Behavior Of Dairy Cattle Research Articles

Effects of Using Mechanical Brushes on the Productive Performance of Dairy Cows

Intensive farming can reduce production costs and maximize animal production efficiency; however, it also causes many adverse effects on the welfare of dairy cows. A mechanical brush is an automated grooming device that promotes the grooming behavior of dairy cattle, thereby helping to alleviate stress. In the present study, we evaluated the effects of using mechanical brushes on the production performance of dairy cows by comprehensively analyzing their milk production, health status, and reproductive performance. The cows were assigned to 6 groups: 109 lactating dairy cows (brush treatment) and 105 controls (without brush treatment), 64 dry milk dairy cows (brush treatment) and 49 controls (without brush treatment), and 198 perinatal cows (brush treatment) and 65 controls (without brush treatment). We found an increasing trend in the daily utility time and usage frequency of mechanical brushes for each cow during the lactating period (7.73 ± 4.02 min/d and 2.90 ± 1.22 times/d, respectively), dry period (15.97 ± 14.16 min/d and 4.21 ± 2.91 times/d, respectively), and perinatal period (25.15 ± 19.05 min/d and 5.45 ± 3.83 times/d, respectively) (p < 0.01 and p < 0.05, respectively). The installation location of the mechanical brush significantly affected the frequency of its usage during the different periods. The head was the preferred body part for using the mechanical brush during the lactation and dry periods (59.32% and 44.54%, respectively), while the hip was the main preferred grooming part during the perinatal period (40.17%). Overall, the time, frequency, and preferred body part of dairy cows that used mechanical brushes varied across different physiological stages. Additionally, mechanical brush use in lactating and dry dairy cows significantly improved cleanliness of the body’s surface (p < 0.05) and enhanced milk production of lactating cows (p < 0.01), particularly for cows with four and five parities. Thus, the use of mechanical brushes could improve the production performance of dairy cows and enhance sustainability of large-scale farms.

PSIII-12 Dynamics of neonatal dairy calf behaviors and their association with early gut microbiota

Abstract The behavior of dairy cattle can be both an indicator and a determinant of their productivity and health. Additionally, animal behavior is also associated with their gastrointestinal microbiota through the bi-directional pathways of the gut-brain axis, influencing nutrient utilization and gut health. Few studies have looked at the dynamics of neonatal calf behaviors and their associations with early microbiota development. Therefore, the objective of this study is to observe feeding behaviors and activity of neonatal dairy calves and investigate its associations with the diversity and composition of early-stage gut microbiota. We used Holstein-Angus crossed calves (n = 25) raised in individual outdoor hutches and bucket-fed milk replacer twice daily. The number of milk exposures until calves were successfully bucket trained was recorded, along with milk consumption times during the AM feedings on d 7, 11, and 14. We also monitored the activity of the calves using HOBO Pendant G Data Logger accelerometers secured on the right hind leg of each calf to monitor standing and lying behavior from d 3 to d 13. Fecal samples were collected from the recto-anal junction of the calves at d 7 and 14 after birth and gut microbiota were analyzed using full-length 16S rRNA gene amplicon sequencing on an Oxford Nanopore sequencer. The Generalized Linear Model (GLM) was applied to evaluate effects of gender and birth weight on behavior and gut microbiota using RStudio 4.2.1. The Linear discriminant analysis Effect Size (LEfSe) was used to determine the unique bacterial species for each behavioral group. The results revealed that there was no influence of sex or birth weight on bucket training or consumption time; however, male calves exhibited significantly increased total standing time compared with female calves. We found no significant difference in microbiota between fast-learning calves (one milk exposure; n = 3) and slow-learning calves (5 or more exposures; n = 3). We observed greater alpha diversity of slow drinking calves (top 25%; n = 6) compared with fast drinking calves (top 25%; n = 6) on d 7 (Chao1; P = 0.03). The LEfSe analysis identified Akkermansia muciniphilia to be more abundant in fast drinking calves, and Megasphaera elsdenii to be more abundant in slow drinking calves. Additionally, a trend of differing microbiota composition was observed between the most active and least active calves (n = 4 per group) on d 14 (Bray-Curtis; P = 0.1), and many Prevotella species were more abundant in the most active calves. In conclusion, this study sheds light on the gut-brain axis of neonatal dairy calves at the species-level and provides further insights into cognitive, consumptive, and active behaviors.

