Heat stress in a temperate climate leads to adapted sensor-based behavioral patterns of dairy cows

Behavioral Adaptations in Tropical Dairy Cows: Insights into Calving Day Predictions

This study examined changes in the activity patterns of tropical dairy cows during the transition period to assess their potential for predicting calving days. This study used the AfiTag-II biosensor to monitor activity, rest time, rest per bout, and restlessness ratio in 298 prepartum and 347 postpartum Holstein Friesian cows across three lactation groups (1, 2, and ≥3). The data were analyzed using generalized linear mixed models in SPSS, and five machine learning models, including random forest, decision tree, gradient boosting, Naïve Bayes, and neural networks, were used to predict the calving day, with their performance evaluated via ROC curves and AUC metrics. For all lactations, activity levels peak on the calving day, followed by a gradual return to prepartum levels within two weeks. First-lactation cows displayed the shortest rest duration, with a prepartum rest time of 568.8 ± 5.4 (mean ± SE), which is significantly lower than higher-lactation animals. The random forest and gradient boosting displayed an effective performance, achieving AUCs of 85% and 83%, respectively. These results indicate that temporal changes in activity behavior have the potential to be a useful indicator for calving day prediction, particularly in tropical climates where seasonal variations can obscure traditional prepartum indicators.

Hypothalamic Neuromodulation and Control of the Dermal Surface Temperature of Livestock during Hyperthermia

Hyperthermia elicits several physiological and behavioral responses in livestock to restore thermal neutrality. Among these responses, vasodilation and sweating help to reduce core body temperature by increasing heat dissipation by radiation and evaporation. Thermoregulatory behaviors such as increasing standing time, reducing feed intake, shade-seeking, and limiting locomotor activity also increase heat loss. These mechanisms are elicited by the connection between peripheral thermoreceptors and cerebral centers, such as the preoptic area of the hypothalamus. Considering the importance of this thermoregulatory pathway, this review aims to discuss the hypothalamic control of hyperthermia in livestock, including the main physiological and behavioral changes that animals adopt to maintain their thermal stability.

The Impacts of Heat Stress on Rumination, Drinking, and Locomotory Behavior, as Registered by Innovative Technologies, and Acid-Base Balance in Fresh Multiparous Dairy Cows

This study hypothesizes that heat stress adversely affects dairy cows, resulting in reduced rumination, altering eating and drinking behaviors, changes in their locomotory patterns, and significant variations in their acid-base balance. The aim of this study was to investigate the impacts of heat stress on rumination, drinking, and locomotory behavior, as registered by innovative technologies, and acid-base balance in fresh multiparous dairy cows. This study was conducted during the summer, from 15 June to 8 July 2023, on a Lithuanian commercial dairy farm. We assessed 350 German Holstein cows that produced an average of 11,400 kg of milk annually throughout their second and subsequent lactation periods. We used the temperature-humidity index (THI) to divide the cows under investigation into three periods: I. high HS-THI >78 (period: 15-23 June 2023); II. medium HS-THI 72-78 (period: 24-30 June 2023); and III. low HS-THI <72 (period: 1-8 July 2023). The appropriate RumiWatch sensor (RWS) parameters were assessed between 15 June 2023 and 8 July 2023. Cows were acclimatized to the rumination, drinking, and locomotory behavior parameters during the adaptation period (1-30 June 2023). The registration process started on 15 June 2023 and terminated on 8 July 2023 and was performed every hour during the 24 h day. The acid-base balance was recorded from 15 June 2023 until 8 July 2023, once per week. The cows' activity increased by 11.75% in the high HS period compared to the low HS period (p < 0.01); high mean differences were detected for rumination, which was 17.67% higher in the high HS period and 13.80% higher in the medium HS period compared to the low HS period (p < 0.01); and the change in activity was 12.82% higher in the low HS compared to the medium HS period (p < 0.01). Cows under high HS had higher blood urea nitrogen (BUN) levels compared with cows under medium HS (p < 0.01). The observed alterations in the rumination, drinking, and locomotory behaviors, in addition to the acid-base balance, highlight the multifaceted impacts of varying heat stress on the physiological and behavioral responses of dairy cows. This suggests that the utilization of advanced technologies may assist dairy farmers in effectively monitoring and controlling heat stress in cows. Additionally, regularly assessing blood urea nitrogen levels can enable farmers to modify their feeding practices, thus promoting optimal cow well-being and productivity.

