Milk Flow Research Articles (Page 1)

Kangaroo Mother Care (KMC) is an effective intervention shown to significantly lower neonatal morbidity and mortality, especially among low-birth-weight (LBW) infants. Despite its success, many families struggle to implement KMC effectively post-discharge. This qualitative study employed a hermeneutical-phenomenological approach to explore the experiences of mothers and families practicing KMC after discharge from the hospital in South India. In-depth, semi-structured interviews were conducted with eight mothers, fathers, and grandmothers, focusing on their experiences with community KMC (cKMC) and their challenges in maintaining cKMC at home. All the data were transcribed verbatim and reflexive thematic analysis was done to identify the enablers and barriers to practice cKMC. Three main themes emerged from the analysis: Breast Feeding - Persevering Despite Initial Difficulties, Kangaroo Mother Care - Seeing benefits but struggling to practice, and Family Boon or Bane - Family as a crucial context for cKMC practice. While encountering challenges, participants expressed a strong commitment to breastfeeding, persevering to breastfeed by expressing breast milk, getting donor milk and using skin-to-skin contact to increase the milk flow. KMC was adopted positively and benefitted from support by the healthcare team and infrastructure during hospital stay, but continuation at home was difficult due to inadequate counselling, lack of community follow-up and challenging home environment. Family emerged both as a support system and a source of a tension to KMC practice. While fathers and grandmothers actively supported KMC in hospital settings, post-discharge traditional gender norms and domestic responsibilities hindered continuity at home. To promote sustained family-inclusive cKMC practices, there is a need for structured education to empower all caregivers, including grandmothers and fathers. Adoption of gender inclusive terminology such as "Kangaroo Family Care" can help to dismantle gender-oriented perceptions and encourage participation of all family members. Engaging grandparents as champions of KMC can promote intergenerational support for families and improve the outcome of LBW newborns. Community health teams should strengthen through tailored training on antenatal counselling and post-discharge support.

In the leading breeding farms for dairy cattle, current types of holsteinized Black-and-White cattle with high dairy productivity have been bred under various natural and climatic conditions of the Russian Federation. The influence of different factors including cow calving seasons is of great importance on the productive and technological traits of cows. The purpose of the research was to study the influence of the calving season on some morphological and functional traits of udder and milk yield of holsteinized first-calf heifers of Black-and-White breed. Four groups of fresh-calf heifers were formed in accordance with the calving seasons (1st group – winter calving, 2nd – spring calving, 3rd – summer and 4th – autumn calving). The morphological and functional traits of the udder were studied during the first three months of lactation. The main functional traits of the udder of holsteinized Black-and-White heifers that calved in different seasons of the year have been described in the article. It was found that the evaluated animals had optimal parameters of technological traits of the mammary gland and high suitability for machine milking. The largest number of first-calf heifers (88 %) had the desired udder shape. It was found on the base of data obtained that the intensity of milk fl ow rate in cows of all four groups on the scale of minimum requirements for the functional properties of the udder was evaluated with five points. Holstinized Black-and-White fi rst-calf heifers have udder traits well suited for machine milking and a high milk flow rate of 2.40 kg/min in autumn. The maximum daily milk yield (31.5 kg) was in cows that calved in the winter season.

