Hasil untuk "Dairying"

Riasad Alvi, Mohaimenul Azam Khan Raiaan, Sadia Sultana Chowa et al.

Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study presents a physics-informed digital twin (DT) framework combined with an uncertainty-aware, expert-weighted stacked ensemble for multimodal forecasting of Core Body Temperature (CBT) in dairy cattle. Using the high-frequency, heterogeneous MmCows dataset, the DT integrates an ordinary differential equation (ODE)-based thermoregulation model that simulates metabolic heat production and dissipation, a Gaussian process for capturing cow-specific deviations, a Kalman filter for aligning predictions with real-time sensor data, and a behavioral Markov chain that models activity-state transitions under varying environmental conditions. The DT outputs key physiological indicators, such as predicted CBT, heat stress probability, and behavioral state distributions are fused with raw sensor data and enriched through multi-scale temporal analysis and cross-modal feature engineering to form a comprehensive feature set. The predictive methodology is designed in a three-stage stacked ensemble, where stage 1 trains modality-specific LightGBM 'expert' models on distinct feature groups, stage 2 collects their predictions as meta-features, and at stage 3 Optuna-tuned LightGBM meta-model yields the final CBT forecast. Predictive uncertainty is quantified via bootstrapping and validated using Prediction Interval Coverage Probability (PICP). Ablation analysis confirms that incorporating DT-derived features and multimodal fusion substantially enhances performance. The proposed framework achieves a cross-validated R2 of 0.783, F1 score of 84.25% and PICP of 92.38% for 2-hour ahead forecasting, providing a robust, uncertainty-aware, and physically principled system for early heat stress detection and precision livestock management.

Feiyan Yang, Guangfan Qu, Yuchi Wu et al.

ABSTRACT: Due to the high altitude and low oxygen levels, individuals residing or traveling in high-altitude regions often experience hypoxic cardiac dysfunction, which significantly affects their overall well-being and quality of life. Our previous investigations showed that peptide from yak milk residue exhibits notable antioxidant, anti-inflammatory, and anti-apoptotic properties that may have a good regulatory effect on hypoxic cardiac dysfunction. In this study, our results suggest that oral administration of yak milk peptide T3 improves the cardiac dysfunction of mice by the hypoxia-inducible factor 1α (HIF-1α) pathway, and these results may be related to the regulation of T3 on the gut microbiota of mice. Additionally, oral administration T3 enhances the permeability of the intestinal barrier and reduces intestinal inflammation. Further analysis revealed that the genera Oscillospira, Clostridium, and Staphylococcus are associated with aspartate aminotransferase, lactate dehydrogenase, and reactive oxygen species levels in heart tissues, which could ameliorate hypoxia-induced myocardial injury in mice. In vitro cell models have also confirmed that T3 intervention can activate the HIF-1α pathway and inhibit myocardial inflammation and cardiomyocyte apoptosis. These findings suggest that T3 may be a potential candidate for developing functional foods to reduce hypoxia-induced cardiac dysfunction.

Anna Flynn, Wiley Barton, Catherine McAloon et al.

ABSTRACT: Feeding waste milk, a common practice in dairy farming, exposes calves to subtherapeutic levels of antimicrobials, potentially contributing to antibiotic resistance—a growing concern globally. Many dairy farmers, including those in Ireland, continue this practice, feeding waste milk from antibiotic-treated cows to calves. Although previous studies have linked waste milk feeding to changes in calf growth and health during the preweaning period, its effects postweaning remain unclear. This study examined how the duration of antimicrobial exposure at levels equivalent to those found in waste milk influences health and growth outcomes of dairy heifer calves both before and after weaning. It also assessed the prevalence of extended-spectrum β-lactamase (ESBL)-producing antimicrobial-resistant Escherichia coli in feces and changes in the fecal microbiota over time. To mimic waste milk, as derived from a cow treated with an intramammary suspension of antibiotics, a simulated waste milk (SWM) was prepared by adding amoxicillin (1.68 mg/L) and neomycin (2.28 mg/L) to a conventional milk replacer (MR). The study employed a randomized block design with 87 dairy heifer calves assigned to 1 of 3 treatments: (1) long-term antibiotic (LTA), with calves fed SWM until weaning at 12 wk; (2) short-term antibiotic (STA), with SWM fed from 3 to 5 wk; and (3) control (CONT), with calves fed antibiotic-free MR. Calves were weighed weekly, and health scores, including fecal scores (tail and hindquarters cleanliness as diarrhea indicator), were recorded twice per week. Fecal and blood samples were collected to analyze microbiome changes and the shedding of antimicrobial resistance. Blood samples were taken to measure systemic inflammation, using serum amyloid A as a biomarker. Results indicated that SWM feeding did not affect average daily gains before or after weaning. However, higher fecal scores were observed in the LTA group during weaning and after weaning in the STA group. Antibiotic-resistant isolates were present in all groups, with the highest prevalence in LTA. Fecal microbiota analysis revealed treatment-specific microbial community variations, with an increase of Enterococcus faecium genes resistant to macrolide, aminoglycoside, and tetracycline antibiotics in LTA and STA compared with CONT. In summary, SWM feeding did not significantly affect growth or overall health, but it was associated with increased fecal shedding of resistant bacteria and some changes in the microbiota, indicating potential long-term implications for antimicrobial resistance in dairy herds.

