Hasil untuk "Dairying"

Aqeel A. Qraidi, Muslim Ashor Al-etby, Aqeel Alyousuf et al.

A molecular diagnosis study was conducted on termite insect that invades palm trees. BLAST results showed that most of the samples were matched to the Microserotermes sp. with accession number KY224717.1, except one sample matched with Amitermes desertorum and Amitermes vilis with accession number KU523914.1, KU523912.1, respectively which is Garma-2 with query cover reaching 95.73% , 95.445 respectively. The results of the similarity and likelihood algorithm analysis showed the emergence of two main clusters, the first cluster includes taxa samples of the Microcerotermes diversus species with a taxa from the National Gene Bank (KY224717.1) for comparison, the second cluster includes the taxa from Gurma-2 region, which was morphologically classified as Amitermes vilis, with the comparison taxa from the National Gene Bank (KU523914.1) as out group (O.G) with a divergence branch length 0.06357. In general, the sequences of the cytochrome c oxidase (COXII) gene of the studied samples matched the sequences of the standard recorded samples in US GenBank with a matching rate of more than 97%, but some samples in phylogenetic tree showed a difference, as they gave a subcluster, which is an indicator of the development of a new subspecies or another species in the future perhaps.

G. Mazon, J.M.V. Pereira, K. Nishihara et al.

ABSTRACT: This study evaluated the effects of an oral probiotic capsule containing a live culture of Megasphaera elsdenii NCIMB 41125 on performance, feeding behavior, rumen pH and VFA concentration, and development of dairy-beef crossbred calves. Thirty-one male dairy-beef crossbred calves (Holstein × Angus; mean ± SD; 45.3 ± 7.1 kg; 8.2 ± 2.0 d old) were enrolled in a blinded, 76-d randomized trial. Calves were randomly assigned to one of 3 treatments: placebo, probiotic capsule administration on d 15, or probiotic capsule on d 15 plus a second capsule on d 39 of the study. Calves were housed individually with ad libitum access to water and calf starter and were fed 7 L/d of milk replacer (1,050 g of powder/d) in 2 meals until d 41, then 3.5 L/d in 2 meals until weaning on d 56. Behavioral observations were recorded in 1-min intervals using a wall-mounted camera. Rumen fluid samples were collected on d 14, 35, 49, 58, and 70, and analyzed for pH and VFA. Upon euthanasia on d 77, forestomach weights were recorded and rumen papillae dimensions were measured. Mixed linear models were used for statistical analysis. Probiotic treatment resulted in greater daily solid feed DMI and ADG, particularly during weaning and postweaning periods. Additionally, probiotic-treated calves spent more time drinking water and tended to have lower rumen pH compared with control calves. Empty rumen weight and papillae area were greater in calves supplemented with the probiotic capsule on d 15 compared with the other treatments. These findings suggest that preweaning M. elsdenii supplementation enhances performance and rumen development in dairy-beef crossbred calves. However, the effects of timing and number of capsule applications on rumen development and calf performance should be further investigated. Further research should also investigate the probiotic's effect on the rumen microbiome and fermentation dynamics throughout the rearing period using detailed microbiome analysis.

Simon J.R. Woodward, Lydia J. Farrell, Chris R. Burke et al.

ABSTRACT: The health, welfare, and production impacts of heat stress are of increasing concern to dairy farmers. For cows grazing pasture, solar radiation is a key driver of heat stress load, and provision of shade (e.g., trees) is a primary mitigation option. To date, research on shade use choices by dairy cows has been limited to small-scale observation-based studies, and analysis at a commercial scale using sensor-derived data using machine learning has not been attempted. This study quantified the availability and use of shade at a herd level using cow global positioning system location data from herds of lactating dairy cows grazing pasture for 1 month in summer on 4 farms in the North Island of New Zealand, along with 15-min weather data and software that predicts potential shaded areas from aerial light detection and ranging imagery. Farms ranged from 60 to 400 ha of flat to rolling terrain. Cow shade use was quantified as the percentage of cows in shade above what would be expected from independent random walking and was modeled using 9 contrasting machine learning approaches. Shade use was found to be predictable and dependent on several interacting variables. Shade use increased when solar radiation exceeded 2 MJ/m2 per hour, provided at least 1.3 m2 of shade was available per cow, especially when air temperature exceeded 24°C and wind speed was less than 4.2 m/s. These results can be applied to historic or forecast weather data to help farmers make informed decisions about investment in shade resources or to maximize the use of existing resources.

