivalents and 45.1 MJ of cumulative energy demand/kg of consumed mozzarella produced directly from raw milk, whereas mozzarella from purchased curd had larger emissions than mozzarella from raw milk due to added transport of curd from specialty manufacturing plants, as well as electricity usage from additional processes at the mozzarella plant that are required to process the curd into mozzarella. Normalization points to ecotoxicity as the impact category most significantly influenced by mozzarella consumption. From a farm gate-to-grave perspective, ecotoxicity and freshwater and marine eutrophication are the first and second largest contributors of mozzarella consumption to average European effects, respectively. To increase environmental sustainability, an improvement of efficiency for energy and packaging usage and transport activities is recommended in the post-farm gate mozzarella supply chain.

Association of candidate gene polymorphisms with milk technological traits, yield, composition, and somatic cell score in Italian Holstein-Friesian sires

Advances in DNA-based marker technology have enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to investigate 96 single nucleotide polymorphisms (SNP) located in 53 candidate genes previously reported to have effects on milk production and quality traits in a population of highly selected Holstein-Friesian bulls. A total of 423 semen samples were used to genotype the bulls through a custom oligo pool assay. Forty-five SNP in 32 genes were found to be associated with at least 1 of the tested traits. Most significant and favorable SNP trait associations were observed for polymorphisms located in CCL3 and AGPAT6 genes for fat yield (0.037 and 0.033 kg/d, respectively), DGKG gene for milk yield (0.698 kg/d), PPARGC1A, CSN1S1, and AGPAT6 genes for fat percentage (0.127, 0.113, and 0.093%, respectively), GHR gene for protein (0.064%) and casein percentage (0.053%), and TLR4 gene for fat (0.090%), protein (0.066%), and casein percentage (0.050%). Somatic cell score was favorably affected by GHR (-0.095) and POU1F1 (-0.137), and interesting SNP-trait associations were observed for polymorphisms located in CSN2, POU1F1, and AGPAT6 genes for rennet coagulation time (-0.592, -0.558, and -0.462 min, respectively), and GHR and CSN2 genes for curd firmness 30 min after rennet addition (1.264 and 1.183 mm, respectively). In addition to the influence of individual SNP, the effects of composite genotypes constructed by grouping SNP according to their individual effects on traits considered in the analysis were also examined. Favorable and significant effects on milk traits were observed for 2 composite genotypes, one including 10 SNP and the other 4 SNP. The former was associated with an increase of milk (0.075 kg/d), fat (0.097 kg/d), protein (0.083 kg/d), and casein yields (0.065 kg/d), and the latter was associated with an increase of fat (0.244%), protein (0.071%), and casein percentage (0.047%). Although further research is required to validate the identified SNP loci in other populations and breeds, our results can be considered as a preliminary foundation for further replication studies on gene-assisted selection programs.

Development and validation of a near infrared spectrophotometric method to determine total antioxidant activity of milk

In the present study a spectrophotometric method for the determination of total antioxidant activity (TAA) based on ABTS assay was developed and validated on raw milk (RM), whole UHT milk (WUM), partially skimmed UHT milk (SUM), whole pasteurised milk (WM) and partially skimmed pasteurised milk (SM). The most suitable solvent for antioxidant extraction was 80% acetone. Regardless of the type of milk, the coefficient of determination from the linearity test was greater than 0.95. The limit of detection ranged from 0.74 to 6.07μmoll^-1 Trolox equivalents. Repeatability, calculated as relative standard deviation of twenty measurements within a day, and reproducibility, calculated as relative standard deviation of sixty measurements across three days, ranged from 1.24 to 4.04% and from 2.18 to 3.52%, respectively. Preservative added to RM had negligible effects on the TAA of milk. The greatest TAA was measured for SM followed by SUM, RM, WM and WUM.

Predictive ability of mid-infrared spectroscopy for major mineral composition and coagulation traits of bovine milk by using the uninformative variable selection algorithm

Milk minerals and coagulation properties are important for both consumers and processors, and they can aid in increasing milk added value. However, large-scale monitoring of these traits is hampered by expensive and time-consuming reference analyses. The objective of the present study was to develop prediction models for major mineral contents (Ca, K, Mg, Na, and P) and milk coagulation properties (MCP: rennet coagulation time, curd-firming time, and curd firmness) using mid-infrared spectroscopy. Individual milk samples (n=923) of Holstein-Friesian, Brown Swiss, Alpine Grey, and Simmental cows were collected from single-breed herds between January and December 2014. Reference analysis for the determination of both mineral contents and MCP was undertaken with standardized methods. For each milk sample, the mid-infrared spectrum in the range from 900 to 5,000cm(-1) was stored. Prediction models were calibrated using partial least squares regression coupled with a wavenumber selection technique called uninformative variable elimination, to improve model accuracy, and validated both internally and externally. The average reduction of wavenumbers used in partial least squares regression was 80%, which was accompanied by an average increment of 20% of the explained variance in external validation. The proportion of explained variance in external validation was about 70% for P, K, Ca, and Mg, and it was lower (40%) for Na. Milk coagulation properties prediction models explained between 54% (rennet coagulation time) and 56% (curd-firming time) of the total variance in external validation. The ratio of standard deviation of each trait to the respective root mean square error of prediction, which is an indicator of the predictive ability of an equation, suggested that the developed models might be effective for screening and collection of milk minerals and coagulation properties at the population level. Although prediction equations were not accurate enough to be proposed for analytic purposes, mid-infrared spectroscopy predictions could be evaluated as phenotypic information to genetically improve milk minerals and MCP on a large scale.