Mingsi Liao, Gota Morota, Ye Bi et al.

Monitoring calf body weight (BW) before weaning is essential for assessing growth, feed efficiency, health, and weaning readiness. However, labor, time, and facility constraints limit BW collection. Additionally, Holstein calf coat patterns complicate image-based BW estimation, and few studies have explored non-contact measurements taken at early time points for predicting later BW. The objectives of this study were to (1) develop deep learning-based segmentation models for extracting calf body metrics, (2) compare deep learning segmentation with threshold-based methods, and (3) evaluate BW prediction using single-time-point cross-validation with linear regression (LR) and extreme gradient boosting (XGBoost) and multiple-time-point cross-validation with LR, XGBoost, and a linear mixed model (LMM). Depth images from Holstein (n = 63) and Jersey (n = 5) pre-weaning calves were collected, with 20 Holstein calves being weighed manually. Results showed that You Only Look Once version 8 (YOLOv8) deep learning segmentation (intersection over union = 0.98) outperformed threshold-based methods (0.89). In single-time-point cross-validation, XGBoost achieved the best BW prediction (R^2 = 0.91, mean absolute percentage error (MAPE) = 4.37%), while LMM provided the most accurate longitudinal BW prediction (R^2 = 0.99, MAPE = 2.39%). These findings highlight the potential of deep learning for automated BW prediction, enhancing farm management.

Taminul Islam, Toqi Tahamid Sarker, Mohamed G Embaby et al.

Carbon dioxide (CO$_2$) emissions are critical indicators of both environmental impact and various industrial processes, including livestock management. We introduce CarboFormer, a lightweight semantic segmentation framework for Optical Gas Imaging (OGI), designed to detect and quantify CO$_2$ emissions across diverse applications. Our approach integrates an optimized encoder-decoder architecture with specialized multi-scale feature fusion and auxiliary supervision strategies to effectively model both local details and global relationships in gas plume imagery while achieving competitive accuracy with minimal computational overhead for resource-constrained environments. We contribute two novel datasets: (1) the Controlled Carbon Dioxide Release (CCR) dataset, which simulates gas leaks with systematically varied flow rates (10-100 SCCM), and (2) the Real Time Ankom (RTA) dataset, focusing on emissions from dairy cow rumen fluid in vitro experiments. Extensive evaluations demonstrate that CarboFormer achieves competitive performance with 84.88\% mIoU on CCR and 92.98\% mIoU on RTA, while maintaining computational efficiency with only 5.07M parameters and operating at 84.68 FPS. The model shows particular effectiveness in challenging low-flow scenarios and significantly outperforms other lightweight methods like SegFormer-B0 (83.36\% mIoU on CCR) and SegNeXt (82.55\% mIoU on CCR), making it suitable for real-time monitoring on resource-constrained platforms such as programmable drones. Our work advances both environmental sensing and precision livestock management by providing robust and efficient tools for CO$_2$ emission analysis.

Antonio Desiderio, Alessia Galdeman, Franziska Bauerlein et al.