Non-invasive and high-resolution blood flow velocity (BFV) measurement using Doppler optical coherence tomography (DOCT) is critical in diagnosing and monitoring clinical diseases. However, the inherent phase wrapping problem with inevitable noise in the acquired phase data severely limits the accuracy of flow quantification. To overcome this challenge, this paper takes phase unwrapping as a regression task and proposes a deep neural network called Transformer-enhanced residual network (TRNet) for automatic and noise-robust phase unwrapping in DOCT flow measurement. Considering the importance of long-range dependency for resolving phase discontinuities in noisy environments, TRNet integrates a Transformer block after each convolutional block, which is equipped with a residual strategy and row attention mechanism in the encoder path, forming a hybrid network that synergizes local feature extraction with global contextual awareness through self-attention mechanisms. To mitigate the lack of paired phase images used for network training, we construct a practically representative dataset with DOCT real phase images by leveraging Mamba-YOLO-based object detection and morphological image processing, avoiding reliance on simulated or synthetic data. Extensive evaluations on the rat middle cerebral artery (MCA) Doppler images demonstrate that TRNet outperforms traditional and other deep learning methods under varying signal-to-noise ratios (0-25 dB) in both visual inspection and quantitative evaluation. Notably, TRNet-derived flow velocities exhibit near-perfect correlation with the actual flow velocities in phantom milk flow experiments and show strong agreement with manual measurements in in vivo blood flow experiments, further validating the effectiveness of the proposed phase unwrapping method and its clinical feasibility for precision hemodynamic analysis.

Breast milk (BM) serves as the primary source of nutrition for infants from birth until six months of age. However, during the early postpartum period, BM production is often limited, necessitating non-pharmacological interventions such as a combination of breast care and oxytocin massage to stimulate prolactin and oxytocin hormones. The purposed this study is Intervention of Combined Breast Care and Oxytocin Massage to Improve Breast Milk Flow in Postpartum Mothers. This study employed a pre-experimental design with a one-group pre-test post-test approach. A total of 45 post-cesarean section mothers who met the inclusion criteria were selected using consecutive sampling. The intervention, consisting of breast care combined with oxytocin massage, was administered twice daily for seven days. Research instruments included a breast milk adequacy questionnaire and an observation sheet. Data were analyzed using the Wilcoxon Signed Ranks Test via SPSS version 26. Before the intervention, 41 respondents (91.1%) experienced inadequate BM flow, while 4 respondents (8.9%) had adequate BM flow. After the intervention, all respondents (100%) achieved adequate BM flow. The Wilcoxon test yielded a p-value of 0.000 (p<0.05), indicating a significant effect. The combination of breast care and oxytocin massage was proven effective in improving BM adequacy among postpartum mothers and can be recommended as a non-pharmacological approach to support exclusive breastfeeding programs.

Evaluating the contribution of behavioral, milking system, and environmental data to short-term milk yield prediction in commercial dairy cows using machine learning.

Estimation of genetic parameters for udder quarters milk yield and milking traits in Holstein cattle.

Ineffective breastfeeding is a common issue among post-cesarean mothers due to inadequate milk supply, postoperative pain, and psychological distress. This study aims to evaluate the effectiveness of oxytocin massage in improving breast milk production and release. A descriptive case study was conducted on a 27-year-old mother experiencing breastfeeding difficulties after cesarean delivery. Nursing interventions were provided over three consecutive days, including breastfeeding education, oxytocin massage, and emotional support. The results showed improved milk flow, reduced maternal anxiety, and better infant latch. Oxytocin massage proved to be an effective non-pharmacological intervention for addressing ineffective breastfeeding. This study recommends integrating oxytocin massage into postpartum nursing care.

AI modeling of Ag-ZnO milk dynamics in a squarely elevated electromagnetic tunnel with dynamic thermal modulation.

