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Milk fat is an important nutrient for young animals and humans, and its composition [fatty acids (FA)] may vary broadly. The objective of this study was to describe the development of global FA models for high-throughput Fourier transform infrared milk analysers. The developed models for major FA, FA grouped by chain length, by degree of unsaturation and by their origin, showed good accuracy, repeatability and correlation to gas chromatography. Moderate performance was obtained for low concentration FA (short chain, polyunsaturated and trans). Possible practical applications could be to enhance dairy products, optimise milk processing and/or optimise dairy cow performance through improved feeding and management.

A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates. A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates.

Among the dairy sector's current concerns, the as-sessment of global animal health status is a complex challenge. Its multidimensionality means that global monitoring tools are rarely considered. Instead, specific disease detection is often studied separately and, due to financial and ethical issues, uses small-scale data sets focusing on few biomarkers. Several studies have already been conducted using milk Fourier transform mid-infrared (FT-MIR) spectroscopy to detect mastitis and lameness or to quantify health-related biomarkers in milk or blood. Those studies are relevant but they focus mainly on one biomarker or disease. To solve this issue and the small-scale data set, in this study, we proposed a holistic approach using big data obtained from milk recording, including milk yield, somatic cell count, and 27 FT-MIR-based predictors related to milk composition and animal health status. Using 740,454 records collected from 114,536 first-parity Holstein cows in southern Belgium, we performed repeated unsupervised learning algorithms based on Ward's agglomerative hierarchical clustering method to find potential interesting patterns. A divide-and-conquer approach was used to overcome the limitation of computational resources in clustering a relatively large data set. Five groups of records were identified. Differences observed in the fourth group suggested a relationship to metabolic disorders. The fifth group seemed to be related to mastitis. In a second step, we performed a partial least squares discriminant analysis (PLS-DA) to predict the probability of belonging to those specific groups for the entire data set. The obtained global ac-curacy was 0.77 and the balanced accuracy (i.e., the mean between sensitivity and specificity) of discrimi-nating the fourth and fifth groups was 0.88 and 0.96, respectively. Then, a validation of the interpretation of those groups was performed using 204 milk and blood reference records. The predicted probability associated with the metabolic disorders issue had significant cor-relations of 0.54 with blood beta-hydroxybutyrate, 0.44 with blood nonesterified fatty acids, -0.32 with blood glucose, -0.23 with milk glucose-6-phosphate, and 0.38 with milk isocitrate. In contrast, the predicted prob-ability of belonging to the mastitis group had correla-tions of 0.69 with milk lactate dehydrogenase, 0.46 with milk N-acetyl-beta-D-glucosaminidase, -0.18 with milk free glucose, and 0.16 with milk glucose-6-phosphate. Consequently, these results suggest that the obtained quantitative traits indirectly reflect some of the main health disorders in dairy farming and could be used to monitor dairy cows on a large scale. By using unsuper-vised learning on large-scale milk recording data and then validating the pattern using reference laboratory measures, we propose a new approach to quickly assess dairy cow health status.

The intestinal immune barrier is considered to be the gatekeeper of the human body and rapidly develops directly after birth. Many pre- and postnatal factors influence the development of the gut-barrier, which is composed of the microbiota, the mucus, the epithelial layer and the mucosal immune system. Even minor disturbances during barrier development can have consequences for health far into adulthood. Here we critically discuss the current knowledge on which pre- and postnatal factors influence development, maturation, and maintenance of the gut immune barrier. Human milk has a unique composition and is the gold standard for adequate development of the intestinal immune barrier. Not only the influence of human milk oligosaccharides (HMOs) but also that of glycoproteins (HMGPs) is reviewed. We discuss the influence of maternal genetic factors, such as the secretor and Lewis phenotypes on breast milk fucosylation and sialylation of HMOs and HMGPs. This diversity in HMOs and HMPGs influences microbiota composition and also the development of the immune barrier. Cow milk-derived infant formula is often being used as an alternative for human breast milk. The consequences of this for proper development of the intestinal immune barrier and, in particular, the differences in the type of oligosaccharides and glycosylation patterns (sialic and fucose composition) between cow and human milk are critically discussed. Current and prospective strategies to promote proper gut-immune maturation are proposed. These might include more personalized infant formulas when breast milk is not an option.

The role of unregulated and inappropriate dispensing, and use of antibiotics remains significant in the development of antimicrobial resistance in infectious disease endemic regions of developing countries. The exposure to antibiotics from unfamiliar and unsuspecting sources such as drinking water and food, and adulterated herbal medicines remains a cause for concern. A sensitive SPE-LC-MS/MS method was developed and validated for the quantification and qualification of 12 antibiotics, including amoxicillin, clavulanic acid, metronidazole, ampicillin, cefuroxime, tetracycline, ceftriaxone, sulphamethoxazole, trimethoprim, ciprofloxacin, benzylpenicillin, and erythromycin, in the urine of healthy volunteers. The method was linear (r(2) > 0.98) within the concentration range 50-5000 ngmL(-1) for all the analytes. Instrument precision of 8-27% and 4-21% at 100 and 1000 ngmL(-1) levels were demonstrated. High mean recoveries between 71 and 125% with minimal variations were obtained for all compounds in the accuracy study. Limits of detection and quantification ranged between 70.3-271.0 ngmL(-1) and 213-821 ngmL(-1) respectively. The validated method successfully detected and quantified 9 of the 12 analytes, with the exception of clavulanic acid, cefuroxime, and benzylpenicillin. Most of the samples contained one analyte (52, 86.7%), with a handful containing two (7, 11.7%) and three analytes (1, 1.7%). Ciprofloxacin was the modal analyte detected (17, 24.6%), with amoxicillin and trimethoprim recording the average lowest (22.76 x 10(3) ngmL(-1)) and highest concentrations (255.47 x 10(3) ngmL(-1)) respectively. The developed method is a useful tool for non-invasive monitoring of consumption and the irrational use of antibiotics in microbial resistant-prone regions of the world.

