Automatic Milking Research Articles

Exploring baseline behaviour in group-housed, pre-weaned dairy calves

With increasing public concern for farm animal welfare, understanding their current welfare status is paramount. Animal welfare can be inferred from their behaviour, as behaviour represents the combination of internal and external cues. The aims of this study were to quantify a behavioural baseline for group-housed, pre-weaned dairy calves that were reared under conventional management conditions, and to determine how different internal (i.e. age) and external (i.e. temperature) factors affected this behaviour. Female dairy calves (n=47) were allocated to 1 of 3 pens based on birth date and reared under conventional Irish management conditions; after 3-4 d in individual pens, calves were moved into group pens where they had ad libitum access to water, concentrates, and forage (first barley straw, then hay). Milk replacer (6L/d) was fed through an automatic milk feeder; calves were gradually weaned from day 42 to 84. A 24h period/week of video recording was used for behaviour scoring for 8 consecutive weeks (scan sampling at 10-min intervals). Behaviours included posture (lying or standing) and activity (17 behaviours). Calves were scored for clinical health twice weekly and only healthy calves were used in the analysis (n=39). Behaviour proportions were analysed using generalised linear mixed models. Proportion of time spent lying decreased as calves aged (week 1 vs. 9; percentage mean ± standard deviation; 79.8 ± 4.04 vs. 72.1 ± 6.52%; P=0.004), while time spent ruminating (2.0 ± 2.51 vs. 14.1 ± 8.72%; P<0.001), eating bedding (0.8 ± 1.16 vs. 6.1 ± 4.66%; P<0.001), eating forage (0.9 ± 1.20 vs. 1.8 ± 1.81%; P=0.007), and eating concentrates (0.5 ± 1.15 vs. 2.2 ± 1.72%; P=0.018) increased with age. On days when the minimum shed temperature was <4°C compared to >6°C, calves spent more time lying (75.9 ± 5.27 vs. 72.3 ± 5.78%; P<0.001) and less time eating concentrates (0.8 ± 1.11 vs. 1.4 ± 1.49%; P=0.035), eating forage (0.8 ± 0.91 vs. 1.5 ± 1.57%; P=0.005), eating bedding (2.7 ± 2.87 vs. 4.0 ± 4.78%; P=0.003), and walking (1.5 ± 1.20 vs. 2.0 ± 1.40%; P=0.017), independent of age. These findings provide a normal behaviour baseline for future calf behaviour studies and highlight potential areas of improvement in current, conventional calf rearing practices.

Predictive Models for the Implementation of Targeted Reproductive Management in Multiparous Cows on Automatic Milking Systems

Targeted reproductive management (TRM) aims to improve the fertility efficiency of the dairy herd by applying group-level management strategies based on expected reproductive performance. Key to the utility of TRM is the accuracy with which an animal's reproductive performance can be predicted. Automatic milking systems (AMS) allow for the collection of data relating to milk quantity, quality, and robot visit behavior throughout the transition period. In addition to this, auxiliary data sources such as rumination and activity monitors, as well as historical cow-level data are often readily available. The utility of this data for the prediction of fertility has not been previously explored. The objective of this study was first, to assess the accuracy with which the likelihood of expression of oestrus between 22 and 65 d in milk (DIM) and conception to first insemination between 22 and 80 DIM could be predicted using data collected by AMS from 1 to 21 DIM. Our second objective was to assess the change in model performance following the addition of 2 auxiliary data sources. Using data derived solely from the AMS (RBT data set) a binary random forest classification model was constructed for both outcomes of interest. The performance of these models was compared with models constructed using AMS data in conjunction with 2 auxiliary sources (RBT+ data set). Expression of oestrus was classified with an area under the receiver operator curve (AUC-ROC) of 0.6 and 0.65, conception to first insemination with an AUC-ROC of 0.56 and 0.62 for the RBT and RBT+ data sets respectively. No statistically significant improvement in classification accuracy was achieved by the addition of auxiliary data sources. This is the first study to report the utility of data collected by AMS for the prediction of reproductive performance. Though the performance described is comparable with previously reported models, their utility for the implementation of TRM is limited by poor classification accuracy within key sub-groups. Of note within this study is the failure of the addition of auxiliary data sources to increase the accuracy of prediction over models built using AMS data alone. We discuss the advantages and limitations the integration of additional data sources imposes on model training and deployment and suggest alternative methods to improve performance while preserving model parsimony.

Reasons for milking system adoption: The case of Switzerland

This paper studies the importance which farm managers attach to the investment in the milking system in terms of their (management) objectives and expectations. According to a survey of 455 Swiss farm managers, the main reasons for investment decisions for all milking systems were to reduce labour and physical stress. For parlours, income objectives and animal welfare were more important than for other milking systems. In the case of automatic milking systems (AMS), the focus was on making working hours more flexible and increasing family time. According to farm managers, these objectives were largely achieved. The study shows, that higher income or production volume become less important reasons over the observed time period and that AMS are implemented by older farm managers.