Safe and effective infant feeding requires precise coordination of sucking, swallowing, and breathing, yet disruptions in this coordination affect a significant number of infants. Altering sensory input, such as bottle nipple flow rate, is used to address poor coordination in infants. However, prior studies often compare different nipples used across different feeds, which introduces confounding variables and limits insight into neuromotor responses. To address this, we used infant pigs as a validated animal model to assess real-time neuromotor responses to dynamic changes in flow rate within a single feeding session using a custom, computer-controlled nipple. We collected high-speed biplanar videofluoroscopy, intraoral pressure, and respiratory data to evaluate kinematics, physiology, and coordination patterns. We found that while sucking and breathing rates remained stable, higher flow rates elicited greater tongue, hyoid, and thyroid translations, larger bolus sizes, and lower intraoral pressures. Notably, swallow rate increased, resulting in a shift to suck-swallow-breathe coordination, with swallows occurring earlier in the suck cycle and more frequently per breath. These changes suggest that infants rapidly adapt their motor output to changing sensory conditions. This study demonstrates that real-time flow variation significantly impacts feeding mechanics and coordination, highlighting the potential for sensory-based interventions rooted in motor learning and neuromotor rehabilitation principles. Understanding how infants dynamically adjust to sensory changes offers critical insights into feeding development and provides a framework for developing more effective interventions for infants with feeding disorders.NEW & NOTEWORTHY We developed a novel method to dynamically alter milk flow rate mid-feed in infant pigs to assess real-time neurophysiological responses. Unlike prior studies, our approach avoids confounding variables that would result from providing nipples of different flow rates during separate feeding sessions and reveals how motor output adapts to sensory input in real time, offering new insight into the neuromotor control underlying infant feeding.

Animal husbandry has long been a key component of agriculture, fulfilling essential nutritional needs. Technological advancements have gradually replaced human labor with machines, particularly in dairy farming, where the milking process is vital for income generation. Robotic milking systems have emerged as significant innovations, allowing for efficient, hygienic, and automated milking while reducing dependence on labor.This study aims to predict lactation milk yield (LMY) in Simmental cows during their first lactation period in robotic milking farms by using various factors, including Days in Milk (DIM), Status (S), Number of Inseminations (IN), Milk Flow Rate (MFR), Robot Rejection Rate (RRR), Rumination Time (RT), Time Spent in the Robot (TSR), Feed Amount in the Robot (FAR), Feed Consumption Rate in the Robot (FCRR), and Milking Frequency (MF). The analysis incorporates Classification and Regression Trees (C&RT) and Chi-squared Automatic Interaction Detector (CHAID) algorithms, identifying DIM as the primary predictor.The CHAID analysis revealed that newly calved cows (DIM < 30) had an average LMY of 5,692 L, while those receiving over 5.09 kg of feed achieved an average of 8,426 L. For cows in the 30 to 81 days of lactation, higher feed allocation correlated with increased milk yield. The CART algorithm confirmed these findings, establishing DIM as the most influential factor. Overall, robotic milking systems facilitate individualized management of dairy cows, optimizing factors such as feed allocation and milking frequency. By leveraging advanced algorithms to analyze these variables, this study highlights the potential for improving milk yield and animal welfare in modern dairy farming practice.

The kinetics of milk release is influenced by several factors, including the milking facility, which affects the milk emission profile and quality. In dairy goats, the typical working vacuum level is 41-44 kPa; higher levels negatively impact health, quality, and milkability traits. This study, which was conducted on a commercial dairy farm located in the Latium region (central Italy), evaluates the impact of two vacuum levels (38 kPa and 42 kPa) on the milk emission profile and somatic cell content in Saanen goats. Statistical analysis (one-way ANOVA) of 400 milk flow curves recorded from 100 goats in four different afternoon milking sessions (200 at 42 kPa and 200 at 38 kPa) showed no significant differences in terms of milk yield, total milking time, or bimodal curve percentage when using two different operating vacuum levels. However, the milk emission time was longer at 38 kPa (1.86 vs. 1.71 min), while the peak flow rate (1.04 vs. 0.96 kg/min) and blind time (0.32 vs. 0.24 min) were higher at 42 kPa. Somatic cell content decreased significantly as the working vacuum level decreased (2470 vs. 2167 × 1000 cells/mL). This is in line with current studies which suggest that high vacuum levels increase the risk of udder injury and intramammary infection. In conclusion, adjusting the milking machine to a working vacuum level of 38 kPa, and performing proper maintenance and routine checks, significantly improves somatic cell content, and, consequently, milk quality, in goats.