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations 1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R2 values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for negative energy status, indicated by detrimental morning blood plasma NEFA levels (>0.6 mmol/L), could be identified with a sensitivity and specificity of, respectively, 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens an opportunity for regular metabolic screening and improved resilience phenotyping. ispartof: JOURNAL OF DAIRY SCIENCE vol:103 issue:7 pages:6422-6438 ispartof: location:United States status: published

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and “intermediate cows” with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1-50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R2cv) and root mean squared error (RMSEcv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R2cv = 0.40 (95% CI: 0.29-0.50) at 14 DIM and 0.35 (0.23-0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R2cv = 0.28 (0.24-0.33) vs 0.21 (0.18-0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95% CI: 0.39-0.68) to 0.65 (0.55-0.75) for MME and 0.51 (0.37-0.65) to 0.68 (0.53-0.81) for FT-MIR. R2cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted.

Background Infrared spectral analysis of milk is cheap, fast, and accurate. Infrared light interacts with chemical bonds present inside the milk, which means that Fourier transform infrared milk spectra are a reflection of the chemical composition of milk. Heritability of Fourier transform infrared milk spectra has been analysed previously. Further genetic analysis of Fourier transform infrared milk spectra could give us a better insight in the genes underlying milk composition. Breed influences milk composition, yet not much is known about the effect of breed on Fourier transform infrared milk spectra. Improved understanding of the effect of breed on Fourier transform infrared milk spectra could enhance efficient application of Fourier transform infrared milk spectra. The aim of this study is to perform a genome wide association study on a selection of wavenumbers for Danish Holstein and Danish Jersey. This will improve our understanding of the genetics underlying milk composition in these two dairy cattle breeds. Results For each breed separately, fifteen wavenumbers were analysed. Overall, more quantitative trait loci were observed for Danish Jersey compared to Danish Holstein. For both breeds, the majority of the wavenumbers was most strongly associated to a genomic region on BTA 14 harbouring DGAT1. Furthermore, for both breeds most quantitative trait loci were observed for wavenumbers that interact with the chemical bond C-O. For Danish Jersey, wavenumbers that interact with C-H were associated to genes that are involved in fatty acid synthesis, such as AGPAT3, AGPAT6, PPARGC1A, SREBF1, and FADS1. For wavenumbers which interact with –OH, associations were observed to genomic regions that have been linked to alpha-lactalbumin. Conclusions The current study identified many quantitative trait loci that underlie Fourier transform infrared milk spectra, and thus milk composition. Differences were observed between groups of wavenumbers that interact with different chemical bonds. Both overlapping and different QTL were observed for Danish Holstein and Danish Jersey.

The aim of this study was to investigate the sources of variation of milk fatty acids (FA) routinely predicted by mid-infrared spectroscopy in Holstein-Friesian (HF), Brown Swiss (BS), Simmental (SI) and Alpine Grey (AG) cattle breeds. A linear mixed model was used to analyse the data which included 153,801 individual milk samples from 14,301 cows. Fixed effects included in the model were breed, month of sampling, year of sampling, stage of lactation, parity and first order interactions between them, and random effects were herd nested within breed, cow nested within breed and the residual error. Milk of AG cows exhibited the lowest content of saturated FA and the greatest content of unsaturated FA, whereas milk of BS had an opposite pattern. Holstein-Friesian and SI were intermediate between AG and BS breeds for all the FA except for total C18:1, which was the greatest in HF. Saturated FA, C14:0 and C16:0 increased from calving until 120 days in milk, whereas unsaturated FA and C18:1 decreased. First parity cows produced milk with lower concentration of de novo FA than multiparous animals. The greatest content of unsaturated FA and C18:1 was observed in summer, whereas saturated FA, C14:0, C16:0 and C18:0 decreased in summer and increased in winter. The differences in milk FA profile among breeds are useful for genetic selection and for feeding strategies.

This Research Communication describes the adaptation and testing of an RP-HPLC method, previously tested for the determination of lactoferrin (LF) in whey, for its applicability to determine milk lactoferrin content. Milk samples of various species, namely, ovine, caprine, bovine, donkey and human milk, were tested. The advantage of this RP-HPLC method includes speed and convenience, as it does not include extensive pretreatment or separation steps. A simple pre-treatment step was added in order to remove fat and proteins of the casein family and the samples were tested. The results varied in terms of elution of the LF peak both between the milk of the different species as well as from the initial application on whey. The peak resolution was satisfactory in the cases of ovine, bovine and donkey milk samples while for caprine and human milk an interference with other peaks was observed. Nevertheless, quantification of LF was found possible for all samples. This new application of the modified method will allow the determination of LF in milk samples of the tested species either for everyday analysis or as a useful qualitative screening for presence or absence of LF. ispartof: JOURNAL OF DAIRY RESEARCH vol:86 issue:2 pages:238-241 ispartof: location:England status: published

Milk is an important protein source in human diets, providing around 32 g protein/l (for bovine milk, which constitutes some 85% of global consumption). The most abundant milk proteins are α-lactalbumin, β-lactoglobulin, αs-casein, β-casein, and κ-casein. Besides their nutritional value, milk proteins play a crucial role in the processing properties of milk, such as solubility, water bonding, heat stability, renneting and foaming, among others. In addition, and most importantly for this review, these proteins are the main source of bioactive components in milk. Due to the wide range of proposed beneficial effects on human health, milk proteins are considered as potential ingredients for the production of health-promoting functional foods. However, most of the evidence for bioactive effects comes from in vitro studies, and there is a need for further research to fully evaluate the true potential of milk-derived bioactive factors. Animal genetics and animal nutrition play an important role in the relative proportions of milk proteins and could be used to manipulate the concentration of specific bioactive peptides in milk from ruminants. Unfortunately, only a few studies in the literature have focused on changes in milk bioactive peptides associated to animal genetics and animal nutrition. The knowledge described in the present review may set the basis for further research and for the development of new dairy products with healthy and beneficial properties for humans.

Dairy fat is one of the most complex natural fats because of its fatty acid (FA) composition. Ruminant dairy fat contains more than 400 different FA varying in carbon chain length, and degree, position and configuration of unsaturation. The following article reviews the different methods available to analyze FA (both total and free) in milk and dairy products. The most widely used methodology for separating and analyzing dairy FA is gas chromatography, coupled to a flame ionization detector (CG-FID). Alternatively, gas chromatography coupled to a mass spectrometer (GC-MS) is also used. After lipid extraction, total FA (TFA) are commonly converted into their methyl esters (fatty acid methyl esters, FAME) prior to chromatographic analysis. In contrast, free FA (FFA) can be analyzed after conversion to FAME or directly as FFA after extraction from the product. One of the key questions when analyzing FAME from TFA is the selection of a proper column for separating them, which depends mainly on the objective of the analysis. Quantification is best achieved by the internal standard method. Recently, near-infrared spectroscopy (NIRS), Raman spectroscopy (RS) and nuclear magnetic resonance (NMR) have been reported as promising techniques to analyze FA in milk and dairy products.