M.Q. Zhang, S. Heirbaut, K. Hertogs et al.

ABSTRACT: Interactions among metabolic, oxidative, and inflammatory states are expected to influence cow health and physiology during the transition period. However, the interrelation remains to be elucidated. In this study, 66 lactations from 57 individual multiparous Holstein Friesian cows with a complete profile of oxidative and inflammatory status-related variables at both −7 and 21 d relative to calving were involved under similar transition management. Blood samples were collected at −7 (7 d before the expected calving date) and 3, 6, 9, and 21 DIM to analyze metabolic markers, including BHB acid (BHBA), nonesterified fatty acids, and insulin. Additionally, oxidative variables (proportion of oxidized glutathione to total glutathione in red blood cells [GSSG {%}], the activity of glutathione peroxidase [GPx] and of superoxide dismutase [SOD], concentrations of malondialdehyde [MDA], and oxygen radical absorbance capacity [ORAC]) and acute phase proteins (APP), including Hp and SAA, and albumin-to-globulin ratio (A:G) were assessed in the blood of −7 and 21 d relative to calving. Initially, 5 oxidative variables (GSSG [%], GPx, SOD, MDA, and ORAC) at 21 DIM were subjected to fuzzy c-means clustering, delineating 2 groups: lower antioxidant ability (LAA80%, n = 27) and higher antioxidant ability (HAA80%, n = 14), with 80% referring to the cut-off value for cluster membership. Twenty-five lactations with membership values below this threshold were excluded. Subsequently, using k-medoids clustering on 3 APP (Hp, SAA, and A:G) at 21 DIM, clinically healthy cows were categorized into 2 groups: those exhibiting an acute phase response (APR, n = 13) and those without this response, termed non-APR (n = 41). Cows that developed one or more clinical diseases during the transition period (n = 12) were considered as a distinct group. A modest association was observed between compromised antioxidant ability and enhanced inflammatory status at a systemic level. Clinically diseased cases manifested increased GPx activities compared with clinically healthy cases, independent of their inflammation levels. A limited association was noticed between oxidative status at −7 and 21 d relative to calving. However, at −7 d relative to calving, the non-APR group exhibited reduced SAA levels in comparison to both the APR and diseased groups. Energy metabolic stress was more pronounced in the LAA80% group than in the HAA80% group, characterized by elevated BHBA concentrations during the transition period. Between 5 and 21 d of lactation, a decline in milk yield was observed in the LAA80% group. Moreover, the LAA80% group displayed increased milk fat percentages. Nevertheless, the detrimental effects of the transition period were relatively muted when clinical symptoms were absent in the APR group. Notably, the clinically healthy cows produced more milk than the diseased cows. During the transition period, the diseased cases exhibited elevated BHBA concentrations. These findings highlight the heterogeneity in the oxidative and inflammatory status of dairy cows during early lactation. Cows with impaired oxidative status require close monitoring, whereas those with higher antioxidant ability and no clinical symptoms appear capable of managing elevated inflammatory responses.

M.M. Perez, E. Cabrera, C. Rial et al.