Food waste represents a major challenge to global climate resilience, accounting for almost 10% of annual greenhouse gas emissions. The retail sector is a critical player, mediating product flows between producers and consumers, where supply chain inefficiencies can shape which items are put on sale. Yet how these dynamics vary across geographic contexts remains largely unexplored. Here, we analyze data from Denmark's largest retail group on near-expiry products put on sale. We uncover the geospatial variations using a dual-clustering approach. We characterize multi-scale spatial relationships in retail organization by correlating store clustering -- measured using shortest-path distances along the street network -- with product clustering based on promotion co-occurrence patterns. Using a bipartite network approach, we identify three regional store clusters, and use percolation thresholds to corroborate the scale of their spatial separation. We find that stores in rural communities put meat and dairy products on sale up to 2.2 times more frequently than metropolitan areas. In contrast, metropolitan and capital regions lean toward convenience products, which have more balanced nutritional profiles but less favorable environmental impacts. By linking geographic context to retail inventory, we provide evidence that reducing food waste requires interventions tailored to local retail dynamics, highlighting the importance of region-specific sustainability strategies.

Mayuri Kate, Suresh Neethirajan

The convergence of IoT sensing, edge computing, and machine learning is transforming precision livestock farming. Yet bioacoustic data streams remain underused because of computational complexity and ecological validity challenges. We present one of the most comprehensive bovine vocalization datasets to date, with 569 curated clips covering 48 behavioral classes, recorded across three commercial dairy farms using multiple microphone arrays and expanded to 2900 samples through domain informed augmentation. This FAIR compliant resource addresses major Big Data challenges - volume (90 hours of recordings, 65.6 GB), variety (multi farm and multi zone acoustics), velocity (real time processing), and veracity (noise robust feature extraction). Our distributed processing framework integrates advanced denoising using iZotope RX, multimodal synchronization through audio and video alignment, and standardized feature engineering with 24 acoustic descriptors generated from Praat, librosa, and openSMILE. Preliminary benchmarks reveal distinct class level acoustic patterns for estrus detection, distress classification, and maternal communication. The datasets ecological realism, reflecting authentic barn acoustics rather than controlled settings, ensures readiness for field deployment. This work establishes a foundation for animal centered AI, where bioacoustic data enable continuous and non invasive welfare assessment at industrial scale. By releasing standardized pipelines and detailed metadata, we promote reproducible research that connects Big Data analytics, sustainable agriculture, and precision livestock management. The framework supports UN SDG 9, showing how data science can turn traditional farming into intelligent, welfare optimized systems that meet global food needs while upholding ethical animal care.

Fatih Ramazan Istanbullugil, Ali Risvanli, Ruslan Salikov et al.

ABSTRACT: The aim of this study was to determine the components and cytokine and immunoglobulin levels of koumiss during different fermentation periods, and to reveal the interrelation between these parameters. For achieving this objective, 10 samples of koumiss were prepared and randomly divided into 2 groups: the first group was sampled at 0, 1, 5, 12, and 24 h of incubation at room temperature for analysis. The second group was stored at +4°C, and samples were taken on d 5, 10, 15, and 20. The counts of Enterobacteriaceae spp., Staphylococcus, and Micrococcus spp. progressively decreased with the period of fermentation until becoming undetectable in the final samples of both groups. We fond positive or negative correlations between cytokine and immunoglobulin levels and the physicochemical and microbiological parameters in the koumiss samples in both groups. However, the levels of IFN-γ, IL-2, TNF-α, and IgG did not change significantly over time in both groups. Overall, it is clear that traditionally prepared koumiss under different fermentation times and temperatures does not show any differences in cytokine and immunoglobulin concentrations.