Background: Agalactia, a common lactation problem in postpartum women and a significant cause of breastfeeding failure, is a public health issue. It is a medical condition that leads to lactation insufficiency or complete failure due to inadequate breast milk production. Pharmacological interventions involve the use of galactogogues such as dopamine antagonists and hormonal therapy. Several medicinal plant extracts have been used to manage many medical conditions, including agalactia. The plant exudates called palm sap and wine obtained from several species of Borassus, Elaeis, Hyphaene, Phoenix, Raphia, Ancistrophyllum, Calamus, Eremospatha, Podococcus, and Sclerosperma are remedies for the management of agalactia in the southern states of Nigeria. This review presents a thorough literature evaluation on research findings on Raphia palm sap and wine and their ethnomedicinal uses as lactation inducers and enhancers of lactogenesis in post-partum and lactating mothers. Methods: Thoroughly crafted queries using an online search of Google Scholar and other bibliographic databases and a careful and rigorous search of published literature were performed using Raphia palm sap and wine ethnomedical uses. Relevant articles were retrieved and used for this review, covering two decades. Review Findings: Empirical evidence from various studies supporting the ethnomedicinal use of palm wine and sap to enhance breast milk flow in post-partum and lactating mothers was widely reported. Experimental studies of the effect of palm wine on the histology of the mammary gland of female Wistar rats showed mammoplastic effects on the postpartum mammary gland and consequently increased the quantity of breastmilk production. Compositionally, there are some similarities between the constituents of breast milk and Raphia palm wine both have basic vitamins and minerals in common, including phosphate, glucose/sugar, potassium, magnesium, calcium, lipids, sodium, chloride, protein, and appear whitish and milky. Raphia palm wine, a piquant drink, was also reported to contain vitamins A, C, E, B1, niacin, riboflavin, thiamine, β – ββ-carotene, alcohol, yeast, and water. Conclusion: The ethnomedicinal use of palm sap and wine as a remedy for enhancing lactogenesis in post-partum and lactating mothers is well reported. However, establishing the pharmacological basis to corroborate this position is yet to be elucidated.

Introduction: Breast milk duct obstruction, or bendungan ASI, is a common challenge experienced by breastfeeding mothers and can lead to complications such as mastitis if not addressed properly. Pijat Oketani is a specific massage technique known to facilitate breast milk flow and prevent duct blockage. Objective: The purpose of this community service activity was to increase mothers’ knowledge and skills in applying the Oketani massage technique as a non-pharmacological effort to prevent breast milk duct obstruction. Method: The activity was conducted on Wednesday, April 18, 2025, at the Puskesmas Sadananya service area, involving 25 breastfeeding mothers with infants aged 0–6 months. The method included a pre-test, interactive counseling, demonstration, hands-on practice, and post-test. Quantitative evaluation was conducted using a questionnaire and observation checklist. Result: There was a significant increase in participants’ knowledge, with average post-test scores rising from 56% to 88%. Additionally, 76% of participants were able to correctly perform the Oketani massage during the practice session. Participants reported feeling more confident and equipped to manage breastfeeding challenges independently. Conclusion: The Oketani massage technique can be effectively introduced through community-based education and hands-on training. This program has proven successful in empowering mothers to prevent breast milk duct obstruction and is recommended for wider implementation in maternal and child health promotion.