Red clover (Trifolium pratense L.) is the predominant legume used in northern European agriculture. Official red clover variety trials are conducted by Natural Resources Institute Finland (Luke) to determine the value of field crop varieties. The trials used for the current analysis were conducted in Luke units in southern Finland (Mikkeli) and northern Finland (Ruukki) in two consecutive years. Plant samples for isoflavone analyses were collected from four varieties grown as four replicates and harvested twice during both growing seasons. The four main isoflavones biochanin A, genistein, daidzein and formononetin were analysed using high performance liquid chromatography. Total phytoestrogen content in the varieties varied in the range of 11.2−14.8 mg g-1 dry matter (DM). The variety and the time of harvest had most effect on the isoflavone, especially formononetin, contents of red clover. A more northern growing area and challenging weather conditions were associated with increased isoflavone concentrations.

Following a request from the European Commission, the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA) was asked to deliver an opinion on whey basic protein isolate as a novel food (NF) pursuant to Regulation (EU) 2015/2283. The NF is obtained by ion exchange chromatography of skimmed cow's milk. The applicant intends to market the NF in infant and follow-on formulae and meal replacement beverages, dietary foods for special medical purposes and as food supplements. The highest estimated intake of the NF based on the proposed uses and use levels would be 24.8 mg/kg body weight (bw) per day in infants and 27.8 in toddlers. The information provided on composition, specifications, production process and stability of the NF do not raise safety concerns. Taking into account the composition of the NF and the intended use levels, the Panel considers that the consumption of the NF is not nutritionally disadvantageous. The Panel considers that there is no concern with respect to genotoxicity. The no observed adverse effect level (NOAEL) of a subchronic 13-week rat study was 2000 mg/kg bw per day. Considering the source, the production process and nature of the NF, the Panel considers the margin of exposure (MOE) of 154 to be sufficient for the adult population (on a high-estimated intake of 13 mg/kg bw). For infants and toddlers, the MOE would be at least 81 and 72, respectively. Taking into account the composition of the NF, its source, the history of consumption of the main components of the NF, the production process and that the NOAEL in a subchronic rat study was the highest dose tested the Panel considers that also the MOE for infants and toddlers are sufficient. The Panel concludes that the novel food ingredient, whey basic protein isolate, is safe under the proposed uses and use levels. (C) 2018 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.

Background Despite of the presence of sulfhydryl oxidases (SOXs) in the secretomes of industrially relevant organisms and their many potential applications, only few of these enzymes have been biochemically characterized. In addition, basic functions of most of the SOX enzymes reported so far are not fully understood. In particular, the physiological role of secreted fungal SOXs is unclear. Results The recently identified SOX from Aspergillus tubingensis (AtSOX) was produced, purified and characterized in the present work. AtSOX had a pH optimum of 6.5, and showed a good pH stability retaining more than 80% of the initial activity in a pH range 4-8.5 within 20 h. More than 70% of the initial activity was retained after incubation at 50 °C for 20 h. AtSOX contains a non-covalently bound flavin cofactor. The enzyme oxidised a sulfhydryl group of glutathione to form a disulfide bond, as verified by nuclear magnetic resonance spectroscopy. AtSOX preferred glutathione as a substrate over cysteine and dithiothreitol. The activity of the enzyme was totally inhibited by 10 mM zinc sulphate. Peptide- and protein-bound sulfhydryl groups in bikunin, gliotoxin, holomycin, insulin B chain, and ribonuclease A, were not oxidised by the enzyme. Based on the analysis of 33 fungal genomes, SOX enzyme encoding genes were found close to nonribosomal peptide synthetases (NRPS) but not with polyketide synthases (PKS). In the phylogenetic tree, constructed from 25 SOX and thioredoxin reductase sequences from IPR000103 InterPro family, AtSOX was evolutionary closely related to other Aspergillus SOXs. Oxidoreductases involved in the maturation of nonribosomal peptides of fungal and bacterial origin, namely GliT, HlmI and DepH, were also evolutionary closely related to AtSOX whereas fungal thioreductases were more distant. Conclusions AtSOX (55 kDa) is a fungal secreted flavin-dependent enzyme with good stability to both pH and temperature. A Michaelis-Menten behaviour was observed with reduced glutathione as a substrate. Based on the location of SOX enzyme encoding genes close to NRPSs, SOXs could be involved in the secondary metabolism and act as an accessory enzyme in the production of nonribosomal peptides. Electronic supplementary material The online version of this article (10.1186/s12858-017-0090-4) contains supplementary material, which is available to authorized users.

Plasmin is a protease in milk, which concentration is increased during mastitis. The aim of the study was design and characterize short, tailor made fluorogenic substrates for plasmin to see differences in plasmin activity in healthy milk compared to mastitic milk. According to the specificity matrix of plasmin, containing 125 currently known plasmin substrates, six novel plasmin specific substrates were designed and characterized. Eight other substrates were insensitive for plasmin, which was in line with our expectations. The plasmin-sensitive substrates showed no cross-reactivity with proteases from mastitogenic bacteria in vitro. A proof of concept to distinguish healthy milk from mastitic milk is described. Potentially, these substrates present a rapid alternative to the currently established methodologies to detect mastitis in milk.

We have developed a rapid mastitis detection test based on the immobilization of tag-specific antibody molecules, the binding of double-tagged amplicons, and as a secondary signal a conjugate of black carbon nanoparticles having molecules of a fusion protein of neutrAvidin and alkaline phosphatase at their surface. The antibodies were inkjet printed onto three different nitrocellulose membrane slides, Unisart (Sartorius), FAST (GE Whatman), and Oncyte-Avid (Grace-Biolabs), and the final assay signals on these slides were compared. The blackness of the spots was determined by flatbed scanning and assessment of the pixel gray volume using TotalLab image analysis software. The black spots could be easily read by the naked eye. We successfully demonstrated the detection of specific amplicons from mastitis-causing pathogens in less than 3 h. Using a similar protocol, we also showed that it was possible to detect specific amplicons from four different mastitis-causing pathogens (six strains) on the same pad. The influence of two different printing buffers, phosphate-buffered saline (pH 7.4) and carbonate buffer (pH 9.6), on the functionality of the primary antibodies was also compared.