Selective Dry Cow Therapy: Clinical Field Trial on Prevention and Cure of Intramammary Infections

Intramammary antibiotic dry cow therapy (DCT) at the end of lactation is one of the key measures in the management and control of bovine mastitis. Currently, livestock production is under pressure to reduce antibiotic consumption, emphasizing the need to avoid medicating all cows at dry-off, and instead to treat only infected cows. The study objective was to evaluate IMI cure risk, new IMI risk, and post-calving IMI risk between DCT-treated and untreated quarters over the dry period. The sample totaled 269 cows from 12 Finnish automatic milking system herds entering the dry period between 2019 and 2021. Cows eligible for the study had a final DHI test-day SCC ≥ 100,000 cells/mL and had no clinical signs of mastitis. Based on odd or even identification numbers, cows with an SCC between 100,000 and 250,000 cells/mL were sequentially assigned to either receive DCT at dry-off (DCT100-250) or remain untreated (NoDCT100-250). All cows with an SCC > 250,000 cells/mL received DCT (DCT > 250). No quarters received teat sealants. Farmers collected aseptic quarter-milk samples for microbiological quantitative real-time PCR (qPCR) analysis 0 to 4 d before dry-off and 0 to 4 d after calving. The outcome of the statistical model was the odds of a quarter having an IMI at freshening 0 to 4 d after calving. The statistical tool was a generalized linear mixed-effects model with logit link function and 2-level random intercepts, cows nested within herds. Quarter-level IMI prevalence at dry-off was NoDCT100-250 17.6% (45/256), DCT100-250 22.2% (83/374), and DCT > 250 32.0% (132/413). Quarter-level IMI prevalence at freshening was NoDCT100-250, 36.2% (84/232), DCT100-250, 13.6% (50/369), and DCT > 250, 11.6% (46/397). The untreated quarters in the NoDCT100-250 group had a 1.1 times higher risk of failing to cure over the dry period than did the treated quarters in the DCT100-250 group (unadjusted RR 1.10, 95% CI 0.94-1.28) and a 1.2 times higher risk than the treated quarters in the DCT > 250 group (unadjusted RR 1.15, 95% CI 1.00-1.33). The untreated quarters in the NoDCT100-250 group had a 1.5 times higher risk of having a new IMI over the dry period than did the treated quarters in the DCT100-250 group (unadjusted RR 1.48, 95% CI 1.35-1.63) and a 1.4 times higher risk than the treated quarters in the DCT > 250 group (unadjusted RR 1.35, 95% CI 1.23-1.49). The principal cause of new IMI was NAS, followed by Streptococcus dysgalactiae. Quarters in the NoDCT100-250 group had 6.6 times higher odds for having an IMI at freshening than did quarters in the DCT100-250 group (95% CI 3.52-12.21). According to our findings within the framework of this experiment, selectively DCT-treated cows with an SCC between 100,000 and 250,000 cells/mL at dry-off demonstrated that, although the group-specific cure risks over the dry period were high, untreated quarters had a higher risk of acquiring a new IMI over the dry period than did treated quarters, highlighting the effectiveness of DCT in reducing IMI risks. The prophylactic use of antibiotics, however, is not recommended, and in some countries is even prohibited.

Addition of the By-Pass Fat into Diet of Awasi Sheep on Milk Composition

By-pass fat is an important source of essential fatty acids for ruminants. It affects yield rather than maintenance requirements. This study was carried out to investigate the effect of adding by-pass fat into diet of dairy sheep on milk components. The study was carried out in a private dairy sheep farm in Konya. For this purpose, 99 Awassi sheep were used after 1 month of the birth during the fresh lactation period. The sheep were randomly divided into 2 groups, the control (C) group (n=54) was fed with total mixed ration (TMR) twice a day, the by-pass fat (BF) group (n=45) was fed with TMR twice a day and 30 g/day of commercial Ca-soap palm oil by-pass fat was given individually during milking. The trial last 15 days with 11 days of adaptation and 4 days of sample collection. The animals in the experimental group consumed 30 g/day of Ca-soap by-pass fat individually during morning milking. The animals were milked for once with an automatic milking system and the lambs were suckled for once by creep. Milk yields of the animals were recorded automatically during the sample collection period, also 50 ml milk samples were taken from each animal at the milking times on the 2nd and 3rd days, and milk fat, non-fat dry matter, protein, lactose, density, freezing point, and somatic cell counts were determined. Fat, non fatty dry matter, density, protein, lactose and somatic cell were respectively; 4.50±0.14 and 5.65±0.17%, 10.86±0.07 and 11.16±0.12%, 34.66±0.45 and 34.33±0.64%, 5.42±0.06 and 5.70±0.10%, 4.49±0.01 and 4.47±0.01%, 121.556±16987 and 171.222±28348 in the C and BF groups, Among milk components, while fat, nonfat dry matter and protein were higher in BF group than C group (p&lt;0.05), density, lactose and somatic cell were similar between groups (p&gt;0.05). It can be concluded that the even though addition of 30 g of Ca soap by-pass fat significantly improved milk fat, non-fat dry matter and protein in dairy sheep fed with TMR at the level of maintenance and yield.