Background: Mother's milk (ASI) is the best natural nutrition for babies with the most appropriate nutritional content for optimal growth. Currently, there are still many mothers who do not breastfeed their babies. This is influenced by various factors, including breast milk not coming out immediately after giving birth or not producing breast milk (ASI). The reality in the field shows that low breast milk production in the first days after giving birth is an obstacle in providing breast milk early. In efforts to express breast milk (ASI), there are 2 things that influence it, namely production and expenditure. The production of breast milk (ASI) is influenced by the hormone prolactin, while production is influenced by the hormone oxytocin. The decrease in the production and release of breast milk (ASI) in the first days after giving birth can be caused by a lack of stimulation of the hormones prolactin and oxytocin which play an important role in smooth production and expenditure of breast milk (ASI). Several factors influence the flow and flow of breast milk (ASI), namely breast care, frequency of breastfeeding, parity, stress, illness or maternal health, consumption of cigarettes or alcohol, contraceptive pills, nutritional intake. Research Objective: To determine the effect of giving breast milk-stimulating drugs at 36-40 weeks of pregnancy for smooth breastfeeding after giving birth at PMB Bd. Elin Yulianengsih., S.Si.T. Research Method: The research design uses the One Group Pretest-Posttest form, namely a design that is observed twice, namely before and after being given breast milk-stimulating medication. Research Results: Based on the Paired T Test, it was found that Asymp Sig (2-tailed) was 0.000 < 0.05, meaning that Ho was rejected and H1 was accepted, so it can be said that there is a significant influence between the administration of breast milk-stimulating drugs on breast milk production in breastfeeding mothers at PMB Bd. Elin Yulianengsih. Conclusion: There is an influence between the administration of breast milk-stimulating drugs on breast milk production in mothers after giving birth at PMB Bd. Elin Yulianengsih.

Invited review: Contribution of milk harvesting research to optimal interaction between biology and milking technology.

Problems that can arise in pregnant women who do not do breast care during pregnancy include nipple pain, breast swelling, mastitis, breast abscess, and irregular breast milk flow. The purpose of this study was to determine the relationship between pregnant women's knowledge and breast care behavior at the BP Annisa Banyuasin Clinic. The design of this study was a correlation with a cross-sectional approach. The sample was 60 pregnant women with a cross-sectional technique. The independent variable is the knowledge of pregnant women and the dependent variable is breast care behavior. Data collection used questionnaires and breast care checklists. Data processing techniques used Editing, Coding, Scoring, Tabulating and statistical tests using the Chi Square test. The results of this study were obtained from 60 respondents, almost half showed poor knowledge and bad behavior, 25 respondents with a percentage (41.6%). For good knowledge and bad behavior, there are 8 respondents with a percentage (13.3%). And those who have good knowledge and good behavior are 18 respondents with a percentage (30%). From the data above, statistical analysis was then carried out using the chi Square test using SPSS 17. The results of the analysis of chi Square p value = 0.001. The results of the analysis in this study, the p value (0.004) is smaller than the α value (0.05), then H0 is rejected and H1 is accepted so that it can be concluded that there is a significant relationship between the knowledge of pregnant women and breast care behavior at the BP Annisa Clinic, Banyuasin Regency.

Breast milk production is significantly influenced by hormonal and psychological factors, one of which is stimulation of the hormone oxytocin. Oxytocin massage is a simple technique that can be performed by family members to stimulate breast milk production. This community service program aims to provide oxytocin massage training to families of breastfeeding mothers as a promotional intervention to increase breast milk production. The activity was implemented through counseling, demonstrations, hands-on practice, and follow-up mentoring for 25 families in Sukamaju Village. Evaluation results showed an increase in family knowledge and skills in performing oxytocin massage, as well as a positive impact on breast milk flow. This training has proven effective and can be recommended as a routine program in pregnancy and breastfeeding classes at the community level.