The aim of this study was to estimate breed differences in milk fatty acid (FA) profile among 5 dairy cattle breeds present in the Netherlands: Holstein-Friesian (HF), Meuse-Rhine-Yssel (MRY), Dutch Friesian (DF), Groningen White Headed (GWH), and Jersey (JER). For this purpose, total fat percentage and detailed FA contents in milk (14 individual FA and 14 groups of FA) predicted from mid-infrared spectra were used. Mid-infrared spectrometry profiles were collected during regular milk recording from a range of herds with different combinations of breeds, including both purebred and crossbred cows. The data set used for the analyses contained 41,404 records from a total of 24,445 cows. In total 7,626 cows were crossbreds belonging to the breeds HF, MRY, DF, GWH, and JER; 1,769 purebreds (≥87.5%) belonging to the breeds MRY, DF, GWH, and JER; and the other 15,050 cows were HF. Breed effects were estimated using a single-trait animal model. The content in milk of short-chain FA C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, and C16:0 was higher for JER and the content in milk of C16:0 was lower for GWH compared with the other breeds; when adjusting for breed differences in fat percentage, however, not all breed differences were significant. Breed differences were also found for cis-9 C14:1, cis-9 C16:1, C18:0, and a number of C18 unsaturated FA. In general, differences in fat composition in milk between HF, MRY, and DF were not significant. Jerseys tended to produce more saturated FA, whereas GWH tended to produce relatively less saturated FA. After adjusting for differences in fat percentage, breed differences in detailed fat composition disappeared or became smaller for several short- and medium-chain FA, whereas for several long-chain unsaturated FA, more significant breed differences were found. This indicates that short- and medium-chain FA are for all breeds more related to total fat percentage than long-chain FA. In conclusion, between breed differences were found in detailed FA composition and content of individual FA. Especially, for FA produced through de novo synthesis (short-chain FA, C12:0, C14:0, and partly C16:0) differences were found for JER and GWH, compared with the breeds HF, MRY, and DF.

Penicillins are used universally in both human and veterinary medicine. The European Union (EU) has established maximum residue levels (MRLs) for most ss-lactam antibiotics in milk and animal tissues and included them in the National Residue Monitoring Programs. In this study, a novel method is described for the determination and confirmation of eight penicillins in porcine tissues, milk and animal feed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). To prevent degradation of penicillin residues during workup, a derivatisation procedure was developed, by which penicillins were converted to stable piperidine derivatives. Deuterated piperidine derivatives were synthesised for all relevant penicillins, enabling the use of isotope dilution for accurate quantification. Penicillin residues were derivatised in the crude extract with piperidine and isolated using solid-phase extraction. The penicillin piperidine derivatives were determined by LC-MS/MS. The method was validated at the current MRLs, which range from 25-300 microg kg(-1) in muscle and kidney to 4-30 microg kg(-1) in milk as well as at the target value of 100 microg kg(-1) chosen for animal feed, according to the EU requirements for a quantitative confirmatory method. Accuracy ranged from 94-113% (muscle), 83-111% (kidney) and 87-103% (milk) to 88-116% (animal feed). Intra-day precision (relative standard deviation (RSD)(r)) ranged from 5-13% (muscle, n = 18), 4-17% (kidney, n = 7) and 5-18% (milk, n = 7) to 11-32% (animal feed, n = 18). Inter-day precision (RSD(RL), n = 18) ranged from 6-23% (muscle) to 11-36% (animal feed). From the results, it was concluded that the method was fit for purpose at the target MRLs in animal tissue and target levels for animal feed.

With regard to human health aspects of milk fat, increasing the amount of unsaturated fatty acids in milk is an important selection objective. The cow's diet has an influence on the degree of unsaturation, but literature suggests that genetics also plays a role. To estimate genetic variation in milk fatty acid unsaturation indices, milk fatty acid composition of 1,933 Dutch Holstein Friesian heifers was measured and unsaturation indices were calculated. An unsaturation index represents the concentration of the unsaturated product proportional to the sum of the unsaturated product and the saturated substrate. Intraherd heritabilities were moderate, ranging from 0.23 +/- 0.07 for conjugated linoleic acid (CLA) index to 0.46 +/- 0.09 for C16 index. We genotyped the cows for the SCD1 A293V and DGAT1 K232A polymorphisms, which are known to alter milk fatty acid composition. Both genes explain part of the genetic variation in unsaturation indices. The SCD1 V allele is associated with lower C10, C12, and C14 indices, and with higher C16, C18, and CLA indices in comparison to the SCD1 A allele, with no differences in total unsaturation index. In comparison to the DGAT1 K allele, the DGAT1 A allele is associated with lower C10, C12, C14, and C16 indices and with higher C18, CLA, and total indices. We conclude that selective breeding can contribute to higher unsaturation indices, and that selective breeding can capitalize on genotypic information of both the SCD1 A293V and the DGAT1 K232A polymorphism.

The fatty acid (FA) composition of cows milk has become less favorable to human health in the last four decades due to changed feeding and management practices, notably higher proportions of concentrates and silages in diets with less grazing. Essential FA and conjugated linoleic acid (CLA) concentrations have generally declined and, with more `low-fat¿ dairy products, human intake of these FA has declined even further since ruminant food products are the main source of human CLA intake. Changing societal drivers and consumer demands require dairy production systems that provide food products through sustainable production systems. Milk FA were examined in milk produced in different regions of the world, in the different seasons of the year, and under different feeding systems. FA levels were examined in forages, concentrates and milk. Milk from cows fed fresh green forage, especially those grazing grass, had a much higher unsaturated:saturated FA proportion, with more polyunsaturated FA and more CLA (in particular C18:2 cis-9, trans-11), than milk from silage-fed cows. Farmers from some dairy cooperatives in The Netherlands that produce milk from grazed grass now receive a premium payment in addition to the base milk price, so that primary producers can benefit from the higher market value at the end of the production chain.