ABSTRACT: The objective of this study was to create a framework for training and selecting machine learning algorithms (MLA) to classify cow health status daily using data from multiple automated health monitoring systems (AHMS), including wearable and nonwearable sensors, combined with nonsensor data of potential value for predicting cow health. The work presented in this manuscript is part of a series of studies aimed at identifying a single candidate algorithm that, upon extensive refinement and further development, could be deployed in a commercial dairy operation to identify cows potentially affected by health disorders for clinical examination. Data from AHMS and other cow features and performance data, including the clinical health status of cows, were collected in a prospective cohort study including Holstein cows (n = 1,252). Data from AHMS used for MLA training included rumination, eating, and physical activity measured in the neck (neck sensor), temperature and physical activity measured in the reticulorumen (bolus sensor), physical activity and resting measured in the leg (leg sensor), and milk yield, milk electrical conductivity, and milk components (parlor sensors). Other non-AHMS data used were temperature and humidity index, cow and calving event features, and current and previous lactation performance and management indicators. The dataset included 22,415 cow-day records with 49 features. The dataset was split into training and testing sets in an 80:20 ratio, resulting in 17,887 and 4,528 cow-day records, respectively. Data imputation and standardization were applied automatically or manually. A diverse set of nondeep learning (n = 26) MLA were trained and compared using the open-source automated ML (AutoML) tool Lazy Predict Classifier (LZP). Upon selection of the best-performing nondeep learning algorithms (i.e., XGBoost, AdaBoost, Nearest Centroid, and Bernoulli Naive Bayes) from the pool tested with LZP, classifier algorithms were compared with more complex deep learning algorithms (multilayer perceptron, recurrent neural networks, long short-term memory networks, and gated recurrent unit models) not included in LZP. All algorithms underwent training and evaluation before selection of a single best-performing algorithm, using several metrics of performance. Ensemble learning models, particularly XGBoost, achieved the best performance and balanced results with a sensitivity of 82.4% and a precision of 42.6% combined with a specificity of 86.4% and a negative predictive value of 97.6%. This model also had the highest F1-score (0.56) and area under the curve (84.4%). The XGBoost algorithm also demonstrated robustness in handling missing data. Our comprehensive approach to MLA screening and selection enabled informed decisions in selecting a suitable algorithm for identifying cows for clinical examination based on the daily prediction of health disorder occurrence. The combination of the AutoML tool LZP and manual refinement and testing of multiple MLA provided a robust framework for comparing multiple ML models. Ensemble classification learner algorithms such as XGBoost and Adaboost might outperform other deep learning and nondeep learning algorithms for classifying cow health daily using AHMS and other cow management and performance indicators.

Gaia Meoni, Ingrid Sousa, Leonardo Tenori et al.

ABSTRACT: The rising demand for nondairy and nonanimal protein sources has increased plant-based beverages (PBB) consumption. However, research on their functional properties, metabolic profile, and discrimination potential is limited. This study evaluated the potential of proton nuclear magnetic resonance (1H NMR) spectroscopy as an authentication method to discriminate milk (cow and goat) and PBB macro-groups, including soy-based, fruit-based (almond and coconut), and cereal-based (rice and oat) beverages, based on their metabolic profile. A total of 22 PBB (soy-, almond-, coconut-, rice-, and oat-based beverages), 4 cow milk, and 4 goat milk cartons were analyzed with 1H NMR spectroscopy to obtain their metabolic profile. Relevant metabolites to discriminate PBB macro-groups and cow and goat milk were identified through the Mann-Whitney U test and partial least squares-discriminant analysis. Results revealed that uridine diphosphate glucose and adenosine were key metabolites for the identification of goat and cow milk. At the same time, choline and guanosine emerged as important markers for different PBB macro-group detection. In addition, lactose played a significant role in differentiating milk from PBB. In conclusion, these findings represent an initial step toward applying 1H NMR spectroscopy for authentication and nutritional analysis of PBB, opening the door for further research into their authenticity and metabolic profiling.

O. González-Recio, A. Fernández, J.A. Jiménez Montero

ABSTRACT: Epizootic hemorrhagic disease (EHD) is a noncontagious viral infection that can cause important economic losses on dairy farms. This study aimed to identify epidemiological and genetic factors influencing the susceptibility and severity of EHD in Holstein dairy cattle during the 2023 outbreak in Spain. Data from 2,852 animals in 7 affected farms from 5 Spanish provinces were used. Symptoms were categorized in 5 categories: no symptoms, mild symptoms, severe symptoms and recovery, severe symptoms with aftereffects (sequelae), and severe symptoms followed by death. All animals were genotyped using the Illumina EuroG MD SNP array, and imputation to whole-genome sequencing was carried out using the 1,000 bull genomes dataset as a reference. Risk factors for EHD were explored using linear mixed effects models, as well as the loss of milk yield and culling risk probability due to severe EHD. In all, ∼66% of animals showed EHD virus antibodies, although only 25% of the sample in this study showed severe symptoms, and the death rate was 2% to 3%. Results indicated that age was the main risk factor for severe EHD, with older cows showing greater susceptibility. Production losses were significant in cows with moderate to severe symptoms, especially if the outbreak occurred mid lactation (up to −9 kg/d). Cows exhibiting severe symptoms demonstrated a markedly increased likelihood of being culled, with an odds ratio of 10.86 (95% CI: 6.08–19.41) for cows with severe symptoms. The genetic component of EHD was evaluated using REML procedures, and a GWAS was conducted to investigate genomic regions associated with the disease. An h2 of 0.08 was estimated, with some genes (AOC1, BST1, CD38, DPP6, DPYS, HOGA1, KMT2C, PIK2A, PIK3, and PI4K2A) associated with the disease showing involvement in immunity processes and the development of the pulmonary tree. This study underscores the genetic and epidemiological factors influencing EHD severity in dairy cattle, providing insights for managing future outbreaks and mitigating economic losses in affected regions.