To study behavioral and productive factors to detect changes that may indicate and predict clinical mastitis cure, Holstein dairy cows (n = 60), in an automatic milking system (AMS) and equipped with behavioral monitoring collar, were monitored from the diagnosis of clinical mastitis (D0) until clinical cure. The parameters collected through sensors were feeding activity, milk electrical conductivity (EC), milk yield, Mastitis Detection Index (MDi), milk flow, and number of gate passages. Clinical mastitis cases (n = 22) were monitored and divided into cured cases (n = 14) and non-cured cases within 30 days (n = 8), paired with a control case group (n = 28). Cows were assessed three times per week, and cure was determined when both clinical assessment and California Mastitis Test (CMT) results were negative in three consecutive evaluations. Mixed generalized linear regression was used to assess the relationship between parameters and clinical mastitis results. Mixed generalized logistic regression was used to create a predictive model. The average clinical cure time for cows with clinical mastitis was 11 days. Feeding activity, gate passages, milk yield, milk flow, EC, and the MDi were associated with cure. The predictive model based on data from D0 showed an Area Under the Curve of 0.89 (95% CI = 0.75–1). Sensitivity and specificity were 1 (95% CI = 1–1) and 0.63 (95% CI = 0.37–0.91), respectively. The predictive model demonstrated to have good internal sensitivity and specificity, showing promising potential for predicting clinical mastitis cure within 14 days based on data on the day of clinical mastitis diagnosis.

Overmilking occurs when the teat cups remain attached to the udder during milking, even though there is little or no milk flow. This puts pressure on the teat tissue and reduces milk production due to longer milking times, meaning fewer cows are milked per hour. Therefore, the correct removal of the teat cup at the end of mechanical milking is crucial for the milking process. The aim of this study was to describe the factors influencing automatic teat cup removal (ATCR) at the end of mechanical milking and to demonstrate its importance for udder health, milk production and milk quality. There are considerable differences between milking system suppliers and countries regarding the minimum removal of the teat cup at the end of the milking process. However, to ensure good milk quality, prevent teat damage and reduce the risk of mastitis, it is important to shorten the working time of the milking machine on the udder in both automatic and conventional milking systems. For this reason, several studies have shown that increasing the milk flow switch point effectively reduces milking time, especially in automatic milking systems where dairy cows are milked more than twice a day. However, when the ATCR setting was increased above 0.5 kg·min−1, milk production decreased, and the number of somatic cells in the milk produced increased. Therefore, the use of ATCR at a milk flow rate of 0.2 kg·min−1 significantly increased milk production, improved milk quality and maintained udder health when a low vacuum level (34–36 kPa) was used in milking machines such as MultiLactor and StimuLactor (Siliconform, Germany). In conclusion, ATCR at a milk flow of 0.2–0.3 kg·min−1 is a useful level to achieve various goals on dairy farms when a low vacuum of 34–36 is used in the milking machine. If the milking machine uses a higher vacuum, it is possible to program a higher ATCR at a milk flow of up to 0.5 kg·min−1.

This study analyzes the fluctuating dynamics of milk flow containing silver and magnesium oxide nanoparticles in a parabolically elevated electromagnetic channel exposed to a parabolic thermal ramp-up, employing artificial intelligence (AI)-based machine learning algorithms in Python. This study unifies key physical phenomena comprising thermal heat flux, heat sinks, and porous medium's impendence. Employing rigorous mathematical and computational methods such as the Laplace transform for streamlined solutions to dynamic flow equations, we analyze milk flow dynamics, concentrating on variables like shear stress (SS) and rate of heat transfer (RHT), and presenting results through detailed graphical representations. The findings indicate that nanoparticles significantly enhance thermal conductivity and viscosity, thereby improving heat transport efficiency and modifying flow dynamics. Notably, an elevation in milk momentum is observed with a higher modified Hartmann number, while wider electrode widths help mitigate this effect. In milk flow, escalated pressure oscillation frequencies intensify SS, and elevated heat source parameters enhance RHT. The AI-based machine learning algorithms in Python, reinforced by artificial neural networks, achieves 100% precision in SS prediction on both training and validation datasets and maintains 99.974% accuracy on testing datasets and 99.93% during cross-validation for RHT predictions. The model findings highlight the potential of nanoparticle-enhanced milk for efficient heating, crucial to improving pasteurization and sterilization. Python AI algorithms enable real-time control, boosting efficiency, quality, and sustainability in dairy processing.