N. Titze, Y.-P. Chi, E. Haese et al.

ABSTRACT: The objectives of this study were to determine the range in ruminal degradability of crude protein (CP) and intestinal digestibility of rumen undegradable protein in commercial soybean meal (SBM) and to investigate the range in in situ ruminal AA and phytate (InsP6) degradation and their relationship to CP degradation. An in situ study was conducted using 3 lactating Jersey cows with permanent rumen cannulas. Seventeen SBM variants from Europe, Brazil, Argentina, North America, and India were tested for ruminal CP and AA degradation, and in vitro intestinal digestibility of rumen undegradable protein. Nine variants were used to investigate the ruminal degradation of InsP6. The estimated rapidly degradable fraction (a) of CP showed an average value of 4.5% (range: 0.0%–9.0%), the slowly degradable fraction (b) averaged 95% (91%–100%), and the potential degradation was complete for all 17 SBM variants. The degradation of fraction b started after a mean lag phase of 1.7 h (1.1–2.0 h) at an average rate (c) of 10% per hour, but with a high range from 4.5% to 14% per hour. Differences in the degradation parameters induced a considerable range in CP effective degradation at a rumen passage rate of 6% per hour (CPED6) from 38% to 67%; hence, the concentration of rumen undegradable protein varied widely from 33% to 62%. The range in AA degradation between the SBM variants was high, with Ser showing the widest range, from 28% to 96%, and similar for the other AA. The regression equations showed close relationships between CP and AA degradation after 16 h of in situ incubation. However, the slopes of the linear regressions were significantly different between AA, suggesting that degradation among individual AA differs upon a change in CP degradation. The concentrations of InsP6 and myo-inositol pentakisphosphate in bag residues in the in situ study decreased constantly with longer ruminal incubation times. The ruminal degradation parameters of InsP6 ranged from 11% to 37% for fraction a, 63% to 89% for fraction b, and from 7.7% to 21% per hour for degradation rate c, with average values of 21%, 79%, and 16% per hour, respectively. The calculated InsP6 effective degradation at a rumen passage rate of 6% per hour (InsP6ED6) varied from 61% to 84% among the SBM variants. Significant correlations were detected between InsP6ED6 and CPED6 and between InsP6ED6 and chemical protein fractions A, B1, B2, B3, and C. Linear regression equations were developed to predict ruminal InsP6 degradation using CPED6 and chemical protein fractions B3 and C chosen by a stepwise selection procedure. We concluded that a high range in CP, AA, and InsP6 degradation exists among commercial SBM, suggesting that general degradability values may not be precise enough for diet formulation for dairy cows. Degradation of CP in SBM may be used to predict rumen degradation of AA and InsP6 using linear regression equations. Degradation of CP and InsP6 could also be predicted from the chemical protein fractions.

Oshana Dissanayake, Sarah E. McPherson, Joseph Allyndree et al.

Monitoring calf behaviour continuously would be beneficial to identify routine practices (e.g., weaning, dehorning, etc.) that impact calf welfare in dairy farms. In that regard, accelerometer data collected from neck collars can be used along with Machine Learning models to classify calf behaviour automatically. Hand-crafted features are commonly used in Machine Learning models, while ROCKET and Catch22 features are specifically designed for time-series classification problems in related fields. This study aims to compare the performance of ROCKET and Catch22 features to Hand-Crafted features. 30 Irish Holstein Friesian and Jersey pre-weaned calves were monitored using accelerometer sensors allowing for 27.4 hours of annotated behaviors. Additional time-series were computed from the raw X, Y and Z-axis and split into 3-second time windows. ROCKET, Catch22 and Hand-Crafted features were calculated for each time window, and the dataset was then split into the train, validation and test sets. Each set of features was used to train three Machine Learning models (Random Forest, eXtreme Gradient Boosting, and RidgeClassifierCV) to classify six behaviours indicative of pre-weaned calf welfare (drinking milk, grooming, lying, running, walking and other). Models were tuned with the validation set, and the performance of each feature-model combination was evaluated with the test set. The best performance across the three models was obtained with ROCKET [average balanced accuracy +/- standard deviation] (0.70 +/- 0.07), followed by Catch22 (0.69 +/- 0.05), surpassing Hand-Crafted (0.65 +/- 0.034). The best balanced accuracy (0.77) was obtained with ROCKET and RidgeClassifierCV, followed by Catch22 and Random Forest (0.73). Thus, tailoring these approaches for specific behaviours and contexts will be crucial in advancing precision livestock farming and enhancing animal welfare on a larger scale.

Erika Nozawa, Tetsuo Deguchi

We present a theoretical model and simulation for the formation dynamics of diverse texture patterns that emerge spontaneously or self-organize during phase inversion processes of fresh cream by mechanical whipping. The results suggest that the model should be applied for theoretically designing the texture and quality of whipped cream and butter products. The modeling complexity in phase inversion processes from fresh cream via whipped cream to butter was overcome by using a well-established complex systems approach, coupled map lattice (CML). The proposed CML consists of a minimal set of procedures (i.e., parameterized nonlinear maps), whipping, coalescence, and flocculation, acting on the appropriately coarse-grained field variables, surface energy, cohesive energy, and velocity (flow) of the emulsion defined on a two-dimensional square lattice. In the CML simulations, two well-known and different phase inversion processes are reproduced at high and low whipping temperatures. The overrun and viscosity changes simulated in these processes are at least qualitatively consistent with those observed in experiments. We characterize these processes exhibiting different texture patterns as the viscosity dominance at high whipping temperature and as the overrun dominance at low whipping temperature on the viscosity-overrun plane, which is one of the state diagrams.