Siyuan Liu, Huimin Pang, Chenglong Wang et al.

ABSTRACT: Due to its beneficial effects on human health, Bifidobacterium is commonly added to milk powder. Accurate quantification of viable Bifidobacterium is essential for assessing the therapeutic efficacy of milk powder. In this study, we introduced a novel propidium monoazide (PMA)-antibiotic fluorescence in situ hybridization (AFISH)-flow cytometry (FC) method to rapidly and accurately quantify viable Bifidobacterium cells in milk powder. Briefly, Bifidobacterium cells were treated with chloramphenicol (CM) to increase their rRNA content, followed by staining with RNA-binding oligonucleotide probes, based on the AFISH technique. Then, the DNA-binding dye PMA was used to differentiate between viable and nonviable cells. The PMA-AFISH-FC method, including sample pretreatment, CM treatment, dual staining, and FC analysis, required approximately 2 h and was found to be better than the current methods. This is the first study to implement FC combined with PMA and an oligonucleotide probe for detecting Bifidobacterium.

Nigel B. Cook, Marina A.G. von Keyserlingk

ABSTRACT: The contentious issue of cow-calf separation at birth is incongruent with many views on acceptable farming practices, and carries the risk of eroding public trust in the dairy industry if it is not addressed. The available evidence provides little support for the practice, but research on best practices for maintaining cow-calf contact in a way that enhances animal welfare while preserving farm profitability is nascent. In this article, the authors address the research questions that require answers to better inform producers and facilitate their decision-making and prepare the dairy industry to take another evolutionary step forward.

Diana Giannuzzi, Alice Vanzin, Sara Pegolo et al.

ABSTRACT: Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns. Specifically, the DSCC is the combined proportions of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) on the total SCC, with macrophages (MAC) representing the remainder proportion. In this study, we evaluated the association between DSCC in combination with SCC on a detailed milk mineral profile in 1,013 Holstein-Friesian cows reared in 5 herds. An inductively coupled plasma–optical emission spectrometry was used to quantify 32 milk mineral elements. Two different linear mixed models were fitted to explore the associations between the milk mineral elements and first, the DSCC combined with SCC, and second, DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the proportion of PMN-LYM and MAC by SCC. We observed a significant positive association between SCC and milk Na, S, and Fe levels. Differential somatic cell count showed an opposite behavior to the one displayed by SCC, with a negative association with Na and positive association with K milk concentrations. When considering DSCC as count, Na and K showed contrasting behavior when associated with PMN-LYM or MAC counts, with decreasing of Na content and increasing K when associated with increasing PMN-LYM counts, and increasing Na and decreasing K when associated with increasing MAC count. These findings confirmed that an increase in SCC is associated with altered milk Na and K amounts. Moreover, MAC count seemed to mirror SCC patterns, with the worsening of inflammation. Differently, PMN-LYM count exhibited patterns of associations with milk Na and K contents attributable more to LYM than PMN, given the nonpathological condition of the majority of the investigated population. An interesting association was observed for milk S content, which increased with increasing of inflammatory conditions (i.e., increased SCC and MAC count) probably attributable to its relationship with milk proteins, especially whey proteins. Moreover, milk Fe content showed positive associations with the PMN-LYM population, highlighting its role in immune regulation during inflammation. Further studies including individuals with clinical condition are needed to achieve a comprehensive view of milk mineral behavior during udder health impairment.

Diego B. Nobrega, C. Miltenburg, G. Séguin et al.