Enhancing hoof health and locomotion in crossbred dairy cows: impact of recycled manure solids bedding on lameness incidence and gait kinematics.

Recycled manure solids has emerged as a promising alternative for animal bedding, owing to its economic feasibility, ready availability on farms, and soft, non-abrasive nature. This research aimed to assess the impact of recycled manure solids (RMS) bedding, combined with a conditioner containing 7.5% lime and 6% sodium hydrosulphate, on dairy cow welfare and gait kinematics over three months. Hock and knee injury scores, lameness incidence, and gait kinematic parameters were evaluated for animals housed on cement flooring (Control), RMS bedding (Treatment I), and conditioner-added RMS bedding (Treatment II) on days 0, 45, and 90 of the experiment with six crossbred cows in each group. The results revealed a significant reduction (p < 0.05) in lameness scores (5-point scale) for animals in both the RMS and conditioner-added RMS groups, with scores of 1.09 ± 0.05 and 1.04 ± 0.03, respectively, compared to those on cement floors. Moreover, a noteworthy decrease (p < 0.05) in knee and hock injury scores (4-point scale) was observed in the RMS groups, indicating a potentially positive impact on joint health. Gait kinematic analysis demonstrated that animals in the RMS (1.03 ± 0.04m/s) and conditioner-added RMS (1.02 ± 0.06m/s) groups exhibited higher walking speeds and increased step angles (158.59 ± 4.82° and 149.58 ± 3.85°) compared to their cement-floor counterparts. No significant changes (p > 0.05) were observed in stride length, step asymmetry, step length, and step width. The study concluded that the conditioner incorporated recycled manure solids resulting in a substantial decrease in lameness incidence and a reduction in hock and knee injuries among dairy cows. Additionally, the improved gait kinematics observed in non-lame animals suggest that this bedding combination positively influences overall animal well-being. These findings underscore the potential of sustainable bedding practices to enhance both physical health and locomotor behaviour in dairy cattle.

Multiple factors shape social contacts in dairy cows

Cattle develop preferential relationships with other individuals in the herd. These social interactions between individuals have a significant impact on both animal welfare and production. Given the relevance of social behaviour in dairy cattle, scientific studies have focused on understanding social interactions among cattle. These may also be influenced by individual area preferences, particularly when animals are housed in confined spaces. Therefore, investigating the relationship between individual area preferences and social interactions is essential for understanding social behaviour in dairy cattle. Real-time location systems provide the opportunity to monitor individual area preferences and social contacts at the same time. This study aims to assess the impact of dairy cows' area preferences on their daily social contacts and to determine the potential implications of overlooking individual area preferences in social behaviour studies. The individual position of the lactating cows was automatically collected once per second for two months on a Swedish commercial farm housing dairy cows inside a free-stall barn. The location data of 243 lactating cows was used to construct the social networks and to estimate the similarity of the area utilisation distributions between these individuals. The effect of utilisation distribution similarity in social networks was investigated by applying separable temporal exponential random graph mixed models. The role of different cow characteristics in the similarity of the utilisation distributions was assessed through a linear mixed model. Our analyses stressed the importance of similarity of area preference, parity, kindergarten effect, and filial relatedness in shaping daily social contacts in dairy cattle. The kindergarten effect refers to the effect on cow behaviour of being grouped together in the early stages of their lives. Similarity of area preference was influenced by the kindergarten effect and relatedness by pedigree, which favoured interactions between these individuals. The described approach allowed to disassociate the area preference from the social contacts between cows, providing more accurate results of the importance of the cow’s characteristics on their social behaviour.

A Review of the Effects of Stress on Dairy Cattle Behaviour.