Studying the relationship of the type of higher nervous activity with the milk productivity of cows

The purpose of the presented research was to study the influence of the type of higher nervous activity (HNA) on the secretion of organic components of milk in various milking conditions. The studies were carried out in 2 periods. The first period was standard, and in the second there was a conditioned stimulus - the presence of an outsider. Black-and-white cows were assigned to four types of higher nervous activity: type 1 - strong, balanced; type 2 - strong, unbalanced; 3 - strong, inert; 4 - weak, inhibitory. In the first period, type 2 cows showed a significant decrease in the amount of milk, fat and glucose, but the mass fraction of protein in milk tended to increase separately for each milking by 0.22 %. The ratio of the mass fraction of protein to the percentage of lactose for two milkings was significantly higher by 0.06, in relation to type 1. In type 3, in general, for two milkings, an increase in lactose by 13.3 g, fat - by 7.0 g was noted, in contrast to the indicators of the first type. Animals of the fourth type tended to reduce milk secretion to 18.3 %. Also, the mass fraction of fat in milk was lower to 0.53 % (P &lt; 0.05) and protein to 0.28 %, and the proportion of lactose in milk, on the contrary, was consistently higher in both milkings by 0.25-0,26 % (P &lt; 0.05). In the second period (with a conditioned stimulus), cows of the second group showed a positive trend towards an increase in the mass fraction of protein in the morning with machine milking by 0.26 % (P &lt; 0.05), and with manual milking by 0.32 % (P &lt; 0.05), in relation to the first group. The mass fraction of fat during machine and manual milking in animals of the second type tended to decrease. In the third group, the indicators of milk of the first streams in the morning were higher by 0.99 % (P &lt; 0.05) - fat, by 0.33 % - protein, by 0.09 % - lactose, in relation to the first type of higher nervous activity. In cows with a weak, inhibitory nervous system, the influence of the conditioned stimulus contributed to a decrease in the ratios of the mass fraction of fat and protein in milk to lactose to 0.14 and 0.09, compared with type 1 cows.

Reducing life cycle environmental impacts of milk production through precision livestock farming

In recent decades, the livestock sector has significantly improved its efficiency, productivity, and environmental sustainability. Precision Livestock Farming (PLF) represents a driver in this direction, since it enables to monitor individual animals and herds, and supports the farmer in making better decisions. Although the benefits are clear on a livestock perspective, it is difficult to quantify the environmental benefit of having technology on farm, mostly due to the complexity of collecting data on the same farm before and after a certain solution.In this context, this paper focuses on the assessment of the environmental sustainability of a case-study Italian dairy cattle farm where different technologies were installed one by one: first a mechanical ventilation system (MV) and second an automatic milking system (AMS), without introducing other significant changes to the farm management and practices in the meantime. The environmental impact of milk production on the farm was quantified through the Life Cycle Assessment (LCA) method, and the initial farm configuration was compared with the two scenarios in which each technology was incorporated. Fat and protein corrected milk (FPCM) was used as Functional Unit, and a cradle to farm gate system boundary and biophysical allocation method were selected. This enabled to provide valuable insights for stakeholders about the effect on the environmental sustainability of the use of the two technologies. The results show that for all the evaluated impact categories there is an environmental benefit of the improved scenarios. The biggest benefit can be observed with the installation of mechanical ventilation, to which correspond benefits in terms of animal health, welfare and productivity. Then, also AMS entails sustainability improvements, mainly linked with increased efficiency and productivity. In conclusion, the use of technology on dairy farms improves not only the farm efficiency and the animal management, but also the environmental sustainability. Furthermore, the rapid technological advancements may further enhance this positive trend in reducing the contribution of livestock farming to the environmental impacts provided that farmers adopt them.

Comparing the Performance of Automatic Milking Systems through Dynamic Testing Also Helps to Identify Potential Risk Factors for Mastitis.