Bunching behavior in housed dairy cows at higher ambient temperatures

Bunching behavior in cattle may occur for several reasons including enabling social interactions, a response to stress or danger, or due to shared interest in resources such as feeding or watering areas. There is evidence in pasture grazed cattle that bunching may occur more frequently at higher ambient temperatures, possibly due to sharing of fly-load or to seek shade from the direct sun under heat stress conditions. Here we demonstrate how bunching behavior is associated with higher ambient temperatures in a barn-housed UK dairy herd. A real-time local positioning system was used, as part of a precision livestock farming (PLF) approach, to track the spatial position and activity of a commercial dairy herd (∼100 cows) in a freestall barn continuously at high temporal resolution for 4 mo between August and November 2014. Bunching was determined using 4 different spatial measures determined on an hourly basis: herd full and core range size, mean herd intercow distance (ICD), and mean herd nearest-neighbor distance (NND). For hourly mean ambient temperatures above 20°C, the herd showed higher bunching behavior with increasing ambient temperature (i.e., reduced full and core range size, ICD, and NND). Aggregated space-use intensity was found to positively correlate with localized variations in temperature across the barn (as measured by animal-mounted sensors), but the level of correlation decreased at higher ambient barn temperatures. Bunching behavior may increase localized temperatures experienced by individuals and hence may be a maladaptive behavioral response in housed dairy cattle, which are known to suffer heat stress at higher temperatures. Our study is the first to use high-resolution positional data to provide evidence of associations between bunching behavior and higher ambient temperatures for a barn-housed dairy herd in a temperate region (UK). Further studies are needed to explore the exact mechanisms for this response to inform both welfare and production management.

The effect of heat stress on performance, fertility, and adipokines involved in regulating systemic immune response during lipolysis of early lactating dairy cows

The aim of this study was to assess the potential effect of heat stress on dairy cow productivity, fertility, and biochemical blood indices during the early lactation stage in a temperate climate. Additionally, the study aimed to determine the role of leptin and adiponectin in regulating the immune response accompanying lipolysis after calving in dairy cows. The study included 100 clinically healthy Polish Holstein-Friesian dairy cows selected based on parity and 305 d of milk yield from 5 commercial farms with similar herd management and housing systems. Prospective cohort data were recorded from calving day until 150 d in milk, and microclimate loggers installed inside the barns were used to record temperature and relative humidity data to calculate daily temperature-humidity index (THI) on the calving day, through +7, +14, and +21 d during early lactation. Additionally, monthly productive performance parameters such as milk yield, chemical composition, fatty acids composition, and fertility indices were analyzed. Results showed that the THI from calving day through +7, +14, and +21 d during early lactation was negatively associated with fertility parameters such as delayed first estrus postpartum and an elongated calving interval, respectively, by 29, 27, 25, and 16 d. Furthermore, an increase in THI value during early lactation was associated with an elongated artificially inseminated service period, days open, and intercalving period. Increasing THI from calving day (0 d) through +7, +14, and up to +21 d during early lactation was also linked to decreased milk yield by 3.20, 4.10, 5.60, and 5.60 kg, respectively. The study also found that heat stress during early lactation was associated with a lower body condition score in dairy cows and higher concentrations of leptin, nonesterified fatty acids, and β-hydroxybutyrate, accompanied by a drastic reduction in adipose tissue-secreted adiponectin levels after calving. Additionally, heat stress-induced lipolysis in adipose tissue caused an inflammatory response that increased biochemical blood indices associated with immune responses such as cytokines, acute phase proteins, and heat shock protein. These findings suggest that exposing dairy cows to heat stress during early lactation can negatively affect their productive performance, fertility, and biochemical blood indices in subsequent lactations. Thus, farm management changes should be implemented during early lactation to mitigate the negative consequences of heat stress occurrence.

Farmers´ sense of the biological impact of extreme heat and seasonality on Swedish high-yielding dairy cows - A mixed methods approach

Supporting dairy farmers in becoming resilient towards extreme weather requires a broad understanding of the experiences and perceived risks associated with these events from those who undergo them. We used a mixed methods approach to explore national trends of biological consequences on dairy cow udder health and fertility, combined with in-depth farmer conversations around extreme weather events, focusing on heat. The aim is to provide a comprehensive picture of how dairy farmer perceptions, priorities and decision-making are related to the season and extreme weather to identify preventive pathways that can reduce biological costs of heat stress on Swedish dairy cattle during summer. Data collected monthly at cow and farm level between 2016-2019 as part of the Swedish milk and disease recording system confirm seasonal trends and show increased somatic cell counts (SCC) and negatively impacted fertility during summers. In addition, transcriptions of 18 interviews with dairy farmers across the country and seasonal variations of SCC and fertility were thematically analysed. The results suggest that farmers have a broad definition of extreme weather and are aware of the negative impacts. Yet handling of extreme weather events can mainly be classified as reactive. Nevertheless, there are long-term effects on the farm economy, health and herd dynamics. Swedish dairy farmers are currently showing resilience, albeit a fragile one. The capability to ensure sufficient feed production in extreme weather is critical for farm self-perceived resilience. However, acknowledging the long-term biological costs related to fertility, currently not perceived by farmers, has the potential to support proactive planning and improve farm resilience and profitability.