ABSTRACT: We investigated the prevalence and spatial distribution of selected pathogens associated with infectious diseases of dairy cattle in Ontario, Canada. The cross-sectional study surveyed bulk tank milk for antibodies against bovine leukemia virus (BLV), Mycobacterium avium ssp. paratuberculosis (MAP), and Salmonella Dublin, and for the presence of mastitis pathogens (Staphylococcus aureus, Streptococcus agalactiae, Mycoplasma bovis). Between October 2021 and June 2022, bulk tank milk samples were obtained from every commercial dairy farm in Ontario (n = 3,286). Samples underwent ELISA testing for the presence of BLV, MAP, and S. Dublin antibodies, and quantitative PCR testing for the detection of specific antigens of pathogens associated with mastitis. Bayesian models were used to estimate prevalence, and spatial analysis was carried out to identify regional clusters of high pathogen prevalence. Prevalence varied for different pathogens, and BLV was widespread across dairy farms in Ontario, with an estimated prevalence of 88.3%. The prevalence of MAP, Staph. aureus and S. Dublin in Ontario dairy herds was 39.8%, 31.5%, and 5.1%, respectively. The vast majority of dairy herds in Ontario were free of intramammary infections caused by Strep. agalactiae and M. bovis. Clusters of increased positive test rates were detected for S. Dublin, MAP, and Staph. aureus, indicating potential geographic risk factors for pathogen transmission. For S. Dublin, an area of increased test positivity rates was detected in southwestern Ontario, close to the Canada-United States border where most of the dairy herds in Ontario are located. Conversely, a localized cluster of positive test outcomes involving 14 subdivisions located in the southeastern region of Ontario was detected for Staph. aureus. Findings from our survey highlight the importance of the testing of aggregated samples and conducting spatial analysis as part of disease surveillance programs, and for implementing risk-based trading approaches among dairy producers.

Joice Pranata, Marshall Dunn, MaryAnne Drake et al.

ABSTRACT: Liquid micellar casein concentrate (MCC) is an ideal milk-based protein ingredient for neutral-pH ready-to-drink beverages. The texture and mouthfeel of liquid MCC-based beverages depend on the beverage protein content, as well as the composition of soluble proteins in the aqueous phase around the casein micelle. The objective of this study was to determine the composition of soluble proteins in the aqueous phase around the casein micelles in skim milk and liquid MCC containing 7.0% and 11.6% protein content. Skim milk was pasteurized and concentrated to 7% protein content by microfiltration and then to 18% protein content by ultrafiltration. The 18% MCC was then serially diluted with distilled water to produce 11.6% and 7.0% protein MCC. Skim milk, 7.0% MCC, and 11.6% MCC representing starting materials with different protein concentrations were each ultracentrifuged at 100,605 × g for 2 h. The ultracentrifugation for each of the starting materials was performed at 3 different temperatures: 4°C, 20°C, and 37°C. The ultracentrifugation supernatants were collected to represent the aqueous phase around the casein micelle in MCC solutions. The supernatants were analyzed by Kjeldahl to determine the crude protein, casein, and casein as a percentage of crude protein content, and by sodium dodecyl sulfate PAGE to determine the composition of the individual proteins. Most of the proteins in MCC supernatant (about 45%) were casein proteolysis products. The remaining proteins in the MCC supernatant consisted of a combination of intact αS-, β-, and κ-caseins (about 40%) and serum proteins (14–18%). Concentrations of αS-casein and β-casein in the supernatant increased with decreasing temperature, especially at higher protein concentrations. Temperature and interaction between temperature and protein explained about 80% of the variation in concentration of supernatant αS- and β-caseins. Concentration of supernatant κ-casein, casein proteolysis products, and serum protein increased with increasing MCC protein concentration, and MCC protein concentration explained most of the variation in supernatant κ-casein, casein proteolysis products, and serum protein concentrations. Predicted MCC apparent viscosity was positively associated with the dissociation of αS- and β-caseins. Optimal beverage viscosity could be achieved by controlling the dissociation of these proteins in MCC.

Luna Maslov Bandić, Fabijan Oštarić, Marko Vinceković et al.

Cheese is one of the most popular dairy products, with an incredible diversity of varieties, shapes, textures, and flavours available locally and globally. Extensive research has been conducted on the aroma compounds present in cheese. Numerous studies have identified over 3000 volatile and non-volatile components in cheese. The volatile components, which consist of fatty acids, alcohols, aldehydes, esters, ketones, lactones, sulphur compounds, amines, and other flavour-active compounds, are primarily responsible for the aromatic characteristics (aroma) of cheese. This paper thoroughly discusses the biochemistry behind the formation of significant aroma compounds that affect overall cheese quality and sensory characteristics. It provides an extensive review of the most recent methodologies for the extraction and determination of aroma compounds in cheese.