Automatic milking systems (AMSs) are revolutionizing the dairy industry by boosting herd efficiency, primarily through an increased milk yield per cow and reduced labor costs. The performance of milking machines, whether traditional or automated, can be evaluated using advanced vacuum meters through dynamic testing. This process involves scrutinizing the system and milking routine to identify critical points, utilizing the VaDia™ logger (BioControl AS, Rakkestad, Norway). Vacuum recordings were downloaded and analyzed using the VaDia Suite™ software under the guidance of a milking specialist. Access to data from AMSs across various manufacturers and herds facilitated a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands while identifying potential mastitis risk factors. Using the proper statistical procedures of SPSS 29.1 (IBM Corp., Armonk, NY, USA), researchers analyzed data from 4878 individual quarter milkings from cows in 48 dairy herds. Results indicated a significant variability in milking parameters associated with quarter milk yield and AMS brand. Notably, despite AMSs standardizing teat preparation and stimulation, this study revealed a surprisingly high frequency of two major mastitis risk factors-bimodality and irregular vacuum fluctuations-occurring more frequently than in conventional milking systems. This study, one of the few comparing different AMS brands and their performance, highlights the crucial role of dynamic testing in evaluating AMS performance under real-world conditions.

Association between automatic milking system parameters and intramammary infections in dairy cows at dry-off

IntroductionThe current global concern over increasing antimicrobial resistance among animal and human pathogens has motivated efforts to reduce antimicrobial drug use in food animals and its impact on antimicrobial resistance. One such strategy is to use selective dry cow therapy (SDCT) in dairy cows, which involves treating only cows with intramammary infection (IMI) at dry-off. However, efficient methods are needed to identify cows with IMI at dry-off to implement SDCT. Automatic Milking Systems (AMS) data may help farmers identify cows with IMI when individual Somatic Cell Count (SCC) is not routinely tested. This study assessed the correlation between cow-level and quarter-level AMS parameters and IMI at dry-off.Methods &amp;amp; ResultsA total of 733 udder quarters (comprising both Primiparous [PRIM] and Multiparous [MULT] cows) were sampled and categorized for IMI based on bacterial growth and SCC. Data were aggregated both daily and into 7-day and 15-day intervals preceding dry-off. The quarter-level prevalence of bacterial growth at dry-off was 24.28% overall. When stratified by parity, logistic regression analysis at 15 days to dry-off revealed that the average difference in mastitis detection index (MDi) in PRIM, MDi, and standard deviation milk flow rate in MULT were associated with increased odds of IMI at dry-off. Similarly, data from 7 days to dry-off revealed that average peak milk flow rate in PRIM, and MDi in MULT were associated with increased odds of IMI at dry-off. However, an increase in average milk yield was associated with decreased odds of IMI.Discussion &amp;amp; ConclusionOur findings underscore the significance of MDi, milk flow rate, peak milk flow rate, and milk yield in predicting IMI at dry-off. Notably, stronger associations were observed with data collected 7 days preceding dry-off. Further research is warranted to refine and validate algorithms amalgamating these variables for precise IMI prediction in cows at dry-off.

A computer vision approach for the automatic detection of social interactions of dairy cows in automatic milking systems

The integration of digital technologies and Artificial Intelligence (DT&amp;AI) in veterinary practice is one of the key topics to improve Herd Health Management (HHM). The HHM includes the prevention of diseases, the assessment of the welfare, and the sustainability production of farm animals. In dairy cattle farming, particular attention is paid to automatic cow detection and tracking, as such information is closely related to animal welfare and thus to possible health issues. Cows are highly social animals; therefore, a better comprehension of social context can help improve their management and welfare. In the field of Precision Livestock Farming, computer vision represents a suitable and non-invasive method for automatic cow detection and tracking. In this study, we developed and tested the reliability of a deep learning-based computer vision system for the automatic recognition of dairy cows in a barn equipped with Automatic Milking System. We aimed to build the social network of 240 dairy cows (primiparous and multiparous) to understand how social interactions can influence their welfare and productivity.

Different Types of Milk Flow Curves and Factors Affecting Milkability in Buffalo Species

Buffaloes are characterized by longer teats and teat canals and stronger muscular resistance of the teat wall than cattle; it is necessary to have a high vacuum level to open the teat canal and begin milk ejection. In buffalo milking management, milk yield, and flow profiles are essential parameters to record and evaluate. The milking machine is a critical point, and the characteristics of the milking vacuum and the pulsation rate are closely related to milk flow observations. In Italy, the most used vacuum levels are 44-46 kPa (range 40-53 kPa). The data on the milkability traits of the Mediterranean Italian breed made it possible to classify eight different types of milk flow curves due to anatomical, physiological, and management differences. This study aims to evaluate the main factors influencing milkability in dairy buffaloes. The results suggest the detachment of the milking cluster to reduce the decreasing and blind phases with the following advantages: reduction of the total milking time and consequently of the worker's time, improvement of the farmer's profitability and milk quality through decreasing the incidence of mastitis. Milk ability is influenced by physiological, sanitary, management, and genetic factors. In Mediterranean Italian buffaloes milked with the Automatic Milking System (AMS), a considerable variation in milk ejection and, consequently, in the milk flow curve was found compared to the conventional one, with better pre-stimulation, independent milk ejection for each teat, optimal milking of all quarters. In conclusion, continuous milkability monitoring will help optimize milking practices by reducing labor time and increasing farmers’ income through better milk quality. In addition, the identification of buffaloes with desirable types of milk flow curves could be helpful for buffalo breeders’ associations to address farmer management and to define potential new breeding objectives.