Two experiments were conducted to evaluate the effects on milk composition of transition from a fresh grass diet on pasture to a winter diet of mixed grass/maize silage. In trial 1, the change in milk fatty acid profile for six dairy cows in mid-lactation was followed via analysis of milk samples collected from individual cows on days 0, 2, 6 and 14 after the transition of diet. In trial 2, milk of 12 cows was analysed on days 0 and 4 after transition. In trial 1, dry matter intake and milk production did not change during the experiment. After transition, the average milk fat content increased from 43.7 g/kg on day 0 to 54.9 g/kg on day 14 and the milk fatty acid composition altered within two days. The largest changes occurred in the proportions of C 14:0 (from 89 g/kg milk fat on day 0 to 117 g/kg on day 14), C 16:0 (226-348 g/kg), C18:0 (110-88 g/kg) and C18:1 cis-9 (238-170 g/kg). The average content of conjugated linoleic acid (CLA) decreased from 24.3 g/kg milk fat on day 0 to 4.4 g/kg on day 14, while the proportion of the beneficial n-7 fatty acid (FA) rumenic acid declined from 0.95 to 0.85 of total CLA. Vaccenic acid contents decreased linearly with CLA contents. Two days after transition large changes had occurred, whereas the changes between day 6 and day 14 were relatively small. These results were confirmed by the results of trial 2, which also indicated that most changes actually took place within four days after transition. The milk fatty acid profile of grazing cows was more favourable from a consumer health perspective than that of silage-fed cows. (C) 2004 Elsevier B.V. All rights reserved.

Despite its low natural folate concentration, milk is responsible for 10-15% of the daily folate intake in countries with a high dairy consumption. Milk products can be considered as a potential matrix for folate fortification, e.g., with synthetic folic acid, to enhance the daily intake of folate. In untreated milk, the natural folate, 5-methyltetrahydrofolate (5-CH3-H(4)folate), is bound to folate-binding proteins (FBP). In this study, the extent of binding to FBP for folic acid and 5-CH3-H(4)folate was investigated in a dynamic in vitro model simulating human gastric passage. Protein binding of folic acid and 5-CH3-H(4)folate was characterized using gel-exclusion chromatography. Before gastric passage, folic acid and 5-CH3-H(4)folate were bound mainly to FBP (76-79%), whereas 7% was free. Folic acid remained bound to FBP to a similar extent after gastric passage. For 5-CH3-H(4)folate, the FBP-bound fraction gradually decreased from 79 to 5% and the free fraction increased from 7 to 93%. Although folic acid enters the proximal part of the intestine bound to FBP, 5-CH3-H(4)folate appears to be present mainly as free folate in the duodenal lumen. The stability of FBP was similar in both folate/FBP mixtures, i.e., 70% of the initial FBP content was retained after gastric passage. This study indicated that FBP are partly stable during gastric passage but have different binding characteristics for folic acid and 5-CH3-H(4)folate in the duodenal lumen. This could result in different bioavailability from folic acid- and 5-CH3-H(4)folate-fortified milk products.

Casein phosphorylation is a posttranslational modification catalyzed by kinase enzymes that attach phosphate groups to specific AA in the protein sequence. This modification is one of the key factors responsible for the stabilization of calcium phosphate nanoclusters in casein micelles and for the internal structure of the casein micelles. α(S1)-Casein (α(s1)-CN) is of special interest because it constitutes up to 40% of the total casein fraction in milk, and it has 2 common phosphorylation states, with 8 (α(S1)-CN-8P) and 9 (α(S1)-CN-9P) phosphorylated serine residues. Factors affecting this variation in the degree of phosphorylation are not currently known. The objective of this research was to determine the genetic background of α(S1)-CN-8P and α(S1)-CN-9P. The genetic and phenotypic correlation between α(S1)-CN-8P and α(S1)-CN-9P was low (0.18 and 0.19, respectively). This low genetic correlation suggests a different genetic background. These differences were further investigated by means of a genome-wide association study, which showed that both α(S1)-CN-8P and α(S1)-CN-9P were affected by a region on Bos taurus autosome (BTA) 6, but only α(S1)-CN-8P was affected by a region on BTA11 that contains the gene that encodes for β-lactoglobulin (β-LG), and only α(S1)-CN-9P was affected by a region on BTA14 that contains the diacylglycerol acyltransferase 1 (DGAT1) gene. Estimated effects of β-LG protein genotypes showed that only α(S1)-CN-8P was associated with the β-LG A/B polymorphism (g.1772G>A and g.3054C>T); the AA genotype of β-LG was associated with a lower concentration of α(S1)-CN-8P (-0.32% wt/wt) than the BB genotype (+0.41% wt/wt). Estimated effects of DGAT1 K232A genotypes showed that only α(S1)-CN-9P was associated with the DGAT1 gene polymorphism; DGAT1 AA genotype was associated with a higher α(S1)-CN-9P concentration (+0.53% wt/wt) than the DGAT1 KK genotype (-0.44% wt/wt). The results give insight in phosphorylation of α(S1)-CN-8P and α(S1)-CN-9P, which seem to be regulated by a different set of genes.

Whey permeate is a co-product obtained when cheese whey is passed through an ultrafiltration membrane to concentrate whey proteins. Whey proteins are retained by the membrane, whereas the low-molecular weight compounds such as lactose, salts, oligosaccharides and peptides pass through the membrane yielding whey permeate. Research shows that bovine milk from healthy cows contains hundreds of naturally occurring peptides – many of which are homologous with known antimicrobial and immunomodulatory peptides – and nearly 50 oligosaccharide compositions (not including structural isomers). As these endogenous peptides and oligosaccharides have low-molecular weight and whey permeate is currently an under-utilized product stream of the dairy industry, we hypothesized that whey permeate may serve as an inexpensive source of naturally occurring functional peptides and oligosaccharides. Laboratory fractionation of endogenous peptides and oligosaccharides from bovine colostrum sweet whey was expanded to pilot-scale. The membrane fractionation methodology used was similar to the methods commonly used industrially to produce whey protein concentrate and whey permeate. Pilot-scale fractionation was compared to laboratory-scale fractionation with regard to the identified peptides and oligosaccharide compositions. Results were interpreted on the basis of whether industrial whey permeate could eventually serve as a source of functional peptides and oligosaccharides. The majority (96%) of peptide sequences and the majority (96%) of oligosaccharide compositions found in the laboratory-scale process were mirrored in the pilot-scale process. Moreover, the pilot-scale process recovered an additional 33 peptides and 1 oligosaccharide not identified from the laboratory-scale extraction. Both laboratory- and pilot-scale processes yielded peptides deriving primarily from the protein ß-casein. The similarity of the laboratory- and pilot-scale's resulting peptide and oligosaccharide profiles demonstrates that whey permeate can serve as an industrial-scale source of bovine milk peptides and oligosaccharides.