Michael S. Allen

ABSTRACT: Energy intake and partitioning are determined by many interacting factors and their prediction is the Achilles' heel of ration formulation. Inadequate energy intake can limit milk yield and reproductive performance, whereas excessive energy intake will increase body condition, increasing the risk of health and reproductive issues in the subsequent lactation. Ration composition interacts with the physiological state of cows, making it difficult to predict DMI and the partitioning of energy accurately. However, understanding the factors controlling these allows us to devise grouping strategies and manipulate rations to optimize energy intake through lactation. Eating is controlled by the integration of signals in brain feeding centers. Ration composition affects DMI of cows via signals from ruminal distention and the hepatic oxidation of fuels. Dairy cow rations must contain a minimal concentration of relatively low-energy roughages for proper rumen function, but signals from ruminal distension can limit DMI when the drive to eat is high. Signals from the hepatic oxidation of fuels likely dominate the control of DMI in the peripartum period when cows are in a lipolytic state and later in lactation when signals from distension diminish. Therefore, the effects of the ration on DMI vary with the physiological state of the animal. Furthermore, they interact with environmental stressors such as social (e.g., overcrowding) and thermal stress. The objective of this article is to discuss the effects of ration composition on energy intake and partitioning in lactating cows and how they can be manipulated to optimize productive performance.

M. Baldin, D. Garcia, G.I. Zanton et al.

ABSTRACT: Biohydrogenation-induced milk fat depression (MFD) is a reduction in milk fat synthesis caused by bioactive fatty acids (FA) produced during altered ruminal microbial metabolism of unsaturated FA. The methionine analog 2-hydroxy-4-(methylthio)butanoate (HMTBa) has been shown to reduce the shift to the alternate biohydrogenation pathway and maintain higher milk fat yield in high-producing cows fed diets lower in fiber and higher in unsaturated FA. The objective of this experiment was to verify the effect of HMTBa on biohydrogenation-induced MFD and investigate associated changes in rumen environment and fermentation. Twenty-two rumen cannulated high-producing Holstein cows [168 ± 66 d in milk; 42 ± 7 kg of milk/d (mean ± standard deviation)] were used in a randomized design performed in 2 blocks (1 = 14 cows, 2 = 8 cows). Treatments were control (corn carrier) and HMTBa (0.1% of diet dry matter). The experiment included a 7-d covariate period followed by 3 phases that fed diets with increasing risk of MFD. The diet during the covariate and low-risk phase (7 d) was 32% neutral detergent fiber with no additional oil. The diet during the moderate-risk phase (17 d) was 29% neutral detergent fiber with 0.75% soybean oil. Soybean oil was increased to 1.5% for the last 4 d. The statistical model included the random effect of block and time course data were analyzed with repeated measures including the random effect of cow and tested the interaction of treatment and time. There was no effect of block or interaction of block and treatment or time. There was no overall effect of treatment or treatment by time interaction for dry matter intake, milk yield, and milk protein concentration and yield. Overall, HMTBa increased milk fat percent (3.2 vs. 3.6%) and yield (1,342 vs. 1,543 g/d) and there was no interaction of treatment and dietary phase. Additionally, HMTBa decreased the concentration of trans-10 18:1 in milk fat and rumen digesta. Average total ruminal concentration of volatile FA across the day and total-tract dry matter and fiber digestibility were not affected by HMTBa, but HMTBa increased average rumen butyrate and decreased propionate concentration and increased total protozoa abundance. Additionally, HMTBa increased the fractional rate of α-linoleic acid clearance from the rumen following a bolus predominantly driven by a difference in the first 30 min. Plasma insulin was decreased by HMTBa. In conclusion, HMTBa prevented the increase in trans FA in milk fat associated with MFD through a mechanism that is independent of total volatile FA concentration, but involves modification of rumen biohydrogenation. Decreased propionate and increased butyrate and ruminal protozoa may also have functional roles in the mechanism.

K.M. Tiplady, M.-H. Trinh, S.R. Davis et al.