PSXI-30 Economic impact of pre-training on dairy cattle automatic milking system acclimation

Abstract Pre-training in automatic milking systems (AMS) has the potential to increase milk production and milk quality. In a recent study, cows that experienced pre-training (TRT; i.e. intentional training access with an AMS prior to first AMS milking) had greater milk yield and fat percentages compared with no pre-training (38.4 vs. 37.6 ± 0.2 kg/d; 4.75 vs. 4.38 ± 0.06%; P &amp;lt; 0.01, and &amp;lt; 0.01 respectively). Similarly, cows without pre-training had greater somatic cell count (SCC; 298,860 vs. 188,220 ± 10,700 cells/mL; P &amp;lt; 0.001). The time required for pre-training could be a limiting factor (40 ± 10 h/wk), and the economic implications of labor versus long-term benefits must be examined. To that end, a stochastic simulation tool was developed to consider the increased costs of labor and the potential benefits of improved milk yield, milk fat percentage, and decreased somatic cell count. The GRKS distribution with minimum, mean, and maximum values was used to model increases in milk yield (0, 1.4, 1.8 kg), fat percentage (0, 3.5%, 4.5%), and labor cost ($0.0011, $0.0016, $0.0020 per h) and decreases in SCC (0, 120, 130 x 103 cells/mL) per hundredweight of milk produced. Baseline values for milk production ranged from 14.7 to 59.2 kg/cow/d in 4.4 kg increments with fat percentage of 3.5% and SCC of 312,000 cells/mL. The model assumed a minimum increase across milk yield, fat, and SCC of 0 (no change). The Simetar add-on in Microsoft Excel simulated 500 iterations across three herd size scenarios (60, 120, and 480 cows) and calculated the marginal return on investment across a 90-d period for all milk production ranges. Regardless of starting milk production level, pre-training had a positive economic impact across all levels (30 to 50 h) and herd sizes (Table 1). Financial impact per cow per d with input of 30, 40, and 50 h ranged from $0.58 to $0.73, $0.56 to $0.71, and $0.54 to $0.70. The majority of simulations returned a positive marginal impact for pre-training. If pre-training resulted in a loss, it ranged from $242 to $1,937, $323 to $2,585, $405 to $3,246, across 30, 40, and 50 hours, respectively. Based on these results, the investment in pre-training time was consistently beneficial for simulated herds.

517 The effects of pellet starch concentration and allocation amount for Holstein cows in peak, mid, and late lactation in an automatic milking system

Abstract This study evaluated the effects of pellet starch concentration and amount of pellet delivered in an automated milking system (AMS) on AMS pellet and partial mixed ration (PMR) intake, milk and milk component yield, and milking and feeding behavior for Holstein cows at different stages of lactation. Twenty-four Holstein cows at peak [n = 8; 85 ± 25.7 days in milk (DIM)], mid (n = 8; 185 ± 35.1 DIM) or late (n = 8; 290 ± 69.5 DIM) lactation (3 squares/DIM category), housed in a free-stall barn with a feed-first guided traffic flow AMS, were used. Treatments included low (LS; 24% DM) or high (HS; 34% DM) starch pellets that were provided at low (LA; 2 kg/d DM) or high (HA; 6 kg/d DM) quantities within replicated 4 × 4 Latin square design. Each period lasted 21 d including 16 d of adaptation and 5 d of data and sample collection to evaluate feed intake and behavior, milking characteristics, milk and milk component yields. Pellet starch did not affect the amount of pellet consumed, but HA cows consumed more pellet than LA (4.3 vs. 1.8 kg/d; P &amp;lt; 0.01). Relative to LA, HA had greater pellet refused in the AMS (P &amp;lt; 0.01) and decreased PMR intake (P = 0.04). Total DMI was 1.3 kg/d greater for HA than LA cows (P = 0.05). Pellet starch and DIM did not affect PMR intake or DMI. Neither pellet starch nor allocation affected the number of PMR meals; however, LA increased PMR eating time by 20 min/d (P &amp;lt; 0.01) and PMR meal length by 2 min/meal (P = 0.03). Milking frequency was not affected by pellet starch or DIM, but HA tended to increase total milking frequency (2.7 vs. 2.6 no/d; P = 0.06) over LA, with greater voluntary milkings (2.5 vs 2.3 no/d; P &amp;lt; 0.01). Milk yield/visit and milking duration were not affected by pellet starch or allocation. Milk yield was not affected by pellet starch, or the amount allocated averaging 43.2, 41.3 and 43.2 kg/d for peak, mid, and late lactation cows (P ≥ 0.19). Compared with LS, HS decreased milk fat concentration (4.1 vs 3.9%; P &amp;lt; 0.01) and providing the HA reduced milk fat concentration (4.1 vs 3.96%; P &amp;lt; 0.01) when compared with LA; however, neither pellet starch nor allocation affected fat yield, averaging 1.67 kg/d (P ≥ 0.15). True protein yield was not affected. Cows fed the LA had greater milk urea nitrogen (14.8 mg/dL) relative to HA (14.3 mg/dL; P = 0.03). Increasing the amount of pellet allocated in the AMS reduced PMR intake, while increasing total DMI and resulted in greater amounts of pellet refusals by cows; however, greater amounts of pellet may increase attendance at the AMS without affecting milk or milk component yields. Starch concentration of the pellet had little effect on productivity.