In this narrative review, the authors summarise the relationship between stress and behaviour and how dairy cattle cope with stressors. Based on the available literature, the most common stressors in intensive dairy cattle farming, such as pain, disease, heat stress, poor comfort caused by technology, and social stress, are surveyed. The authors describe how these stressors modify the behaviour of dairy cattle, influencing their feeding patterns, social interactions, and overall well-being. Additionally, the review explores the effectiveness of various coping mechanisms employed by dairy cattle to mitigate stress, including physiological adaptations and behavioural responses. This review is a valuable resource for understanding and grading stress in dairy cattle through behavioural reactions. Elucidating the intricate interplay between stressors and behaviour offers insights into potential interventions to improve animal welfare and productivity in dairy farming. Furthermore, this review highlights areas for future research, suggesting avenues for more comprehensive behavioural studies to enhance our understanding of stress management strategies in dairy cattle.

The effect of feeding and visiting behavior on methane and hydrogen emissions of dairy cattle measured with the GreenFeed system under different dietary conditions

The objectives were to investigate the effect of feeding and visiting behavior of dairy cattle on CH4 and H2 production measured with voluntary visits to the GreenFeed system (GF) and to determine whether these effects depended on basal diet (BD) and 3-nitrooxypropanol (3-NOP) supplementation. The experiment involved 64 lactating dairy cattle (146 ± 45 d in milk at the start of trial; mean ± SD) in 2 overlapping crossover trials, each consisting of 2 measurement periods. Cows within block were randomly allocated to 1 of 3 types of BD: a grass silage-based diet consisting of 30% concentrates and 70% grass silage (DM basis), a grass silage- and corn silage-mixed diet consisting of 30% concentrates, 42% grass silage, and 28% corn silage (DM basis), or a corn silage-based diet consisting of 30% concentrates, 14% grass silage, and 56% corn silage (DM basis). Each type of BD was subsequently supplemented with 0 and 60 mg 3-NOP/kg DM in one crossover, or 0 and 80 mg 3-NOP/kg DM in the other crossover. Diets were provided in feed bins which automatically recorded feed intake and feeding behavior, with additional concentrate fed in the GF. All visits to the GF that resulted in a spot measurement of both CH4 and H2 emission were analyzed in relation to feeding behavior (e.g., meal size and time interval to preceding meal) as well as GF visiting behavior (e.g., duration of visit). Feeding and GF visiting behavior was related to CH4 and H2 production measured with the GF, in particular the meal size before a GF measurement and the time interval between a GF measurement and the preceding meal. Relationships between gas production and both feeding and GF visiting behavior were affected both by type of BD and 3-NOP supplementation. With an increase of the time interval between a GF measurement and the preceding meal, CH4 production decreased with 0 mg 3-NOP/kg DM but increased with 60 and 80 mg 3-NOP/kg DM, whereas type of BD did not affect these relationships. In contrast, CH4 production increased with 0 mg 3-NOP/kg DM but decreased with 60 and 80 mg 3-NOP/kg DM upon an increase in the size of the meal preceding a GF measurement. With an increase of the time interval between a GF measurement and the preceding meal, or with a decrease of the size of the meal preceding a GF measurement, H2 production decreased for all treatments, although the effect was generally somewhat stronger for 60 and 80 mg 3-NOP/kg DM than for 0 mg 3-NOP/kg DM. Hence, the timing of GF measurements next to feeding and GF visiting behavior are essential when assessing the effect of dietary treatment on the production of CH4 and H2 in a setting where a spot sampling device such as a GF is used and where the measurements depend on voluntary visits from the cows.

Social network analysis to predict social behavior in dairy cattle

Dairy cattle are frequently housed in free stalls with limited space, impacting social interactions between individuals. Social behavior in dairy cattle is gaining recognition as a valuable tool for identifying sick animals, but its application is hampered by the complexities of analyzing social interactions in intensive housing systems. In this context, precision livestock technologies present the opportunity to continuously monitor dyadic spatial associations on dairy farms. The aim of this study is to evaluate the accuracy of predicting social behavior of dairy cows using social network analysis. Daily social networks were built using the position data from 149 cows over 14 consecutive days of the study period. We applied the separable temporal exponential random graph models to estimate the likelihood of formation and persistence of social contacts between dairy cows individually and to predict the social network on the subsequent day. The correlation between the individual degree centrality values, the number of established social contacts per individual, between the predicted and observed networks ranged from 0.22 to 0.49 when the structural information from network triangles was included in the model. This study presents a novel approach for predicting animal social behavior in intensive housing systems using spatial association information obtained from a real-time location system. The results indicate the potential of this approach as a crucial step toward the larger goal of identifying disruptions in dairy cows expected social behavior.