Shanaz Mustafa Abdullah, Bahroz Muhammed Saleh Ahmed

Colostrum gives the newborn calf maternal antibodies that help it fight disease. A calf that does not receive colostrum has a higher risk of illness until it develops antibodies of its own at around 6 weeks of age. This study aims to evaluate the immunity background of Karadi calves, measuring physiological responses to different qualities of colostrum and testing Karadi calves for survival in the herd. Twelve females local Karadi calves (0-day olds) were divided into two treatments with two levels for each. Using low and high colostrum quality before 6 hours and after 6 hours from parturition. Regarding calf body weight, withers height, immunoglobulin G concentration, and dry matter intake, there is no significant difference between low- and high-quality colostrum feed. However, our results show that calf body weight, withers height, and respiration rate were higher (P < 0.01) when colostrum was fed six hours after birth compared to those fed six hours after birth. However, there is no significant difference in the rectal temperature of the calf fed before six hours and six hours after birth. Results show that the total white blood cells, lymphocyte, neutrophil, eosinophil, and basophil numbers were unaffected by treatment, time and the interaction between treatment and time. Monocyte numbers have a tendency toward significant by treatment. Total plasma protein was not affected by treatment and time, but it tends significant treatment over time.

P. Zhou, S. Madarshahian, A. Abbaspourrad et al.

ABSTRACT: Photooxidation has long been affecting nutrient and sensory quality of fluid milk. Light oxidation starts from the activation of photosensitive compounds, followed by generation of singlet oxygen that reacts with vitamins, proteins, and lipids in milk. It is hypothesized that wavelength-tailored light schemes possessing spectral properties capable of avoiding excitation maxima of common photosensitizers in milk could slow the chemical degradation of light-exposed milk and thus preserve consumer acceptability. A series of 6 consumer tests with sample sizes from 95 to 119 participants tested hedonic responses to fluid milk samples exposed to light of varying wavelength spectra. For milk in clear plastic bottles (polyethylene terephthalate or high-density polyethylene), consumer panels generally liked milk exposed to light-emitting diodes eliminating wavelengths below 520 or 560 nm more than standard white light, or those eliminating other wavelength bands. This higher degree of liking coincided with panelists citing fewer off-flavors or aromas from these samples. Taken together, these observations suggest such light schemes can protect milk from light damage to some extent. Wavelength-tailored light schemes used in this study did not offer effective protection for milk in glass bottles. Dissolved oxygen, color, riboflavin loss, and hexanal content were instrumentally evaluated, but results failed to indicate significant signatures of light damage in milk compared with sensory measures. The appearance of milk bottles illuminated by the slightly greenish or yellowish light were less liked by consumers, suggesting further efforts on consumer education may be necessary if these light schemes were to be installed in retail dairy coolers.

Buket Aydeniz Guneser, Barıs Aklale, Onur Guneser

The physicochemical, rheological, aroma, and sensory properties of spreadable processed cheese supplemented with chia, quinoa, and teff seeds were evaluated. The changes in proximate composition, color values, rheological parameters, volatile profile, sensory, and microbiological properties of the cheese samples stored at 4 °C for 90 days were assessed. Significant differences in the initial contents of dry matter, protein, and fat were observed among the cheese samples. The pH was affected by the storage time and type of added pseudocereal. Moreover, the storage time and type of pseudocereal interaction affected the titratable acidity and color parameters of the cheese samples. The water-soluble nitrogen content increased slightly in all cheese samples during storage. The cheese samples supplemented with pseudocereals exhibited a pseudoplastic behavior. The consistency index of the cheese samples ranged from 2.277 to 2.550 Pa.sn, and the flow behavior index ranged from 0.528 to 0.665. The counts of total coliform and yeast-mold in all cheese samples were <1 log CFU/g cheese, and the counts of total mesophilic aerobic bacteria ranged from 2.21 log CFU/g cheese to 2.76 log CFU/g cheese. A total of 27 volatile compounds, consisting of acids, aldehydes, ketones, esters, and terpenes, were identified in the cheese samples. The amounts of butanoic acid, hexanoic acid, octanoic acid, and nonanoic acid in all cheese samples were higher than that of other volatiles, with the amounts ranging from 639 µg/kg to 3284 µg/kg, 711.20 µg/kg to 2723.27 µg/kg, 187.60 µg/kg to 722.71 µg/kg, and 75.42 µg/kg to 206.02 µg/kg, respectively. The most preferred cheese in terms of sensory properties was the control sample, followed by the SCT, SCQ, and SCC samples.