A centripetal temperature gradient takes place in Grana Padano (GP) during moulding because of the slow heat transfer within the cheese and the fast cooling of the outer part. This gradient, in combination with the low pH value, induces a centripetal inactivation of alkaline phosphatase (ALP). Throughout the ripening process, the activity of the enzyme keeps > 3 10(5) mU/kg cheese in the peripheral zones and

Since the 1980s, efforts have been made to develop sensors that measure a parameter from an individual cow. The development started with individual cow recognition and was followed by sensors that measure the electrical conductivity of milk and pedometers that measure activity. The aim of this review is to provide a structured overview of the published sensor systems for dairy health management. The development of sensor systems can be described by the following 4 levels: (I) techniques that measure something about the cow (e.g., activity); (II) interpretations that summarize changes in the sensor data (e.g., increase in activity) to produce information about the cow’s status (e.g., estrus); (III) integration of information where sensor information is supplemented with other information (e.g., economic information) to produce advice (e.g., whether to inseminate a cow or not); and (IV) the farmer makes a decision or the sensor system makes the decision autonomously (e.g., the inseminator is called). This review has structured a total of 126 publications describing 139 sensor systems and compared them based on the 4 levels. The publications were published in the Thomson Reuters (formerly ISI) Web of Science database from January 2002 until June 2012 or in the proceedings of 3 conferences on precision (dairy) farming in 2009, 2010, and 2011. Most studies concerned the detection of mastitis (25%), fertility (33%), and locomotion problems (30%), with fewer studies (16%) related to the detection of metabolic problems. Many studies presented sensor systems at levels I and II, but none did so at levels III and IV. Most of the work for mastitis (92%) and fertility (75%) is done at level II. For locomotion (53%) and metabolism (69%), more than half of the work is done at level I. The performance of sensor systems varies based on the choice of gold standards, algorithms, and test sizes (number of farms and cows). Studies on sensor systems for mastitis and estrus have shown that sensor systems are brought to a higher level; however, the need to improve detection performance still exists. Studies on sensor systems for locomotion problems have shown that the search continues for the most appropriate indicators, sensor techniques, and gold standards. Studies on metabolic problems show that it is still unclear which indicator reflects best the metabolic problems that should be detected. No systems with integrated decision support models have been found. Key words: automated

In this study, the effect of antibody adsorption on physicochemical properties of Streptococcus sobrinus was studied. Bacteria were preincubated with polyclonal antibodies or with OMVU10, a monoclonal antibody (MAb) reactive with S. sobrinus. The zeta potentials and the hydrophobicity as determined by microbial adhesion to hydrocarbons were measured in potassium phosphate buffer with a pH ranging from 2 to 9, S. sobrinus preincubated with polyclonal antibodies was positively charged at pH 2, 3, and 4 and had an isoelectric point at pH 4.8. Untreated S. sobrinus cells or cells preincubated with MAbs were negatively charged over the whole pH range. X-ray photoelectron spectroscopy showed a decrease in O/C and P/C ratios for bacteria preincubated with polyclonal antibodies. A combination of the pH-dependent zeta potential and the X-ray photoelectron spectroscopy data of the overall chemical composition of the cell surface suggests that polyclonal antibody adsorption occurs through blocking of surface phosphate. The measurement of hydrophobicity by microbial adhesion to hydrocarbons revealed that S. sobrinus preincubated with polyclonal antibodies was hydrophobic (90% of the bacteria bound to hexadecane), whereas the controls were relatively hydrophilic. S. sobrinus preincubated with OMVU10 was found to be more hydrophobic than the controls at pH 5 and 7. Hydrophobicity as measured by water contact angles shelved an increase in hydrophohicity when S. sobrinus was preincubated with polyclonal antibodies. The epitopes to which the antibodies are directed were visualized by immunogold labeling and electron microscopy. The results suggested that OMVU10 is reactive with only a few epitopes of the cell surface, whereas polyclonal antibodies were found to be reactive with many epitopes. In conclusion, adsorption of polyclonal antibodies was found to influence the overall physicochemical surface properties of the organism, probably by forming a coating over the whole cell surface. Adsorption of MAbs was more localized, which could explain their lesser influence on these surface properties.

Chantier qualité GA; Mastitis, an inflammation of the mammary gland, is the most costly infectious disease of dairy ruminants worldwide. Although it receives considerable attention, the early steps of the host response remain poorly defined. Here, we report a noninvasive method using milk fat globules (MFG) as a source of mammary RNA to follow the dynamics of the global transcriptional response of mammary epithelial cells (MEC) during the course of a bacterial infection. We first assessed that RNA isolated from MFG were representative of MEG RNA; we then evaluated whether MFG RNA could be used to monitor the MEG response to infection. Sufficiently high yields of good-quality RNA (RNA integrity numbers ranging between 6.7 and 8.7) were obtained from goat MFG for subsequent analyses. Contamination of MFG by macrophages and neutrophils, which can be trapped during creaming, was assessed and when using quantitative real-time PCR for cell-type specific markers, was shown to be weak enough (