A methodological approach to compare continuous and instantaneous sampling and two methods to deal with animals out of sight on dairy cattle behavior and interaction with their calf in the first hours post-partum.

Animal behavior can provide useful information about animal welfare, but methods and tools used to gather behavioral data and data treatment can influence the results. Therefore, this study was carried out on dairy cow (Bos taurus) behavior and interaction with calves early post-partum aiming at comparing two sampling rules, namely continuous and instantaneous sampling at scan intervals of 30 s, 1, 2, 3, 4, 5, and 10 min, and of two methods to deal with out of sight animals. The study was based on three assumptions: (1) continuous sampling provides the most complete and accurate data, allowing the observation of seldom behaviors and short events; (2) instantaneous sampling can provide accurate measurements of frequency and duration, especially at short scan intervals; (3) differences in behavioral results may occur depending on whether a correction for time out of sight is applied or not. Thus, 10 dams were observed from videos in the 2 h post-parturition. Ruminating, stereotypies, calf-biting and calf-butting were not recorded during the observation period. Other behaviors were observed only with continuous sampling or with continuous and instantaneous at 30-s scan intervals. The recoding of several behaviors was less accurate when applying longer scan intervals. Data from continuous and instantaneous sampling at 30-s scan intervals were compared with Wilcoxon test. Results showed no significant differences for posture, position in the pen and all behaviors (p > 0.05) except vocalizing (p = 0.003). The same test did not highlight significant differences due to method of dealing with out of sight for both sampling rules (p > 0.05). Correlation between continuous and instantaneous sampling were prevalently high at 30-s intervals and they decreased as the length of scan intervals increased for most behaviors. Results confirmed the first two assumptions suggesting that continuous sampling is more accurate, in particular for short and rare behaviors, and caution against the suitability of dam behavioral data collected using instantaneous sampling at scan intervals of minutes. The third assumption was not proven by this study. Results should be considered in light of the development of new technologies that relies on data acquired by sensors and imaging to monitor cow-calf welfare and behavior post-parturition.

Effect of repeated HPA axis stimulation on hair cortisol concentration, growth, and behavior in preweaned dairy cattle.

The study objective was to investigate the effect of repeated hypothalamic-pituitary-adrenal (HPA) axis stimulation using synthetic adrenocorticotropic hormone (ACTH) intramuscular injections on hair cortisol concentration, growth, and behavior in preweaned dairy calves. Twenty-seven Holstein calves were assigned to nine triads (based on sex and birth order) and randomly assigned to 1 of 3 treatments: 1) control (CON; 2mL saline weekly); 2) moderate (MOD; alternating Cosyntropin [2 mcg/kg body weight (BW)] and saline weekly); or 3) frequent (FREQ; Cosyntropin [2 mcg/kg BW] weekly). Calves received their first injection on study day 0 (7 ± 1 d of age). Hair was collected from the tail switch between days -5 and -3 (baseline), 21, and 49 and analyzed for cortisol concentration. To verify the endogenous cortisol release by Cosyntropin during the treatment period, saliva was collected on days 0, 14, 28, and 42 before injection and every 15min for 2h after injection for analysis of salivary cortisol concentration. Calves were fitted with accelerometers to continuously monitor lying time, number of lying bouts, and lying bout duration throughout the study. Growth measures (BW, hip height, hip width) were recorded weekly. Data were analyzed using repeated measures ANOVA (SAS, Version 9.4), and models included the fixed effects of treatment, time (min or study day), and interaction between treatment and time. Temperature humidity index was included as a continuous covariate in all models. We observed a treatment × min interaction (P < 0.0001), whereby salivary cortisol concentration was lower in CON calves compared to MOD and FREQ calves 15 to 120min postinjection. While hair cortisol concentration was not influenced by treatment, concentration decreased from day 21 (1.28 ± 0.03ng/mL) to 49 (0.93 ± 0.03ng/mL). Average BW was similar across treatments (CON [59.4 ± 1.09 kg], MOD [58.6 ± 0.98 kg], and FREQ [57.6 ± 0.96 kg]; P = 0.50). There was no evidence to suggest a difference in average daily lying time (CON [18.5 ± 0.23h/d], MOD [18.6 ± 0.23h/d], and FREQ [18.5 ± 0.23h/d]; P = 0.99). These results suggest that repeated HPA axis stimulation through Cosyntropin administration increased salivary cortisol concentration, but did not influence hair cortisol concentration, growth, or behavior in preweaned dairy calves.