Contribution of microsatellites markers in the clarification of the origin, genetic risk factors, and implications for conservation of Tunisian native sheep breeds

The genetic diversity and genetic relationship of the two main groups of African sheep, thin-tailed and fat-tailed sheep, represented by the indigenous Tunisian sheep breeds "Barbarine" (BAR, fat-tailed) and "Queue Fine de l'Ouest" (QFO, thin-tailed) were investigated. The genotypes of 110 animals belonging to these two breeds and their crossbreed (CRO) were assessed using 17 microsatellite markers. The results showed high levels of genetic diversity and a total of 256 alleles were identified in the whole population. The mean values of observed and expected heterozygosity were 0.719 and 0.789, respectively, and the mean allelic richness estimate was 10.89. The average FIS (0.112) and FIT (0.118) values over all loci indicated a notable level of inbreeding within the whole population. However, the FST value (0.007) showed a low level of genetic differentiation between these two native breeds. The high level of both gene flow and molecular coancestry coefficient detected between the two breeds and their CRO revealed an old miscegenation between the BAR and QFO breeds. The clustering analysis performed with the STRUCTURE software confirmed gene flow between these two breeds. Results arising from this study provide evidence regarding the genetic structure and variability of the two main local sheep breeds, and the implications of their actual management, which indicates the need for an urgent conservation strategy in order to prevent significant gene flow and preserve the remaining breed specificity for future generations.

Short communication: Selecting the most informative mid-infrared spectra wavenumbers to improve the accuracy of prediction models for detailed milk protein content

The objective of this study was to investigate the ability of mid-infrared spectroscopy (MIRS) to predict protein fraction contents of bovine milk samples by applying uninformative variable elimination (UVE) procedure to select the most informative wavenumber variables before partial least squares (PLS) analysis. Reference values (n=114) of protein fractions were measured using reversed-phase HPLC and spectra were acquired through MilkoScan FT6000 (Foss Electric A/S, Hillerød, Denmark). Prediction models were built using the full data set and tested with a leave-one-out cross-validation. Compared with MIRS models developed using standard PLS, the UVE procedure reduced the number of wavenumber variables to be analyzed through PLS regression and improved the accuracy of prediction by 6.0 to 66.7%. Good predictions were obtained for total protein, total casein (CN), and α-CN, which included αS1- and αS2-CN; moderately accurate predictions were observed for κ-CN and total whey protein; and unsatisfactory results were obtained for β-CN, α-lactalbumin, and β-lactoglobulin. Results indicated that UVE combined with PLS is a valid approach to enhance the accuracy of MIRS prediction models for milk protein fractions.

Short communication: characterization of soluble thiols in bovine milk

Antioxidants are molecules essential for the maintenance of cell homeostasis and their intake through the diet has positive effects on human health. Among antioxidants, low-molecular-weight (LMW) thiols represent an important class of compounds. The aim of this study was to identify LMW thiols in bovine milk. A total of 96 individual milk samples from Brown Swiss, Holstein-Friesian, Alpine Grey, and Simmental cattle breeds were collected in 8 herds. The LMW thiols were extracted from the soluble fraction of milk and, following a derivatization protocol, they were separated by reverse phase HPLC and detected fluorimetrically. Six thiol species were detected and 2, glutathione (GSH) and cysteine-glycine (Cys-Gly), were identified and quantified. Regardless of the breed, the average concentration of Cys-Gly in milk was greater than that of GSH. Overall, milk from dual-purpose breeds (Simmental and Alpine Grey) was richer in LMW thiols than milk from dairy cows (Holstein-Friesian and Brown Swiss). Glutathione and Cys-Gly, closely linked metabolically, were strongly correlated. Pearson correlations of Cys-Gly with protein and casein contents were moderately low, and no relationship was found between GSH and milk chemical composition. Future research should focus on the identification of all detected LMW thiol species.

Effect of microparticulated whey proteins on milk coagulation properties

The enhancement of milk coagulation properties (MCP) and the reuse of whey produced by the dairy industry are of great interest to improve the efficiency of the cheese-making process. Native whey proteins (WP) can be aggregated and denatured to obtain colloidal microparticulated WP (MWP). The objective of this study was to assess the effect of MWP on MCP; namely, rennet coagulation time (RCT), curd-firming time, and curd firmness 30 min after rennet addition. Six concentrations of MWP (vol/vol; 1.5, 3.0, 4.5, 6.0, 7.5, and 9.0%) were added to 3 bulk milk samples (collected and analyzed during 3 d), and a sample without MWP was used as control. Within each day of analysis, 6 replicates of MCP for each treatment were obtained, changing the position of the treatment in the rack. For control samples, 2 replicates per day were performed. In addition to MCP, WP fractions were measured on each treatment during the 3 d of analysis. Milk coagulation properties were measured on 144 samples by using a Formagraph (Foss Electric, Hillerød, Denmark). Increasing the amount of MWP added to milk led to a longer RCT. In particular, significant differences were found between RCT of the control samples (13.5 min) and RCT of samples with 3.0% (14.6 min) or more MWP. A similar trend was observed for curd-firming time, which was shortest in the control samples and longest in samples with 9.0% MWP (21.4 min). No significant differences were detected for curd firmness at 30 min across concentrations of MWP. Adjustments in cheese processing should be made when recycling MWP, in particular during the coagulation process, by prolonging the time of rennet activity before cutting the curd.