Effects of subclinical mastitis on automatic milking system data, hematological and biochemical parameters, and milk composition in Holstein cows.

Subclinical mastitis decreases milk production and quality, despite the normal appearance of the mammary glands and milk. Herein, we aimed to investigate changes in factors monitored via automatic milking systems (AMS) prior to subclinical mastitis onset and identify differences in hematological and biochemical parameters and milk composition at subclinical mastitis onset. Thirty-two Holstein cows were divided into two groups according to somatic cell counts (SCC) from AMS and milk composition analysis and the California mastitis test (CMT): healthy cows (controls [CON], n=16, SCC <500×103 cells/ml and negative for CMT) and cows with subclinical mastitis (SCM, n=16, SCC ≥500×103 cells/ml and positive for CMT). Eventually, 121 milk samples from the CON ([mCON], n=60) and SCM ([mSCM], n=61) groups were obtained; SCM samples were categorized as those from non-inflamed (mNQ) or subclinically-inflamed (mIQ) quarters. We evaluated AMS factors; hematological, biochemical, and milk composition parameters; and bacterial isolation. In cows with SCM, milk yield decreased and electrical conductivity (EC) changed before disease onset. Milk EC decreased in mNQ although increased in mIQ (p<0.05). The SCM group had higher globulin levels and lower basophil counts; albumin-to-globulin ratio; and total cholesterol, albumin, and blood urea nitrogen levels than the CON group (p<0.05). The mIQ group had higher SCC but lower levels of lactose and milk solids-not-fat than those in the mCON and mNQ groups (p<0.05). The mCON group had higher levels of milk non-protein nitrogen than the mNQ group (p<0.05). Opportunistic mastitis pathogens were isolated in the mIQ group. Changes in milk yield and EC measured using AMS occurred prior to subclinical mastitis, which may be associated with variation in basophil counts; albumin-to-globulin ratio; and total cholesterol, albumin, BUN, globulin, SCC, milk lactose, and milk solids-not-fat levels at disease onset. These findings provide new insights into early-stage subclinical mastitis.

On Developing a Machine Learning-Based Approach for the Automatic Characterization of Behavioral Phenotypes for Dairy Cows Relevant to Thermotolerance

The United States is predicted to experience an annual decline in milk production due to heat stress of 1.4 and 1.9 kg/day by the 2050s and 2080s, with economic losses of USD 1.7 billion and USD 2.2 billion, respectively, despite current cooling efforts implemented by the dairy industry. The ability of cattle to withstand heat (i.e., thermotolerance) can be influenced by physiological and behavioral factors, even though the factors contributing to thermoregulation are heritable, and cows vary in their behavioral repertoire. The current methods to gauge cow behaviors are lacking in precision and scalability. This paper presents an approach leveraging various machine learning (ML) (e.g., CNN and YOLOv8) and computer vision (e.g., Video Processing and Annotation) techniques aimed at quantifying key behavioral indicators, specifically drinking frequency and brush use- behaviors. These behaviors, while challenging to quantify using traditional methods, offer profound insights into the autonomic nervous system function and an individual cow’s coping mechanisms under heat stress. The developed approach provides an opportunity to quantify these difficult-to-measure drinking and brush use behaviors of dairy cows milked in a robotic milking system. This approach will open up a better opportunity for ranchers to make informed decisions that could mitigate the adverse effects of heat stress. It will also expedite data collection regarding dairy cow behavioral phenotypes. Finally, the developed system is evaluated using different performance metrics, including classification accuracy. It is found that the YoloV8 and CNN models achieved a classification accuracy of 93% and 96% for object detection and classification, respectively.

Association of Dry Period Length with Automatic Milking System, Mastitis, and Reproductive Indicators in Cows.