Music enrichment improves the behavior and leukocyte profile of dairy cattle

Music enrichment improves the behavior and leukocyte profile of dairy cattle

Real-time automatic integrated monitoring of barn environment and dairy cattle behaviour: Technical implementation and evaluation on three commercial farms

Due to increasing herd sizes and automation on dairy farms there is an important need for automated monitoring of cow production, health, and welfare. Despite much progress in automatic monitoring techniques, there is still a need to integrate data from multiple sources to create a comprehensive overview and accurate diagnosis of a cow’s state. To aid the technological development of data integration, a prototype of an open and customizable automatic system that integrates data from multiple sensors relating to barn environment and cow behaviour was developed. The system integrates data from sensors that measure barn climate (e.g., temperature, humidity, wind speed), air quality (e.g., CO2 concentration), water use and temperature, the moisture and temperature of the litter and cow behaviour (e.g., lying, eating, ruminating). An external weather system and video recording system are also included. The system’s architecture consists of four main elements: sensors, nodes, gateways, and backend. The data are recorded by sensors, then locally processed on custom-developed sensor nodes, and then transmitted via radio channels to local gateways that combine the data from multiple nodes and transmit them to distributed digital storage (“the cloud”) via a 3G/4G cellular network. On the cloud, the data are further processed and stored in a database. The data are then presented to the user continuously and in real time on a dashboard that can be accessed via the internet. In the design of the local wireless network, care was taken to avoid data packet collision and thus to minimize data loss. To test the system’s performance, the system was installed and operated on three commercial dairy cattle farms for one year. The system provided high data stability with minimal loss and outliers, showing that the system is reliable and suitable for long term application on commercial dairy farms. The system’s architecture, communication network, and data processing and visualization applications form an open framework for research and development purposes, allowing it to be customized and fine-tuned before being deployed as a management assistant on commercial dairy farms. Missing elements that should be added in the future are the integration of the data from the milking parlour and cow identification. Algorithms to integrate information from multiple sensors can be added to provide a comprehensive system that monitors all aspects related to cow welfare, health, and production automatically, remotely and in real time, thereby supporting farmers in important management decision-making.

Genomic Selection for Dairy Cattle Behaviour Considering Novel Traits in a Changing Technical Production Environment.

Cow behaviour is a major factor influencing dairy herd profitability and is an indicator of animal welfare and disease. Behaviour is a complex network of behavioural patterns in response to environmental and social stimuli and human handling. Advances in agricultural technology have led to changes in dairy cow husbandry systems worldwide. Increasing herd sizes, less time availability to take care of the animals and modern technology such as automatic milking systems (AMSs) imply limited human-cow interactions. On the other hand, cow behaviour responses to the technical environment (cow-AMS interactions) simultaneously improve production efficiency and welfare and contribute to simplified "cow handling" and reduced labour time. Automatic milking systems generate objective behaviour traits linked to workability, milkability and health, which can be implemented into genomic selection tools. However, there is insufficient understanding of the genetic mechanisms influencing cow learning and social behaviour, in turn affecting herd management, productivity and welfare. Moreover, physiological and molecular biomarkers such as heart rate, neurotransmitters and hormones might be useful indicators and predictors of cow behaviour. This review gives an overview of published behaviour studies in dairy cows in the context of genetics and genomics and discusses possibilities for breeding approaches to achieve desired behaviour in a technical production environment.