Background Identifying genomic regions, and preferably individual genes, responsible for genetic variation in milk fat composition of bovine milk will enhance the understanding of biological pathways involved in fatty acid synthesis and may point to opportunities for changing milk fat composition via selective breeding. An association study of 50,000 single nucleotide polymorphisms (SNPs) was performed for even-chain saturated fatty acids (C4:0-C18:0), even-chain monounsaturated fatty acids (C10:1-C18:1), and the polyunsaturated C18:2cis9,trans11 (CLA) to identify genomic regions associated with individual fatty acids in bovine milk. Results The two-step single SNP association analysis found a total of 54 regions on 29 chromosomes that were significantly associated with one or more fatty acids. Bos taurus autosomes (BTA) 14, 19, and 26 showed highly significant associations with seven to ten traits, explaining a relatively large percentage of the total additive genetic variation. Many additional regions were significantly associated with the fatty acids. Some of the regions harbor genes that are known to be involved in fat synthesis or were previously identified as underlying quantitative trait loci for fat yield or content, such as ABCG2 and PPARGC1A on BTA 6; ACSS2 on BTA 13; DGAT1 on BTA 14; ACLY, SREBF1, STAT5A, GH, and FASN on BTA 19; SCD1 on BTA26; and AGPAT6 on BTA 27. Conclusions Medium chain and unsaturated fatty acids are strongly influenced by polymorphisms in DGAT1 and SCD1. Other regions also showed significant associations with the fatty acids studied. These additional regions explain a relatively small percentage of the total additive genetic variance, but they are relevant to the total genetic merit of an individual and in unraveling the genetic background of milk fat composition. Regions identified in this study can be fine mapped to find causal mutations. The results also create opportunities for changing milk fat composition through breeding by selecting individuals based on their genetic merit for milk fat composition.

International audience; The aim of this work was to evaluate the effect of intramammary infection (IMI) on the endogenous proteolysis of milk. Four control checks were carried out in the half-udder milk of 10 ewes that acquired unilateral subclinical mastitis. Two of these checks were conducted before the infection was established and 2 after. Ten healthy ewes were tested as a control group. The presence of a subclinical IMI involved an increase of the products of casein hydrolysis, the proteose-peptone (p-p) fraction and minor (m) caseins, and a decrease of beta-casein. As a result, a significant increase in the proteolysis index (PI), calculated as the ratio of m-casein to the sum of caseins (alpha + beta + kappa), took place. a-Casein and K-casein were not significantly affected by IMI. Correlations confirmed the scenario: log(10) of somatic cell count (SCC) was positively correlated with p-p content and negatively with beta-casein, whereas log(10) SCC was not correlated with alpha-casein or kappa-casein. On the other hand, p-p content was positively correlated with m-casein and PI and negatively with beta-casein, but no correlation was detected between p-p content and alpha- or kappa-casein. Furthermore, between casein fractions, m-casein was only significantly correlated with beta-casein. These results suggest that use of indices of proteolysis of caseins such as p-p, m-casein, and PI, could be applied together with SCC to evaluate the cheese-making quality of milk.

Our objective was to perform a genome-wide association study for content in bovine milk of α(S1)-casein (α(S1)-CN), α(S2)-casein (α(S2)-CN), β-casein (β-CN), κ-casein (κ-CN), α-lactalbumin (α-LA), β-lactoglobulin (β-LG), casein index, protein percentage, and protein yield using a 50K single nucleotide polymorphism (SNP) chip. In total, 1,713 Dutch Holstein-Friesian cows were genotyped for 50,228 SNP and a 2-step association study was performed. The first step involved a general linear model and the second step used a mixed model accounting for all family relationships. Associations with milk protein content and composition were detected on 20 bovine autosomes. The main genomic regions associated with milk protein composition or protein percentage were found on chromosomes 5, 6, 11, and 14. The number of chromosomal regions showing significant (false discovery rate

In this study, 154 Staphylococcus aureus isolates were detected from 1070 food samples (14.4%) collected from seven cities in Turkey. Antimicrobial susceptibility testing against 21 antibiotics was performed by agar disk diffusion method, and those isolates resistant to any antibiotic were further analyzed to determine minimum inhibitory concentration by E-test and polymerase chain reaction analysis of vanA and mecA genes. According to disk diffusion test results, a total of 139 strains were resistant to at least one tested antibiotic, with 39 (25.3%) strains being multidrug resistant (MDR) and the other 15 strains being susceptible to all antibiotics. Penicillin G, linezolid, erythromycin, and tetracycline took up 71.4%, 23.4%, 18.2%, and 15.6% of the tested strains, respectively. In addition, all of the strains were susceptible to vancomycin, oxacillin, cefoxitin, and imipenem. Only one strain (S158B) was resistant to both teicoplanin and cefazolin. On the other hand, the presence of vanA and mecA genes was not detected in the strains. Pulsed-field gel electrophoresis analysis was used to identify genetic-relatedness of the MDR strains. It is noteworthy that some strains from different sources showed 100% homology; however, some of MDR strains were found unrelated with 60% or less homology. The high diversity observed in pulsed-field gel electrophoresis results indicated the possible contamination of S. aureus from different sources and routes., The Scientific and Technological Research Council of Turkey (Turkey) (Project number:107T266)

Defense mechanisms of dairy cows against diseases partly rest on their naturally present disease resistance capacity. Natural antibodies (NAb) form a soluble part of the innate immune system, being defined as antibodies circulating in animals without prior intentional antigenic stimulation. Genetic selection on NAb titers in milk, therefore, might improve disease resistance. We estimated genetic parameters of NAb titers binding lipopolysaccharide, lipoteichoic acid (LTA), peptidoglycan, and keyhole limpet hemocyanin, and titers of the NAb isotypes IgG1, IgM, and IgA binding LTA in milk of Dutch Holstein-Friesian heifers. Natural antibody titers were measured in 1 milk sample from each of 1,939 Holstein-Friesian heifers and used for estimating genetic parameters of NAb titers. The data show that phenotypic variation exists among heifers in NAb titers binding lipopolysaccharide, LTA, peptidoglycan, and keyhole limpet hemocyanin, and the NAb isotypes IgG1, IgM, and IgA binding LTA in milk. High genetic correlations among NAb (ranging from 0.45 to 0.99) indicated a common genetic basis for the levels of different NAb in bovine milk. Intra-herd heritability estimates for NAb ranged from 0.10 to 0.53. The results indicated that NAb levels have potential for genetic selection.