Sensor-based behavioral patterns can identify heat-sensitive lactating dairy cows

Heat stress impairs the health and performance of dairy cows, yet only a few studies have investigated the diversity of cattle behavioral responses to heat waves. This research was conducted on an Italian Holstein dairy farm equipped with precision livestock farming sensors to assess potential different behavioral patterns of the animals. Three heat waves, defined as at least five consecutive days with mean daily temperature-humidity index higher than 72, were recorded in the farm area during the summer of 2021. Individual daily milk yield data of 102 cows were used to identify "heat-sensitive" animals, meaning the cows that, under a given heat wave, experienced a milk yield drop that was not linked with other health events (e.g., mastitis). Milk yield drops were detected as perturbations of the lactation curve estimated by iteratively using Wood's equation. Individual daily minutes of lying, chewing, and activity were retrieved from ear-tag-based accelerometer sensors. Semi-parametric generalized estimating equations models were used to assess behavioral deviations of heat-sensitive cows from the herd means under heat stress conditions. Heat waves were associated with an overall increase in the herd's chewing and activity times, along with an overall decrease of lying time. Heat-sensitive cows spent approximately 15 min/days more chewing and performing activities (p < 0.05). The findings of this research suggest that the information provided by high-frequency sensor data could assist farmers in identifying cows for which personalized interventions to alleviate heat stress are needed.

Review of the Heat Stress-Induced Responses in Dairy Cattle

In the dairy cattle sector, the evaluation of the effects induced by heat stress is still one of the most impactful and investigated aspects as it is strongly connected to both sustainability of the production and animal welfare. On the other hand, more recently, the possibility of collecting a large dataset made available by the increasing technology diffusion is paving the way for the application of advanced numerical techniques based on machine learning or big data approaches. In this scenario, driven by rapid change, there could be the risk of dispersing the relevant information represented by the physiological animal component, which should maintain the central role in the development of numerical models and tools. In light of this, the present literature review aims to consolidate and synthesize existing research on the physiological consequences of heat stress in dairy cattle. The present review provides, in a single document, an overview, as complete as possible, of the heat stress-induced responses in dairy cattle with the intent of filling the existing research gap for extracting the veterinary knowledge present in the literature and make it available for future applications also in different research fields.

Assessment of Ruminating, Eating, and Locomotion Behavior during Heat Stress in Dairy Cattle by Using Advanced Technological Monitoring

Heat stress (HS) significantly impacts dairy farming, prompting interest in precision dairy farming (PDF) for gauging its effects on cow health. This study assessed the influence of the Temperature-Humidity Index (THI) on rumination, eating, and locomotor activity. Various parameters, like rumination time, drinking gulps, chews per minute, and others were analyzed. The hypothesis was that precision dairy farming technology could help detect HS. Nine healthy Lithuanian Black-and-White cows were randomly selected for the trial. RumiWatch noseband sensors recorded behaviors, while SmaXtec climate sensors monitored THI. The data collection spanned from 14 June to 30 June. Cows in the THI class ≥ 72 exhibited reduced drinking time (51.16% decrease, p < 0.01), fewer chews per minute (12.9% decrease, p < 0.01), and higher activity levels (16.99% increase, p < 0.01). THI showed an inverse correlation with drinking time (r = -0.191, p < 0.05) and chews per bolus (r = -0.172, p < 0.01). Innovative technologies like RumiWatch are effective in detecting HS effects on behaviors. Future studies should explore the impact of HS on RWS biomarkers, considering factors such as lactation stage, number, yield, and pregnancy.