Vinzent Boerner, Thuy T.T. Nguyen, Gert J. Nieuwhof

ABSTRACT: Interbull's multiple across-country evaluaftion provides national breeding organizations with breeding values for internationally used bulls, which integrate performance data obtained in different breeding populations, environments, and production systems. However, breeding value-based selection decisions on domestic individuals born to foreign sires can only benefit from Interbull breeding values if they are integrated such that their information can contribute to the breeding values of all related domestic animals. For that purpose, several methods have been proposed which either model Interbull breeding values as prior information in a Bayesian approach, as additional pseudo data points, or as correlated traits, where these methods also differ in their software and parameterization requirements. Further, the complexity of integration also depends on the traits and genetic evaluation models. Especially random regression models require attention because of the dimensionality discrepancy between the number of Interbull breeding values and the number of modeled genetic effects. This paper presents the results from integrating 16,063 Interbull breeding values into the domestic single-step random regression test-day model for milk, fat, and protein yield for Australian Red dairy cattle breeds. Interbull breeding values were modeled as pseudo data points with data point-specific residual variances derived within animal across traits, ignoring relationships between integrated animals. Results suggest that the integration was successful with regard to alignment of Interbull breeding values with their domestic equivalent as well as with regard to the individual and population-wide increase in reliabilities. Depending on the relationship structure between integration candidates, further work is required to account for those relationships in a computationally feasible manner. Other traits with separate parity effects nationally could use a similar approach, even if not modeled with a test-day model.

M.S. Nicola, A.L. Kalb, A.A. Barbosa et al.

ABSTRACT: The present study aimed to evaluate the effect of continuous butyrate administration in dairy calves' liquid diet considering diarrhea, metabolic profile, gastrointestinal development, and corporal growth. Immediately after birth, calves were randomly allocated into 2 groups of 62 calves (50 females and 12 males), with access to water and a solid feed ad libitum. The butyrate group (BG) received 4 g/d of sodium butyrate (Admix Easy, Adisseo) diluted in the whole milk, and the control group (CG) received whole milk with no supplementation. Sodium butyrate was administered from d 1 of life until the weaning at 90 d. Feces consistency was assessed daily for the first 30 d of life and characterized by scores from 0 to 4 (0 and 1 for normal, and 2, 3, and 4 for abnormal feces). Diarrhea was diagnosed when the animals had abnormal feces and fever. Morbidity, recurrence, mortality, and lethality data were recorded and compared between the groups. Average daily gain (ADG) and corporal growth (body weight, thoracic perimeter, height at the withers, and croup width) were evaluated weekly, from the first day to d 30, and later at 45, 60, and 90 d of life. Blood samples were taken weekly for up to 30 d to determine the circulating levels of total calcium, phosphorus, chloride, bicarbonate, glucose, β-hydroxybutyrate, and nonesterified fatty acids. The males were euthanized at 15 (n = 6 per group) and 30 d (n = 6 per group) for morphometric, histological, and gene expression analysis of the gastrointestinal tract. The results showed that the BG had a lower rate of morbidity (BG = 30% vs. CG = 50%) and recurrence (BG = 26.7% vs. CG = 60%) of diarrhea than the CG. In addition, the BG had abnormal feces for a shorter period (BG = 4.64 ± 0.47 d vs. CG = 8.6 ± 0.65 d). The ADG tended to be higher in BG than CG up to 30 and 60 d. Metabolic evaluations showed the lowest levels of glucose and highest levels of nonesterified fatty acids in BG. On d 30 of life, rumen papillae length, papilla area, duodenum villus length, and crypt depth were higher in BG than in CG. The duodenal gene expression at 30 d showed that animals with diarrhea episodes that did not receive butyrate had the highest levels of transcripts for the LCT and GLP2 genes. In addition, in different ways, both butyrate and neonatal diarrhea affected the gene expression of IGF1, SLC5A1, and AQP3. These results allow us to conclude that continuous supplementation with sodium butyrate improves gastrointestinal development, reduces the occurrence of diarrhea, and makes clinical conditions milder with faster recovery, favoring a higher ADG in the first 30 and 60 d of life. Based on these results, we conclude that sodium butyrate can be indicated for liquid diet supplementation to accelerate gastrointestinal tract development and prevent severe cases of neonatal diarrhea, tending to improve average daily gain until weaning.