The objective of this study was to evaluate the association between dry period (DP) length and various indicators of productivity, reproduction, and udder health in cows managed with an automatic milking system. We analyzed records from 3861 cows, categorizing them into three groups based on their DP duration: (1) <40 days, (2) 40-70 days, and (3) DP > 70 days. Cows with a DP of 40-70 days had an average energy-corrected milk production that was 8.2 kg greater than that of cows with a short DP and 5.0 kg greater than that of cows with a long DP (p < 0.001). Milk from the 40-70-day DP group exhibited the highest lactose concentration (4.64 ± 0.01%). Additionally, cows with the longest DP had the smallest proportion of animals with a milk fat-to-protein ratio of 1.2 to 1.4. Cows with a DP of 40-70 days also showed the lowest milk electrical conductivity across all udder quarters, whereas cows with the shortest DP had the highest conductivity. The highest conception rates were observed in the group with the shortest DP. These results suggest that a DP of 40-70 days is optimal for maximizing milk production and improving both udder health and reproductive performance under AMS. Proper management of DP duration can be an effective strategy for sustainable dairy herd management.

Kazakhstan dairy market: guidelines for optimization

Milk plays an important role in human life as obligatory and necessary food product, containing the most valuable and easily digestible proteins, fats, carbohydrates, and minerals. The goal is to show the current state of dairy industry in Kazakhstan, factors influencing its development. The economic parameters of production of milk and dairy products, dynamics of production volumes, and the number of cattle by type of management have been studied. The methods are based on the study of domestic and analytical reviews, scientific publications, and statistical information. Results – there is a shortage of raw materials for processing enterprises, their low quality, and a large number of small producers. The authors state that homemade milk from private farms does not meet technological standards, which, in turn, is the reason for poorquality industrial processing of raw materials. Domestic producers satisfy the need only for liquid processed milk and cream (94.9%). Conclusions – indicators that have restraining effect on development of dairy industry in the republic are considered, the need for technological reequipment, formation of cluster structures, and state support for Kazakh producers is pointed out. Compliance with raw milk quality standards is only possible when using the latest methods for obtaining and primary processing of raw milk. To achieve an effect, subsidies for technical equipment are required, especially for small-scale farms (milking and refrigeration machines, disinfectants, express control analyzers, etc.). Forecasts for consumption of dairy products assume the ability to determine in the future the volumes and structure of market demand for this type of product. The fundamental factors are the level of income, trends in changes in retail prices, degree of market saturation, national and historical traditions.

Key udder health parameters on dairy farms with an automated milking system

Despite the increasing use of automated milking systems (AMS), udder health performance of farms has only been limitedly quantified on farms with a milking robot. The objective of this study was to quantify udder health parameters (UHP) at test-day and at herd level on robotic farms using routinely collected somatic cell counts (SCC) from test-day data, and to study the correlations between these UHP. Additionally, the associations between UHP and season, year and farm size as well as the association between the daily milk production and the herd milk SCC were investigated. To this end, we collected SCC test-day data from 48 Belgian and Dutch farms participating in the milk recording of a local dairy herd improvement program. The UHP were calculated based on individual animal records at each test day over three years (2017 until 2019). These UHP included herd milk SCC, average heifer SCC, average cow SCC, percentage of high SCC, percentage of new high SCC, percentage of chronic high SCC, percentage of high SCC cows after calving, and percentage of recovery during the lactation. By fitting a linear mixed model effect for each of the different UHP, significant associations between the UHP and season, year and farm size were observed at test-day level. A poorer udder health was observed during summer compared to other seasons and generally, larger farms performed worse than smaller farms. Using a linear regression model, a significant negative correlation between herd average SCC and average daily milk production was found: an increase of 6,085 cells/mL was associated with a decrease of one kg of milk production. Finally, the cow-level UHP were averaged over all test days of the entire study period per farm to investigate the farm-level udder health performance and correlations between them. At the farm level, UHP analysis revealed most farms had poor udder health performance (i.e. the herd milk SCC, average heifer SCC, average cow SCC, percentage of new high and chronic high SCC were all higher than their target values) as proposed by Barkema et al. (2013). Both at the farm and at test day level, strong correlations were found among the UHP. Similar to studies on farms with conventional milking systems, a strong correlation between herd milk SCC and the percentage of new and chronic high SCC cows was found. This study gives new insights into udder health performance on farms with an AMS and provides veterinarians and other dairy industry stakeholders with concrete benchmarks for udder health performance on farms.