A Review on Information Technologies Applicable to Precision Dairy Farming: Focus on Behavior, Health Monitoring, and the Precise Feeding of Dairy Cows

Milk production plays an essential role in the global economy. With the development of herds and farming systems, the collection of fine-scale data to enhance efficiency and decision-making on dairy farms still faces challenges. The behavior of animals reflects their physical state and health level. In recent years, the rapid development of the Internet of Things (IoT), artificial intelligence (AI), and computer vision (CV) has made great progress in the research of precision dairy farming. Combining data from image, sound, and movement sensors with algorithms, these methods are conducive to monitoring the behavior, health, and management practices of dairy cows. In this review, we summarize the latest research on contact sensors, vision analysis, and machine-learning technologies applicable to dairy cattle, and we focus on the individual recognition, behavior, and health monitoring of dairy cattle and precise feeding. The utilization of state-of-the-art technologies allows for monitoring behavior in near real-time conditions, detecting cow mastitis in a timely manner, and assessing body conditions and feed intake accurately, which enables the promotion of the health and management level of dairy cows. Although there are limitations in implementing machine vision algorithms in commercial settings, technologies exist today and continue to be developed in order to be hopefully used in future commercial pasture management, which ultimately results in better value for producers.

Classifying Chewing and Rumination in Dairy Cows Using Sound Signals and Machine Learning.

This research paper introduces a novel methodology for classifying jaw movements in dairy cattle into four distinct categories: bites, exclusive chews, chew-bite combinations, and exclusive sorting, under conditions of tall and short particle sizes in wheat straw and Alfalfa hay feeding. Sound signals were recorded and transformed into images using a short-time Fourier transform. A total of 31 texture features were extracted using the gray level co-occurrence matrix, spatial gray level dependence method, gray level run length method, and gray level difference method. Genetic Algorithm (GA) was applied to the data to select the most important features. Six distinct classifiers were employed to classify the jaw movements. The total precision found was 91.62%, 94.48%, 95.9%, 92.8%, 94.18%, and 89.62% for Naive Bayes, k-nearest neighbor, support vector machine, decision tree, multi-layer perceptron, and k-means clustering, respectively. The results of this study provide valuable insights into the nutritional behavior and dietary patterns of dairy cattle. The understanding of how cows consume different types of feed and the identification of any potential health issues or deficiencies in their diets are enhanced by the accurate classification of jaw movements. This information can be used to improve feeding practices, reduce waste, and ensure the well-being and productivity of the cows. The methodology introduced in this study can serve as a valuable tool for livestock managers to evaluate the nutrition of their dairy cattle and make informed decisions about their feeding practices.

Graduate Student Literature Review: Sociability, fearfulness, and coping style—Impacts on individual variation in the social behavior of dairy cattle

Dairy cattle typically live in groups, but individuals within these groups vary in their social behavior. An improved understanding of factors affecting the expression of social behavior may help refine management practices on farms to better accommodate the needs of all individuals within the herd. In this paper, we review (1) some examples of how social behavior is expressed in cattle, (2) commonly assessed personality traits in this species (i.e., sociability and fearfulness) as well as coping style, and (3) how these can affect the expression of social behavior of dairy cattle and in turn their welfare. We also identify understudied social behaviors that personality might influence (social learning, social stress, and social buffering of negative emotions), and that could inform how to improve the welfare of intensively housed dairy cattle.

The Impact of Music on Milk Production and Behaviour of Dairy Cattle

The influence of music on the milk performance of dairy cattle has been increasingly studied in recent years, although its efficacy is still being debated due to the inconsistent outcomes and a limited number of studies. This study aimed to investigate the impact of music on the milk production and behaviour of 24 lactating Jersey cattle, consisting of 10 primiparous and 14 multiparous cows. The experiment involved milk collection and behavioural observation before and after exposure to music at a dairy farm in Sitiawan, Perak. The results indicate that music and parity significantly affect the milk yield produced by a cow at p &lt; 0.05. The cows produced significantly less milk after being exposed to music, while multiparous cows recorded significantly higher milk yields than primiparous cows. In terms of the observed behaviour, the cows displayed a significantly higher proportion of feeding and ruminating when no music was played. On the other hand, multiparous cows displayed a significantly lower proportion of feeding and ruminating, and a higher proportion of standing compared to primiparous cows. However, no significant effects of parity and music were observed in walking and lying behaviour. To conclude, music did not improve the milk yield of Jersey dairy cows in this study. Due to the inconsistencies in the outcomes of many studies related to the effect of music on milk yield, more long-term research should be conducted by considering factors that might influence milk yields, such as parity, breed, housing environment, and music selection.