Evaluation of Holstein cows with different tongue-rolling frequencies: stress immunity, rumen environment and general behavioural activity

BACKGROUND

The tongue-rolling behaviour of cows is regarded as an outward sign of stressed animals in a low welfare status. The primary aim of this observational study was to evaluate the association between the frequency of tongue-rolling behaviour and its physiological function. The secondary aim was to explore the relationship between general activities and the frequency of tongue-rolling behaviour of cows. A total of 126 scan sampling behavioural observations were collected over 7 d on 348 Holstein cows with the same lactation stage in the same barn. The tongue-rolling frequency was defined as the number of tongue-rolling observations as a percentage to the total observations per individual cow. According to their tongue-rolling frequency, the cows were grouped into the CON (no tongue-rolling), LT (frequency 1%), MT (frequency 5%), and HT (frequency 10%) groups. Six cows from each group were randomly selected for sampling. Serum samples, rumen fluid, milk yield, and background information were collected. The general behaviour data during 72 continuous hours of dairy cows, including eating time, rumination time, food time (eating time + rumination time), and lying time, were recorded by the collar sensor.

RESULTS

Cortisol (P = 0.012), γ-hydroxybutyric acid (P = 0.008), epinephrine (P = 0.030), and dopamine (P = 0.047) levels were significantly higher in tongue-rolling groups than in the CON group. Cortisol levels and tongue-rolling frequency had a moderate positive correlation (linearly r = 0.363). With the increase in tongue-rolling frequency, the rumen pH decreased first and then increased (P = 0.013), comparing to the CON group. HT cows had significantly less food time than CON cows (P = 0.035). The frequency of tongue-rolling had a moderate negative relationship with rumination time (r = -0.384) and food time (r = -0.492).

CONCLUSIONS

The tongue-rolling behaviour is considered as a passive coping mechanism, as the stress response in cows with high tongue-rolling frequency increased. Food intake and rumination activities were all closely related to the occurrence of tongue-rolling behaviour.

Do you see the pattern? Make the most of sensor data in dairy cows

Sensors are increasingly being used to monitor animal behaviour. Data handling methods have, however, lagged behind the continuous data stream to some extent, often being limited to summarizing data into daily averages at group level. This research reflection presents our opinion of the neglected application of 24-h pattern analysis. Recent studies of dairy cow behaviour have demonstrated that additional ways of analysing data improve our understanding of animal behaviour and add value to data that were already retrieved. The terminology for the described 24-h patterns differs between these studies, making them difficult to compare. Thus, diurnal, circadian, daily, periodicity and 24-h pattern are all terms used to describe dairy cow activities over a 24-h period. Several studies have shown that the 24-h behavioural pattern at herd level is relatively consistent over time, and that with well-established management routines, a specific herd signature will be evident. However, within a herd, individual cows may have individual 24-h patterns with more or less variability. Recent studies suggest that deviations from herd and/or individual 24-h patterns can be used to describe cow robustness, as well as to predict disease. We strongly believe that individual and herd 24-h patterns provide a great deal of information about behaviour and that these patterns offer opportunity for more precise and timely health management and welfare monitoring.

Modeling the profitability of investing in cooling systems in dairy farms under several intensities of heat stress in the Mediterranean

Heat stress (HS) in dairy cows affects dry matter intake, milk yield, reproduction, and culling rate. Cooling systems (CS) may partially revert these effects, but their profitability depends on the price of milk and effectiveness and cost of the CS. Because these effects may interact over time, stochastic dynamic models are useful tools to evaluate the effects of HS and the profitability of CS. Several HS intensity scenarios, from 1,000 to 31,000 temperature and humidity index load (THI_Load, units/yr), were simulated in a stochastic dynamic dairy herd simulator, with 3 milk prices (€0.28, €0.32, and €0.36/L) and 2 initial investment costs in fans and sprinklers (€100 and €200/cow). The HS and CS scenarios simulated were modeled as a function of the THI_Load to predict the technical and economic performance in 21 selected locations of the Mediterranean. The THI_Load mean of the 21 selected locations was 12,530 (ranging from 6,908 to 31,424). Heat stress reduced milk yield in a range of 346 to 1,696 L/cow per year, feeding costs in a range of €63 to €266/cow per year, and pregnancy rate in a range of 1.0 to 3.0%/yr and increased culling rates in a range of 5.7 to 16.4%/yr compared with the control scenario. The implementation of CS increased milk yield in a range from 173 to 859 L/cow per year, feeding cost in a range from €26 to €139/cow per year, and pregnancy rate in a range from 0.1 to 1.0%/yr and reduced culling rate in a range from 1.0 to 3.9%/yr compared with HS scenarios. When the THI_Load was ≤6,300, the implementation of CS was never profitable, from 6,300 to 11,000 was dependent on milk price and CS cost, and over 11,000 was consistently profitable. The Δnet margin (€/cow per year) for CS at an initial investment cost of €100/cow ranged from -9 to 239 and at an initial investment cost of €200/cow ranged from -24 to 225. The profitability of CS depends on the THI_Load, milk price, and CS cost.