COW TRAFFIC DESIGNS IN BARNS WITH AUTOMATIC MILKING SYSTEMS: ADVANTAGES, DISADVANTAGES AND DIFFERENCES

This study describes the most common traffic systems in barns for lactating dairy cows milked in automatic milking systems (AMS). It outlines seven cow traffic designs, each featuring a basic floor plan, taking into account one robot or AMS per barn and considering a maximum system capacity (&gt; 60 cows/AMS). The study describes the advantages and disadvantages of free, milk-first and feed-first traffic and the differences between forced and guided cow traffic designs. Some research data are also shown to emphasize the theoretical concepts included in this document. The main difference is that free cow traffic tends to milk a lesser number of cows than milk-first and feed-first cow traffic designs but warrants more freedom for the cows. However, free cow traffic design increases the number of refusals (cows visiting the AMS without milking permission), leading to system inefficiency. Guided traffic designs emerge as the most efficient, milking more cows throughout the day while reducing the need to fetch cows and overall labour. When operating at full cow capacity, guided cow traffic designs are recommended.

NETWORK PERSPECTIVE: BENEFITS OF INTERNATIONAL SCIENTIFIC COLLABORATION

In 2010 Freeman suggested that "the globalization of scientific and engineering knowledge is the most potent aspect of modern globalization". International research collaboration is an activity that is widely pushed globally, at the level of research institutes and universities. Academic world is increasingly interconnected, fostering such international partnerships that represents the globalization of science from the scientific collaboration perspective. These collaborations extend beyond sharing resources. Main goal of those activities is exchanging ideas, cultures, and visions to address complex global challenges. It is evident that from partnering with institutions and researchers worldwide, National Agricultural and Food Centre (NPPC) can be exposed to diverse pools of knowledge and expertise that significantly enhance the academic quality and reputation of our NPPC. This global exchange of ideas leads to more innovative, comprehensive, and impactful research outcomes. Additionally, as the institute's reputation improves, the research centre will attract more funding, students and talented researchers, achieve globalization, creating a cycle of excellence and improvement. In conclusion, the importance and benefits of international co-research agreements are multiple and profound. Collaboration's activities are pivotal in enhancing academic quality, broadening research horizons, preparing young researcher for global challenges, addressing international issues and policy makers, and fostering cultural understanding and global networks. In the second Editorial article of 2024, I am going to introduce the contents of the articles collected and published in the second issue of 2024 year. Atteh reviewed the effects of fiber on nutrition and reproduction in pigs. Author concluded that the reduction of dietary fiber's hemicellulose in a sow's lactation diet can improve the low-birth-weight piglets' health, post-weaning performance and milk composition. While exogenous enzymes and the extrusion of fibrous feedstuffs enhanced nutrient digestibility and utilisation, other processing methods, including fermentation and extrusion, decreased the dietary fiber components and had a beneficial impact on the performance of the pigs. Agro-industrial residues have enormous potential to improve reproductive efficiency and serving as an economically viable dietary fiber feeding strategy in the pig industry. Awodoyin et al. investigated the dietary supplementation of coffee arabica seed powder on performance and meat quality of broiler chicken. Authors ended up that low pathogenic gut microorganisms and total volatile nitrogen base coupled with high sensory acceptability of meat confirm the antioxidant potential of black coffee in broiler chicken diet. Ngige et al. performed a study aimed at screening the internal and external bacteria found in farmed Nile tilapia and African Catfish. According to microbiological investigation, the presence of the microorganisms, some of which are pathogens (Salmonella enteritidis, Enterobacter aerogenes, Klebsiella oxytoca) to humans, is an indication that undercooked fish may pose health risks to susceptible human and an impediment to the rapid intensification of aquaculture because of mortality of fingerings. Busanello reviewed the most common traffic systems in barns for lactating dairy cows milked in automatic milking systems. The study describes the advantages and disadvantages of free, milk-first and feed-first traffic and the differences between forced and guided cow traffic designs. Some research data are also shown to emphasize the theoretical concepts included in this document. Author concluded that guided traffic designs emerge as the most efficient, milking more cows throughout the day while reducing the need to fetch cows and overall labour. When operating at full cow capacity, guided cow traffic designs are recommended. Sudik conducted a study with the aim to determine the nutritional composition of roselle seed cake (Hibiscus sabdarica L.) and its effect on broiler chickens. Author concluded that roselle seed cake is rich in proteins and energy and it can be included up to 50 % in the diet of broilers without negative effects on growth rate and carcass performance. Rajsky et al. described the flexible duodenal monocannula of the National Agricultural and Food Centre design for the determination of intestinal nutrient digestibility in cattle. The innovativeness of the technical design of the NPPC cannula lies in the fact that the cannula is made of one piece of a straight tube with an inner diameter of 22 mm. As a result, the life of cannulated animals can be extended without age limitation. Editorial Team looks forward to evaluating your submitted contributions and providing all necessary support to Authors in order to best serve animal science and the scientific community, with commitment to research integrity and the highest publishing ethics. Enjoy reading!