ABSTRACT: Accurate and timely pregnancy diagnosis is an important component of effective herd management in dairy cattle. Predicting pregnancy from Fourier-transform mid-infrared (FT-MIR) spectroscopy data is of particular interest because the data are often already available from routine milk testing. The purpose of this study was to evaluate how well pregnancy status could be predicted in a large data set of 1,161,436 FT-MIR milk spectra records from 863,982 mixed-breed pasture-based New Zealand dairy cattle managed within seasonal calving systems. Three strategies were assessed for defining the nonpregnant cows when partitioning the records according to pregnancy status in the training population. Two of these used records for cows with a subsequent calving only, whereas the third also included records for cows without a subsequent calving. For each partitioning strategy, partial least squares discriminant analysis models were developed, whereby spectra from all the cows in 80% of herds were used to train the models, and predictions on cows in the remaining herds were used for validation. A separate data set was also used as a secondary validation, whereby pregnancy diagnosis had been assigned according to the presence of pregnancy-associated glycoproteins (PAG) in the milk samples. We examined different ways of accounting for stage of lactation in the prediction models, either by including it as an effect in the prediction model, or by pre-adjusting spectra before fitting the model. For a subset of strategies, we also assessed prediction accuracies from deep learning approaches, utilizing either the raw spectra or images of spectra. Across all strategies, prediction accuracies were highest for models using the unadjusted spectra as model predictors. Strategies for cows with a subsequent calving performed well in herd-independent validation with sensitivities above 0.79, specificities above 0.91 and area under the receiver operating characteristic curve (AUC) values over 0.91. However, for these strategies, the specificity to predict nonpregnant cows in the external PAG data set was poor (0.002–0.04). The best performing models were those that included records for cows without a subsequent calving, and used unadjusted spectra and days in milk as predictors, with consistent results observed across the training, herd-independent validation and PAG data sets. For the partial least squares discriminant analysis model, sensitivity was 0.71, specificity was 0.54 and AUC values were 0.68 in the PAG data set; and for an image-based deep learning model, the sensitivity was 0.74, specificity was 0.52 and the AUC value was 0.69. Our results demonstrate that in pasture-based seasonal calving herds, confounding between pregnancy status and spectral changes associated with stage of lactation can inflate prediction accuracies. When the effect of this confounding was reduced, prediction accuracies were not sufficiently high enough to use as a sole indicator of pregnancy status.

Mu Tian, Jianjun Cheng, Hao Wang et al.

ABSTRACT: Goat milk whey protein concentrates were manufactured by microfiltration (MF) and ultrafiltration (UF). When MF retentate blended with cream, which could be used as a starting material in yogurt making. The objective of this study was to prepare goat milk whey protein concentrates by membrane separation technology and to investigate the effects of polymerized goat milk whey protein (PGWP) on the physicochemical properties and microstructure of recombined goat milk yogurt. A 3-stage MF study was conducted to separate whey protein from casein in skim milk with 0.1-µm ceramic membrane. The MF permeate was ultrafiltered using a 10 kDa cut-off membrane to 10-fold, followed by 3 step diafiltration. The ultrafiltration-diafiltration-treated whey was electrodialyzed to remove 85% of salt, and to obtain goat milk whey protein concentrates with 80.99% protein content (wt/wt, dry basis). Recombined goat milk yogurt was prepared by mixing cream and MF retentate, and PGWP was used as main thickening agent. Compared with the recombined goat milk yogurt without PGWP, the yogurt with 0.50% PGWP had desirable viscosity and low level of syneresis. There was no significant difference in chemical composition and pH between the recombined goat milk yogurt with PGWP and control (without PGWP). Viscosity of all the yogurt samples decreased during the study. There was a slight but not significant decrease in pH during storage. Bifidobacterium and Lactobacillus acidophilus in yogurt samples remained above 106 cfu/g during 8-wk storage. Scanning electron microscopy of the recombined goat milk yogurt with PGWP displayed a compact protein network. Results indicated that PGWP prepared directly from raw milk may be a novel protein-based thickening agent for authentic goat milk yogurt making.

Yuxiang Song, Yuchen Yang, Wen Zeng et al.