Selective breeding can change milk protein composition to improve the manufacturing properties of milk. However, the effects of such breeding strategies on other economically important traits should be investigated before implementation. The objectives of this study were to examine the association between cow fertility traits and (1) milk protein composition and (2) milk protein variants (β-lactoglobulin, β-casein, κ-casein, and β-κ-casein) in commercial Dutch Holstein-Friesian cattle. Data on 1,644 first-lactation cows were analyzed by fitting linear mixed models. Greater relative concentration of α(S1)-casein within total milk protein had a positive phenotypic relationship with nonreturn rates and calving rate after first insemination. Furthermore, results showed virtually no significant relationship between cow fertility and concentration of other milk proteins or milk protein variants. Results of this study can be used to assess the correlated effects of breeding for improved milk protein composition on reproduction, thereby allowing for better evaluation of breeding programs before implementation. Our findings suggest that selecting cows based on milk protein composition or milk protein variants for improved manufacturing properties would have no negative influence on reproductive performance.

Studies have reported genetic variation in milk urea nitrogen (MUN) between cows, suggesting genetic differences in nitrogen efficiency between cows. In this paper, the results of a genome-wide scan to identify quantitative trait loci (QTL) that contribute to genetic variation in MUN and MUN yield are presented. Two to 3 morning milk samples were taken from 1,926 cows, resulting in 5,502 test-day records. Test-day records were corrected for systematic environmental effects using a repeatability animal model. Averages of corrected phenotypes of 849 cows, belonging to 7 sire families, were used in an across-family multimarker regression approach to detect QTL. Animals were successfully genotyped for 1,341 single nucleotide polymorphisms. The QTL analysis resulted in 4 chromosomal regions with suggestive QTL: Bos taurus autosomes (BTA) 1, 6, 21, and 23. On BTA 1, 2 suggestive QTL affecting MUN were detected at 60 and 140 cM. On BTA 6, 1 suggestive QTL affecting both MUN and MUN yield was detected at 103 cM. On BTA 21, 1 suggestive QTL affecting MUN yield was detected at 83 cM. On BTA 23, 1 suggestive QTL affecting MUN was detected at 54 cM. Quantitative trait loci for MUN and MUN yield were suggestive and each explained between 2 and 3% of the phenotypic variance.

The objective of this study was to assess qualitatively, through a participatory approach, the potential for increasing the value added in the Dutch dairy production chain. A workshop involving stakeholders and experts in the Dutch dairy sector developed three scenarios, envisioned according to the strategic interests of the dairy chain in the Netherlands. These scenarios address major trends including changing consumer preferences, increasing pressure for more cost-efficient production, and rising environmental concerns. The scenarios indicate different directions in which the dairy chain in the Netherlands might develop in the next 5 to 20 years. The first scenario envisions the prevalence of producing differentiated raw milk with enhanced health or improved manufacturing properties. The second scenario envisions a dairy chain that is reduced to producing fresher and more individually customized dairy products with improved shelf life. The third scenario envisions ecologically sustainable dairy farming with improved animal welfare. These scenarios show that when improving the dairy sector it is important to consider the entire chain, and hence concerted and co-ordinated actions by the various stakeholders are necessary. Further studies quantifying the consequences of different scenario settings are necessary.

Recently, selective breeding was proposed as a means of changing the fatty acid composition of milk to improve its nutritional quality. Before implementing such breeding objectives, effects on other economically important traits should be investigated. The objectives of this study were to examine 1) the effect of milk fat composition, and 2) the effect of polymorphisms of DGAT1 and SCD1 genes on female fertility in commercial Dutch Holstein-Friesian cattle. Data on 1,745 first-lactation cows were analyzed by fitting linear mixed models. We found that higher concentrations of trans fatty acids within total milk fat negatively affected reproductive performance. Furthermore, results suggested a potential effect of the DGAT1 polymorphism on nonreturn rates for insemination 28 and 56 d after the first service. Our results can be used to assess the correlated effects of breeding for improved milk fat composition on reproduction, thereby allowing for better evaluation of breeding programs before implementation.

The objective of this study was to estimate genetic parameters for major milk proteins. One morning milk sample was collected from 1,940 first-parity Holstein-Friesian cows in February or March 2005. Each sample was analyzed with capillary zone electrophoresis to determine the relative concentrations of the 6 major milk proteins. The results show that there is considerable genetic variation in milk protein composition. The intraherd heritabilities for the relative protein concentrations were high and ranged from 0.25 for beta-casein to 0.80 for beta-lactoglobulin. The intraherd heritability for the summed whey fractions (0.71) was higher than that for the summed casein fractions (0.41). Further, there was relatively more variation in the summed whey fraction (coefficient of variation was 11% and standard deviation was 1.23) compared with the summed casein fraction (coefficient of variation was 2% and standard deviation was 1.72). For the caseins and alpha-lactalbumin, the proportion of phenotypic variation explained by herd was approximately 14%. For beta-lactoglobulin, the proportion of phenotypic variation explained by herd was considerably lower (5%). Eighty percent of the genetic correlations among the relative contributions of the major milk proteins were between -0.38 and +0.45. The genetic correlations suggest that it is possible to change the relative proportion of caseins in milk. Strong negative genetic correlations were found for beta-lactoglobulin with the summed casein fractions (-0.76), and for beta-lactoglobulin with casein index (-0.98). This study suggests that there are opportunities to change the milk protein composition in the cow's milk using selective breeding.

The objective of this study was to estimate genetic parameters for major milk fatty acids and milk production traits. One morning milk sample was collected from 1,918 Holstein-Friesian heifers located in 398 commercial herds in the Netherlands. Each sample was analyzed for total percentages of fat and protein, and for detailed fatty acid percentages (computed as fatty acid weight as a proportion of total fat weight). Intraherd heritabilities were high for C4:0 to C16:0, ranging from 0.42 for C4:0 to 0.71 for C10:0. Saturated and unsaturated C18 fatty acids had intraherd heritability estimates of approximately 0.25, except for C18:2 cis-9, trans-11, which was 0.42. Standard errors of the heritabilities were between 0.07 and 0.12. Genetic correlations were high and positive among C4:0 to C14:0, as well as among unsaturated C18, but correlations of C4:0 to C14:0 with unsaturated C18 were generally weak. The genetic correlation of C16:0 with fat percentage was positive (0.65), implying that selection for fat percentage should result in a correlated increase of C16:0, whereas unsaturated C18 fatty acids decreased with increasing fat percentage (¿0.74). Milk fat composition can be changed by means of selective breeding, which offers opportunities to meet consumer demands regarding health and technological aspects.