Use of Innovative Tools for the Detection of the Impact of Heat Stress on Reticulorumen Parameters and Cow Walking Activity Levels

The aim of this study was to evaluate the influence of the temperature and humidity index on reticulorumen parameters such as temperature, pH, rumination index, and cow walking activity levels. Throughout the experiment, the following parameters were recorded: reticulorumen pH (pH), reticulorumen temperature (RR temp.), reticulorumen temperature without drinking cycles, ambient temperature, ambient relative humidity, cow walking activity levels, heat index, and temperature-humidity index (THI). These parameters were registered with particular smaXtec boluses. SmaXtec boluses were applied on 1 July 2022; 24 days were the adaptation period. Measurements started at 25 July 2022 and finished at 29 August 2022. The THI was divided into two classes: THI < 72 (comfort zone) and THI ≥ 72 (higher risk of thermal stress). Cows assigned to the 2nd THI class had lower average values for pH, temperature, and rumination index, but not walking activity levels. The mean differences ranged from 0.36 percent in temperature to 11.61 percent in walking activity levels (p < 0.01). An analysis of the THI revealed a significant positive linear relation with hours, where the THI had a tendency to increase on average by 0.2403. The reticuloruminal pH showed a negative linear relation with hours, where the reticuloruminal pH had a tendency to decrease on average by 0.0032, p < 0.001. Data analysis revealed a significant positive linear relationship between walking activity levels and hours, where walking activity levels had a tendency to increase on average by 0.0622 steps per hour, p < 0.001. The rumination index was not significantly related to hours (p < 0.005), although the rumination index had a tendency to increase by 0.4376 per hour, p > 0.05. The influence of HS on reticulorumen parameters increased the risk of acidosis and cows' activity levels. HS had a negative impact on reticulorumen pH, temperature, and the rumination index. A higher THI (≥72) increased the risk of ruminal acidosis and decreased cows' physical activity levels. From a practical point of view, we can use innovative tools for the detection of HS and its impact on reticulorumen parameters and cow walking activity levels.

Effect of THI on Milk Production, Percentage of Milking Cows, and Time Lying in Holstein Cows in Northern-Arid Mexico

The possible effect of heat stress (HS), measured with the temperature-humidity index (THI) across seasons of the year (SY) upon milk production (MP), feed-to-milk efficiency (FME), and cow comfort (CC) was assessed in Holstein-Friesian cows in northern-arid Mexico. Data from 2467 cows (2146 milking and 321 dry) were recorded across SY [spring (SP), summer (SM), autumn (AT), and winter (WN)] between 2016 and 2019 in an intensive dairy farm located in the Comarca Lagunera (25° NL) with large fluctuations regarding ambient temperature and solar radiation. The THI was stratified into four classes: non-HS, <68; light HS, 68-71; moderate HS, 72-76; and intense HS, ≥77. The considered response variables were Milk production: both on a farm basis (totMP) and on a cow basis (cowMP); Nutritional efficiency: dry matter intake (DMI, kg); Feed conversion efficiency (FCE, kg) and energy-corrected milk (ECM, kg); Percentage of milking cows: (MC%); and Cow comfort: lying time (LT, h). Analyses of variance for unbalanced data were performed through "R". Both totMP and cowMP differed (p < 0.05) as HS increased; the largest values (i.e., 77,886 L and 35.9 L) occurred at lower THIs (i.e., <68 and 68-71) while the milk production fell (i.e., 66,584 L and 31.7 L) with the highest THIs (i.e., ≥77). Not only feed-to-milk efficiency (i.e., DMI, FCE, and ECM) but also the MC% exhibited a similar trend; a visible drop (p < 0.05) occurred from a THI of 68-71 onwards. Furthermore, the LT declined as the THI augmented, from 10.6 h at <68 to 8.5 h at ≥77. Moreover, differences (p < 0.05) also arose across seasons; TotMP, cowMP, DMI, FCE, and ECM revealed their largest (p < 0.05) values in WN and SP, halfway ones in AT, with the lowermost figures in SM. In the same way, cow comfort differed (p < 0.05) among seasons, with diverse lying times (h); WT, 10.5; AT, 10.20; SP, 9.3 h; and 8.8 in SM. Finally, the potential economic burden that HS caused at the producer (USD 233.2 million) and industry-market levels (USD 311.1 M), as well as its impact upon nutrient and alimentary security at the society level (i.e., 311 M milk liters and 195,415.82 Gcal), were also quantified.