The Impact of Music on Milk Production and Behaviour of Dairy Cattle

The influence of music on the milk performance of dairy cattle has been increasingly studied in recent years, although its efficacy is still being debated due to the inconsistent outcomes and a limited number of studies. This study aimed to investigate the impact of music on the milk production and behaviour of 24 lactating Jersey cattle, consisting of 10 primiparous and 14 multiparous cows. The experiment involved milk collection and behavioural observation before and after exposure to music at a dairy farm in Sitiawan, Perak. The results indicate that music and parity significantly affect the milk yield produced by a cow at p &lt; 0.05. The cows produced significantly less milk after being exposed to music, while multiparous cows recorded significantly higher milk yields than primiparous cows. In terms of the observed behaviour, the cows displayed a significantly higher proportion of feeding and ruminating when no music was played. On the other hand, multiparous cows displayed a significantly lower proportion of feeding and ruminating, and a higher proportion of standing compared to primiparous cows. However, no significant effects of parity and music were observed in walking and lying behaviour. To conclude, music did not improve the milk yield of Jersey dairy cows in this study. Due to the inconsistencies in the outcomes of many studies related to the effect of music on milk yield, more long-term research should be conducted by considering factors that might influence milk yields, such as parity, breed, housing environment, and music selection.

Precalving behavior in dairy cattle with different calving times.

Predicting the calving time in dairy cattle can help in avoiding calving accidents and reducing burdens on animal caretakers. In this study, we analyzed the behavior of pregnant dairy cattle for 7 days prior to calving, to assess the feasibility of predicting the calving time. Eleven Holstein cows were divided into two groups based on their calving times, that is, in the morning (the Morning Parturition Group) or the evening (the Evening Parturition Group). Their behavior was recorded on video. An analysis was conducted of the daily occurrences of each type of behavior and the number of switches of behavior during the day and at night. A statistical analysis was conducted, using a two-way factorial analysis. The behavioral sequence was analyzed using an adjacency matrix. Hierarchical structure charts were created, using Interpretive Structural Modeling. The results suggest that feeding and exploratory behaviors are associated with the calving time period and thus can be useful when predicting that period. The hierarchical structure charts suggest that the Morning Parturition Group had no definite behavioral sequence pattern, unlike the Evening Parturition Group. The detection of an unstable behavioral sequence pattern might predict the calving time period.

Development of feeding and reproduction technology in dairy cattle breeding based on the use of digital technologies.

A study on the study of the qualitative assessment of the behavior of dairy cattle according to the VAS system (visual analog scale) was conducted in the LLP "Agrofirme "AKAS", located in the West Kazakhstan region of the Republic of Kazakhstan. According to research, it follows that different seasons of time affect the conditions of detention in different ways. So, for the maintenance of cows in the summer, the distance of avoidance at the feeding site according to test 1 and 2 is within 3 meters, whereas in spring and autumn it was 2 meters. The difference between the reference norm and the household ration has been determined, from which it follows that the feeding ration of the farm corresponds to the norm of 12 kg of milk yield per head per day. The vitamin and mineral premix developed by us includes vitamins, minerals, including macro-microelements. The premix also includes components in the following ratio: phosphorus (P) - 5% of monocalcium phosphate, vitamin A - 1.2% of rovimix A 1000, vitamin D3 - 0.64% of rovimix D3, vitamin E - 16% of rovimix E-50, manganese (Mn) - 22.2%, copper (Cu) - 9%, zinc (Zn) - 19%, iodine (I) - 0.28%, selenium (Se) - 7.65 and cobalt (Co) - 0.14%, and feed chalk - 5% and chickpea flour - 13.89% are used as fillers as a source of calcium (Ca).. The average daily milk yield at the beginning of the experiment in both study groups was in the range of 10.6-10.8 kg. At the end of the experiment, the average daily milk yield in animals receiving premix exceeded their peers from the control group by 1.4 kg or 1.6%. According to the chemical composition of milk, the indicators of fat, protein and lactose were higher in the cows of the experimental group compared with the peers of the control group (for fat - 3.92>3.37, for protein - 3.32>3.23, for lactose - 4.16>4.01).

Relationship between animal welfare score by the assessment system for dairy cattle and behaviour of dairy cattle

Relationship between animal welfare score by the assessment system for dairy cattle and behaviour of dairy cattle