Do T. Hue, Kiro Petrovski, Tong Chen et al.

ABSTRACT: Bovine colostrum contains a high concentration of immune-related microRNAs (miRNAs) that are packaged in exosomes and are very stable. In this study, 5 immune-related miRNAs (miR-142-5p, miR-150, miR-155, miR-181a, and miR-223) were quantified in dam blood, colostrum, and calf blood using reverse transcription quantitative PCR. Their levels in calf blood after colostrum ingestion were investigated to assess whether miRNAs are transferred from the dam to newborn calves. Three groups of Holstein–Friesian bull calves were bottle-fed 2 L of colostrum or milk from different sources twice per day. The group A calves received colostrum from their own dam and the group B calves were fed foster dam colostrum. Each pair of group A and group B calves were fed identical colostrum from the same milking of the corresponding group A dam for 3 d and then bulk tank milk for 7 d after birth. Group C calves were fed only 2L of “pooled colostrum” from multiple dams d 0 to 4 postpartum, and then fed bulk tank milk thereafter for 7 d after birth. The groups were fed colostrum from different sources and different amounts to assess possible miRNA absorption from the colostrum. All miRNAs were at the highest level in colostrum at d 0 and then decreased rapidly after d 1. The level of miR-150 had the largest decrease from 489 × 106 copies/µL (d 0) to 78 × 106 copies/µL (d 1). MicroRNA-223 and miR-155 were the most abundant in both colostrum and milk. Dam colostrum had significantly higher levels of miR-142-5p, miR-155, and miR-181a than the bulk tank milk. However, only the miR-155 concentration was significantly higher in the dam colostrum than in the pooled colostrum. The concentrations of miRNAs in the colostrum were less than in the cow blood (100- to 1,000-fold less). There was no significant correlation between the level of miRNAs in the dam blood and their colostrum, suggesting that miRNA is synthesized locally by the mammary gland rather than being transferred from the blood. MicroRNA-223 had the highest level in both calf and cow blood compared with the other 4 immune-related miRNAs. Calves were born with high levels of immune-related miRNAs in their blood, and there were no significant differences in miRNA levels between the 3 calf groups at birth or after they were fed different colostrum. This suggests that these miRNAs were not transferred from the colostrum to the newborn calves.

Yunna Wang, Richard W. Hartel, Yan Li et al.

ABSTRACT: This study aimed to investigate the crystal network of bulk milk fat fractions and the partial coalescence, and the rheological properties of their oil-in-water (O/W) emulsions. Different milk fat fraction model systems were compared for their physicochemical properties, crystallization kinetics, and fat crystal networks across a range of temperatures. The extent of partial coalescence and rheological properties of the O/W emulsion prepared by different milk fat fractions were further analyzed. The results demonstrated that the ratio between saturated fatty acids (SFA) and unsaturated fatty acids and triacylglycerides (TAG) influenced the melting thermal behaviors, solid fat contents (SFC), and crystal networks of various milk fat fractions, which in turn influenced the partial coalescence and rheological characteristics of their O/W emulsions. Moreover, an excellent fit of the trend line confirmed that hardness increased exponentially with SFC. Trisaturated TAG in fractions with high melting points (HMF) such as milk fat fraction MF45, whose clarification temperature was 45°C, enriched long-chain SFA (saturated:unsaturated fatty acid = 2.2:1). We found that MF45 achieved higher SFC and hardness in the range of 0 to 40°C and, ultimately, formed a well-defined microstructural network with thick, rod-like crystals. Further, TAG in fractions with low melting points (LMF) such as MF10, whose clarification temperature was 10°C, were enriched with short-chain and unsaturated fatty acids (saturated:unsaturated fatty acid = 1.5:1), and a disordered crystal network in MF10, composed of randomly arranged, translucent platelets, was detected. Although fat globules of HMF and LMF were stabilized against coalescence, this could be attributed to a variety of mechanisms involving SFC, liquid fat, protective film around the fat globule, and minor lipids. According to the rheological profiles, all O/W emulsions exhibited weak viscoelastic “gel-like” structures [storage modulus (G′) > loss modulus (Gʺ)] over most of the measured range. The G′ values and apparent viscosity of HMF were greater than those of other fractions, indicating that the large and rigid crystals strengthen the networks more effectively.