ABSTRACT: Ketosis in dairy cows often occurs in the peripartal period and is accompanied by immune dysfunction. High concentrations of β-hydroxybutyrate (BHB) in peripheral blood during ketosis are closely related to the impairment of polymorphonuclear neutrophil (PMN) chemotaxis and contribute to immune dysfunction. The specific effect of BHB on PMN chemotaxis in dairy cows and the underlying molecular mechanisms are unclear. Here, 30 multiparous cows (within 3 wk postpartum) classified based on serum BHB as control (n = 15, BHB <0.6 mM) or clinically ketotic (n = 15, BHB >3.0 mM) were used. Blood samples were collected before feeding, and the isolated PMN were treated with platelet-activating factor for 0.5 h to activate their migration. Scanning electron microscopy revealed a longer tail in PMN of ketotic cows. In addition, the phosphorylation and transcription levels of myosin light chain 2 (MLC2) increased in PMN of ketotic cows. Polymorphonuclear neutrophils from control dairy cows were incubated with 3.0 mM BHB for different times in vitro, and 6 h was selected as the proper duration of BHB stimulation according to its inhibition effect on PMN migration using an under-agarose PMN chemotaxis model. Similarly, BHB stimulation in vitro resulted in inhibition of migration distance and deviation of migration direction of PMN, as well as a longer tail in morphology in the scanning electron microscope data, suggesting that BHB-induced PMN migration inhibition may be mediated by impairing the trailing edge contraction. To confirm this hypothesis, sotrastaurin (Sotra)—a specific inhibitor of protein kinase C (PKC), which is the core regulator of cell contraction—was used with or without BHB treatment in vitro. Sotra was pretreated 0.5 h before BHB treatment. Accordingly, BHB treatment increased the phosphorylation level of PKC and MLC2, the protein abundance of RhoA and rho-kinase 1 (ROCK1), and the mRNA abundance of PRKCA, MYL2, RHOA, and ROCK1 in PMN. In contrast, these effects of BHB on PMN were dampened by Sotra. As demonstrated by immunofluorescence experiments in vitro, the BHB-induced inhibition of trailing edge contraction of PMN was relieved by Sotra. In addition, Sotra also dampened the effects of BHB on PMN migration in vitro. Furthermore, as verified by in vivo experiments, compared with the control cows, both abundance and activation of PKC signaling were enhanced in PMN of ketotic cows. Overall, the present study revealed that high concentrations of blood BHB impaired PMN migration distance through inhibition of the trailing edge contraction, mediated by enhancing the activation of PKC-MLC2 signaling. These findings help explain the dysfunctional immune state in ketotic cows and provide information on the pathogenesis of infectious diseases secondary to ketosis.

Nada Smigic, Jelena Miocinovic, Jovana Tomic et al.

The aim of this study was to evaluate the effect of nisin and storage temperature on the microbiological, physico-chemical and sensory properties of processed cheese. Processed cheese samples were prepared without and with 12.5 ppm nisin, stored at different temperatures (4, 8 and 20 °C). Research covered microbiological, physico-chemical and sensorial analysis of the samples. In processed cheese samples prepared without nisin, aerobic colony count (ACC) significantly increased over the experimental period, while in nisin supplemented samples no significant increase was determined. At lower storage temperature (4 °C), the effectiveness of nisin was more pronounced. Yeast and moulds (YM) and psychrotrophic colony count (PCC) were below the limit of quantification over the entire experimental period. Also, no significant changes in pH values and textural characteristics (firmness and stickiness) were determined. Sensory analyses confirmed that processed cheese samples became whiter and less yellow, compared to fresh samples. The viscosity of all samples decreased over the experimental period, which was in line with the results of baking stability. The obtained results confirmed the potential of using this type of processed cheese in baking industry.

Greta Krešić, Irena Colić Barić, Borislav Šimundić

The aim of this work was to determine the portion of milk and dairyproducts as a source of macronutrients, energy, vitamins and minerals in average hotel menus for some category of hotel guests. For this purpose the evaluation of 66 whole day meals (breakfast, lunch and supper) on daily menus was made. Meals were therefore mathematically and statistically analysed and compared with recommendations (RDA and DRI) for middle aged and elderly guests, both genders. The obtained results indicated that the meals should be balanced according to nutritional principles, because of too high energy share derived from fats (average 47.95%) while just about 37.57% of daily energy was from carbohydrates origin. The energy values were much higher than recommendations for both genders, respectively. The energy share from milk and dairy products origin was 11% of total energy what should be considered as a suitable. The most served dairy product was milk while the ice-cream took the second place. It is necessary to increase the yogurt and similar fermented products consumption, especially for the elderly guests. With milk and dairy products consumption males and females fulfill 92% RDA for calcium, and 61.80 % DRI for elderly, respectively.